AI Blueprint for Go-to-Market: Sales Personalization

This is the AI blueprint for go-to-market, a five-part series where Snowflake's own marketers and sales leaders show honestly how they use AI day-to-day. No theory, no hype, just what's actually working and what isn't yet.

We want our sales teams in front of customers more and behind their desks less. And we want their conversations to be high quality and hyper-personalized on the customer priorities. And when you're running a highly federated team, running into hundreds of people across an incredibly diverse theater, doing thousands of transactions in a quarter, figuring out how to actually make that happen consistently, that's not a simple problem to solve.

Hi, I'm Stuart Nyemecz. I'm Vice President of EMEA Acquisition at Snowflake. I look after our acquisition sales motion across Europe, Middle East and Africa. What that means day to day is thinking about how we identify value propositions for potential new customers, how we engage them more effectively, and how we build a sales team that does that at scale. AI has fundamentally changed how we approach all three, and that's what I want to share with you today.

Best case, the cost was time. Worst case, it was leaving business on the table. A conscientious rep preparing properly for a meeting would have to invest a significant portion of their week just to research. Pulling news on the account, working out the tech stack, cross-referencing CRM notes, tracking down the right person to speak to, finding customer stories relevant to that industry and so on. It was not one task, it was multiple separate tasks across multiple different systems and it had to happen before a single productive customer conversation had occurred. And here's the bitter irony. Even after all that effort, the outreach often still landed like a generic pitch. Because pulling research together is one skill, but articulating it in a way that genuinely resonates to a specific person in a specific situation is completely different. So you had reps who had done the work and still sent emails, social outreach, cold calls, that came across like vanilla pitches. And then you had reps who were under pressure back to back and thought they were doing the right thing by being highly active and skipping the research entirely. Both outcomes were costing us time and were costing us money.

Then there was the lack of consistency, which is not to be underestimated. When I looked across my team, the gap between how my best sales reps performed and what my average sales rep achieved was significant. And upon closer inspection, it was really not about effort or raw talent. It was about access to context. My top performers had built up years of pattern recognition in specific industries and accounts. They walked in already knowing the dynamics, already speaking the language of the person across from them, already knowing which customer stories would land well. And a rep with far fewer selling years experience covering a new vertical simply does not have that same inherent context. You just need to find a way to unlock that tacit knowledge which exists across your organization. And once you have the raw sales talent in your team, you just need to give them the context, which today, thanks to AI and a trusted data platform, is a problem that is far more solvable than it first appears.

The most immediate change is in account preparation and discovery. Now a rep can get a real-time insightful picture of an account in just a few minutes. Current news that is actually relevant to them. The latest technology they are running. Recent organizational changes. What came up on the last few calls from different people speaking with the customer. What comparable customers have done with us. What engagement the customers had with our marketing content. All of it surfaced in one place, from the data we already hold, enriched with the data in the public domain, without the rep having to know which system to look in or how to stitch it all together.

But what really matters is what happens next, because the rep does not just absorb the information passively. They use it to form an opinion and then to identify a hook. A new decision maker just joined three weeks ago. A relevant announcement has just dropped. A competitor of the customer mentioned on a previous call is now in the news. A geopolitical event or a natural disaster impacting the markets or their supply chain. Any one of those changes the entire angle of the conversation. You are not pitching based on your generic value proposition, as credible as it may be. You're reaching out because something real and specific is happening in their world. And you have something genuinely relevant and impactful to share with them.

Now, the first thing most people ask when I describe this, surely this just floods the world with more AI generated outreach that everyone can see through immediately. And the answer is it absolutely would if it were generic. We've all started receiving those emails, I know my inbox has never been more peppered with direct outreach. But they're clearly templated, obviously automated. Those messages that signal the sender do not think once about you, if indeed they're an actual real person. In fact, they're arguably worse than no outreach at all, because they actively damage the relationship in your brand before it even starts, and often means all future communications are not considered. The reason this works differently is what it is grounded in. This is not a template with a name dropped in. It is built on real current and dynamic account specific intelligence. The rep writes the message. The rep edits the message. They add their personal flavor. They decide what angle to take and what to leave out. The tool doesn't do that. What the tool does is remove the hours of groundwork and research so the rep can spend their energy on the part that actually requires human judgment. And that distinction between AI generated and AI assisted is the difference between spam and a message that lands with impact.

It of course extends beyond the outreach and into the meeting itself. A rep who walks in with confidence, knowing there was a recent leadership change, knowing what the champion said on the last call, knowing what comparable customers in the same industry have achieved with us. That rep is having a completely different conversation. They can ask better questions. They can connect things the customer has not connected yet. They can be useful in the room from the moment they arrive, rather than spending the first 20 minutes catching up on the context they should have had before they walked in the door. Candidly, this has fundamentally changed our sales process and how much time we spend on discovery compared to building assets of value for our customers, so they can then make an informed decision on how to move their business forward quicker. We can show customers what we can do for their business in bespoke MVPs built in hours, not weeks, rather than telling them what we can do and going into weeks and months of trying to build out proofs of concept. That has fundamentally shifted our sales trajectory.

The technology was genuinely the easy part. What I underestimated was the cultural challenge in getting people to adopt it. When you have a large and diverse sales force, literacy and comfort levels with AI tools vary dramatically. So when you're trying to drive consistency and best practice across an organization which relies on the adoption of such tools, it can be a challenge. Encourage, almost mandate the use of them in the first instance. Make people curious, give them permission to experiment, and then quickly pivot to highlighting the great examples and innovation from the field. Be sure to focus on the old adage, what's in it for me, not what's in it for the company. Once the field understand what it can do for them, and they've seen firsthand the impact it can have, then you will see the adoption. We also encouraged the team to not confuse being busy with being effective and that the tools weren't going to replace them. It was about helping them scale. They were another resource for them.

So in the case of discovery and preparation, the reframe we had to make was redefining what good preparation means. The research itself was never the value. The resulting conversation is. The time you get back gets reinvested into developing yourself, creating thinking time for the meeting, the questions you want to ask, the angle you want to take, how you connect what you know about their situation to something that genuinely helps them. That's the job, getting to value faster.

On trust, I have two things to say. The first is about what the rep is responsible for. Nothing the AI surfaces ever goes to a customer without the rep engaging their own thinking. Not because the output is wrong, but because a rep who stops thinking about what they send stops understanding their accounts. And then when the conversation meanders and deviates, which it always does, they have nothing to fall back on. The tool earns you a fast start. The rep has to own the finish.

The second is about the platform itself, which matters more than people realize. Intelligence is built on our own data, our CRM records, our course transcripts, our product usage data, our marketing history. It's not reaching out to third-party sources without governance or pulling in data we don't control or that's not unique. It only services the data the teams are entitled to see through role-based access. So when you ask a question, you get an answer. It's based on your sales territory and remit. If I ask the same question, I may get a broader answer based on my expanded role within the company. And it's those policy and role-based security and access controls that mean a sales leader can confidently roll this out to hundreds of reps without exposing any data. That is not to be underestimated. The data your people are working on is governed. It's yours. It does not leave the environment. It's a very different risk profile from asking your team to use consumer AI tools and hope for the best.

Start where the burden is highest in your sales process. Very often it's in the preparation and value proposition. That's where reps are losing the most amount of time, where the saving is most immediately visible, and where you get a fast, real win. You need that early evidence because there will be scepticism. And on a sales floor, proof is the only currency that actually moves people. Direction, even from the VP, can get a polite nod and then nothing changes. Of course, we love to measure things in sales, but you have to measure the right things. This isn't really about tool adoption. It is at first, but quickly it's about what the tools are doing for your business. So if you aren't seeing an uptick in sales productivity, in customer conversion, in average deal sizes, in response rates on outreach through the use of these tools, then maybe they aren't being used in the right way.

And make sure you set the cultural expectation before the rollout, not after. Be explicit. This makes good reps better. It does not make preparation optional or effort negotiable. I've seen many rollouts quietly fail because the expectation was left implicit and the floor interpreted that silence as permission to coast. The standard is higher now, not lower, because what prepared looks like has changed. So be consistent with that message and reinforce, force it through every part of your sales process.

The thing I come back to is what it actually feels like when I see a sales rep walk out of a get out of your comfort zone meeting, maybe a boardroom they've never been in before, because they had the context to have a real conversation from the start. They were not reciting a briefing, they'd done the work, the tool would help them do it faster, they had developed their knowledge, and they had an opinion, and they showed up ready. Ultimately, long-term strategic selling and being a trusted advisor to our customers is about two things, value and trust. What value can you bring me and why should I trust you? And the AI tools we have at our disposal today helps us to establish that position more readily, enabling the sales teams to have a better conversation and our customers to get more value from the interaction. That's what we are building with AI.

That's one piece of the blueprint. The rest of the series covers campaign creation, digital mix, account targeting, forecasting and sales personalization. Watch the next one and if you want to see how this runs on your own data, the link below is where to start.