Data is everywhere these days. We are constantly assaulted with it, in just about every sphere of our lives. At work many of us are ruled by KPIs (key performance indicators – see my earlier blog post). Our businesses run on cloud-based systems like Xero which allow realtime tracking of all sorts of metrics that we used to have to pay an accountant a fortune to provide. You can’t watch sport on TV without getting an endless stream of statistics, and if you turn on the news you’ll get the running Covid-19 total for the day. With all this data around to help us make better decisions, you would think we would be the most perfectly-optimised, happy and effective generation to ever inhabit the earth. Maybe we are… but I’m not feeling it.


As a digital marketing company, one of the questions we hear over and over again is “What is the data telling us?”. Data can tell you whatever you want. It depends on what you need to know, the questions you’re asking, and your motivation for finding out. But I’ve seen plenty of projects turn bad because not enough thought was put into measuring whether things were actually working or not.

(Warning:  I’m the guy in the room who, after everyone high-fives, asks awkward questions like “What have we not thought about? Who should be in the room but isn’t? Who have we not talked to?”)

When it comes to data, I am much more interested in the question “What is the data not telling us?”. Collecting data is easy. Putting it into spreadsheets is easy. Making pretty graphs – anyone can do that. But understanding how that data actually maps onto reality – that can be extremely difficult – and if you don’t get it right, you can blunder into some massive traps. I think most of us remember Brexit and the Trump election in 2016. All the data was pointing one way – Hillary by a landslide, Remain would win comfortably. Whoops. Someone was looking at the wrong numbers. It’s difficult to take opinion polls seriously after that.

At Mogul we’re not in the business of predicting elections, but we get paid to help our clients make the right decisions with their digital projects and spend their precious marketing budgets as effectively as possible. We often deal with ‘user engagement’ metrics like bounce rates, pages per visit, and conversion rates. If you’ve ever spent any time looking at Google Analytics, Google Ads, or Facebook’s insights, it can be very overwhelming and there is a serious temptation to go down the rabbithole, also known as ‘analysis paralysis’. The graphs are so pretty and the reporting is so flexible that you never actually get anything done. 

Next time you’re producing a report (or reading one), ask yourself “Why are we collecting this data?”. If you can’t answer that question in about 20 words or less, then stop. Just stop. Walk away from your computer. Put the jug on. Have a good hard think about what you’re up to.

For example, if you’re looking at Google Ads data, your answer should be something like “we want to know which ads are working best because we want to sell more tractors”. And that would be perfectly fine. The Ads data might tell you which version of your ads is bringing in the most customers, which one is generating the most quote requests, and that’s probably good enough to decide whether it’s worth spending more money or not. But you should still ask yourself “What is the data not telling me?” It’s probably not telling you a whole lot of stuff. 

If your answer is something like “we want to know how many people are visiting our website”, then that is extremely weak. Again, ask yourself “what is the data not telling me?”. It’s not telling you all sorts of things. How long do they spend on the site? Is it getting shorter or longer? Where are they coming from? How are they finding out about your site? Are they coming back again and again? Are they adding items to their shopping cart? Which products are the most popular?

One of the reasons so many businesses have loyalty schemes (like Countdown’s oneCard, AA Rewards, etc.) is to fill in the gaps in their data about their customers. It’s easy for a supermarket to keep a record of how many people went through the checkout each day and what each person bought. But without a loyalty scheme they have no way of knowing who those people are, and can’t keep a record of how their purchasing behaviour is changing. For the cheap price of an occasional discount, they can store a vast amount of data about you. All the stuff that comes up when they ask themselves “What is the data not telling me?”. Most of the time this is helpful – for example, you will be presented with recommendations based on your previous purchases when you shop online, saving lots of time. Sometimes it can be jarring – like when remarketing ads follow you around the web. We are still in the early days of mass data collection so it’s still an imperfect science.


There are a lot of ways to collect data, but one of the best is also the oldest: talk to people. Ask them questions, make the questions open-ended as much as possible, listen, and take notes. It can be time-consuming, boring, and difficult. That’s OK – it means your competitors probably can’t be bothered doing it. And listening to real people will give you the best answers to the question “What is the data not telling me?”.

Good luck with your data – and if you have any questions, let us know. We are always keen to help – and we want to know what you think…