I’ve just completed a crossword. Truth be told, it’s taken me a little longer than it should have because I got distracted by one of the clues:
16D: Fact (4 letters)
The answer was ‘data’. And that started me thinking. When it comes to CRM, are the two quite so directly linked? They might be. Data certainly can provide facts. But in order for that to happen, you need four essential elements in place first.
Is your data just sitting there? Is it part of an endlessly growing list that you use to feed a monthly email or the occasional voucher offer? Is it impersonal and irrelevant, a blanket approach that doesn’t get results, never has got results and never will get results?
Data needs to be interrogated. Without it, it’s just a list of ‘stuff’.
2. Asking the right questions
Companies collect lots of data, masses of the stuff. If you’re debating a new campaign, a change of strategy or new ways to engage with your consumers, it’s almost inevitable that hidden in your data are the answers that can help you. The trick is teasing those answers out.
The answers you get depend on the questions you ask. Focused, targeted questions help to laser in on the right data. Big, open-ended woolly questions invite big, open-ended masses of woolly data.
What does the right question look like? It doesn’t ask for truths about your entire customer base. Instead, it breaks down that base into segments. The more you can break your segments down the more refinement you can give to the questions you ask, and the answers your data gives back.
For example, we’ve been working with Northern Rail recently to develop a CRM strategy that drives off-peak ticket purchases. To understand more about the company’s passengers we broke them down into segments: commuters, families, students and so on, and then again by value.
Why did we do that? Because asking the data how the huge variety of people that make up Northern Rail’s customers use its services is far too broad a question to generate meaningful answers. But when you ask how high-spend commuters are using the service, then you can start to find real understanding. And if you don’t already have the data piling up somewhere on a server, asking the right questions can help inform what data you gather, which leads us nicely to…
3. Gathering the right data
In 1982, Steven Spielberg’s ET was everywhere. Keen to cash in on the merchandise frenzy, video game manufacturer Atari created the ET video game. Then two things happened. The bottom fell out of the home video game market. And the game, released a year after the film, sucked. Estimates suggest 700,000 copies of the game now sit buried beneath the New Mexico desert. Wrong product, wrong market, wrong time.
The point of course, is this: bad data is also the wrong ‘product’ for the wrong market at the wrong time. And like Atari’s video game, it too is little more than intellectual landfill.
Data gathered just in case. Data gathered with no specific purpose. Data that doesn’t add to understanding, but does add to the sheer mass of information you need to wade through to find the good stuff isn’t worth having. Cull it. Cleanse it. And leave yourself with data you can manage.
4. Analysing the data in the right way
For data and fact to truly be linked, the former has to lead directly to the latter. That means not jumping to conclusions when the analysis is half done. It means not assuming X causes Y when all you’ve really established is a relationship. It means not assuming option B is fact just because you’ve disproved option A. And it means not over-analysing until you start seeing patterns that aren’t really there, or under-analysing to the point where a blip becomes a trend.
There’s a reason scientists work in clean rooms: so they don’t contaminate the materials they’re working with and skew the results. We need to examine our data under a similar virtual cleanroom – because it’s all too easy to find facts contaminated by outside forces.
Data is fact? I’d say there’s a lot more going on before one can definitively become the other. But then that makes for a really long crossword question.