Debunking First-Party Data Activation Myths

March 29, 2023 

With data from customers and prospects at an all-time high, businesses have never been more informed about customer interests. Capitalizing on this data – especially in the wake of technological and legislation changes around third-party data collection and utilization,  has many marketers (rightly so) looking to data activation.  

Let’s start with a definition of data activation. Sounds easy right? 

Unfortunately, when you plug this phrase into Google you’re going to get some definitions that have been crafted to explain data activation in a way that makes you think you can’t activate data without implementing a complex (and expensive) infrastructure. 

Example: Data activation gives marketers the power to shape each interaction with their customers by combining every action or behavior together in a single data pool that informs marketing decisions as soon as it’s gathered.

Here’s another one: Data Activation is the method of unlocking the knowledge sorted within your data warehouse, and making it actionable by your business users in the end tools they use every day.

And another: The process of putting the data stored in a DMP into action.

Single data pool, data warehouse, DMP… are you seeing a pattern here? This leads us to our first myth.


Myth #1: You have to have all of your data altogether in one unifying place before you can do anything.

I believe a big reason why this myth is so deeply entrenched is that it revolves around the perceived complexity of the infrastructure required to even start data activation. 

There are all kinds of data. There are all kinds of touchpoints. Organizations often encounter a kind of “analysis paralysis” when trying to bring all of the touch points together to generate this sort of mythical unified view of ALL of the customer’s interactions with ALL of the touch points. And then, and only then, do they see there to be an opportunity to activate against this data.  But that’s not necessarily true.

It’s important to note that trying to accomplish this unifying view of everything is as much an organizational challenge as it is a technological one. 

There’s a huge cost in technical infrastructure to unify data not just because the tools cost money, and deploying them costs money, but because all of the different data owners need to be involved in this kind of project, and getting everyone to agree, and then getting the resources to actually affect this kind of change is a significant organizational challenge. 

Yes. There are some advantages to architectures that bring data together. But you don’t have to necessarily embark on this large infrastructure and organizational overhaul in order to get to a place where you can start capitalizing on the value of activating first-party data. Instead, view it as an iterative process. Choose a few key data points from a few key data owners from a few key systems and bring that together to prove the value of unifying the data set.  

The reality is, if you understand what data you have, you have a solid foundation. Then, activating that data becomes a question of connecting the right dots to be able to affect a change or make a decision that ultimately generates lift, and impacts your performance. 


Myth 2Having all of your data together in one unifying place is all you need.

What if I were to wave a magic wand and gave you all of this magical infrastructure you think you need? And what if I gave you a CDP that was fully aligned, and you had data flowing from all the different places and everything was perfect? You would be done, right? You can now put a big check mark beside First-Party data activation, right?


What would you do with it? Do you even know what you would do with it? And, even if you were somehow magically doing the right things,  how would you know that you’re succeeding in doing those things? 

The bottom line is if you never go through the iteration and the process of data activation:  

  • I think this is what we want to try and do, 
  • then trying it, 
  • and then measuring it, 
  • then seeing what the output is
  • Then learning what the data is actually telling you as opposed to what you thought it would

If you don’t learn these lessons,  you don’t necessarily have the ability to actually activate against the data. If you don’t know what the data is telling you, you don’t really know what it means or what to do with the result. You need to live through the experience to recognize the sophistication of the things you are trying to accomplish in order to grow as your understanding grows. 


Myth #3: First-Party Data Activation is Hard


The third myth I want to debunk is that first-party data activation is hard. This perception is based on believing you need to purchase some sort of CDP/DMP,  perform a complex infrastructure overall, and commit to numerous huge investments, and all of this HAS to happen BEFORE you can even start. 

Again, this is not necessarily true. It really depends on your use cases. Knowing what they are, and knowing what you have available to help augment your decision-making for these use cases –  That’s where the battle starts.

The key to success is to start with use cases that are straightforward, based on what you know, and clearly move the bar on the performance metrics you’re looking to tune.  

Decide what you are trying to accomplish AND how you are going to know when you’ve accomplished it (if I do this, I expect to see that).  Start by identifying the business objectives, then the marketing goals, then the tactics you are going to employ. 


Myth #4: I can do this by myself

No, you can’t. And for the simple reason that you don’t own all of the data. In fact, marketing isn’t the owner of most of the first-party data. If you try to pull data from other sources and jam it all together into a marketing dataset that’s only used for marketing, you’re going to spend a lot of money,  you’re not going to get buy-in from the other stakeholders, and even if you succeed,  the business isn’t going to get any value beyond marketing. 

While it is true there is a huge possibility for marketing output for this kind of work, your data strategy needs to look at more than just marketing. 

There is value in this data well beyond the marketing silo. 

Discovering and communicating this value is one of Napkyn’s differentiators. When we talk about a data strategy, we’re not talking about activating only for your marketing team, we want to talk to your user experience team, your IT team, etc.

While there’s clearly value to be had in leveraging first-party data for Marketing outcomes, our experience shows that companies can get the most benefit by engaging with other parts of the organization as well.  Helping each function (eg: user experience, product, IT) understand how first-party data can help them gain greater insights and improve outcomes ensures buy-in across the org chart. 



With some of these myths debunked, let’s go back to where we started and look at the definition of data activation:

Data activation is the concept of unlocking value in data through the development of insights and turning those insights into action.

That’s it. No big expensive infrastructure, no unifying place, no impossible-to-climb mountain, just developing insights and turning those insights into action, by planning, identifying metrics, strategizing, resource allocation, testing and learning, and constant evaluation.

Look at data activation as an iterative process that evolves as you ask questions like, “What happens when I try to grow the types of analysis I perform?” and   “What do I need to do to scale for resilience?” 

When you have the answers, you can iterate on the infrastructure you have in order to make it more resilient, more powerful, and more comprehensive. You may find investing in a more complex infrastructure makes sense for what you want to achieve, but it doesn’t have to be in place to start activating your data. 


More Resources

If a first-party data initiative is something your organization would like to learn more about, here are some resources we recommend:

5 Key Characteristics of a Solid Analytics Foundation (article)

How to Build a Future-proof Media Measurement Plan (article)

 How to Identify and Leverage First-Party Data (on-demand webinar recording)

3 First Party Data Activation Trends you Need to Know About (article)

And of course, you can always reach out to us.

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