We get the data, decisions and customers we design for
How do we determine if the data we have is the data we need to make the decisions we want?
There isn’t good or bad data, every data point tells a story. But which part of the story? What can we assume from looking at different data types e.g. web-statistics, sales, leads, demographics etc.?
We get what we design for. If the data we collect is e.g. channel performance data, we will ask channel performance questions, make channel performance assumptions and end up designing channel performance experiences.
And in a world of easy to collect quantitative product or channel proxies it’s easy to end up understanding the world through the lens of our products or channels, but thinking / wishing / not realizing that we are not seeing the humans behind our customers, but our own internal silos, products or marketing technologies.
If we design for our own needs, measure our own channels ask questions about our own efficiency, we are effectively creating our own bubble.
So how do we change it?
It’s much easier than we think.
The wonderful thing about the Internet is that it can record anything at the same time as we can design any experience we want in order to learn anything we want. And this is where the opportunity lies: What do we want to learn? Which questions do we want answered? Through which lens do we want to see the world (our own products or channels and/or our customers’ situations and needs)?
Let’s look at an imagined example:
Sophie is an accountant. She knows what her speciality is, her skill level, her assistants’ skill level, the type of clients she has, the nature of her relationships with them and their businesses. She knows how she earns money and the nature of her network. With all this information Sophie goes online looking for specific answers.
What do we know about Sophie based on the data we collect? We know the click-through rates, time-on-site, scroll depth and conversion rates of visitors broken into categories based on their browsers, computers, platforms or geography (a bit simplified :)
Do we spot the difference?
Instead of designing experiences that capture the insights about Sophie that is relevant to her and make the experience better (and vastly more effective) we capture information that is only relevant to our own channels (I guess that is why we call it channel performance data) we remove the customer from the equation and tell ourselves that our own channel performance are valid windows into the humans behind our customers (or that it doesn’t matter).
With our creativity we can learn anything
And we don’t have to ask people who they are to learn more about them (in fact this might produce more bias).
We only have to give them options and see how they choose. If we can do deep listening (1) in real-life we can do it online .. if we design for it.
[e.g. there are examples where car manufacturers found that the customer preference data coming from the “customize your own car”-websites was more accurate than any other type of market research ]
If we build experiences to learn Sophie’s skill level, speciality, how she earns money etc., then that is what we would learn.
But it means knowing that we can learn so much more from our customers than we are currently doing, and start by asking: what do we really need to learn?
Then go out there and design for it!
Sources:
(1). Deep listening, https://www.youtube.com/watch?v=IrZWPiQxXxI
