Better hypotheses, better research, using one mental model - Ben Labay
Ben Labay from CXL shares his mental model for creating really strong hypotheses and research and testing.
What Ben covers:
- The importance of identifying a value proposition that resonates with customers
- Two practical ecommerce examples of relevant value props
- How to understand the core motivating values for customers
- How to create a leap from data → to information → to knowledge
Click below to read the transcript.
Better hypotheses, better research, using one mental model - transcript
Hey everybody. Here it is: my number one mental model for creating really strong hypotheses and research and testing.
So knowing the name of something is not the same as knowing something, right? I want to provide a couple of examples from the heuristic side of things on how to apply this. So a couple of website rip downs, and from the analysis side of things, so an example for codifying data.
But more broadly before I jump in, the concept speaks to system one versus system two, it's foundational to this idea of the reptilian brain versus the mammalian brain, jobs to be done framework as well. It's foundational as to why we suck at communicating, generally.
Marketing, using voice of customer data, you see the thing is we think that our product is what we sell, but it's not. It's just the name of what we sell, right?
For example, the record industry. Did they sell records? Do colleges these days, do they really sell education? That's becoming a big question. So it's not the name, it's our perception of value that becomes really important. And that's the leap that we need to take as marketers and researchers, the leap from the names of something to the something.
So let's make this real. Let's first dive in to an example from Procter & Gamble.
We worked on this site for about three years doing conversion work. This is a native deodorant, premium all natural $12 a stick deodorant. Now in the jobs to be done framework, do I hire 12 deodorants at $12 an hour to stay fresh and clean? No, I don't think so. I can get it way cheaper.
Let's change this value prop. There. I hire this deodorant to stop worrying about polluting myself, right? So this is a value proposition that means something to someone that's going to shop for this and be a loyal customer, right? This was a massive win in communication and conversion.
Let's drive the point home with another e-commerce example. Here's a product detail page for a super fancy baby camera and monitor nightlight kind of thing from a company called Nanit. Now product detail pages are supposed to have details, but the problem is that I landed here from a retargeting Instagram ad after visiting the website only one time. It's not a huge deal, but notice that there are a lot of names of something, right? A lot of details. If we scroll down a bit, though, we start seeing some shiny, happy people and some cool numbers that start to mean something. 92% efficiency, not sure what that means, but I want it for my baby, 12 minutes for baby to fall asleep, I love it. I'm a data nerd. I want to track that.
This is powerful because now I start having the questions in my head for the things that the camera provides answers for, right? I didn't have that before. All I had was a bunch of names of stuff.
So this is an example, as well as the last one from sort of that conversion heuristic angle.
Now I want to switch over to the research angle and see where this mental model applies there. And so here is a result of a recent coding exercise that we did, real data from a real client, selling jewelry online. This was code, this is coding of a customer survey question that we asked recent first-time purchasers, getting at motivation, right? Question: What matters to you most when buying jewelry? This isn't the raw data, it's been coded, it's thus information a little bit.
It's linked data to an extent and now it's a signal of strength of the names people give to what mattered to them. But we're still listening to what they say at this point. We need to try to make that leap a little bit further from the name of the something to the something. We need to find the patterns and the connections, and there's different kinds of patterns? Similarity, correspondence, causation.
Usually, the first stop when I do some coding like this is to find patterns of dissimilarity. The categories. And what we see here are that there's codes that are related generally to quality, price, and style. And when you reevaluate based on this sort of category code methodology here within the pattern, we move away from quality being the biggest factor to actually style and meaning to being the focus.
So now we have the better foundation so for some cool hypotheses and theories. And this is where we really start to take a leap in towards understanding that in this case, material, you know, meaning and core value were motivating themes, especially material value.
And they want the jewelry to connect to something in their lives. And this gives us a really good platform for some test hypotheses. The framework that what we're talking about here is tactically going from and creating that leap from data to information, to knowledge. From the real to the abstract, from the names of something to the something. This mental model stretches over a ton of amazing hypotheses and marketing. Think about it some, start reminding yourself of it. You'll start to see it everywhere, you'll start to use it everywhere.
My name is Ben Labay. I hope you enjoyed this five minute lightning talk, and cheers.
A research process: so simple, and yet... - Aly Abel
Aly Abel from Moonpig believes that too many companies don’t bother defining or implementing a research process to ensure research informs design.
What Aly covers:
- What's the right way for research to inform decisions
- How to explain the value of research and customer data to stakeholders
- The 5 steps of the design-thinking process
- An example of her ecommerce team's 12-month research roadmap
Click below to read the transcript.
A research process: so simple, and yet... - transcript
Hi, I'm Aly and I'm a UX Researcher at Moonpig. Part of my role has been to define a research process. And by that I mean teach about the right way for research to inform rather than post-rationalize decisions that have already been made without customer input.
So over the last decade, I've worked client-side and in agencies across healthcare and consumer brands and one thing I've learned is that most companies don't define a research process.
And you might think, "Why should we care?" Well, the consequence of this kind of ignorance means that research requests come in last minute, questions aren't properly defined, answers are needed now, which means work is rushed.
How many of you have delivered research knowing it's too late, the decisions are made and customer input's already been shelved? Enjoying locked down, a lot of us are baking, so we can probably all agree that you don't put the ingredients in the oven, expect it gets to come out perfect if you haven't kneaded the bread.
And research is the same.
So what's the solution? Well, we all know it's changing the process. And if you're facing this problem in your company or with your clients, turn it around and say to the stakeholder, "Do you want your late nights to be wasted "because you've launched a product that could fail? "Or an A/B test that could have had better results "if we put designs in front of customers?" So yes, it's right, in research we can get answers very fast, but are we giving our stakeholders enough time to reflect on the customer problem?
A research process will help everyone involved.
So here's something many of you are very familiar with, the design thinking process that's embedded in many teams. And it is a brilliant process. It starts with research, which doesn't have to be with customers. It's just evidence that something is wrong. Then you agree what the problem is and then you set out to solve it. And finally, test it with customers or users.
In reality, teams are often focused on the last three stages, which means testing often squeezes in empathize and problem identification. So what you test could be a great idea, but we haven't yet learned that customers might actually need something else.
Or as another example, your company might have come up with a brilliant name for a new product, but what if there's a fundamental problem with how to find the product on your website? So starting research earlier would help uncover all of these problems so that ideation can then consider everything.
So, research process. Well at Moonpig we don't wait for the briefs to roll in. Our process includes a 12-month research roadmap made of three pillars. What's the topic? Why is it important? And when will it happen? So start by listing your research topics, think strategy, what are bigger questions and needs for the business? Have you had a surge of new customers during lockdown? How are you going to retain them?
Then think wider. What other research adds value? What are the big trends? What does loyalty mean these days? What's the difference between a US consumer and UK? This affects every area of your business and findings will help inform future decisions.
Then decide when these projects should happen. So, if Christmas is a peak in your business, work backwards, run customer research in August, and anchor questions based on last year's decisions, and this year's plans.
So as I said, don't wait for briefs to roll in. You have this in place and you're halfway there through the process.
And this takes me to my final points. So our recent process supports design thinking. And by that I mean empathizing and problem identification must happen before we test ideas.
Here's an overview.
What are your goals with the process? We have three, one being that research should always inform.
What are your principles? We have four. One being that you UX should come before UI.
What roles do researchers play in your business? We have three; coaching, collaborating and delivering.
What are your responsibilities? Ours are upskilling teams, driving best practice, overseeing customer research and knowledge sharing to break down the silos.
And then outline your plan. Use your roadmap. Decide what meetings will keep projects moving forward.
And finally, outline a research approach.
For us, it's always starting with gathering existing data before customer research. And this process helps us to make sure that when research is requested, it comes earlier in the decision making so that we can empathize before we ideate.
Best of luck with your process and thanks so much for watching.