Using AI to Grow Smarter | Fuelius & HubSpot

The most valuable partners will go big on data, they'll build that data practice, they'll specialize, separate themselves into a lane of their own. And I think partners needs become more consultative. I think AI will cause a shift whereby partners will need to be less transactional. FuelUs are a 27 year old business that have been in the HubSpot ecosystem now for 12 of those years. Elite partner and seen a lot of change in the ecosystem, mainly driven by AI and very excited about the opportunity.

How do you think AI and agentic solutions are going to change? Go to market teams, they're going to.

Completely disrupt every sector, every industry. I think it's a real opportunity for GTM teams to become AI first. There's a lot of noise about agentic AI at the moment and I think there's a lot more talk and execution. But also there's a possibility that, and I've been guilty of this myself, there's a possibility that you get roped into the next shiny AI opportunity. It's really important that every single use case is sort of anchored to a real commercial whim for the business, whether that is revenue growth, whether it's profitability, scalability. What is probably quite unprecedented at the moment is that we now have the ability to completely disrupt this sort of linearity that has always existed in that growth equals headcount. You know companies are reaching you know, 100 million ARR with 20 staff and 30 staff and they're sort of armed with fields of agents.

You know fuelus has had this really long history as an elite solution partner and really a pioneer in like digital transformation. How do you see AI affecting digital transformation for your mid market and enterprise clients?

It's no longer a sort of wish, it's a must have. Companies of all shapes and sizes, particularly in mid market and enterprise are small sort of AI must be part of the solution. What we're seeing is bigger gsis and we're seeing consultancies very quickly pivot to AI and people are now hoping that AI solves use cases that couldn't be solved previously.

Yeah. What if some of those use cases succeed?

People didn't have these functions in the business previously and with Copilot and whatnot they sort of now gained that skillset. And even myself, I in my late teens spent a lot of time learning to code and learn to develop and put that down at sort of 19 and 15 years later, haven't touched it since. But now I find myself being able to sort of apply myself to Python scripts and so on and so forth. So there's just a lot of opportunity ahead of organizations to sort of try new things and sort of build new arms their business without that headcount.

Yeah, it's exciting to be a builder and pick up tools again.

Yeah, definitely.

What is your advice to businesses that might just be starting to explore AI and unify data? How would they get started?

I as an individual am somebody that tries to go all in and I think that would be the opposite. That would not be my advice. And I think it doesn't need to be rag pipelines and vectorization and all these different things. You don't have to build the best AI solution around. There are tools out there, agent AI and relevance AI and other tools that allow people in a low code, no code way to try an agent. And I think for me it's better to get moving with AI than perfect something that could solve every single opportunity and problem in the business.

What do you think are the most promising applications of AI, especially those that draw across unified customer data.

What we're seeing in the world of CRM and sales ops and gtm, they will always be examples I lean into because of I guess our experience as an organization. Whether that is, I've seen people use it for sort of predictive deal support. I've seen people use AI to sort of almost be an assistant in that sales process and sort of support on deal forecasting and give salespeople access to what may be missing in a deal to get it over the line. I think content creation, sales enablement, there's a whole host of opportunity. Obviously customer success is a big area where we're seeing and HubSpot have seen quite dramatic numbers really in the number of cases that are now solved by AI agents. So I think anything really that required lots of human touch points, lots of manual intervention has real capabilities being disrupted by AI.

Yeah, I see the same. Right. Your AI is only as good as the data that powers it. And so giving it that complete context and having it be great and clean.

It'S not a nice, it's not like a fun task, is it cleaning data? It's the task that everybody wants to avoid. It's the task that people don't necessarily have the expertise in house to carry out, but it just makes the whole agentic AI piece A more achievable and B give people a chance to really realize the ROI from AI.

How do you help customers integrate their unstructured data so that like emails or PDFs or things that captured in calls? How do you Help them integrate that into their CRM.

It's absolutely necessary and I think it's about prioritizing what we're bringing into CRM first. Everybody has this utopian goal of CRM being a single source of truth. We should be bringing in everything, every single piece of data structured and unstructured. At the moment we tend to leverage the marketplace within HubSpot quite a bit more than we have done in the past.

That's great.

I think we've seen call recording providers and meeting note takers and so on. We've seen them develop plugins now that allow us to integrate that data very quickly and seamlessly into CRM platforms.

Julius offers custom portal development services. How do you know when a custom solution should be built?

I would say our ICP is very much in that top end of mid market and into the corporate space. Nine times out of ten we are building a custom solution. We're not sort of templatizing our builds and sort of cookie cuttering them. It's, you know, we're solving to the customer and we're building a solution around their needs.

With Fuelus expansion into the US market, how have you seen the differences of what people need between the UK market and the us?

I think I've seen this for many years. I think we in the UK lag behind somewhat in terms of adoption of certain technologies. And even now I think GDPR is a very interesting thing in the UK and in the EU whereby there are now sort of AI tools coming out that allow de anonymisation of visitors on websites and so on. And we're not able to use them in the uk, we're not able to use them in the euro that there is more of a appetite in the US to experiment and if something fails, let's fail fast and let's try something and rule it in or out for our business. The UK tends to be a lot more methodical, a lot more carefully considered. I think we see much quicker buying processes in the us.

So what practical advice would you give for people who are trying to adopt, you know, start small and iteratively adopt AI in their existing HubSpot setup?

I think it's about ensuring that every single use for AI and everything you seek to build AI is based around a commercial business case. So I mentioned earlier, does it drive revenue? Does it increase profitability? Does it drive scale? Does it do something that propels your business forward? Once you know it does and there's a real application to build something with AI, I think you have to Start small. You have to look to solve things that can be solved fairly quickly, where you can see a positive result or perhaps a negative result. You know, start small, continue to iterate and don't look away from the ideas that might seem, you know, a bit obvious and not so cool.

We recently released this IDC report that showed that it was a $30 billion ecosystem opportunity for HubSpot. How did you decide to start building for HubSpot?

So our journey with HubSpot's I think, really interesting. So 12 years ago we were very much an SEO PPC web agency. I think most of the partners in the ecosystem sort of started in that path or partners who've been around that long. We realized that SEO had become very commoditized. Every year you would churn 30 to 50% of your customers because somebody was in their inbox telling them they could get them higher. On Google, we saw the sort of rise of content marketing and at the same time saw the rise of inbound marketing and sort of saw this tool that looked quite cool, which was called HubSpot and you know, went to the website, filled in a form and sort of took the process from there. We took a punt and for about 18 months. The honest answer is we thought we knew better than HubSpot on how to sell and how to scale our agency. So we spent circa two years, I would say probably not listening to HubSpot's advice. Two years in, HubSpot flew over to us and said, look, we think you're somewhat of a sleeping giant. Please listen to us and please give this a go. So we co hosted an event with HubSpot in London. We brought 14 of our customers over and within three months 12 of them became HubSpot customers.

That's cool.

Yeah, it was really good. And I think there is an incredible opportunity for partners within the space.

What advice would you give to other HubSpot customers who want to be AI first? And the same thing for partners.

I think for partners there's been a, I would say, lack of differentiation over the years because everybody was a marketing automation partner. Everybody, as you said with your three chapters, everybody then became a marketing automation and CRM partner. And there's been a, I would say a resistance from other partners to specialize by a sector or specialized in a particular niche because I think we all believe that maybe that corners the market for you. But I think it's now more important than ever that partners really differentiate with service offering. AI is so broad that you can't just be an AI partner. You have to pick a real specialism within there, whether that is service hub, whether it's data enrichment, whether it is sort of integration and unstructured data. I would say pick a lane, stick to it and excel in it.

Love it. Thanks so much for joining us.

Thank you.