It is the year 2009. I was introduced to tools that provide insight into web behavior: where are visitors, what do they buy, what don't they buy and where do they drop out? At that time, there was little to choose and less possibilities. In addition, the interfaces of the tools were a lot less easy and more “technical”. More for the experts.

By now it's 2020 and marketing software has taken a bird's-eye view, or say it, the shape of a high-speed train. Currently, the marketing landscape has about 8,000 tools that help you gain insight into your customer or visitor's behavior in all sorts of ways. From email, chatbot, social, website to app usage, you see all sorts of things, more and more within the confines of what is allowed and possible. You could say that the rise of all these tools has made marketers' jobs easier. More insight into consumer behavior means you can make easier and better choices, right? In practice, you often find just the opposite: the more you know, the more complex things turn out to be and the more difficult the trade-off becomes. While you can use numerous tools and processes to deal with the abundance of data, it helps to start with the following 3 steps:

1. Measure what you want to know and is the measurement correct?

The first step is (always): verify that what you're measuring online is complete and accurate. Is your data reliable to base business decisions on? 

Problems I encounter relate to too many unique pages, sources not properly tagged, bots not excluded or too high bounce rates. Key components are not being measured or there is no connection between backend systems and online tools (frontend).

When we get to work we always do a prior analytics check. In it, we go through the implementation of the analytics package(s) to see if everything is set up properly or if any measurements are missing. Too often we find out that measurement is not going well, and in fact there are always opportunities to measure extra. By checking the quality of your data in advance, potential problems can be spotted early and remedied. If you don't check in advance that your measurements are reliable, you run the risk of basing your important business decisions on loose sand.

An interesting, if somewhat older article from MIT on this is still relevant today (unfortunately). The essence of the article is that if you use data to base and guide your choices, make sure the data quality is good.

2. The human aspect of data science

The quantity, quality, velocity, complexity and layering of data sometimes makes it difficult to interpret. What do your visitors or customers want? What are they looking for? And why are they suddenly ordering now and not tomorrow? 

More and more companies are investing heavily in the technical side of data, such as smart platforms, the use of artificial intelligence and automating data. While less attention is paid to how the organization should use and interpret it. Behavior of your visitors and customers is complex, so try to learn and capture as much as possible. Depending on your options, you can do this by researching, experimenting, doing analysis with the help of psychologists, consulting science and continuing to ask questions. When using data and technology, make sure you also look at the setup of your teams and their goals, knowledge and skills of colleagues and how these teams work together to achieve the end goal.

You can purchase great, comprehensive tools as an organization, but you also need to have the right people and steps in place to get started with them. The article ‘Getting Serious about the human side of data’ addresses this well.

3. Provide an appropriate marketing stack

It happens quite often that organizations have many tools live, but barely use many of them or get few insights from them. What a waste! Choose your tools carefully and depending on your needs, use only those tools in your marketing stack that are really valuable. A jumble of tools leads to distraction and ensures that your data is everywhere and nowhere. Make sure you can integrate the data you use with each other, making it clearer and easier to use to interpret behavior. 

Focus not just on technology, but rather on organization

When you see the lightning-fast developments in marketing software over the past few years, it is to be expected that the next decade will only accelerate. When choosing and using the right tools, the importance of data quality, the right people and integration with other tools will only increase. It is moving faster and requires creativity on the part of organizing people, knowledge, skill and action.