Insight Sprints
Using common sense to fuel rapid research
I’m beginning to realise that a lot of the time insight is really just common sense. I have never looked at a piece of insight and gone ‘woah, that doesn’t make any sense at all’. And I’m not just talking about the pointless stuff like ‘customers are mobile’, but even the good stuff that actually provides a new perspective on your customers or brands — once it has been discovered, it suddenly seems kind of obvious.
I think a lot of the time we are so immersed in the current that we can miss the obvious. We’re so close that even if there is something right in front of us, it is too blurry to see properly. And so we try to find ways to change our perspective until the insight comes into focus — it was always there of course; just now we can see it. Which leads me back to my point, what if we worked in a smarter way up front, using our common sense as an input to research, rather than an output?
If we consider why insight is often common sense, it is largely because we are all customers. This means, just like our customers, we are people. As people we have a broadly similar sense of what is good and bad and whether what we experience is good or bad. And good customer experience (CX) is always going to be preferred to bad CX. So as long as we always start by considering about our CX, we will always be able to form an opinion on what can be improved.
We must try and remove ourselves from being so blind to our own brands flaws and also try and step above our own stubborn beliefs of the customer to consider the sometimes brutal reality. If we remember that our customers will likely care about our brand infinitely less than we do; and if we can be open to learning more about our customers, rather than having solidified perceptions of their personality; then we can really start to interrogate our CX enough to identify where we need to improve.
But, this is a balance; we cannot divorce ourselves completely from our brand pride, because we can be our own customers. If you are the Brand Manager of Bisto, I expect you to at least like gravy (he does, I know this because he’s my brother). And even if we don’t buy our products, we should still love our brand. You can have entirely male Tampax marketing teams or vegetarians marketing meat products. They aren't the customer, but they can empathise with them because they are passionate enough about the brand to care who buys it.
This is absolutely not to say that we don’t need research. We do. I am also not suggesting that we should ignore our customers, as I've written before, they can be the key to unlocking what your brand should do. But sometimes, people don’t know what they want, you have to tell them — ask Apple.
“If I had asked people what they wanted, they would have said faster horses,”
said Henry Ford (This quote isn't real, but it is brilliant)
But what I would like to sketch out here is this idea of ‘Insight Sprints’ based on validation as much as identification. Because if we take some time up front to be smart about the challenge we are solving we could be phenomenally more effective with the research we do. If we consider scientific investigation, we start out with a hypothesis to prove or disprove, then through a series of experiments we answer our hypothesis with a degree of confidence. I would like to use short bursts of insight in a similar way to this.
I’d like to make a quick caveat here; I have seen plenty of research reports that do take this hypothesis approach to research. However, the 114 pages that follow the hypothesis suggest that there was nothing quick about it. We can be a little disappointed when the research we commission is summed up in 6 bullet points, because we want our investment to be considered and lengthy. But what I am suggesting is that for the same cost, but a fraction of the time, we could do 14 reports that are a tenth of the size, and stagger them across the process from concept ideation to product delivery. Short bursts of intense pieces of research to answer specific questions — Insight Sprints.
At the beginning of product design we often use iterative design to expedite the process from concept to testable product. Is there a way we can start to approach research in the same way using Insight Sprints? And the beauty of this model is that it lets us be much more flexible with the research methodologies we utilise. Instead of doing one big block of one type of research, we go through short bursts of multiple different types of research. Mixing digital landscaping with focus groups, social listening with online surveys and phone interviews with user testing.
Roughly the process I am suggesting follows:
1. Review customer experience to create a hypothesis of where and actually how we can improve
2. Use multiple Insight Sprints to validate the need and the underlying ‘why’ of the need whilst simultaneously challenging and building the idea
3. Enter iterative design cycles between prototyping and user testing — which is really just another form of Insight Sprinting
4. Deliver, learn and evolve
Of course we must approach this in a balanced manner — for two important reasons. Firstly, there is enough dud data out there that you can cherry-pick statistics to support any hypothesis you want, so we must have a backbone in our approach. Secondly, we wouldn't have penicillin and bevacizumab would have only ever been used for cancer and not Wet AMD if we become too rigid with the way we approach research. Sometimes we must push beyond our own expectations and even the insight right in front of us to form something quite unexpected. But I truly believe that by approaching research with an idea, rather than blank question, and implementing insight sprints to validate one idea, more than identify every opportunity, we can work in a more modern and agile manner, getting to our end solution more efficiently and a hell of a lot quicker.
Insight Sprints
“Good research is completely unbiased and tells you the story as it is. Great research has an opinion and tells you what you should do next.”
I just made this up. Sorry.
Example: Starbucks
Let me give you an example using an idea I have. It involves Starbucks (who I don’t and have never worked for/with). So let’s start by making some assumptions about the Starbucks customer — they are going to own a smartphone, they are more likely than the average population to own a wearable and they spend time almost every day near a Starbucks (i.e. most Starbucks regulars live in cities) but might not buy a Starbucks every day. My “Input Common Sense” is that people want coffee more when they are tired. So, what I am suggesting is that the Starbucks app should sync to the data of their customers wearable to see how they slept the night before. If they slept badly, they should push a notification when the person is near the general vicinity of a Starbucks store and send them a notification, such as “Sorry you slept so badly last night, here’s £1 off your coffee this morning.”
To go from this idea through to a reality I would want to go through the following Insight Sprints. And of course this is an example; the exact sprints you devise would change as you go through the process, so I am missing a lot of the smaller 1–2 days quick questions we would want to answer:
Firstly, let’s actually check my assumptions around wearables and buying behaviours — I’d suggest a speedy survey pushed out through the app (as ultimately this will be the users we target) or even an internal-facing survey (we are our own customers after all).
(Time: 5 days)
Secondly, let’s examine the app analytics to understand and optimise the effectiveness of the app’s push notifications.
(Time: 1 day)
Thirdly, let’s get a prototype built and tested with our customers, I’d suggest a focus group that then becomes part of a pilot scheme to measure the impact of increased sales using this concept and also overall satisfaction. There will almost definitely be a few bounces between this kind of user testing and rapid prototyping as the product naturally evolves.
(Time: Cycles of 10 days)
Lastly, let’s see if we really need to incentivise the coffee-buying, could we simply send a notification along the lines of ‘Sorry you slept badly, time for your morning Starbucks?’ An A/B group in the pilot scheme in the last bullet point should define whether the notification alone is efficient or patronising.
(Time: 14 days)
This isn't radically different from where we are now, the same way iterative design isn't radically different from before. The important difference is that I start with the idea, an idea that should be found through examining the CX and understanding the strategy. What we then do is take a long and sometimes arduous journey to insight and break it into bite size pieces — this lets us get hands on with the findings a lot sooner and disprove or support our ideas in a more agile manner. Does this completely supersede large-scale research? Probably not, but it does allow us to stop using research to state the obvious and hopefully it would allow insight to be more firmly embedded into the creative process.
