Customer data strategies don’t fail, they just don’t deliver

It usually sounds something like: we’ve invested in the data, we’ve built the infrastructure, we’re running personalization, but honestly… we’re not seeing the impact we expected. Why is that?

What strikes me about this is that it’s never said with embarrassment. It comes from organizations that have done serious work. Teams that have spent years getting the foundations right. And they’re not wrong to feel frustrated, because from the outside, their setup looks solid.

So what’s going on?

The data isn’t the problem

Here’s what I’ve come to believe, after seeing this pattern repeat across a lot of different organizations: the data is rarely the problem.

Most companies at this stage have already solved the hard parts. They know what their customers are doing. They have the history, the behavior, the signals. The dashboards exist. The pipelines run. And if you ask the team what’s happening with a given customer segment, they can usually tell you something meaningful within minutes.

The gap shows up at the next step.

Once you have the insight, you need to do something with it. And that part — translating what you know into action, consistently, at the right moment — is where things break down.

What I typically see is this: insights get discussed. Use cases get identified. People agree something should happen. But then execution falls back into whatever the existing rhythm was. Campaigns go out according to a calendar. Channels operate independently of each other. And the action, when it does finally happen, is often too late to matter.

It’s not that organizations don’t care. It’s that there’s no clear, shared way to take a signal — a customer doing something meaningful right now — and turn it into a decision that happens every time, reliably, without needing someone to catch it and push it through manually. That missing piece is small on paper. In practice, it’s the difference between a data capability that produces reports and one that produces results.

The thing about timing

You only really feel the full weight of this problem in situations where timing is everything.

Think about a marketplace. Someone is browsing a category. They start watching an item. They place a low bid. Then another. The auction has six hours left and they’re checking back more frequently. Every one of those moments is a signal that something is building — interest turning into intent, intent building toward a decision.

If you can catch that and respond to it at the right moment, in the right way, you have a real chance of turning that interest into action. Wait too long and the moment’s gone. The auction closes, they move on, and whatever they were feeling has already faded. You can analyze it afterwards, but that’s all you can do with it at that point.

This is not a theoretical problem. We ran a campaign for Catawiki — an online auction platform — where the specific challenge was exactly this. Not to run better campaigns in the traditional sense, but to actually respond to what users were doing as they were doing it. To treat browsing patterns, early bids, and accelerating activity as live signals, not as data to be reviewed in next week’s meeting.

The results were striking. In a single week:

• 75,000 app installs — an all-time record for the platform
• +14% more bidders than forecast
• +8% more bidding activity during the campaign
• ROI of +6,000%, well above what was expected going in

Those numbers are worth pausing on. Not because they’re impossible, but because of what produced them. The organisation didn’t suddenly have better data than before. It had the same customers, the same behaviour, the same underlying intent. What changed was the ability to act on that behaviour while it was still relevant.

What this tells us about the real gap

Once you see this dynamic clearly, you start to notice it everywhere.

The organizations getting the best results from their customer data aren’t necessarily the ones with the most of it, or the most sophisticated models behind it. They’re the ones that have figured out how to act on what they know — consistently, at scale, without it depending on someone catching a signal and manually pushing it through.

That might sound obvious. But it’s actually quite rare. Because getting there requires more than good technology. It requires agreement, across teams and functions, on how decisions get made. What triggers what. Who’s responsible for what outcome. What the guardrails are. How you know if something is working or not.

Without that clarity, even great data ends up producing the same thing: interesting reports that inform the next planning meeting, rather than actions that happen in real time.

And this challenge looks different depending on where an organization is in its journey. For some, it starts with trust — data quality isn’t quite there yet, or different teams are working from different numbers, and nothing gets decided with real confidence as a result. For others, the foundation is solid, but execution is inconsistent. Decisions get made at the top but slow down or get reinterpreted by the time they actually reach a customer. And for more advanced organizations, it becomes a deeper question: is the operating model actually built around responding to customers, or just around sending to them?

The common thread, in every case, is not a lack of knowledge. It’s a gap between knowing and doing.

Something in the industry is quietly changing

It’s worth acknowledging that this problem has, for a long time, had a structural cause that wasn’t entirely the organization’s fault.

For years, the technical landscape made it genuinely difficult for signals and actions to live close together. Customer data sat in one system. Decisions happened in another. Execution was handled somewhere else again. Every handoff added time. And time — even a few hours — reduces relevance in ways that are hard to measure but very real.

That’s slowly starting to change. The systems organizations use to understand customer behavior are getting closer to the systems that act on it. The gap between recognizing a signal and responding to it is narrowing, technically at least.

What this means in practice is that the technical excuse is running out. If a system can detect that a customer is in the middle of making a decision, and can respond to that in real time, then the question becomes: why isn’t it?

Often the answer is that the organization hasn’t yet made the decisions it needs to make. Not about the technology itself, but about how it wants to operate. What actions should happen automatically. What still needs a human to approve. What the boundaries are and who sets them.

The technology has caught up. The hard work now is the organizational thinking.

The question worth asking yourself

If you’re leading marketing, CRM, or data at an organization, there’s one question I’d encourage you to sit with.

Not do we have enough data? Most of the time, the honest answer is yes.
Not do we have the right tools? Usually that’s not the core issue either.

The better question is this: when a customer does something that matters, what happens next and does it happen every time?

If the honest answer is it depends on who’s watching — or we’d bring it up in the next sprint — or it shows up in the weekly report — that’s the gap. Not a data gap. Not a technology gap. An execution gap.

And the encouraging thing is that it’s solvable. It doesn’t require starting over. It requires getting specific about how decisions get made, who owns them, and what consistent looks like in practice. That work is less glamorous than buying a new tool or hiring more analysts. But it’s the work that actually changes outcomes.

The organizations that compound their advantage over time aren’t doing something magical. They’re just acting on what they know, reliably, while it still counts.

So what is actually holding you back: technology, governance, or decision ownership?

This is an article by EMAS 2026 Gold Sponsor Dignify.

Curious how to put this into practice? Visit EMAS 2026 on June 11 at Circa Amsterdam. Be inspired by international speakers and discover how to take your email marketing to the next level. Tickets and programme: emas.nu

Just Greve

Country Director NL at Dignify

• LinkedIn