Data-Driven? No you’re not!

A bit of a bold statement. I know. But I’m glad I’ve got your attention.

Don’t you see a lot of posts & tweets passing by on data-driven this and data-driven that?
I bet you do. You see’m too.

About 99% of those posts are wrongfully using the word data-driven. They talk about things like they’re an expert. They aren’t. Me neither! Working data-driven is hard!

pls, let me explain.

First of all, you need to know the difference between data-driven and data-informed.

Data-informed marketing is using data as _a_ factor to make decisions. Not the _only_ factor!

Data-driven marketing is using data _only_ as a factor to make decisions. Not _a_ factor!

There you have it.
Plain & simple.

Translating this into a marketing context, you get this:

  • Data-informed = data + human interaction to make a decision
  • Data-driven = data to make a decision

Forget working data-driven for now.
Start with data-informed first.

The only thing really matters is that your marketing department needs to learn how to read those stats and how they can use them to get a clear view on what decision they should take next along side their marketing ideas and communication efforts.

If you’re planning on working data-driven (which should be backed by data-informed decisions first), you’re going to need a team that keeps focus, launches & test things until they break or hire some wiz-kid to do some crazy stuff with data. This team needs to move the needle and get things done in order to work data-driven. If not, they’re fall back into working data-informed, which isn’t bad at all. That’s ok! The difference is in the effort you put into it.

Let me show you what I mean
and how I’m using this.

Working Data-informed

Your website is a lean mean lead machine in several countries.
Things are going great, but you want to work on site speed and don’t know where to begin.

Here’s one thing you can do with your Google Analytics data to get you informed about site speed and leads:

  1. Export the average site speed per country
  2. Export the conversion rate (or amount of leads) per country
  3. Do some Excel wizardly stuff (not so much actually – just match the countries)
  4. Make a graph out of it

You’ll probably get something like this:


Tadaaaaaa! Informed by data.
Now you can think about moving your site to another server in the area of the best performing countries. Or you could think about load balancing & CDN solutions. Just a thought. In the end, every second counts.

So, what did we do? We used data to inform ourselves about the site speed and leads per country in order to make form the idea about re-locating the website or find a solution to speed up the site with other techniques. We’re not even deciding yet because we need more info & data about other examples before we make up our mind.

So… add some more countries that are the most interesting ones to focus on in the near future. The new data visualization gives you better insights with adding even more countries.


Looks like we’ll have some issues in Iceland.
Time to get around the table with the development team to see what we can come up with as a solution.


The best thing about working data-informed is that you’re still using your knowledge of past experiences, things colleagues remember, etc. It’s the best of both worlds. Clear and honest data + the experience and the human interaction of people in order to make a good decision on what’s next.

Working Data-driven

This is a bit harder. There are two ways of working data-driven.

1) Rates

Working with the example above. The website with the international coverage. If marketing should be data-driven, there need to be set some rates to focus on.

For instance: the Leads to Site speed ratio

The idea about this is different to working data-informed. Data-informed working is based on lagging metrics (data that comes from past events), where as data-driven metrics are based on leading metrics (data as it happens). This is why startups focus on rates, so they can act to it before it is too late. It’s a different mindset (which I’m a big fan of!).

In the end, working with rates gives you a clear number to focus on and orders you to do what ever it takes to increase that rate!

Some time ago, I did some test on the rate of followers I was gaining across platforms.

I tried to grow at least 1% per week. Didn’t work out. Yet.


The best thing about working data-driven is that you don’t look back. You don’t get into “how did I manage to pull this off in the past”. It’s a waste of time! If you’re in SEO for instance, you’ll still have your best practices, but you know things changed.

The algorithm, the competition, the products, the customers and their behaviour, design standards, UX standards, … and the list goes on. Focus on what you want to achieve and start from there.

2) Algorithms

This is the hardest way. The idea is fairly simple but the execution is very hard. Based on the data, the created algorithm will adjust the output. In marketing, this is fairly unseen because of the human interaction marketing has to take in account.

SAAS comes close in some ways, but they’re data-driven by rates, most of the time.

The best example is the Google Algorithm that contains, for instance, the pogo sticking metric aka dwell time. This metric calculates the time between clicking on a search result and going back from the website to the search engine pages. This is a metric taken in account to measure how good this search result was in order to the question asked in the query field.

Everything happens automatic. This one metric, out of +200 (even more now), is a part of an data-driven process and ranking sites automatically.

The dark side of algorithms is that they often mess things up although the data shows the output should be correct. Facebook had some unfortunately issues with their like & photo algo some time ago, letting people showing off their past year. Woops.


The original tweet can be found here.

The best way of working

The best way, for marketing? Do both, and combine them in any order.

Use data-informed working to get a clear view of what happened in the best so you can take decisions based on data and marketing ideas. If you find a problem and you’re informed good enough, you’re sure that is the biggest problem to fix for the next few days, weeks or months, then… go into data-driven mode.

Set up that dashboard with:

  • A goal to strive for (for instance: the amount of leads)
  • KPI’s to measure progress (for instance: the amount of leads after 30 days)
  • The rate to strive for (based on calculation of the goal to achieve)

Focussing on the rate will keep you focused on getting things done. If the rate increase and gets above the calculated rate, you’ll sure get to that ultimate goal. The KPI’s are a motivator to speed up things and pull through.

For instance, a dashboard to focus on revenue per quarter. There is no rate defined in this exercise. Only a minimum daily target we need to focus on in order to get to that goal.


How do you read this graph?

We’re not even close to the daily target, but it looks like there are days we can do a little better. I also start to see a pattern, a bit early to say, but there is a pattern rising. Can you see it too?

Questions to ask about this graph:

  • What did we sell that lifted our revenue that day?
  • Why did we sell those products?
  • Who bought the products?
  • What was the time till first visit/subscription till buying the product

You can _do_ stuff with these insights!
Just learn how to read the data. That’s the most important part.

The good news about this approach, the KPI’s and goals I mean, is that you can use this for any goal or idea.

Data does not solve disputes! It only helps you make decisions.

So .. big data? It only gives you insights and a bigger probability to drown in too much information and loose focus & common sense.

Can you do everything data-informed or data-driven?

Yes. But only in a short period of time.
Depending on what data you have, probably a lot of data captured by following lagging metrics, you can optimize accordingly, but here’s the twist, you can’t if you’re focusing on the long-term.

If you’re focusing on the long-term, you need to set your KPI’s differently. You won’t focus on subscriptions or transactions or even conversion rate. That’s insane. You’ll need to set a long-term goal.

Long-term retention rates for instance. You’ll need to think about lifecycle management, customer life time value and profiling in order to get there.

From what I see, not even 50% of businesses out there have the basics in order. So… in order to get there, you’ll need a team that can track, read and interact with data, a strategist to match the vision of the company with the team in order to get there.

If I may give you some humble advice, if you’re strategy is set, build 3 teams that get shit done:

  1. Build a campaign team
  2. Build an acquisition team
  3. Build a retention team

Need more and other interesting thoughts about this?
Check out this video by Adam Mosseri (Facebook).

Take one hour off, grab a coffee & pls watch this

Since I watched the video below on OKR, my mindset has changed dramatically. These days, I’m noticing the same thing happening with compagnies and the teams they’re building. They don’t know the framework, but you see that it starts to live. Many marketing teams and other teams are evolving into this way of working.

That makes me _VERY_ happy!

If you want to talk about this way of working & my vision about this, let me know.

I would really appreciate if you would help me spread the word about this.

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