HubSpot Inbound '25 - AI learnings from end user best practice

At diginomica we’re always on the lookout for learnings from tech implementations in practice in the real world. One of the most popular panel sessions at this year’s HubSpot Inbound dealt with how AI is pushing change in go -to-market (GTM) strategies.

Chaired by Jonathan BURG, SVP of Revenue, at revenue performance management company, New Breed, the session examined how successful organizations are using AI, based on the results of a worldwide survey of over 1600 HubSpot customers from sales, marketing, revenue, operations and finance. Burg kicked off the discussion:

Last year, I stood on this stage and spoke about disruption. The year before that, we spoke about change, and this year, we really wanted to find that right word, because we're not just being forced to re-invent our GTM strategies, but invent an entirely new motion all together.

Sydney Sloan, CMO for technology, software and services marketplace G2 picked up the future theme:

This is not a paradigm shift. This is a ‘burn it down’ moment. It's changing so much, so it's not a tweak here or there. I encourage people to really imagine starting over. Like a blank blueprint, now we have moved away from traditional models that worked for a really long time.

Cathy McPhillips, CMO SmarterX, an AI centred research, education and advisory company, agreed:

We've re-invented our brand, and we've been looking at what our customers need? Our mission is AI literacy, and that is a moving target. So we're not only trying to figure out what our customers need, and what's happening with the industry, but what's going on with our brand. We are constantly having to re-invent all of these things on an hour to hour, day to day basis.

Bottom line hit

But this constant re-invention is impacting the bottom line. The survey found that only six percent of revenue leaders believe that they're going to hit their targets this year. But there were some key trends from organizations who are likely to hit their targets.

The most successful organizations are investing in automation and agents, but the ones who really skyrocketed in figures from year are investing in talent. So, what is top talent? G2’s Sloan commented:

I hear a lot about people re-designing their organizations, and trying to get teams up to speed. The first thing to do is make sure that your AI skills are on point. I don't think anybody's going to get hired today if they can't demonstrate how they use AI. You want to showcase things like curiosity, adaptability to change, how to embrace change. Make sure you're spending your time really honing those skills.

McPhillips had recommendations for organizations integrating agents into their talent strategy:

We've been hiring some new talent for some of our roles, and we built into our job descriptions, ‘Using AI agents to fundamentally change how you're working and to improve your output’.

She added that knowing how to improve and learning how to do your job better using agents is key.

I built a 'Kathy GPT' that I use every single day. I've been doing this for 30 years, and it's changed the way I'm working. So having your teammates figure out how to use  AI agents is very, very important. It's not like, ‘Oh yeah, I'm curious. It's like, you have to be doing this stuff’.

Re-defined

The most successful companies are totally re-defining their GTM strategies, according to the survey. Burg commented:

Last year I said that inbound [marketing] is dead, and that was re-inforced through the research. Organizations are now investing in a more agile, more account driven and a customized GTM that's more in line with the expectations of their buyers.”

Kerry Cunningham, Head of Research and Thought Leadership at revenue intelligence platform, 6Sense, said some things in the GTM fundamentals have changed, but more importantly users' understanding of those fundamentals are shifting:

One of the shifts is the buying person, as there is now more than one person inside the organization you're selling to. That matters, because it's a lot easier to see when multiple people are exhibiting interest in a solution, and it gives us a great advantage in seeing them, but it also means that we have to be able to influence multiple people, and that those people inside those organizations have different biases.

Cunningham’s company 6Sense has just done research which  found that buyers have done between five and 10 times more evaluation of solutions than they used to. He said:

So everybody that your marketing is selling to is deeply experienced in your category, and everybody comes to every buying journey with preferences that they develop, and personal experience. That buying journey is not about some sort of objective view of vendor information and deciding which is best.

About five or six, 10 or 11 people start a buying journey with biases and want a vendor to come out on top, and they spend six to nine or 12 months arguing about who's going to win, and they're looking at your information to help them either boost their case or knock you out. The buying journey is not some objective evaluation of criteria,  that's kind of quaint now.”

Sloan’s organization, G2 does yearly buyer behavior research that backs this up, discovering that buyers who use LLMs (Large Language Models) to influence their buying decisions has increased from four or five people saying they use them as part of their research, to most recently 90% of buyers, with 51% saying they start their research process that way. She commented:

How do you influence the LLMs to make sure that you're part of their research process? It could be people are bringing their biases, but then they're going to LLMs to do the extra research validation. We've heard stats about people doing research, they are so much further along in their decision and research by the time they come to you.

Data

The best customers, according to the HubSpot survey, are heavily investing in data strategies, and are leaning into predictive analytics. They are also integrating systems across their organizations so that they can quickly have that data available to action across the entire process.

Highlighting this intersection of AI and data McPhillips recommended not only being data ready, but also people ready:

Your people really need to know why, what data you're using, and where it's going. Everybody needs to talk to one another. Really educating your people on all of this is so important.

Burg added:

I think there's this underlying notion of people and alignment, and we do find that organizations that are more aligned around the metrics that matter, outperform their peers.

The research found that the best performers are not just investing in productivity and efficiency, they're investing in insights, strategic planning, and in AI to create the most personalized experience possible. But 68% don't feel ready to take advantage of AI and autonomous agents.

McPhillips urged companies to take that first step.

It's been three years since Chat GPT launched, and you haven't started yet, or you haven't gotten your team to the right place? I have to tell you, be vulnerable, take that first step, just do it.

My take

One needs to be careful with supplier research, but this session highlighted some interesting insights from the research that could apply across the whole AI arena. Top challenges for organizations are keeping up with changing technology landscapes, integrating AI in a meaningful way, and finding and retaining the right talent.