The AI Edge for Modern Growth | Avidly & HubSpot

I want to take away sort of the sci fi feeling about AI and make it a lot more pragmatic, relatable to your actual business.

You work across many verticals. Construction, manufacturing, you work with a lot of SaaS companies. What are you seeing is the typical offering that these customers need in this new sort of agentic future?

That's an interesting question and it does a little bit differ between the businesses you can say in the more traditional businesses like manufacturing and construction, it's very much point solution based ideas that they have come across some solution they thought were really valuable and want to see can we do replicate this? If you go into SaaS businesses that are digitally a little bit more mature, they look on, okay, how can we restructure? What do we need to do? How do we rethink this? It could be the whole buyer's journey, they want to change out. For instance, what is evident across is that they sort of jump straight into the solution and they forgot a little bit the platform you need in order to make this work out properly. So normally we need to sort of pull them back a little bit, take down the expectations about the quick win and come back to the, you know the basics first, which is to organize your data.

And you were mentioning earlier that it's you have to reel your customers back in sometimes. And I was talking to some partners around. AI is not a silver bullet. But once you actually get your data in order and you get it set up, it can be completely transformational and feel like a silver bullet. Do you have that experience with your customers?

100%. 100%. It's a little bit. Who addresses it to you? You have different stakeholders in a business and the larger type enterprise you interact with, some of the enterprises are, some stakeholders are not as mature. But then if you go to the C level, they've been to events, they've seen things and they sort of want to push that through their organization with maybe not super clear on exactly what they're looking for. That puts a little bit of pressure on us as a partner to give them more of a consultative advice first before you look into the data and what this is actually, what's the business value you want to sort of extract out of this? Is it margin improvement? Is it new type of revenue growth that you're looking for and you have to sort of start digging a little bit more point Solution can sometimes feel like a silver bullet even though it is just one small thing. The true value for me what you see is that the lifespan of a lot of These solutions are much shorter than what you normally would expect. I'm a big believer in this sort of compound effect that, you know, you need to build on small minute changes over time, builds a big change and sort of shifts the whole attitude.

Something you said you hear a lot people saying, you know, data is the foundation of AI. It doesn't work without data and garbage in, garbage out. But you had a twist on that statement, I think, which was garbage in, hallucinations out.

Yeah, true.

What would you say your typical customer's state of their data is when you start working with them and how much work for AI actually starts with data?

I would say it's pretty terrible. To be frank. Nobody. You could say if you start with the quality of the data, we normally categorize it like A, B, C, D type category. So if you go down to B, you might have 70% accuracy, for instance, on certain data because you have duplicates, you have incorrect data and all that. So that has to be cleaned up. And it's not the one one off solution. Then you need to sort of maintain that data quality over time. So that's more of a recurring business for us to make sure that they have that quality of the data across. The benefit of AI is that it can help you to organize that data a lot. Like taking duplicates, for instance. You can take a large amount of data and get that sorted out quickly.

How much quicker can you get people's data in order with AI by park than you could in the past?

Well, it's, it's minimum 10x, but I rather think would say that it's a lot more than that.

Wow.

I really do believe that it's a little bit on how you get people to utilize it, that if you take the traditional sort of chatgpt, you can get lost in just writing an email. All of a sudden you spent one hour on ChatGPT because you think that email become better. But if you spent that hour actually writing the email, you probably do the same amount of time. So you need to work a little bit slower, sort of thoughtfully with all these different tools where you can see the best benefits. And I think there is more to build up. I think the underlying, if it's a template, if it's a playbook, instead of just going into each and every small item and try to use a new tool for each and everything.

You know, the complexity of switching systems, it's so much easier now to get up and running.

I would love to say yes.

No. You disagree?

Well, it's always painful to change system. Anyone who's changed, you know, even to install a small, simple software on your computer, it's just a mess. But I do think that yes, it is significantly easier and that's improving in light speed at the moment.

You're still delivering the same outcomes, but you're doing it faster and you're doing it with different tooling.

In one way you can say you deliver the same outcome in terms of integrating and implementing a system. I think what you do better, you generate a lot better insight, a lot faster. Our own Venn diagram has sort of velocity, visibility and impact and all of those three are highly impacted by AI. So if you're a business, you know, the faster you can do business, longer visibility you have on your future revenue stream, these it's going to be to plan and the impact you can generate is significant. So those three actually elements you, all of those you improve with with these AI tools. So the insight piece is not only the speed of implementation, but it's definitely also the insight, the value of the.

Insight, the business insights. Yeah, yeah, yeah. It's transformational.

Yeah, it is transformational. And I think a lot of people are afraid of these tools. Are they going to take jobs away? And they might take certain jobs away, but they also will generate new type of jobs and competences.

So I would say that Avidly is an AI first partner of ours. And when did that pivot happen for you? Did you have an aha moment when you realized that this was not a flash in the pan trend?

We did have a few people that were into machine learning and stuff like that early on, all the way back actually in 2019 when it comes to us as a company, I think that was more in 2022. And of course that was when ChatGPT became sort of easily available for everyone. It actually started with my oldest son who told my younger son, you don't never need to do another homework. And then they showed that place and I thought this is actually pretty amazing. And still it was all data it was trained on at that time, but just started to realize the impact of this, how big this could be.

I've been in the HubSpot ecosystem for about 11 years now and you said, it's exciting, it's fun. And a lot of people have said this feels like 2010, 2015 era, where inbound was new. It was so transformational. We were saying there's a better way to do things. Do you feel this way about this moment?

I do, I do. I've been in this since 2017 and I told this to you before, I'm just extremely passionate about what I do. And this is a new passion. It's just, it's unbelievably interesting what you can do and it's like an unbroken territory. No one really knows how this is going to play out. The only thing you can see that you want to be in the game, you want to be early in the game. I still think it's super early. Even though we feel we've been in this for a few, few years now or several years.

Yeah, you say we're early, which I agree. But you know what everyone is saying about AI and how it's different than other transformations in history is how fast it's moving. And so on that spectrum of being excited about the future versus sort of the doomsday mindset, where are you in terms of the opportunity that this has for customers but and for services based businesses?

Yeah. If you look like historically you said okay, you have a cycle of 100 years. Then when automation of robots it came down to like 50 years. So sort of the transition. Now we're maybe talking three to five years for a transition of a whole business or industry. And that's okay for me. I don't mind. Because if we are sort of say in that space, we will be able to work with it and not sort of feel obliged to or forced to go into it.

The IDC released a brief this year. It's an update of something we did back in 20 years ago. The opportunity around the HubSpot ecosystem was described as applications ISVs, software that integrates with HubSpot versus services. What our solution partners offer and the updated projection is it's a $30 billion ecosystem by 2028. But the categories are different. There's this blurred line between software and services now with this agentic opportunity in the middle. Is that what you're referencing?

Yeah, I think if you look on many of the ecosystems, including HubSpot's has been that you have sort of the app partner ecosystem, you have a solution partner ecosystem, those two will most definitely start going together. Together much more. So I think that's something for HubSpot to consider. How do we make this actually a joint AI ecosystem and move that ecosystem forward? I think the other super relevant piece is that if you look on that IDC report, 30% something of that 30 billion you talked about, I think it was 10 billion, is actually related to AI type services. So I mean if you miss out on that piece, you are a little bit sitting on the sidelines. So I think you need to refocus and reset that a little bit. The end. You need to be true to your core always and try to build around that core.

So we talked a bit about Agentix solutions for your customers, but I know you do a lot with predictive analytics as well. Can you talk a bit about the other opportunities that AI has opened up for your customers?

Yeah. So I think in general, customers are primarily looking into how do we do this as a margin improvement exercise internally. But it does show that even though we go ahead with a project like we've been working with someone who's been doing for pottery, where they had customer service section where customers go on an E commerce, they go in and look for a certain plate or a certain cup or something like that. And if, if it's not available, the AI agent actually proposed. Well, last time you were in, you were looking into this one. They have a similar look and feel. Do you want to try these out? They go well with this, etc. So instead of just responding on traditional customer service question, they also propose new type of deals. So it was not just saving something like 22,000 hours on customer service, it was also actually adding on potential new business.

So it started as a customer service agent essentially, but now it's actually cross selling and upselling pottery.

Yeah. By just having access to the PIM system, the inventory management, product and inventory management.

And how many hours saved did you say?

That one? I think specifically was 22 full time equivalents.

Full time equivalents. That's huge.

Yeah, so it is huge.

So it's an efficiency. You're saying it was an efficiency project, but it turned out to be a revenue booster as well.

And it was initially thought to be for peaks, you know, you have around Christmas or Easter, you know, certain periods. And then it started to be realized. This goes across always works really well.

Always. Yeah. And I think that speaks to the unified data opportunity, like how important it is to unify data across your systems. Can you speak to that a bit?

The important piece when you talk to clients, because it sounds a little bit boring, but it's not the luxury to have good unified data. It's actually today it's a competitive edge. If you have really clean, proper data, you have a competitive edge compared to your market peers.

I think when we think of data, we all think of structured data, we think of information in a spreadsheet. But unstructured data is a huge opportunity now with generative AI and the ability to parse all of that information how have you been leveraging unstructured data for your customers?

First of all, before we actually go into the unstructured data, we start to sort of define sort of the naming convention and all these things to make that what you want to see as an outcome. Once you have the desired outcome, it's so much easier to use tools to take the unstructured data and categorize it into whatever structure you think is relevant. The other piece of that is that structure might be relevant for this period of time, but you need to make it adaptable for future changes. So also the dynamics that you create into this is very important.

So you recently took on the CEO role at Avidly. So what is your vision as CEO for how your customers will be adopting AI and just the future vision for Avidly?

First of all, it's a super pragmatic approach and vision. I think I want to take away sort of the sci fi feeling about AI and make it a lot more pragmatic, relatable to your actual business. That's the first piece. The other piece is that I want us to be much more of an advisory, feeling the passion for the client. And once you have that passion, you know, whatever knowledge we have internally, you will use all of those resources to drive towards your clients, to make them generate the impact. Then I have a vision for the relationship with HubSpot as well on that, which is I do believe that we come with some real client insights and some real client data that I think we would like to feed into the HubSpot product development because it's so fast moving.

So you're one of our largest partners, you're a global partner. What advice do you have for other solution partners in the ecosystem in terms of how they should be adapting their business model right now?

I mean, if you're completely new into it, I would say start with your own business, not necessarily with client business, and learn on that. And it should always start with nail your data layers first. I mean nail that, understand your own CRM, how it's set up and really drill into that. Then start small, start with a point solution and of course, if it's business critical, try to actually go deep, dive into it, try to even build it yourself. If it is more sort of something like this would be great to have. Maybe there's something you can just take into the business and try it and if not, stop, stop using it. And I think unfortunately also you need to look on how your setup is. For my vision, I have three areas which I focus on. One is the customers. Since I started in February as a CEO, I spent about 30, 40 client meetings, which I love. And the second part of that is also sort of the capital, which is how do we build the business around this to make it a sustainable business? And the third part is the colleagues. You know, how do we build our organization? I think that third part is for agencies that haven't touched upon this, they need to start, okay, how are we set up as a business?

Where do you see the service industry going over the next three years? What will customers still want to outsource and need help with?

I think you can still do that, but at a high velocity. So you might not get this much money. But the simple way to do it. I know a lot of agencies that say, okay, they tell the clients, we're going to do your website, 80% of it. We're going to do with AI, the content and, and the last 20%. You guys have to sort of just sign it off. And we have an editor to help you. So that could be one way you move with that sort of. You just need to be transparent with clients because clients understand that.

So how are you thinking about agents and really the role they're playing in go to market teams?

So agents for us, I mean, as I said in the beginning, we started off very process oriented. So we have a huge playbook for everything we do. And a lot of that playbook can be sort of the challenge there is that of course that's going to be with our existing colleagues that they have all of a sudden as an agent, as a mini co worker and that adoption is not necessarily friction free. That's something that could be sometimes looked upon as a threat. And I would love to say that all of us have sort of AI in our DNA, but we do speak, I think, AI with a little bit of accent still. So we need to improve that. There might be sort of singular agents doing certain work, but it's also coming soon or it's already there in some places that you have sort of a team agent as well, managing other agents for separate tasks. I still think you always have to have a human in the loop. That's very necessary. But I also see that we can do a lot with agents and team agents going forward.

So you've said you're a one platform company. So why HubSpot? Why are you betting on the HubSpot ecosystem?

This actually started 2017 when we started the business. We came across this when this was actually just an app, the market automation app pretty much. And then started to be more hubs. And all of a sudden it's a platform. And we have embraced that all along because we see that we can't keep up with another system like HubSpot. And you're developing faster than we can actually build competence. And it's also, you've been fantastic in terms of growing the market. And for us to ride on that tailwind is a great opportunity. We just need to try to adapt and build our competence in the same speed. For us, if we do this really well, we stay on the tailwind, we help, and we co sell together with HubSpot. That's actually how we make both of us win in the market. So I'm really happy we took that decision.

Well, we are also very happy you made that decision. So thank you. And thank you for joining us and being here today.