Data-driven marketing:
Challenges and tips for growth

I don’t want to sell you our solution in this article, but instead, share some interesting studies with you. Data-driven marketing is often referred to as the future. However, various studies show that we as marketers still have to overcome the necessary hurdles to be data-driven.

Jurgen Verheijen
Marketing lead

Do your online advertisements reach the right people?

To be able to work data-driven, it is first of all important to ask yourself how good the quality of that data actually is. For example, where does the data you see come from? And how did that data come about? Relevant questions to ask yourself.

A few years ago, research was done into the quality of data regarding programmatic display advertising. In this system, various automated processes are used, including determining target groups. To make this concrete, people who visit websites about pensions are placed in an older age group than people who are frequently found on websites about children’s clothing. Now the researchers (MIT, GroupM and Melbourne Business School) have looked at how well those automated processes work in accurately reflecting age and gender.

Turns out, the automated processes match the gender in an average of 42% of the cases and the age only gets matched in 24% of the cases. Other examined attributes score even worse. In short, millions are spent on incorrect and irrelevant target groups.

It is also stated that optimization software is available that can improve the identification of target groups, but the relative extra costs involved do not outweigh the benefits, according to the researchers.

Put it to the test yourself!

To test for yourself how well such automated models can predict you as a person and your characteristics, you can also test it yourself to see whether it is predicted correctly. I did that too, here’s the link, by uploading a printout of my LinkedIn data. My gender is shown correctly, but in terms of age they are a year off. I’m estimated to be younger, but perhaps that’s a subtle compliment from the software.

In addition, your personality is also looked at and I also read a few things there that I think fit who I am as a person. In short, in my real-life example, the prediction is actually heading in the right direction. Although in this case it is of course N=1 for 1 party.

Robots clicking your advertisements?!

The results of the study were presented by Peter Weinberg (LinkedIn B2B Institute) to Dr. Augustine Fou, an advertising fraud researcher and consultant. Fou indicates that in addition to incorrect data, robots should also be taken into account. It is in fact possible for someone to set up a website and from there automatically have a bot click on advertisements on that website. Enough clicks to stand out and too few to be suspicious. Buyers then see that this website does have a good click-through ratio and a budget is therefore allocated to it. Here too, it would be millions in advertising budget that are used incorrectly.

What marketers think about the quality of data .

In addition to the previously discussed research, various studies also show that confidence in the quality of marketing data can be improved.

In 2017, it turned out that only 12% of B2B marketers have great confidence in the accuracy of the data they manage. Additionally, 84% of the Forrester panel said they view the quality of their marketing data as one of their top 5 weaknesses.

Recent European research by DVJ Insights confirms that data-driven working is still a challenge. According to 72% of the surveyed marketers, data is the biggest challenge for the future due to the proliferation and application of data. Many indicate that they do not have access to the correct information. Only the lack of the right capabilities to analyse data becomes an even bigger hurdle to overcome.

In short, we see the challenges as marketers ourselves. However, we also still continue to invest in advertising to incorrect audiences and communicating to incorrect and irrelevant contacts. Maybe it’s time to have an internal data steward/controller or to make use of an external data expert? After all, there is also collaboration with online/digital experts, copywriters, etc. Why not in the field of data?

Is data-driven work really the future?

With all the challenges that exist, you could almost ask yourself whether it is still worth applying data-driven marketing? Well luckily I have a short answer: yes. It’s definitely worth it. The DVJ Insights study also compared well-performing companies with less-performing companies.

This analysis clearly shows that the high-performing companies are more data-driven. And to put that in perspective, the 2000 marketers place it above consistent marketing policy and innovation as a driver for growth.

Data-driven, but how?

Data quality is therefore an issue and we also see the challenges there and in the meantime it is also an important driver for growth. That’s clear, but how am I going to tackle the challenges, I hear you think.

Well, let’s start with the facets that the high-performing companies have mastered from the European research quoted earlier. It was therefore indicated that having the right capabilities is more important than the right data or the right tools. That makes sense in itself, because your data can be so good and come from the right tools, but you still need the capabilities to draw the right conclusions from it.

Going back to my earlier point about perhaps using an external data expert, who can also provide the necessary capabilities here to analyse the data.


Becoming an expert in data, step by step.

In addition to that search for the right capacity, there is also a process that emerges from the research. This is subdivided into 3 development phases: the start, the use and the deepening(the expert phase). Only 27% are seen as data experts.

Before I go into this any further, it is important to know that this phasing is comparable to the data maturity model that Gartner presented in early 2018. There too, it was already concluded at the time that there are still few data experts or organizations that have reached the highest level of data maturity. In short, still plenty of challenge as we concluded earlier.


In the 3 phases that are explained, the greatest gains appear to be made in particular in scaling up use to in-depth. The key point here is not to have data that supports the decision for every decision. No, the point is that you use data in all decisions. It also appears that high-performing companies use data from pricing and brand strategy to product introductions. Incidentally, these parties also indicate that even more data can be used to further optimise every decision.

From silo’s to data-integration

In addition to the right capacity and dedication, it is also important that you integrate data. This has also been mentioned for many years by various parties, but in practice only 25% is applied. This appears to be largely due to the complexity that this entails. My tip: start simple.

You also realise which elements of the marketing technology you apply are fundamental and put them first. Is it mainly about sales and customer management? Then your CRM is probably the most fundamental, and use it as a basis. Is it just the content? Then naturally choose a content management solution. From that basis you can then look at how you can/want to connect things to it.

Things you can get started with

In this blog I have shown that data-driven marketing brings the necessary challenges with it and things that you as a marketer need to look at critically. Where does data come from, how good is the quality, but above all do we have the right capabilities to analyse the data?

Daarbij heb je als marketeer een belangrijke rol, los van het aandragen van het belang van datagedreven marketing, is het ook van belang dat je de juiste vragen stelt, integratie intern hoog op de agenda zet en dat je het ook vooral kort en simpel houdt om mee te starten. Te veel data kan juist de besluitvorming verlammen en een averechts effect hebben.  

You are certainly not alone in this approach and you can make use of the help and expertise of various colleagues. For example, other departments, such as the IT department, will also benefit from data integration, because the more silos, the more maintenance and the more IT costs. In addition, your colleague from the purchasing department can help to keep the lines as short as possible when purchasing data. As Weinberg also points out, the shorter the lines, the fewer intermediate links and the less risk. Many buyers will wholeheartedly agree with this and can help you make it work.

However, also consider the deployment of external data experts who can provide the necessary piece of analysis capabilities, data management and so on. As a result, you can continue to focus on your marketing tasks, just as you can by deploying online/digital experts and copywriters, among others.