And is Adam Gareth?

It should be Gareth Ruppet.

Oh, there we go.

Justin I sent a sent an email yesterday

just sort of wanted to confirm the agenda so

you know last time and of course when Gareth and

Adam get here we'll just sort of have a recap but

just just in terms of just you know prior to

joining so the last time we there was sort of

this mentioned around the price optimization and the

bundling upsell kind of piece which is sort

of more of the level three and four aspects and

then you know I thought it wasn't you know we

also spoke when we when we met the first time

and then also the second time we sort of spoke about

there's probably some need to do some some work

on the data quality but I thought it's prudent to

say well that's more of a foundational piece we

kind of spoke about the timing of like you know

we'll get that done and then do the planning

on the level three and four things which we're going

to show today yeah so there's kind of no delay

so I wasn't we weren't necessarily going to cover off

any of the data quality pieces which are probably

more your time okay yeah so Adam said you'll be

going to be fine okay we'll have Adam again four

minutes okay we're going to lay the floor up so

are you going to use the screen I am yes he is

that's why that's why I thought I'd sit over the side to be

Where are you asking from?

Me, personally, North London.

Yeah.

About half an hour.

As long as the district line of working.

Which is 50.50.

Yeah, exactly that.

Give yourself about half an hour, at least.

That's what you're talking about.

Yeah, I live in South East London so this is a bad spot.

I get just an hour and a half or something.

Oh, okay.

And are you in the office every day or?

At the moment, three days.

Okay.

I used to do four and three come back up in the summer.

Okay.

Do you remember three?

Four.

Depends.

Some weeks, two, some weeks, four.

Some weeks, none.

It just depends on what's going on.

I try and get them on in two days a week.

Just move on to some camera.

I think it's really important.

Yeah.

You know, to have people in a couple of days a week.

You know, because in various companies, you

know, the company before this one, so when

I joined, they were sort of on the back of COVID.

And so they all sort of come in and

said, let's just agree a couple of days a week.

Because it's good.

You can come in.

You can have some lunch and catch up.

And it's just much better than someone comes

in on Monday, someone comes in on a Friday.

You never see each other.

You might as well not come in.

Yeah.

Yeah.

It's only worthwhile if the whole team comes in three days a week.

Yeah.

And do you live to a place for?

Yeah.

Probably the closest.

More than not.

Yeah.

Stains.

So if I take the tumours from station

to station, it's 24 minutes, which is great.

So what's the most for you?

That's not bad.

Oh, no.

Yeah.

Anything under the arms?

Yeah.

I used to work in the city.

Right.

And it wasn't happy.

I could walk in the last minutes.

Oh, nice.

I can just top that.

Yeah.

So when I moved here, I was moved here eight years ago.

First two and a half years, we didn't happy.

Okay.

So I was an Aboriginal road, so it was literally...

If you cross the bridge, three minutes to my apartment.

Right.

Yeah.

I had a similar thing to yourself where I was very close.

But then the downside, of course, I always felt like I was around work.

Because you put...

Yes.

On the weekend, you pop in and you go,

I've seen the same places I've seen when I'm working.

I like the detachment.

I like saying this is...

It's one of my crew working, isn't it?

Yeah.

You get up, you scroll into your computer, and suddenly it's dark.

You know, what have I done with it?

Yeah.

Well, my wife...

My wife works from home a lot more than I do.

And she hates it.

She says, you know, I hate her dining room.

I hate her kitchen.

You know, I hate all the rooms in the house.

But she'll sit there, or maybe it's just her.

But she'll just sit there literally all day long.

Just kind of working.

And I said, you've got to mix it up.

Yeah.

Or, you know...

She's making it redecorates things.

Oh, this could be the other thing as well.

This is the other one.

Like, you know, we need to buy some

more codes or whatever, as wives sometimes do.

But I think it's just important to, you know, to get out and see people.

Yeah, I'll do horses.

Walk.

Well, yeah.

If you're slightly desperate.

Sorry.

Hi.

Nice to meet you.

Hi.

Good to see you.

Bye, Watson.

Yeah, it's very true.

The days I worked with both, at some

point about six o'clock, I've literally done like 600

steps in a day, because...

It's not like a bar to get coffee.

Yeah.

And I'm still eating my best, but if you

come to the office, like, you know, it's 500

people walk to the stage and present.

Yeah.

You know, I sound exactly like shit.

I'll colour up between you guys.

Okay.

Thank you.

Thank you.

Thank you.

terrific how do we how are we for time

so I know we had an hour originally so just

okay okay let's uh we'll see how we go so

I think you know great to great to see in person

um so sort of just to recap when we first

met we sort of talked through the the five levels

you sort of acknowledged that you were pretty well

uh you know pretty mature in terms of level

one level two if we want to kind of call

it those and the real interest of moving the business

forward was level three and four um we then had to

catch up uh with Justin we sort of dug into some

of those you know some of those other aspects in

terms of what he's doing um and then we thought

based on the you know the interest last time that

we're trying to focus on on sort of bundling and

cross-selling and sort of how that looks like which

is really a couple of things within uh level three

and four that's that sort of framework okay okay

um is that is that a good good yeah yeah

terrific okay all right so this is what it

was that you're able to figure out so level one

to level five so what we did was based

on the competition that we had last time and again

we have created that we'll show you it's based

on a collective experience on what we have done in

the past okay um but we have to create our

own platform to show you the art possible so what you've

done in the past plus what can happen in the near

future with what's been happening in the last three to six

month here as well so we put that all together and

we'll talk about how we can do it what it means

for you and of course the outcomes that uh might mean

of that okay so this is just go back two months

So what, as I said, what we've done is over a period

of time, given our experience, we have created a simple demo platform.

And this is adding pieces as we go along,

use cases, business problems that we hear from different clients.

And we have put together this platform. This is

purely demo data, nothing, no client data as such.

But this gives us different slices and nice little

data in the way we want to see it, right.

So this is again a homegrown platform that we've built.

But the idea is this can be put over

different platforms as well, so this is a solution.

So one piece that we talked about last

time was around cross selling and bundling, right?

So what we did was we looked at one

of your events, just highly reviewed it and took examples

of what it could mean when we apply this to that particular event.

So in this case, let me come back.

So we've taken digital transformation as an

example, which is meant to happen in October.

four months out so typically three to four

months out that's how you would look at

cross-renewals into the exhibitors so in this

case what you've done is looked at okay

the overall metadata and you can send

that for the expected expected numbers attendees exhibitors

so if you want to focus on that particular

event right so you would have exhibitors who have signed

up for that event so typically what they would

do is buy space right that's perfect and same time

you might sell them certain other products that

you already have but at the same time there's

always an opportunity to cross-sell and upsell other

products to them which you would have as a

product portfolio but the question always is how you

do that and how do you make it either

self-service or either the commercial folks going

after them and again there are different options

for all this but the first piece is the

fact that you have exhibitors in the list who have

have workspace or maybe are in the process of my space.

That the list you already have in place What we have done is

just taken certain examples on what that would look like So this is just

top line numbers that we have here at the moment which come up So

let say there one exhibitor in this case right which is Oakline Data Products

So let me just open that. So the first thing

you would do is there are, because we know that all

customers are not open, right, so you have

certain exhibitors who would be selling more to you.

In this case, what we have done is for every

event, there's four levels of customers that you would have.

Again, you might have something different. Every

company has classified that in a different way.

Either peers. So in this case, you just

put an example of platform goals that were brought.

Right. And there's a product mix, which

is proposal packages. I'll come back to that.

But you already have a list of products,

typically digital products or it could be panel sponsors.

I'll show you the list as well that we have considered as a product sample.

And the way we have done it in the

past is, based on the data sets, we typically would

recommend top three products to the exhibitors.

That's what we've done.

The example that we showed you earlier, that

you saw for the AI business, for example,

talked about those three products.

But what we have now done is done a lot more on top of it.

And I'll show you what that means as well.

Because this was based on how AI stood at that point in time.

But with the combination of what data can do,

what AI can do as of today, there's a

lot more that we can add on top of it.

I'll show you what that means.

So let me show you first what this looks like. So what we have

done is, this is not exactly how the clients would see, but this includes

all the information that comes from CRM, that comes from other datasets as well.

So we have considered certain inputs as a part of what

we have done for this particular model that we recommend certain products.

The exhibitors have already bought certain products like

Direct Re-Listing, or Stamp Package, Brawn Showroom for example.

One of the things we want to do is look at the sales fit rationale.

So every event or typically every portfolio

would have a different sales fit rationale.

For example defense and security might have a different view of

looking at how exhibitors would buy certain things or certain products Whereas

technology would be different gaming would be different But in this case

we have considered a sales fit rationale that we think was right

We want to be sure intent, recorded meetings. So, for example,

gaming meetings might not be as important as it is in defense.

But in this case, we have considered meetings are important.

And this sales fit rationale, one is comes from the data

and the other side comes from the commercial teams as well,

because they are the ones who will be top exhibitors,

and not everything will be encoded in your CRM map of it.

It's not everything is typed in.

No, it's not.

So exactly.

So that's why the rationale is always common.

And this is common, by the way.

This is not a problem with clients,

it's common to all companies in that sense.

And then you have to find engagement agenda first,

you know, here and this, given the fact that we are.

Can I ask a question on this?

Do you, or is there a potential to enrich that

with outside data?

So let's say, could you do, you know,

that company do a search, web search, like using an agent,

and actually they've had three product launches in the last three months.

Yeah, 100%.

You know that something, they might actually want to amplify that.

So there might be a digital product that would.

All of those signals are the reasons why you might buy.

And if you think about how we're doing our outreach,

so I don't have a team of BDRs.

We're looking at signals.

Who the company is, do the research on them.

What are the things?

there's a new CTO, you know, the share price

is going down, or up, or these are all just

signals that can then feed into the

agent to then make the recommendation. So absolutely.

Okay. And in this case, what we've done is

just, this is the product inventory that we have,

and this is a list of digital products, would

be different for you for sure. So this is just

generally what the list looks like, right?

And this is typical for portfolio, not payments,

portfolio tends to be a similar list of products.

And this is what we have considered for the seven

and this portfolio, right?

And this might be different on this, right?

And what we want to do is,

the exhibitors have bought certain products already,

but can we look at upselling across the internet That what we need

So we look at the rationale and what the model does in the

background is it gives you So different products that fit for that particular

Exhibitor based on what they have done in

the past with you what they are doing now

The profile that they have entered of course looking at what their

interest is and at the same time looking for outside signals as well

Now outside signals could not

Don't just have to be limited to web, it could be paid data as well

for example zoom in, it could be different and

the agents can do that quite easily so synthesize

data and talk together and give you a view so

what used to happen previously was you used to just get

three recommendations to say that this is a

product and some description right but now with

Jenny and I coming in with LLMs you can get

a lot of description around it so there is data

that's working together on agents to get this in

place and this is something you can push back

into salesforce yes there is something down there but

this is just a product rationale but the idea

is to come up with bundles as well right so

in this case the bundles are custom bundles you could have

predefined bundles as well if you need to but

these are custom bundles that the ai is suggesting so

there are for example three different bundles you

see that and in those bundles there are products

and there's a rationale given as well for each of them

on why it is saying so yeah and in this case

we see three different packages and you can select

that either you can do different things out of

of this right so you do not want to of

course replace crm over here one is it can generate an

email to say that based on what you

selected from package what the exhibitors are looking at

can have an email in place you can create a sales

script as well for the sales uh for sales uh the

commercial team they can take that and put

that into salesforce for example right to actually do

more with it but the point is you'll get

that based content from here or if you have those

those predefined packages for your you want those packages you can push that in

CRM as well which is what we had at the very end here.

There's no, you don't have this interface that we could run in Salesforce.

You'd have to work here and then push it back.

Typically yes. But if you need that in Salesforce we can embed that as well.

Okay.

Yeah, but then what you've done is taken all the data points together,

because typically it's a first one to have everything, right?

It's not meant to.

And that's what Justin has done fantastic work with Databix already,

which we had a chat about last time.

If you have the data over there, the point is,

it's just worth putting that together with external signals,

and then pushing it to the marketing automation, Salesforce, CRM.

Ultimately, you can push it anywhere you like, ultimately.

Yeah.

So that's what you would do for each exhibitor,

and, of course, we have other examples of exhibitors as well.

And the idea is that AI will give you a view on what it recommends

and gives you the confidence as well,

but you still need human freedom, right?

That's what we always recommend to go

through on what it is actually showing you.

It will actually put the pricing and discount as well.

In this case, for example, it's put 15% discount because it's bronze.

But if it's platinum, for example, it will give you a certain range of discount

based on the past and what's happened in the past,

or you can pre-configure it depending on what you're looking at.

And, again, it's not replacing...

Do you have CPQ in place already?

No.

No, right?

Even if you have...

It's not inventory management either.

Sorry.

There's no list that says how much, what's available, skill to sell.

Okay.

That's all.

It's a bit of a charge.

Yeah, and I can imagine that, but the thing

is, there's a similar challenge with Rx as well,

but this fulfilment is depending on what you recommend can be different.

So there was a proper element in

between to make sure that before it's recommended,

to check if you can fulfil those amounts.

Yeah, because there's two parts of the fulfilment, right?

It's do we have the space where that feature is still available?

You know, if it's a meeting room or if

it's a showcase or something like that, but then

when you sell it to digital services

side of things, these promotional campaigns by like

email or social and those sort of things

as well is the actual manpower capacity or bandwidth

to be able to fulfil that at the point in time when that sales will be made.

Is that inventory piece, is that on the roadmap somewhere?

No.

So I guess, you know, would it be useful for it to be on the roadmap?

So, you know, if you want to build

any automation like this around, you know, product recommendations,

feature recognitions, bundling, pricing, all that

sort of stuff, you need, you know,

you need the inventory management side of things. Our

price book at the moment is probably, you know,

over, I don't know, tens of thousands or a hundred thousand items on it.

It's a lot of product families.

We don't have products on there. What we have is propositions.

So, if we create a new bronze medallion yielded package

for the TTF that will be in there as a thing,

even though the things in it are also available.

Yeah.

So it eventually becomes a bundling exercise because

the core price is probably, I don't know, five,

five or ten, but then they get changed.

But the marketing name goes in there. So

that's what they want. So we use Salesforce,

not a sales order, but a sales order contract and sort of.

Yeah.

And what they need to put onto the

product catalogs, what appears on the end list.

Okay.

So there needs to be some reconciliation in terms

of that, because I guess what it sounds like is,

you know, two years ago, somebody came up with

a product, we call it, and then, you know,

today somebody says, we need this product. There's a

long list there. I can't kind of find it,

so I'll just create a brand new one.

Yeah, exactly what happens.

And we have no idea what's in it. We don't

have all discounts on that, based on what's put in it.

So we have no idea on the margin, based on what's put in it.

Yeah.

I don't know the cost to serve, but then we have a bundle with it.

The bundle's not a combination of things that we've discounted in.

It's just, it's a bundle of surprises.

Yeah.

So then...

Yeah.

As opposed to, well, if you sold this, these

are the two things you want to sell to bring

the margin back up on that account.

The other piece of thing that's important with this

is, and it comes back to the product side of

things, is having clear product descriptions

and definitions, so that when you're doing...

So when it's making the recommendations based on what a customer is looking for,

it has context to why it's recommended products, which,

you know, I can see it's got that in here,

but we need to have that in the

metadata to actually enable that recommendation to drive.

Which probably FedSander will call it the data quality.

Yeah, yeah, yeah.

A little, half of that doesn't work for

this capability that needs to be built out.

Yeah.

And that's the first people in Tomah right now,

and it's public as well, where they have well done

taxonomy, so that's when AI come out and their descriptions.

But it's just synthesizing that information

across the taxonomy and defining it up.

And you can't really do it across events, of course.

You can need to build a portfolio department and kind of put that out.

But I agree with that, because still, that's there.

You can't really have a combination of things.

Yeah, and the same on the floor plan side of things.

I think one of our floor plan systems,

or two of them, aren't integrated with Salesforce.

So even if you put in propositions together in

terms of how much floor space you want to sell,

someone manager goes and looks in the floor

plan system to see what's available in different areas.

So that's the whole sort of, yeah.

And it seems like the, you sort of talked about pricing.

So it seems like, so we had to

lift prices there and then kind of bundling prices.

And then I'd imagine that the ability to then provide dynamic pricing, okay,

and then make that intelligent based on certain things.

And, you know, two different exhibitors might

get a different price for the same things,

because, you know, one is more profitable than the other, for example.

And so you could then maximize, you could optimize your pricing.

Where we have differential prices, it's normally based

on how valuable they are to be there.

Okay.

So one of the things that's different about trade shows,

and certainly I've asked in my head around this with some conferences,

is actually, although we want to charge exhibitors for being there,

that's the whole part of our business model, certain exhibitors,

if they weren't there, would ruin the show.

Right.

They're not being there, would ruin the show.

And so I remember talking about eFo,

we've got some key big brand name individuals,

and actually they pay the large rates.

Okay.

They have huge stands, but the margin we make them is not very high,

because we want them to turn up, because

then everyone else calls out to turn up.

Okay.

They're like they're for tenants.

So I guess that comes down to, you know, we want to make pricing decisions,

which might vary across the period from sort of now until October,

if we think about that event.

And that pricing decision or recommendation will

be based on a number of parameters,

such as are they an anchor exhibitor, great, or whatever else it might be.

And that's at a high level, but there could be a number of other parameters of

the product information.

But from a commercial team perspective, so when they price it,

is it based on their own, based on the conversation that they have,

and what they see as fit at the moment?

So overall, there's an objective, a revenue target, right?

Then there is some discipline, I would say there's not no discipline,

there's some discipline in kind of pricing once that's been set.

But it does vary, and it's really quite

varied because of the things that Gareth has mentioned.

And there is some leeway for discounting, but

I think that typically needs to be signed off

by the event director of the MD in that business unit.

So again, this is one of the least unstructured parts of our data heads.

It's frustrating because you can see the real value.

Again, data was structured in a different way.

It was, you know, standardized.

It's just not how we've gone to market in the past.

So one of the challenges is,

it's like, how do you prove that doing all the work to clean that up

is going to accelerate our revenue?

And, you know, typically, not always, but typically,

our products are usually quite important in their market.

So there has never been a commercial incentive to say,

okay, we need to get our shit together because we have a lot of revenue leakage.

Now, we know there is, but it gets masked by the power of those events,

the criticality of those events that you, in some cases, have weightiness.

So it's like, okay, it's not.

And so that's, I guess, a big challenge for us.

When we sit here and think, okay, we can have a marginal improvement.

You know, it's not going to go from 5% revenue growth to 15%.

It might go from five to six or five to seven.

If you aggregate that, that's a massive change for our organization.

But down at the individual level, it's like,

well, how much work do I have to do?

Do I have to learn to do this new thing?

Do I have to, I can't do the things I used to do?

It becomes a massive change management project.

So that's, it's just a, it's just a

challenge that we have in terms of that trade-off.

Right.

And, I don't know if your other customer client.

Yeah, but do you have any targets about

space that you give to the commercial teams?

Yes.

So, besides space, you have those targets and things as well.

Yes.

Usually, are they met overall from our management perspective?

What do you think?

Like, you mean the space targets or the additional?

Additional.

Typically, it will be some combination of sponsorship.

Yeah.

Which will be some of the things I saw on that list.

Yeah.

I would say it's mixed in terms of the, of the delivery of the targets.

Now, this is, what was also, what would not,

especially in Europe, our managing directors

are a bit ambitious about specs because

selling trade-off space is great margin, sort of 40% margin.

Some specs is really easy.

Sponsoring the toilets, a bit of signage, it's still a great margin.

Yeah.

But a lot of the sponsor things actually require a feature to go into the show

and actually they're a bit margin-destroying because

that they're good, but they're 25%

And sometimes those features can take space

that you might want to start with these

interests.

So, it's not a really obvious question of

just keep adding sponsorship and you'll make more

money.

And it's, and this is where the discipline comes in.

It's getting a little better now because

it gets highlighted, but sales team will often

try to bundle in some sponsors, some features,

because it helps with the, with the space sale.

And they're still going, well, it helps with space sale.

And they're still on rhythm, you don't want to.

Correct.

So they will actually sell stuff that is really low margin.

In some cases, it costs money to actually.

So, sort of, you know, thinking, thinking to the future and sort of thing,

you sort of talked about how to,

you're choosing successful and it's really easy,

making those money.

Terrific.

Obviously, you know, this is going to be improvement.

What sort of, you know, rigor or, you

know, details required to then put a, you know,

put a case score to say, all right, you know, here's an event.

We're going to go do this.

There's an investment or some, you know, services to go and build, you know,

some things that we kind of see on the screen.

And this is what we think is going to result in.

It's going to, you know, result in an uptick of, you know, the revenue.

Our margin is going to improve because we'll have more accurate visibility on

actually the cost of the items.

Yeah.

And it'll be.

I'm going to turn around and ask you a question.

So, because this is what you think, how the hell is this business working?

I don't know when you're selling.

I'll be honest.

There's not been a single company.

You know, I, I speak to companies are making $20 billion a year.

And you go, and you go, really?

You're running on a spreadsheet?

Well, we run out of event directors.

So, there are event directors in the middle

of our organization who know in their market

what's going on, personally improve the window scales deals.

They know the margin in the back of their mind.

They're doing all the calculations we're talking about on the flying methods.

So, that's why we work.

So, what you're asking is, do we, that's what we employ them to do.

We're taking that work away from them.

We're standardizing.

We want to prove that by standardizing, we can do it better.

So, my question to you guys is, having been in other companies,

is that easier to do on a

failing event where everyone's worrying about it already,

or is it easier to do on a growing event when you have the acceleration of that?

Because that first step of going, in essence,

we want to take away event directors' work

and replace it with their computer, when they're

already doing a good job because we've got

massive margins, that's the hard part for us.

It's not a formal business case.

It's coming across, why is a computer

doing that best in what we're doing already?

You know, I think the answer will, so the answer will depend.

And so, for every person, we have to then figure out why would they care.

And so, you've got two different sides of that spectrum.

Now, you've got to, oh, I'm making loads of money anyway.

Okay?

So, you're asking me to change what I'm doing.

Yeah.

And I've got all this autonomy, and like, I've been doing this job for 20 years,

and et cetera, et cetera.

Okay.

So, you know, there'll be different ways to

implement the change based on where people fit.

Okay?

But one thing is true is that when you bring

a new technology in, it doesn't matter what it is,

you know, there'll be some resistance to change.

And so, there's another, we're doing this for another events company.

It's, and if you think about agentic solutions,

you know, having them transparent to the user.

So, using the same tools.

Okay?

And so, there's another demo we can show you at another point.

We've got another synthetic work environment where,

you know, showing how somebody would do some,

you know, a data analyst, okay, for an event.

And, you know, you know, the current state, they go

to power, you know, they get a reminder on Outlook,

and they open up Power BI, and then the

data's not there, they need to export to Excel, and

they do some V lookups and everything else.

And then you turn on the agents, and it's transparent to the user.

Okay?

So, it's the same tools they're using, you know,

Power BI and everything else, but then the agents,

you know, sit transparently in there.

So, to your point, we have to think around, you know, who are these people?

Okay?

You know, the person that's got a, you know, a show which is hugely successful,

why would they care?

Okay?

Versus, you know, the one where it's not,

if it's failing, that's probably a little bit easier,

because people say, we want to be better.

So, we just need to think about those use cases

of how we then position it to get people on board.

Otherwise, they could be reluctant to the change.

And the other way to look at the characters, the

way we've done it, one is look after the anchor,

and the other way to do it is,

people are most ambienable to change, even the actors.

So, that's the way to look at it as well,

because the ones who want to get new things in place,

to increase their revenue, right?

So, the business case here is increase

their revenue, that's what you're putting into it.

As long as they are even able to do it, it makes it easier to start somewhere,

and let them champion it, so it helps you champion that cause as well.

So, what we have seen in the

experience is typically some false surveil in between,

who are not very successful because they don't come and touch me.

Yeah.

The ones who are not doing so well because you're

not confident that there will be some uptake on that.

We don't know that, but I'm just saying.

So, that's it.

If you see somewhere in between, there are

some elements who are happy with the change,

then take it in a portfolio, and then take it in a portfolio.

You've worked with other clients or clients implementing something like this.

What a, you don't have to tell me because it's probably a commercial assessment,

but is it meaningful uptake?

What were the challenges?

Was it data?

Was it people?

Was it process?

I'd be interested to hear how you worked

with clients who then really tried to implement it,

and obviously faced, maybe two changes, faced challenges.

Yeah, it's all three people in process.

Data typically because of the fact that

how events company work, right, sort of typical,

as you've seen.

I mean, there have been programs where they

kind of get data right, their quality as well,

but what you've heard from just at least you have got it to some extent, right?

You have a platform in place, you put that data together.

The data quality challenges are slightly different because they are upstream,

which cannot control directly that way.

That's one thing I believe is in place

as compared to what we've seen with others.

And you have something on top of it already.

The people that we talked about, right, people is a big challenge,

but as long as you have the right champions

in place that you can identify, it makes things easier.

With Read, we started with Pharma, for example, where we

saw that they were happy to actually get this on board.

So they were meeting the targets, because

every company has digital targets as well,

so they were falling short of it, just short of it.

They said that this is a good chance to actually get that over the line,

and that was the starting point for them.

There's a motivation to say that, okay, this is

going to help us actually get us over the line.

So that's where the people change challenge still comes in.

The idea is because this is something that's happening at the moment, right?

We've seen a lot of change in terms

of technology in the last three to six months,

and this is something that companies have to adopt in some shape or form.

But at least what we've seen is you have the right

combinations in place to actually put things on top of it.

The other part is process, which again, I agree with.

There are things that need to change, right?

Like I said, one way to think about it is

that you have these large events, like the defense events,

and there's IFA, for instance, which are on the other side of the scale.

And it's not just humans who will be working with exhibitors, like the ACS post,

we can't have ATF, but that can happen somewhere down the line.

But till you define that process upfront,

and I'm not saying, I'm not stringing about defining the exact process,

because a lot of it will still happen because you'll never get that in place.

But probably not for the platinum exhibitors, so to speak,

but the rest of them, they can follow this process, is what I've seen.

You'll have the top exhibitors in the sales course,

which will always have that portfolio,

they will call up and get that thing done.

But in spite of that, you'll have recommendations coming from them,

because the sales, what we've seen in the past is,

again, a lot of commercial folks did not take this up right away,

because they thought that, you know, I

know what the customer wants, I'll just...

Just do whatever, pitch whatever I think.

Exactly.

But what we have seen now is this technology coming into play,

it tells you a lot more, and you are...

The actual context.

Exactly, the context.

And the signals that you get from your data, from external,

and you won't get it right away.

You can't refer to each other in the exhibitor,

and you don't know what's happening this morning, for instance, right?

This is what you would get out of this.

And when the... during the implementation, have you gone back,

or has informed upon back, and looked

at the percentage uptake on the recommendations.

Because, obviously, you've got a couple things that happen.

One is, here's a recommendation engine,

the next best action, with all these different signals.

Then it's like, okay, well, how often do the customers actually

take out those camera recommendations?

Then there's a sort of loop for me,

which is around how satisfied was the customer

on the delivery of the product, which is great to have a list of inventory,

but not have the ELC benefit, but how does that start to feed into, again,

improving those recommendations?

And also, you know, frankly, improving the

product development, because that's also great to do.

Correct.

So, the improvement part was CSAP, so that was specifically included.

CSAP, okay.

Yeah, that was specifically included in terms of recommendations.

So, hey, Informa had this loop in place,

in terms of what they do with audience, and because they have content as well,

so they look at how customers actually go through digitally.

So, they have something else, Tracker, Passport,

which is interesting enough, similar to what you

already have, and then there's Document, right,

based on how you can actually improve

the audience engagement.

The segment is inside that kind of data,

but insights are the one where you actually

understand what's happening with the equipment.

But that includes CSAP as well, mostly matter.

Yes.

And obviously, you can track all that in terms of the response rate.

So, if, you know, salespeople today are emailing

people and saying, we've got some products here,

whatever price, you can obviously track that

in terms of that was the response rate.

We now have some AI-generated response, which is

going to be more tailored because they're pulling

in the signals, and then we can obviously track a response rate there.

And then you have the other aspects of, okay, we're at the pricing.

You know, is the pricing, is the pricing better?

And if the pricing is dynamic and looking

at more signals, then the, you know, the uptake

of those will be, will be also better.

Where you guys have done this before, but how much of what was needed for that

measurement framework to actually be put in place was ready or not?

Because things like that, but like even

something simple, like I've been able to track

what's the conversion of the salesperson who sends

an email versus the email they sent from AI.

Like we don't track what emails the

salesperson sends, you know, those examples, right?

But it's, I think that's the stuff that's

really the valuable part of it because, yeah,

because I think the challenges you might, let's

say we could show that's had really good

growth, for example, is there can be so many

other factors that are driving that growth as well.

So it wouldn't all be, you know, if it was 10% last year, now it's 20%,

it wouldn't all be down to this.

It might be, in reality, it might be down

to a customer, there's a new product they need to

launch and they've suddenly just gone and spent an extra half a million pounds.

Those are all the details that we need to get into the discovery to understand,

because we want a positive business case.

We want to say, this is where you were, okay, then

we made a change and then it was a positive change.

And then the metrics that we talked

about, increasing revenue, increasing NPS, they all improved,

because, you know, we want that.

And so that's all the detail that comes out

of discovery of like, how do we track these things?

Because I think we all know intuitively that it's going to make things better,

but then the question to your point is how much better?

And because then the question comes, well, do we, you know, do we do this?

Okay.

Or, you know, do we have a small pilot?

Actually, this is going to be so good for the business that we'd like to do,

we'd like to do this for like the next 10 events or whatever,

like just work fast in that vertical place.

So that all comes in a discovery in terms of understanding

how we think this, you know, what your environment looks like.

And how, so what, switching away from this

event, what does your commercial engagement typically look like?

So you talked about discovery, there's build phases,

obviously, what, I think I remember seeing this.

Yeah.

Yeah.

Yeah.

Yeah.

And this is what we do.

So what we typically do out of this, so

The first three stages, what we tend to do,

which is discover, looking at what you already have.

And because we have in the background, that shouldn't take a long time,

Envision is the part of looking at what that means from a business perspective

and from a cost technology perspective, and

a change perspective, putting that part together.

And looking at what does starts more mean, and that's the true part of it,

where we actually prove that value.

So if you say, hey, let's do DTX, for example, at an event.

So we work with you to actually ensure

that the things quality is for that particular event,

prove it, measure it, and then you actually

scale that up, which is the transform phase, right?

So you take it across the events in

that portfolio or growth portfolio, and we recommend that

portfolio, that should apply.

So that could look at different things, so

for example, if you want to start with DTX,

that's just an example.

We typically would go deeper into the portfolio.

First.

Yeah, first, and then you take it across, right?

But depending on which events you want to do,

and as I said, there are different parameters that we

need to consider as well, who's able to change,

and we can actually bring up all of that to

people as well, because we have worked with commercial teams.

We know the behaviour, we know the challenges,

and the resistance that I can see, but again,

of course, with the support, we've gone about

it, because we know the technology that you have

in hand today.

This can be really game-changing in terms of what the commercial impact is.

And picking that event, picking the first

one is really important, picking the pilot,

because to your point, we want to make

sure it's successful, and also we want to learn,

so we don't want one which is too easy.

Yeah.

So we had another customer, for example, that

a couple of months ago, they were recommending,

right, our pilot site should be Saudi Arabia.

Yeah.

Because we've got 450 people out there, it's nice and self-contained, etc.

We roll on a bit of a month and

say, are we sure that's still the right location?

Okay.

So, you know, thinking, we just picked

DTEX, you know, randomly, but thinking around,

What are we going to learn from that?

Okay.

How do we then scale out from there?

So there is some conversation to be had around where we should start,

so we can actually learn.

And then, of course, at some point, you need to say, well, if we've done this,

what does it look like if we roll this out?

And, you know, we need to learn enough about

from the pilot to be able to then model out

what this looks like as we scale it out.

And if it's too easy or too small,

all of a sudden, and everyone's super friendly,

we get to the next, you know, the next

event, for example, and, you know, it goes horribly,

of course, and then our pricing is all wrong, as an example.

So the pilot site's really important.

Yeah, and one of the parts of the mission in

that way, if we want to bring to the table,

it's not just looking at data and say, hey, this is what will happen downstream,

you look at upstream as well and say that these are the changes,

you could make that to be better for you, because this is what you've seen.

So we have seen larger programs as well, right?

I mean, what inform, for example, when they took over the book,

so we've seen that happening in front of the eyes, how it has changed.

How many events is this running across now in the format?

How many events is this running across in the terminal?

It's about 4.50, I don't know?

Yeah.

Because we had, you're still acquiring companies, they have 4.50 events.

Yeah, so that's...

And is this running across?

Sorry, across this, are you talking about Informa in general or...?

Yeah, so you're, the upsell, you mentioned that.

But that is for Rx Prime, so Informa is...

So Informa has done parts of it.

So the beta showed it before, right?

This was you doing Informa.

Yeah, the technology is moving really fast.

And so if you look at sort of six months ago...

So it's completely different.

So the way, you know, the way you solve, you know, bundling six months ago

is sort of different than you solve today.

And so this is how we solve today with other customers.

Yeah, I was going to ask, I was going to ask on that.

Because I guess in terms of...

I think you mentioned that you guys did quite a bit of work forward as well.

Yeah.

I don't know if that was both quite forward or not.

But I guess in terms of workflow, there's like a lot of what's...

Like, you know, the engine there is the models

that are in the background to do the recommendations,

stuff like that, right?

Or the data that you give it access, you know,

to Claw's APIs or whichever platform you use in the

background to, you know, look at that, do

the analysis, put the recommendation back in a

metadata layer, for example, and then serve it up through the platform.

I guess in terms of where you see teams working in six months' time,

do you see them, like, working there?

Or actually, you know, is the value involved in a number of skills,

which when a salesperson works with something

like Claw, that's because it would have access

to the same data, for example, which

would go, okay, well, these are your customers,

that's the analysis, these are our recommendations.

Here's the email that's integrated with Outlook and sends the email.

It creates the logs, so that's doing

all of the measurement framework in the background

and understands every customer that it has touched and what is different to them

versus the last year versus those that hasn't.

And yeah, I understand, this comes up a lot.

And so generally speaking, sort of the conversations we have,

you sort of start with the value chains.

And you say, right, what does the business do?

What are the value chains within that, the business process, et cetera, okay?

And then it's a conversation around, you know, for these things that people do,

which ones are going to be solved by some sort of AI solution or application?

And maybe the company should lead on that

because they just know it a lot better, okay?

Maybe they have some, they have some, their

own, you know, head of AI, et cetera, okay?

So there's those.

Then there's the ones where you might go to a third party, okay?

Like us, for example.

And then there's the use cases, which can just be solved by Claude, okay?

Or whatever, Gen AI, because it's very capable.

But the idea is to have a framework of

like, of all the work that has to be done,

which ones can be solved by Claude and user

versus, you know, some sort of AI app or,

you know, depending on who's going to go do that.

And then the other one, which we discussed bringing today, but we didn't,

is thinking around because the technology changes

so much, it has to be modular, okay?

And so, you know, how do we ensure that you have an application and a logic flow

and we can bolt in, you know, maybe there's a new anthropic around the corner

that we want to kind of bolt into it.

And so, you know, with some of the tools we've developed internally,

you know, we'll swap and change a lot of the backend technology.

Yeah.

And so, for example, a lot of things we use internally now, you know,

that's powered by Claude, because it's just so much, it's so much better than,

you know, what we had six months ago.

But at the same time, what we've done is, that's what we've learned as well.

So you can use Claude to work and

tomorrow there'll be something around the corner again,

and it's probably a couple months away, right?

But what we have done is abstracted that away, and this event is an example.

I love how to change up what the model is exactly right.

And not just model now, because you

need agents, because it's managed agents as well,

and that's something you need to have in place.

So that, again, framework that you know, like just ADP and stuff like that,

but the models can change over your time.

And that's what we have abstracted to it.

Julian was referring to the marketing tool that it's homegrown fully, like AI,

that it's AI and everything on which you can shape separately for you.

But again, what we've done is abstracted away

what the AI looks like in the background.

Claude is the best at the moment, but it has seen that expensive.

Right, good.

But then we have looked at 4X right now on the other side.

So those are the things we are changing, but we're

keeping the tab as well on what that looks like.

But that has to be abstracted to it in some shape or form.

Because it will all come back to the apps, and

AI will be a layer on top of it, of course.

But yeah, that has to be minimum, if that makes sense.

And so what is your typical commercial model?

So if we went and did this piece of work, I

don't need to tell us like down to the last pence,

but range-wise, what are we talking about if we

wanted to do, if you're going back to your...

Yeah, I'm going there, exactly there.

Just another example, but I'll come to the other day from.

I'm happy to do that.

Yeah, if we go and do a discover, envision, and prove,

because that's kind of where you make a natural decision, do you do more or not.

Yeah, what would we talk about in terms of money?

So just before that, I'll come to that as well.

And just before that, what we would do is do a pre-discovery workshop.

Yeah, because we have to understand, right?

What are we looking at?

Are there any specific...

And this will be a meeting.

There are commercials in place there.

And based on that, then we'd say, I think this is what it would look like.

Correct, exactly.

Because what we would do is do a

pre-discovery, a couple of hours, four hours, depending on...

And make sure that that falls into place

first, and then we give you the commercials.

But what we typically envisage is, this should be between six to ten weeks.

Again, depending on event and data that you're looking at.

So if you have data and process and people already ready, in some shape or form,

it would be...

The timeline would be much shorter, right?

Because you're talking about certain bits of changes, but we want to

make sure that people are using it at the end of the day.

Yeah.

So considering that, it would be six to ten weeks, is what I would say for us.

And the range would be between, again, between

the highest range three, is between 60 to 150k.

That's quite with the outcomes as well.

Yeah.

We want to make sure there is change in revenue for you.

It's not just about saying that, then you go and we take a step back.

Yeah.

And plus with upstream recommendations, I think, because

what we have seen with these companies is,

and what we have gained experience, if you do some upstream changes,

we have talked about as well, in terms of

data quality, in terms of how you work with marketers.

And you mentioned that you outsource

your marketing operations at the moment, right?

Is that right?

A mix.

Yeah, it's a mix.

Okay.

It's a mix.

It was the social and the...

Oh, social, that's fine.

Okay.

Yeah.

Yes.

So the email will stop you ourselves.

Yes.

Oh, you got it outside.

So your campaign planning, you know, the opposite of things is all internal.

Perfect.

Outside of email, a lot of the actual activation.

Okay.

Is what it is, I was like to say.

Okay, got it.

Well, that's good.

But then most of it is still internal.

This is correct.

I thought it was the other way around this year.

And in terms of...

So you've given us none of the first stop rate, do quite a bit of work.

How does that then scale?

Is it a license fee and TNM?

Is it...

We can go mix and match with that.

So by that, I mean, if we know how it works initially.

Initially, when you TNM, that's what we would recommend,

because you don't know how we work with it.

If you don't know your environment as well.

But if you get the first success out of the place, it could be outcome-based.

So for example, let's say, if you do one event on

TTS, let's pick up other events in the world for you.

Then we say that over a period of time, depending

on when the events are fall into place, six months,

this is what we're going to do, and it could be outcome-based.

And again, you can have a conversation on that, right?

Depending on how you're going to try.

And it's a mix and match as well, because it's not just us doing it on our own.

Because then you can have a mix and match.

Your team's now, you're picking that up and extending it up over there.

And so it could be both ways.

Okay, thank you.

Because it just depends, you know, if you

think about like there's 10 things to be done,

depending on, you know, availability and the capability of the internal teams,

maybe they can do the first two.

Or maybe they can do, you know, number one and number five.

If you think about the various steps in the process,

it's just about figuring out what's best for the company.

And then how do we, you know, how do we get the outcome we're looking for,

to then, you know, make the company better.

And the other side of this is

because now you're working with feedback companies too,

we understand speed, value, and what e-companies look like.

That's what happened.

And I think we know, I personally know that's gone pretty well,

because of my experience in the past, and

what they would be demanding of all of you.

So we exactly know that.

And that's why speed would be, speed is

something that we work for, no doubt for it.

If you say six weeks, we'll get them six weeks, of course,

if there's support and anything coming

from you, touching you from our perspective.

And given the fact that there's a platform

that you've built or need to adjust it,

that seriously helps a lot.

Because then you're not able to do something from scratch on the other side.

Conscious of, we've got a few minutes for Gareth Esther.

Well, excuse me, we've got these things, so if you're upstairs.

I'd ask Jason's name for the three of us to catch up after this.

I'll leave you to finish.

Sure, okay.

I think you've probably read the thread

of the challenge through the conversation so

it's very helpful to see it in practice, it's

always nice to see stuff. Which is the idea.

Which you can visualize it. It sits within the

things that we would like to do. And the reason

we're gonna have to have this conversation is,

and also with our commercial leads, is like with

all the other things we're doing, where does this

fit in? So it's not about whether we want

to do this or not, it's more about, because

we have so many other things that we're doing,

how can we, because if we don't have a

commercial partner, no matter what I say, Justin says,

or Gary says, it doesn't work. So there's a

bit around that, there's a bit around how does this

fit into the roadmap that we're thinking about,

particularly around the use of AI in most

organizations. And to be pretty candid with you,

we are more focused on audience at the moment.

And that's because there's two components to it.

There's still an opportunity here, because one of our

focuses is around monetization of audience. And

we have certain segments of that audience,

it's not necessarily every single person, there's certain

segments that we think have a much higher

monetization propensity. And things like next, that's

offer or recommendation engines and things like

that. Those are the sorts of things that we would

be interested in, which is probably a little bit more

aligned in terms of our frequency of where we want

to go. So generally, how I'm thinking about it is,

how do we get audience, this was asking about the

demand gen, I didn't say, can you put it to audience,

but how do we find more of the right audience?

How do we then convert and monetize, well, convert all of

them into participation as many as we can into the

show? And then how do we monetize a segment on that,

at least initially? And then it flows through

through the customer journey, which is all the

things that you've been seeing around these

AI concierges or co-pilots or events, it's that

identity experience. So you think about that end-to-end customer

journey, how do we find them, how do we

convert them, and how do we make sure they have a

great experience on the show? So that's kind of the first one.

Why? It's because that's what our exhibitors pay us

money to have access to, and we can also drive

monetization of the audience or a segment of

it, which we've historically not been able to do.

So that's kind of our priority kind of mix.

So yeah, so we can bring that to the

table as well, the audience monetization part. So the case

you did, level four is about that. This is buy

and seller on both sides. For example, in my PGE

that we've done. Similarly, what Informa has done is...

Some people like you said, yeah, we gotta go.

Yeah, sure. Sorry guys. No, I'm sorry. This is about monetization for Informa.

And is Adam Gareth?

It should be Gareth Ruppet.

Oh, there we go.

Justin I sent a sent an email yesterday

just sort of wanted to confirm the agenda so

you know last time and of course when Gareth and

Adam get here we'll just sort of have a recap but

just just in terms of just you know prior to

joining so last time we there was sort of a

smudged around the price optimization and the bundling

upsell kind of piece which is sort of

more of the level three and four aspects and then

you know I thought it wasn't you know we also spoke

when we when we met the first time and then

also the second time we sort of spoke about there's

probably some need to do some some work on

the data quality but I thought it's prudent to say

well that's more of a foundational piece we kind

of spoke about the timing of like you know we'll

get that done and then do the planning on the

level three and four things which we're going to show

today yeah so there's kind of no delay so I

wasn't we weren't necessarily going to cover off any of

the data quality pieces which are probably more

you're doing okay yeah so Adam said you'll be

fine okay we'll have Adam again four minutes

okay we're gonna lay the floor up so

are you gonna use the screen I am yes he is that's

why that's why I thought I'd sit over the side to be

Where are you asking from?

Me, personally, North London.

Yeah.

About half an hour.

As long as the district line of working.

Which is 50.50.

Yeah, exactly that.

Give yourself about half an hour at least.

That's what you're talking about.

Yeah, I live in South East London so this is a bad spot.

I get just an hour and a half.

Oh, okay.

And are you in the office every day or?

At the moment, three days.

Okay.

I used to do four and three come back up in the summer.

Okay.

Three, four.

Depends.

Some weeks, two, some weeks, four.

Some weeks, none.

It just depends on what's going on.

I try and get them on in two days a week.

Just move on and just come right up and see.

I think it's really important.

Yeah.

You know, to have people in a couple days a week.

You know, because in various companies, you

know, the company before this one, so when

I joined, they were sort of on the back of COVID.

And so they all sort of come in and

said, let's just agree a couple of days a week.

Because it's good.

You can come in.

You can have some lunch and catch up.

And it's just much better than someone comes in on Monday.

Someone comes in on a Friday.

You never see each other.

So you might as well not come in.

Yeah.

It's only worthwhile if the whole team comes in three days.

Yes.

And do you live close to them?

Yeah.

Probably the closest.

Yeah.

Stains.

Yeah.

If I take the tube, it's from station

to station, it's 24 minutes, which is perfect.

So what's the worst for you?

That's not bad.

Oh, no.

Yeah.

Anything under the arms?

Yeah.

I used to work in the city.

Right.

I could walk anything in the mountains.

I can just top that.

Yeah.

So when I moved here, I was moving here eight years ago.

First two and a half years, we didn't happy.

Okay.

So I was an apparition road.

So it was literally, if you cross the bridge, three minutes to my apartment.

That's great.

Yeah.

Yeah.

I had a similar thing to yourself where I was very close.

But then the downside, of course, I always

felt like I was around work because you put

on the weekend, you pop out and you're going,

I've seen the same places I've seen when I'm

working.

I like the detachment.

I like saying this is...

This is where you're working.

Yeah.

You get up, you store your computer, and suddenly it's dark.

You're like, well, I don't want to.

Yeah.

Well, my wife, my wife works from home a lot more than I do.

And she hates it.

She says, you know, I hate her dining room.

I hate her kitchen.

You know, I hate all the rooms in the house.

She'll sit there, or maybe it's just her,

but she'll just sit there literally all day

long, just kind of working.

And I said, you've got to mix it up.

Yeah.

Or, you know, this could be the other thing as well.

Like, you know, we need to buy some

more curves or whatever, as wives sometimes do.

But I think it's just important to, you know, to get out and see people.

Yeah, I'll do horses to walk.

Yes.

Oh, yeah, yeah.

If you're slightly desperate.

Oh, hi.

Sorry.

Nice to meet you.

Hi.

Okay.

Good to see you.

Bye, Watson.

Yeah, it's very true.

The days I worked for you both, sometimes

by 6 o'clock I've literally done, like, 600 steps

in a day, because...

It's not that far to get popping.

And I just don't eat my best, but if

you come to the office, like, you know, it's 500

people walk to the stage and present.

Yeah.

Oh, you know I sound exactly like shit.

I'm not having a good job.

I'll cover up between you guys.

Okay.

Come on up, I need that.

Absolutely.

Sorry.

Sorry.

terrific how do we how are we for time

so I know we had an hour originally so just

okay okay let's uh we'll see how we go so

I think you know great to great to see in person

um so sort of just to recap when we first

met we sort of talked through the the five levels

you sort of acknowledged that you were pretty well

uh you know pretty mature in terms of level

one level two if we want to kind of call

it those and the real interest of moving the business

forward was level three and four um we then had to

catch up uh with Justin we sort of dug into some

of those you know some of those other aspects in

terms of what he's doing um and then we thought

based on the you know the interest last time that

we're trying to focus on on sort of bundling and

cross-selling and sort of how that looks like which

is really a couple of things within uh level three

and four that's that sort of framework okay okay

um is that is that a good good yeah yeah

terrific okay all right so this is what it

was that you're able to figure out so level one

to level five so what we did was based

on the competition that we had last time and again

we have created that we'll show you it's based

on a collective experience on what we have done in

the past um but we have to create our own data

our own platform to show you the art possible so what

you've done in the past plus what can happen in

the near future with what's been happening in the last

three to six months yeah as well so we put that

all together and we'll talk about how we can do it

what it means for you and of course the outcomes

that might mean okay so this is just go back to

So what, as I said, what we've done is over a period

of time, given our experience, we have created a simple demo platform.

And this is adding pieces as we go along,

use cases, business problems that we hear from different clients.

And we have put together this platform. This is

purely demo data, nothing, no client data as such.

But this gives us different slices and nice little

data in the way we want to see it, right.

So this is again a homegrown platform that we've built.

But the idea is this can be put over

different platforms as well, so this is a solution.

So one piece that we talked about last

time was around cross selling and bundling, right?

So what we did was we looked at one

of your events, just highly reviewed it and took examples

of what it could mean when we apply this to that particular event.

So in this case, let me come back.

So we've taken digital transformation as an

example, which is meant to happen in October.

four months out so typically three to four

months out that's how you would look at

cross-renewals into the exhibitors so in this

case what you've done is looked at okay

the overall metadata and you can send

that for the expected expected numbers attendees exhibitors

so if you want to focus on that particular

event right so you would have exhibitors who have signed

up for that event so typically what they would

do is buy space right that's perfect and same time

you might sell them certain other products that

you already have but at the same time there's

always an opportunity to cross-sell and upsell other

products to them which you would have as a

product portfolio but the question always is how you

do that and how do you make it either

self-service or either the commercial folks going

after them and again there are different options

for all this but the first piece is the

fact that you have exhibitors in the list who have

have workspace or maybe are in the process of my space.

That the list you already have in place What we have done is just

taken certain examples on what that would look like So this is just top line

numbers that we have here at the moment which come up So let say there

one exhibitor in this case right which is open

line data products. So let me just open that.

So the first thing you would do is there

are because we know that all customers are not open

right so you have certain exhibitors who would be

selling more to you. In this case what we have

done is for every event there's a four levels

of customers that you would have again you might have

something different every company has classified that in

a different way even peers so in this

case you just put an example of platinum goals

right and there's a product mix which is proposed

in packages i'll come back to that but you

already have a list of products typically digital products

or it could be banners sponsors i'll show you

the list as well that we have considered as a

And the way we have done it in the

past is based on the data sets we would recommend

top three products to the examiners.

That's what we've done.

The example that we showed you earlier, that

you saw for the AI units for example, talked

about those three products, but what we have now done

is done a lot more on top of it and

I'll show you what that means as well.

Because this was based on how AI stood

at that point in time, but with the combination

of what data can do, what AI can do as

of today, there's a lot more that can add up

and show you what that means.

So let me show you first what this looks like.

So what we have done is, this is not exactly how the clients would see,

but this includes all the information that comes from

CI and that comes from other datasets as well.

So we have considered certain inputs as a part

of what we have done for this particular model

that we recommend certain products.

The exhibitors have already bought certain products like Direct Re-Listing,

or Stamp Package, Brawn Showroom for example.

One of the things we want to do is look at the sales fit rationale.

So every event or typically every portfolio

would have a different sales fit rationale.

For example defense and security might have a different view of

looking at how exhibitors would buy certain things or certain products Whereas

technology would be different gaming would be different But in this case

we have considered a sales fit rationale that we think was right

We want to be sure intent, recorded meetings. So for example,

gaming meetings might not be as important as it is in defense.

But in this case, we have considered meetings are important.

And this sales fit rationale, one is comes from the data

and the other side comes from the commercial teams as well,

because they are the ones who will be top exhibitors,

and not everything will be encoded in your CRM map of it.

It's not everything is typed in.

No, it's not.

So exactly.

So that's why the rationale is always common.

And this is common, by the way.

This is not a problem with clients,

it's common to all companies in that sense.

And then you have to find engagement agenda first,

you know, here and this, given the fact that we are.

Can I ask a question on this?

Do you, or is there a potential to enrich that

with outside data?

So let's say, could you do, you know,

that company do a search, web search, like using an agent,

and actually they've had three product launches in the last three months.

Yeah, 100%.

You know that something, they might actually want to amplify that.

So there might be a digital product that would.

All of those signals are the reasons why you might buy.

And if you think about how we're doing our outreach,

so I don't have a team of BDRs.

We're looking at signals.

Who the company is, do the research on them.

What are the things?

there's a new CTO, you know, the share price

is going down, or up, or these are all just

signals that can then feed into the

agent to then make the recommendation. So absolutely.

Okay. And in this case, what we've done is

just, this is the product inventory that we have,

and this is a list of digital products, would

be different for you for sure. So this is just

generally what the list looks like, right?

And this is typical for portfolio, not payments,

portfolio tends to be a similar list of products.

And this is what we have considered for the seven

and this portfolio, right?

And this might be different on this, right?

And what we want to do is,

the exhibitors have bought certain products already,

but can we look at upselling or processing So we look at the rationale and

what the model does in the background is it gives you so different products that

fit for that particular exhibitor based on what they have done in the past with you

what they are doing now, the profile that they

have entered of course looking at what their interest is

and at the same time looking for outside signals as well. Now

outside signals could not, don't just have to be limited to web

it could be data as well, for example, Zoom and Zoom.

It could be different, and the agents can do that quite easily.

So synthesize the data, put that together, and give you a view.

So what used to happen previously was you used to just get three recommendations

to say that this is a product and some description, right?

But now with JNI coming in with LLMs,

you can get a lot of description around it.

So there is data that JNI are working together on agents to get this in place.

And this is something you can push back into Salesforce.

I'm coming back. Yes, there is something on there as well.

this is just a product rationale but the idea is

to come up with bundles as well right so in this

case the bundles are custom models you could have

predefined bundles as well if you need to but

these are custom models that the ai is

suggesting so that for example three different models

you see that and within those bundles there

are products and there's a rationale given as well

for each of them on why it is saying so

yeah and in this case we see three different packages

and you can select that either you can do

different things out of this right so you do not

want to of course replace CRM over here. One is

it can generate an email to say that based on what

you selected from package, what the exhibitors are

looking at, you can have an email in place.

You can create a sales script as well for

the sales, for sales, the commercial team. They can

take that and put that into Salesforce for example to

actually do more with it. But the point is you

will get that base content from here. Or

if you have those predefined packages for your,

you want those packages, you can push that in CRM as well,

which is what we had at the very end here.

There's no, you don't have this interface

that we could run in Salesforce.

You'd have to work here and then push it back.

Typically, yes.

But if you need that in Salesforce,

then you can embed that as well.

That's a part of it, that's not a problem.

Okay.

Yeah, but then what you've done is taken all the data points together,

because typically it's a first one to have everything, right?

It's not meant to.

And that's what Justin has done fantastic work with Databix already,

which we had a chat about last time.

If you have the data over there, the point is,

it's just worth putting that together with external signals,

and then pushing it to the marketing automation, Salesforce, CRM.

Ultimately, you can push it anywhere you like, ultimately.

Yeah.

So that's what you would do for each exhibitor,

and of course, we have other examples of exhibitors as well.

And the idea is that AI will give you a view on what it recommends,

and gives you the confidence as well,

but you still need human freedom, right?

That's what you always recommend to go

through on what it is actually showing you.

It will actually put the pricing and discount as well.

In this case, for example, it's put 15% discount because it's bronze.

But if it's platinum, for example, it will give you a certain range of discount,

based on the past and what's happened in the past,

or you can pre-configure it depending on what you're looking at.

And again, it's not replacing...

Do you have CPQ in place already?

No.

No, right?

So even if you have...

It's not inventory management either.

Sorry.

There's no list that says how much,

what's available, still to sell.

Okay.

That's all.

It's a bit of a charge.

Yeah, I can imagine that.

But the thing is, there's a similar challenge with Rx as well,

but this fulfilment is depending on what you recommend can be different.

So there was a proper element in

between to make sure that before it's recommended,

to check if you can fulfil those or not.

Right.

It's do we have the space where that feature is still available?

You know, if it's a meeting room or if it's a showcase or something like that.

But then when you sell in the digital services side of things,

these promotional campaigns via email or social, those sort of things as well,

is the actual manpower capacity or bandwidth to be able to fulfil that

at the point in time when that sales will be made.

And is that inventory piece, is that on the roadmap somewhere?

No.

So I guess, you know, would it be useful for it to be on the roadmap?

So, you know, if you want to build any automation like this around, you know,

product recommendations, feature recommendations,

funneling, pricing, all that sort of stuff,

if you need, you know, you need the inventory management side of things.

Our price book at the moment is probably, you know, over, I don't know,

tens of thousands or a hundred thousand items on it.

We don't have products on there. We have propositions.

Okay.

So, if we create a new bronze medallion yielded package

for the TTF that will be in there as a thing,

even though the things in it are also available.

Yeah. So it eventually becomes a bundling exercise because the

core price is probably, I don't know, five, five or ten,

but then they get changed.

But the marketing name goes in there.

Okay.

So that's what they want.

So we use Salesforce and what's a

sales order, what's a sales order contracting tool.

Yeah.

And what are you put on, what are catalysts, what appears on the end list.

Okay.

So there needs to be some reconciliation in terms

of that, because I guess what it sounds like is,

you know, two years ago, somebody came up with a product, we'll call it.

And then, you know, today somebody says, we

need this product. There's a long list there.

I can't kind of find it. So I'll just create a brand new one.

Yeah, exactly what happens.

Okay.

And we've no idea what's in it. We don't have

all discountes on it based on what's put in it.

So we've no idea on the margin of most of our product process.

Yeah. There's no cost to serve at the moment, aren't it?

Yeah, there's no cost to serve because then there's

a bundle with it. The bundle's not a combination of

things that we've discounted in. It's just, it's a bundle of surprises.

Yeah. So then...

We could bundle three things together which

actually bring your margin down as opposed to,

well, if you sold this, these are the two things you

want to sell to bring the margin back up on that account.

The other piece of thing that's important with this is,

and it comes back to the product side of things,

is having clear product descriptions and definitions so that when you're doing,

so when it's making the recommendations based on what a customer is looking for,

it has context to why it's recommended products, which,

you know, I can see it's got that in here,

but we need to have that in the

metadata to actually enable that recommendation to drive.

Which probably FedSundir will call it the data quality piece.

Yeah, yeah, yeah.

A little part of that doesn't work for

this capability that needs to be built out.

Yeah.

And that's the first people in Forma right

now, and they have this project as well,

it's a mix of experts coming in and saying that this is what it looks like,

but it's just synthesizing that information

across the taxonomy and defining it up.

And you can't really do it across events, of course.

You can either go to a portfolio or an event, I haven't kind of wrote that out.

But I agree with that, because until that's

there, you can't really have a combination of things.

Yeah, and the same on the floor planning side of things.

I think one of our floor planning

systems, two of them aren't integrated with Salesforce.

So even if you are putting propositions together in

terms of how much floor space you want to sell,

someone manager goes and looks in the

floor planning system to see what's available

in different areas. So that's the whole sort of, yeah.

And it seems like the, you sort of talked about

pricing. So it seems like, so we had for the list

prices there and then kind of bundling prices. And

then I'd imagine that the ability to then provide

dynamic pricing, okay, and then make that

intelligent based on certain things. And, you know,

two different exhibitors might get a different

price for the same things because, you know,

one is more profitable than the other,

for example. And so you could then maximize,

you could optimize your pricing.

Absolutely. Where we have differential prices,

it's normally based on how valuable they are to be there.

Okay.

So one of the things that's different about trade shows,

it took me a little while to get my head around because of conferences,

is actually, although we want to charge exhibitors for being there,

that's the whole part of our business

model, certain exhibitors, if they weren't there,

they would ruin the show. They're not being there, they would ruin the show.

And so I remember talking about ETH,

we've got some key big brand name individuals,

and actually they pay the large rates.

Okay.

They have huge demands, but the margin we make them is not very high,

because we want them to turn up, because

then everyone else pulls out to turn up.

Okay.

They're like the acre tenants.

So I guess that comes down to, you know, we want to make pricing decisions,

which might vary across the period from sort of

now until October, if we think about that event.

And that pricing decision or recommendation will

be based on a number of parameters,

such as are they an anchor, exhibitor, Cray, or whatever else it might be.

And that's at a high level, but there could be a number of other parameters.

But from a commercial team perspective, so when

they price it, is it based on their own,

based on the conversation that they have and what they see as fit at the moment?

So overall, there's an objective, a revenue target, right?

Then there is some discipline.

I would say there's not no discipline.

There's some discipline that you're kind of pressing once that's been set.

But it does vary, and it's really quite varied,

because of the things that Gareth has mentioned.

And there is some leeway for discounting.

But I think that typically needs to be signed off

by the event director of the MD in that business unit.

So again, this is one of the least unstructured parts of our data heads.

It's frustrating because you can see the real value

of the data was structured in a different way.

It was standardized.

It's just not how we've gone to market in the past.

So one of the challenges is how do you

prove that doing all the work to clean that up

is going to accelerate our revenue?

And typically, not always, but typically our

products are usually quite important in their market.

So there has never been a commercial incentive to say,

okay, we need to get our shit together because we have a lot of revenue leakage.

Now, we know there is, but it gets masked by the power of those events,

the criticality of those events that you, in some cases, have weightiness.

So it's like, okay, it's not.

And so that's, I guess, a big challenge for us when we sit here and think, okay,

we can have a marginal improvement.

You know, it's not going to go from 5% revenue growth to 15%.

It might go from 5% to 6% or 5% to 7%.

If you aggregate that, that's a massive change for our organization.

But down at the individual level, it's like,

well, how much work do I have to do?

Do I have to learn to do this new thing?

Do I have to, I can't do the things I used to do?

It becomes a massive change management project.

So that's, it's just a, it's just a

challenge that we have in terms of that trade-off.

Right.

I don't know if you're either a customer client.

Yeah, but do you have any targets about

space that you give to the commercial teams?

Yeah.

So besides space, you have those targets and things as well.

Yes.

Usually, are they met overall from an organization perspective?

What do you think?

Like, you mean the space targets or the additional?

Additional.

Typically, it will be some combination of sponsorship.

Yeah.

Which will be serious of things I saw on that list.

Yeah.

Now, this is, but there's also, we would not,

especially in Europe, our managing directors

are a bit ambitimate about specs because

selling trade shows places with great margin, sort of 40% margin.

Yeah.

Some specs is really easy.

Sponsoring the toilets, a bit of signage is still great margin.

Yeah.

But a lot of sponsored things actually require a feature to go into the show.

And actually, they're a bit margin-destroying because,

that they're good, but they're 25%, they're on 40% margin books.

And sometimes, those features can take space that

you might want to start a visitor instead.

Same.

So, it's not really an obvious question of just keep adding sponsorship.

And it's, and this is where the discipline comes in.

It's getting a little better now because

it gets highlighted, but sales team will often

try to bundle in some sponsorship, some features,

because it helps with the, with the space sale.

So, sort of, you know, thinking, thinking to the

future and sort of thing, you sort of talked

about how to, you're choosing successful and

it's really easy, making those money, terrific.

Obviously, you know, this is going to be improvement.

What sort of, you know, rigor or, you

know, details required to then put a, you know,

put a case score to say, all right, you

know, here's an event, we're going to go do this.

Okay, there's an investment or some, you know,

services to go and build, you know, some things

that we kind of see on the screen.

And this is what we think is going to result in.

It's going to, you know, result in an uptick of, you know, the revenue.

Our margin is going to improve because

we'll have more accurate visibility on, actually,

the cost of the items.

Yeah.

It'll be...

I'll be honest, there's not been a single

company, you know, I, I speak to companies

that are making $20 billion a year and you

go, you go, really, you're running on a spreadsheet?

who know in their market what's going

on, personally improve the window scales deals,

they know the margin in the back of their mind.

They're doing all the calculations we're talking about on the flying methods.

So that's why we work.

So what you're asking is, do we, that's what the employees do,

we're taking that work away from them and

we're standardising and want to prove that by standardising

we can do it better.

So my question to you guys is, having been in other companies,

is that easier to do on a

failing event where everyone's worrying about it already,

or is it easier to do on a growing event when you have the acceleration event?

Because that first step of going, in essence,

we want to take away an event director's work

and replace it with their computer, when they're

already doing a good job because we've got massive

margins, that's the hard part of us. It's not

a formal business case, it's coming across why is,

why is a computer doing that best in what we're doing already?

You know, I think the answer was, so

the answer will depend. And so for every person,

we have to figure out why would they care.

And so you've got two different sides of that spectrum.

Now you've got to, I'm making loads of money

anyway. Okay, so you're asking me to change what

I'm doing. And I've got all this autonomy and

like, I've been doing this job for 20 years,

and etc, etc. Okay. So, you know, there'll

be, there'll be different ways to implement the change

based on where people fit. Okay, but one thing is

true is that when you bring a new technology in,

it doesn't matter what it is, you know, there'll

be some resistance to change. And so there's another,

we're doing this for another events company,

it's, and if you think about agentic solutions,

you know, having them transparent to the user. So

using the same tools, okay, and so there's another

demo, we can show you at another

point, we've got another synthetic work environment where,

you know, showing how somebody would do some, you

know, a data analyst, okay, for an event. And,

you know, you know, the current state, they go

to power, you know, the get a reminder on Outlook,

and they open up Power BI, and then the data

is not there, they need to export to Excel, and

they do some V lookups and everything else. And

then you turn on the agents, and it's transparent

to the user. Okay, so it's the same tools

they're using, you know, Power BI and everything else,

but then the agents, you know, sit transparently in

there. So to your point, we have to think around,

you know, who are these people? Okay, you know,

the person that's got a, you know, a show,

which is hugely successful, why would they care?

Okay, versus, you know, the one where it's not,

if it's failing, that's probably a little bit

easier, because people say, we want to be better.

So we just need to think about those use cases

of how we then position it to get people on board.

Otherwise, they could be reluctant to the change.

Yeah, and the other way to look at it is

the way we have done it. One is looking at

feeding and current, the other way to do

it is people who are most aiming to change,

even directors. So that's the way to look at

it as well, because the ones who want to get

new things in place, they increase their revenue,

right? So the business case here is increase

in revenue, that's what you're putting into it. As

long as they are even able to do it,

it makes it easier to start somewhere and let them

champion it. So it helps you champion that cause as well.

So what we have seen in XP is typically

some fall somewhere in between, who are not very successful

because they won't say that, I'm going to come and

touch me. The ones who are not doing so well

because you're not confident that there will be some uptake

on that. We don't know that, but I'm just saying.

So that's it. If you see somewhere in between,

there's some element who are happy with the change

and say that, okay, let's go ahead and start with

one event, for example, then take it in a portfolio,

and then take it in a portfolio of your

clients. When you've worked with other clients or clients

implementing something like this, what a, you

don't have to tell me because it's probably

a commercial sense of it, but is it

meaningful uptake? What were the challenges? Was it data?

Was it people? Was it process? I'd be really

interested to hear how you worked with clients who then

really try to implement it and obviously

faced some of the changes, faced challenges?

Yeah, it's all three people in process. Data

typically because of the fact that how events

companies work, right? So typically, you see,

there have been programs where they can get

data right, their quality as well, but what you've heard

from just at least you have got it to some

extent, right? You have a platform in place, you

put that data together. The data quality challenges are

slightly different because they are upstream,

which cannot control directly. That's one thing,

I believe, is in place as compared to what we've seen

with others. And you have something on top of it already.

The people that we talked about, right? People is

a big challenge, but as long as you have the

right champions in place that you can identify,

it makes things easier. With READ, we started with

Pharma, for example, where we saw that they were happy

to actually get this on board. So they were meeting

the targets, because every company has digital targets

as well. So they were falling short of it,

just short of it. They said that this is a

good chance to actually get that over the line and that

was the starting point for them. There's a motivation

to say that, okay, this is going to help us

actually get us over the line. So that's

where the people, the team challenge still comes in.

The idea is because this is something that's

happening at home. We've seen a lot of change

in terms of technology in the last three

or six months. And this is something that companies

have to adopt in some shape or form. But

at least what we've seen is you have the right

combinations in place to actually put things on top

of it. The other part is process, which again,

I agree with. There are things that need to change. Like

I said, one way to think about it is that you have

these large events like the defensive events and this,

IFA, for instance, which are on the other side

of the scale. And it's not just humans who

will be working with the exhibitors in this case,

it's close. We can have 8 or 4 people,

but that can happen somewhere down the line. But

will you define that process upfront? And I'm

not saying, I'm not stringing about defining the exact

process, because a lot of it will still happen in

the cause and you'll never get that in place. But

probably not for the platinum exhibitors, so to

speak, but the rest of them, they can follow

this process. That's what I've seen. You'll

have the top exhibitors in the sales course,

which will always have that portfolio of things

where they'll call up and get that thing down.

But in spite of that, you'll have recommendations

coming from there, because the sales, what we've

seen in the past, I mean, a lot of commercial

folks did not take this up right away, because they

thought that, you know, I know what the customer wants, I'll just...

Just do whatever, pitch, pitch whatever I think.

Exactly. But what we have seen now is, with

this technology coming into play, it tells you a lot

more. And a lot of context.

Exactly, the context. And the signals that

you get from your data, from your external

thing, you won't get it right away, because

you can't refer to each other in the exhibitor,

and you don't know what's happening this morning, for instance,

right? This is what you would get out of this.

And when the, during the implementation, have you

gone back and, or has informed gone back and

looked at the percentage uptake on the recommendations?

Because, obviously, you've got a couple things that

happen. One is, here's a recommendation engine with

the next best action, with all those different

signals. Then it's like, okay, well, how

often do the customers actually take out those

recommendations? Then there's a sort of loop for me,

which is around how satisfied was the customer on

the delivery of the product, which is great to have

a list of inventory, but not happy unless you benefit

credit. How does that start to feed

into, again, improving those recommendations? And also,

you know, frankly, improving the product development, because that's also great.

Great. So, the improvement part was CSAP, so that was specifically included.

CSAP, okay.

Yeah, that was specifically included in terms of recommendations.

So, AI Informa had this loop in place, which

is known, in terms of what they do with audience,

and because they have content as well, so

they look at how customers actually go through digitally,

so they have something else, tracker, passport,

which is interested enough, similar to what you

already have. And then there's the comment, right,

based on how you can actually improve the audience

engagement. The segment is inside that kind of

data, but it's inside that one where you actually

understand what's happening with the equipment. But

that includes CSAP as well, mostly matter.

And obviously, you can track all that in terms of,

in terms of the response rate. So, if you know,

salespeople today are emailing people and saying,

we've got some products here, whatever price,

you can obviously track that in terms of that

was the response rate. We now have some, you know,

AI generated response, which is going to be

more tailored because they're pulling in the signals.

And then we can obviously track the response rate

there. And then you have the other aspects of,

okay, we're at the pricing, is the pricing, is

the pricing better? And if the pricing is dynamic

and looking at more signals, then the, you know,

the uptake of those will be, will be also better.

Where you guys have done this before, how

much of what was needed for that measurement

framework to actually be put into place

was ready or not? Because things like that,

probably even something simple like I've been able

to track, what's the conversion of the salesperson

who sends an email versus the email they send

from AI. Like we don't track what emails the salesperson

sends, you know, as examples, right. But

it's, I think that's the stuff that's really

because, yeah, because I think the challenges you

might, let's say we could show that's had really

good growth, for example, is there can be so

many other factors that are driving that growth as well.

So it wouldn't all be, you know, if it was

10% last year, now it's 20%, that outlook wouldn't all be

down to this. In reality, it might be down

to a customer, there's a new product that needs to

launch and they've suddenly just going to spend an extra half a million pounds.

Those are all the details that we need to get into the discovery to understand,

because we want a positive business case, we

want to say, this is where you were, okay,

then we made a change. And then it was a

positive change. And then the metrics that we talked about,

increasing revenue, increasing NPS, they all improved,

because, you know, we want that. And so

that's all the detail that comes out of discovery of

like, how do we how do we track these things?

Because I think we all know intuitively, that it's going to make things better,

but then the question to your point is how

much better? And because then then the question comes,

well, do we, you know, do we do this?

Okay, or, you know, do we have a small pilot,

actually, this is going to be so good for

the business that we'd like to do, you know,

we'd like to do this for like the next 10

events or whatever, like just work fast in our vertical

place. So that all comes in a discovery in

terms of understanding how we think this, you know, what

your, you know, what your environment looks like.

Okay. And how, so what, switching away from this,

what does your commercial engagement typically

look like? So you talked about discovery,

discovery, there's bill faces, obviously, what, I think I remember seeing this.

Yeah.

And this is what we do.

So what we typically do, Adam, is, so if

you want to engage, we always say that starts more,

right, you know, the first three stages, what we tend

to do, which is discover looking at what you already

have, and because we have event background, that

shouldn't take a long time, given the experience

that we've already talked about. Envision is the part

of looking at what that means from a business

perspective and from a cost technology perspective

and a change perspective, putting that part together

and looking at what does starts more mean and

that's the true part of it, where we actually prove

that value. If you say, hey, let's do DTX, for

example, at an event. So we work with you to actually

ensure that the things quality is for

that particular event, you prove it, measure it,

and then you actually scale that up, which is

the transform phase, right. So you take it across

the events within that portfolio or growth portfolio

and we recommend that portfolio that should apply.

And then one is you start adoption yourself, right.

So that could look at different things. So for

example, if you could start with DTX, that's just

an example. We typically would go deeper into the portfolio.

First. Yeah, first, and then you take it across,

right. But depending on which events you want to do,

and as I said, there are different parameters that

need to be considered as well, who's able to change,

and we can actually bring that all of that to

you as well, because we have worked with commercial teams

and we know the behavior, we know the challenges,

we know the resistance at LTC, but again, of course,

we have support, we have gone with it, because

we know the technology that you have in hand today.

This can be really game-changing in terms of what

the commercial teams are going to get out of this.

And picking that event, picking the first

one is really important, picking the pilot,

because to your point, we want to make sure it's

successful and also we want to learn. So we don't

one which is too easy. So we had another

customer, for example, that a couple of months ago,

they were recommending, right, our pilot site

should be Saudi Arabia, because we've got 450

people out there, it's nice and self-contained, etc. We roll

on a bit of a month and say, are we sure

that's still the right location? Okay, so, you

know, thinking, we just picked DTX, you know, randomly,

but thinking around what is the pilot site? What are

we going to learn from that? Okay, how do we then

scale out from there? You know, if that one's

successful, what do we do next? So there is some

conversation to be had around where we should start.

So we can actually learn and then of course,

at some point, you need to say, well, if we've done

this, what does it look like if we roll this out?

And we, you know, we need to learn enough about

from the pilot to better then model out what this

looks like as we scale it out. And if it's too

easy or too small, all of a sudden, and everyone's super

friendly, we get to the next, you know, the

next event, for example, and, you know, it goes horribly,

of course, and then our pricing is all wrong,

as an example. So the pilot site is really important.

Yeah, and one of the parts and measure in

that way, if we want to bring to the table,

is not just looking at data and say, hey,

this is what will happen downstream, you know, look at

upstream as well and say that these are the changes,

you could make that to be better for you, because

this is what you've seen. So we have

seen larger programs as well, right? Again, what,

enforcement, for example, so we've seen that happening

in front of the eyes, how that has changed,

how they were super interested. How many events

is this running across now in the format?

Sorry? How many events is this running across the terminal?

It's about 4.50, am I wrong? Yeah.

Because they're still acquiring companies, they're acquiring 8 targets.

Yeah, they have, yeah, they have 4.50 events.

Yeah, so that's right. And is this running across?

Sorry, across this? Are you talking about the format in general?

Yeah, so you're, um, the upsell, you mentioned that.

Well, that is for on-exprime, so Informa has done

parts of it, so the beta showed it before, right?

This was even in Informa.

Yeah, the technology is moving really fast, and so

if you look at sort of six months ago,

so it's completely different. So the way, you know,

the way you solve, you know, bundling six months ago

is sort of different than you solved today. So

this is how we solve today with other customers.

Yeah, I was going to ask, I was going to ask on that, because I guess in terms,

because I think you mentioned that you guys did

quite a bit of work at Ford as well,

other than that was built by Ford or not, but

I guess in terms of workflow, there's like a lot of

what's like, you know, the engine there's the

models that's in the background to do the recommendations,

stuff like that, right? Or the data that

you could get access, you know, to Claude's APIs,

or whichever platform you use in the background

to, you know, look at that, do the analysis,

put the recommendation back in a metadata layer,

for example, and then serve it up through

the platform. I guess in terms of where you see

teams working in six months' time, do you see them

like work in there, or actually, you know,

is the value involved in a number of skills,

which when a salesperson works with something

like Claude, that's because it would have access

to the same data, for example, which

would go, okay, well, these are your customers,

that's the analysis, these are our recommendations,

here's the email that's integrated with Outlook,

it sends the email, it creates the logs, so

that's doing all of the measurement framework in the

background, it understands every customer that it

has touched, and what is different to them,

you know, versus the master of the business that hasn't.

And yeah, I understand, this comes up a

lot, and so generally speaking, sort of the conversations

we have, you sort of start with the value

chains, and you say, right, what does the business do,

what are the value chains within that, the

business process, et cetera, okay, and then it's a

conversation around, you know, for these things that people

do, which ones are going to be solved by

some sort of AI solution or application, and maybe

the company should lead on that, because they just

know it a lot better, okay, maybe they have some, they

have some, their own, you know, head of AI, et cetera,

so there's those. Then there's the ones where you

might go to a third party, okay, like us,

for example, and then there's the use cases, which

can just be solved by Claude, okay, or whatever,

Gen AI, because it's very capable. But the idea is

to have a framework of like, of all the work that

has to be done, which ones can be solved by

Claude and user, versus, you know, some sort of AI app,

or, you know, and depending on who's going to

go do that. And then the other one, which we,

you know, discussed bringing today, but we

didn't, is thinking around because the technology changes

so much, it has to be modular. Okay. And so, you

know, how do we ensure that you have, you have a,

you have an application and a, and a logic flow,

and we can bolt in, you know, maybe there's a new

anthropic around the corner, that we want to kind of

bolt into it. And so, you know, with some of the

tools to have developed internally, you know, it was

swap and change a lot of the, the backend technology.

Yeah. And so, for example, a lot of things

we use internally now, you know, that's powered by Claude,

because it's just so much, it's so much better

than, you know, what we had six months ago.

But at the same time, what we've done is, that's what

we've learned as well. So you can use Claude to work

kind of, to model it in something around the

corner again, and it's probably a couple months away, right?

Yeah. But what we have done is abstracted that away,

and this event is an example, so in the background,

I don't know how to change what the model is exactly about.

Exactly. And just, not just model now, because

you need agents, because it's managed agents as well.

Yeah. And that's something you need to have

in place. So that, again, framework that you know,

like just ADP and stuff like that. But the

models continue over your time, and that's what we have

abstracted today. Julian was referring to the

marketing tool, that it's homegrown fully, like,

AI, it's AI and everything on which you

can shape separately from the vector. But again,

what we've done is abstracted away what AI looks

like in the background. Claude is the best at the

moment, but it's not seen as expensive. Right.

So then we have looked at codex right now,

on the other side. So those are the things

we are changing, but we're keeping the tab as well

on what that looks like. But that has to be abstracted

in some shape or form, because it will all come back

to the apps, and AI will be a layer on

top of it, of course. But yeah, that has to be,

that has to be minimum, that makes sense.

And so what is your typical commercial model?

So if we went and did this piece of work,

I don't need to tell us, like, down to the last

pence, but range-wise, what are we talking about if

we wanted to do, if you're going back to your-

Yeah, I'm going there, exactly there. Just another

example, but I'll come to the other day from.

Yeah, if we go and do a discover, envision,

and prove, because that's kind of where you make a

natural decision, do you do more or not? Yeah.

What would we talk about in terms of money?

So just before that, I'll come to that as well.

Just before that, what we would do is do a pre-discovery

a couple of passwords, and then we would do

a free workshop, because we have to understand, right,

what are we looking at? Are there any specific,

and this will be a window. There's more commercials

in place there. And based on that, then we'd

say, this is what it will look like, exactly.

Because what we would do is, again, from a pre-discovery, four to six weeks,

it was meant to be four weeks, it took six

weeks because of that, that we were working with different

even digital and different people. But we

knew the data there. We knew the systems,

we knew the data, and we were already in

there. What we would typically do is do a pre-discovery,

couple of hours, four hours, depending on, and

make sure that that falls into place first,

and then we give you the commercials. But

what we typically research is, this should be between

six to ten weeks, again, depending on event and

data that you're looking at. So if you have data

and process and people already ready, in some shape

or form, it could be, the timeline would be much

shorter, right? Because you're talking about certain bits of

changes, but we want to make sure that people

are using it at the end of the day. So considering that, it

will be six to ten weeks, is what I would say for us.

Yes. And the range would be between,

again, between the highest range three, is between

60 to 150K. But with the outcomes as well. We

want to make sure there is change in revenue for you.

It's not just about saying that, then you go

and we take a step back. And plus with upstream

recommendations, which I think, because what we have

seen with these companies is, and what we have

gained experience, then you do some upstream changes,

like we talked about as well, in terms of

data quality, in terms of how you work

with marketers, and you mentioned that you outsource your

marketing operations at the moment, right? Is that right?

A mix, yeah.

It's a mix.

It's a mix.

It'd be good to know that as well.

It was the social and the...

Oh, social, that's fine. Okay.

Yeah, yes.

So the email will stop you ourselves.

Yes.

Oh, you ran it outside.

Okay, cool.

Okay, sorry.

So your campaign planning, you know, the upside of things is all internal.

Okay.

Outside of email, a lot of the actual activation is what it comes to.

Okay.

Well, that's good.

But then most of it is still in terms

of, so you've given us none of the first stop

rate to do quite a bit of work. How

does that then scale? Is it a license fee and

CNN? Is it...?

We can do a mix and match with that. So

by that I mean, if we know how it works initially,

initially when we PNM, that's what we would recommend

because you don't know how we work with it.

We don't know your environment as well. But if

you get the first success out of the place,

it could be outcome based. So for example,

let's say, if you do one event with TTS,

let's pick up other events in the port for

you. Then we say that over a period of time,

depending on when the events are falling to place,

six months, this is what we deliver to you.

And again, you can have a conversation on that,

right? Depending on how you want to do that.

And it's a mix and match as well, because it's not just us doing it on our own,

because then you can have a mix and

match. Your team's now, you're picking that up and

extending it up over there. And so it could be both ways.

Okay. Thank you.

It just depends, you know, if you think about like there's 10 things to be done,

depending on, you know, availability and the capability of the internal teams,

maybe they can do the first two, or maybe

they can do, you know, number one and number five.

If you think about the various steps in

the process, it's just about figuring out what's

best for the company. And then how do we, you

know, how do we get the outcome we're looking for

to then, you know, make them make the company better.

And the other side of this is

because now you're working with feedback companies too.

We understand speed, value, and what e-commerce companies are looking for.

That's what happens. And I think we

know, I personally know that's not really well,

because of my experience in the past, and

what they would be demanding of all of you.

So we exactly know that. And that's why speed

would be, yeah, speed is something that we work

with for a while, no doubt for it. If you

say six weeks, we'll get them six weeks. Of course,

if there's support and anything coming from you,

that should be from, from our perspective. And

given the fact that there's a platform that

you've built on the page, Justin, that seriously

helps a lot, because then you're not able

to do something from scratch on the other side.

Conscious of, we've got a few minutes for Gareth Esther.

Well, I'm going to, excuse me, let me select it if you're upstairs.

I'd ask Jason's name for the three of us to get your partners.

Are you using this initial?

Sure, okay.

I think you probably read the thread

of the challenge through the conversation so

it's very helpful to see it in practice, it's

always nice to see stuff. Which is the idea.

Which you can visualize it. It sits within the

things that we would like to do. And the reason

we're gonna have to have this conversation is,

and also with our commercial leads, is like with

all the other things we're doing, where does this

fit in? So it's not about whether we want

to do this or not, it's more about, because

we have so many other things that we're doing,

how can we, because if we don't have a

commercial partner, no matter what I say, Justin says,

or Gary says, it doesn't work. So there's a

bit around that, there's a bit around how does this

fit into the roadmap that we're thinking about,

particularly around the use of AI for most

organization. And to be pretty candid with you,

we are more focused on audience at the moment.

And that's because there's two components to it.

There's still an opportunity here, because one of our

focuses is around monetization of audience. And

we have certain segments of that audience,

it's not necessarily every single person, there's certain

segments that we think have a much higher

monetization propensity. And things like, next, that's

offer or recommendation engines and things like

that. Those are the sorts of things that we would

be interested in. Which is probably a little bit more

aligned in terms of our frequency of where we want

to go. So generally, how I'm thinking about it is,

how do we get audience, this was asking about the

demand gen, I didn't say, can you put it to audience,

but how do we find more of the right audience?

How do we then convert and monetize, well, convert all of

them into participation as many as we can into the

show? And then how do we monetize a segment of that,

at least initially? And then it flows through

through the customer journey, which is all the

things that you've been seeing around these

AI concierges or co-pilots or events, it's that

identity experience. So you think about that end-to-end customer

journey, how do we find them, how do we

convert them, and how do we make sure they have

a great experience on the show? So that's kind of the

first. Why is because that's what our exhibitors pay us

money to have access to, and we can also drive

monetization of the audience or a segment of

it, which we've historically not been able to do.

So that's kind of our priority kind of mix.

So yeah, so we can bring that to the

table as well, the audience monetization part. So the case

you did, level four is about that. This is buy

and seller on both sides. For example, in my PGA

that we've done. Similarly, what Informa has done is-

Some people like you said, yeah, we gotta go.

Yeah, sure. Sorry guys.