Hypothesis Generation vs. Validation

A lot of people ask me what sort of research they should be doing on their products. There are a lot of factors that go into deciding which sort of information you should be getting from users, but it pretty much boils down to a question of “what do you want to learn.”

Today, I’m going to explore one of the many ways you can go about looking at this: Hypothesis Generation vs. Hypothesis Validation. Don’t worry, it’s not as complicated as I’ve made it sound.

What is Hypothesis Generation

In a nutshell, hypothesis generation is what helps you come up with new ideas for what you need to change. Sure, you can do this by sitting around in a room and brainstorming new features, but reaching out and learning from your users is a much faster way of getting the right data.

Imagine you were building a product to help people buy shoes online. Hypothesis generation might include things like:

• Talking to people who buy shoes online to explore what their problems are
• Talking to people who don’t buy shoes online to understand why
• Watching people attempt to buy shoes both online and offline in order to understand what their problems really are rather than what they tell you they are
• Watching people use your product to figure out if you’ve done anything particularly confusing that is keeping them from buying shoes from you

As you can see, you can do hypothesis generation at any point in the development of your product. For example, before you have any product at all, you need to do research to learn about your potential users’ habits and problems. Once you have a product, you need to do hypothesis generation to understand how people are using your product and what problems you’ve caused.

To be clear, the research itself does not generate hypotheses. YOU do that. The goal is not to just go out and have people tell you exactly what they want and then build it. The goal is to gain an understanding of your users or your product to help you think up clever ideas for what to build next.

Good hypothesis generation almost always involves qualitative research. At some point, you need to observe people or talk to people in order to understand them better.

However, you can sometimes use data mining or other metrics analyzation to begin to generate a hypothesis. For example, you might look at your registration flow and notice a severe drop off half way through. This might give you a clue that you have some sort of user problem half way through your registration process that you might want to look into with some qualitative research.

What is Hypothesis Validation

Hypothesis validation is different. In this case, you already have an idea of what is wrong, and you have an idea of how you might possibly fix it. You now have to go out and do some research to figure out if your assumptions and decisions were correct.

For our fictional shoe-buying product, hypothesis validation might look something like:

• Standard usability testing on a proposed new purchase flow to see if it goes more smoothly than the old one
• Showing mockups to people in a particular persona group to see if a proposed new feature appeals to that specific group of people
• A/B testing of changes to see if a new feature improves purchase conversion

Hypothesis validation also almost always involves some sort of tangible thing that is getting tested. That thing could be anything from a wireframe to a prototype to an actual feature, but there’s something that you’re testing and getting concrete data about.

You can use both quantitative and qualitative data to validate a hypothesis, but you have to choose carefully to make sure you’re testing the right thing. In fact, sometimes a combination of the two is most effective. I’ve got some information on choosing the right type of test in my post Qual vs. Quant: When to Listen and When to Measure.

Types of Research

Why is this distinction between generation and validation important? Because figuring out whether you’re generating hypotheses or validating them is necessary for deciding which type of research you want to do.

Want to understand why nobody is registering for your site? Generate some hypotheses with observational testing of new users. Want to see if the mockups for your new registration flow are likely to improve matters? Validate your hypothesis with straight usability testing of a prototype.

These aren’t the only factors that go into determining the type of research necessary for your stage of product development, but they’re an important part of deciding how to learn from your users.

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Designers Need to A/B Test Their Designs

The other day, I posted something I strongly believe on Twitter. A few people disagreed. I’d like to address the arguments, and I’d love to hear feedback and counter-arguments in the comments where you have more than 140 characters to tell me I’m wrong.

My original tweet was, “I don't trust designers who don't want their designs a/b tested. They're not interested in knowing if they were wrong.”

Here are some of the real responses that I got on Twitter with my longer form response.

“There’s a difference between A/B testing (public) and internally deciding. Design is also a matter of taste.”

I agree. There is a big difference between A/B testing in public and internally deciding. That’s why I’m such a huge fan of A/B testing. You can debate this stuff for weeks, and often it’s a huge waste of time.

When you’re debating design internally, what you should be asking is “which of these designs will be better for the business and users.” A/B testing tells you conclusively which side is right. Debate over!

Ok, there’s the small exception of short term vs. long term effects, which is addressed later, but in general, it’s more definitive than the opinion of the people in the room.

With regard to the “matter of taste,” that’s both true and false. Sure, different people like different designs. What you’re saying by refusing to A/B test your designs is that your taste as a designer should always trump that of the majority of your users. As long as you like your design, you don’t care whether users agree with you.

If you want your design aesthetic to override that of your users, you should be an artist. I love art. I even, very occasionally, buy some of it.

But I pay for products all the time, and I tend to buy products that I think are well designed, not necessarily ones where the designer thought they were well designed.

“If Apple had done A/B tests for the iPod in 2001 with a user-replaceable battery, that version would’ve likely won—initially.”

Honestly, it still might win. Is taking your iPod to the Apple store when the battery dies really a feature? No! It’s a design tradeoff. They couldn’t create something with the other design elements they wanted that still had a replaceable battery. That’s fine. 


But all other things about the iPod being totally equal, wouldn’t you buy the one where you could replace the battery yourself? I would. The key there is the phrase “totally equal.”

“Seeing far into the future of technology is not something consumers are particularly great at.”

I feel like the guy who made this argument was confusing A/B testing with bad qualitative testing or just asking users what they would like to see in a product.

This isn’t what A/B testing does. A/B testing measures actual user behavior right now. If I make this change, will they give me more money? It has literally nothing to do with asking users to figure out the future of technology.

“A/B testing has value but shouldn't be litmus test for designer or a design”

Really? What should be the litmus test for a designer or a design if not, “does this change or set of changes actually improve the key metrics of my company”?

In the end, isn’t that the litmus test for everybody in a company? Are you contributing to the profitability of the business in some way?

If you have some better way of figuring out if your design changes are actually improving real metrics, I’d love to hear about it. We can make THAT the litmus test for design.

“Data is valuable but must be interpreted. Doesn't "prove" wrongness or rightness. Designer still has judgment.”

I agree with the first sentence. Data certainly must be interpreted. I even agree that certain design changes may hurt certain metrics, and that can be ok if they’re improving other metrics or are shown to improve things in the long run.

But the only way to know if your overall design is actually making things better for your users is by scientifically testing it against a control.

If your overall design changes aren’t improving key metrics, where’s the judgement there? If you release something that is meant to increase the number of signups and it decreases the number of signups, I think that pretty effectively “proves wrongness.”

The great thing about A/B testing is that you know when this happens.

“Is it the designers fault, surely more appropriate to an IA? After all the IA should dictate the feel/flow.”

First off, I don’t work for companies that are big enough to draw a distinction between the two, but I’m sure there’s enough blame to go around.

Secondly, I think that everybody in an organization has the responsibility to improve key metrics. If you think that your work shouldn’t increase revenue, retention, or other numbers you want higher, why should you be employed?

Design of all kinds is important and can have a huge impact on company profitability. That impact can and should be measured. You don’t get a pass just because you’re not changing flow.

“A/B tests are a snapshot of current variables. They don’t embody nor convey a bigger strategy or long-term vision.”

Also, “That’s only an absolute truth you can rely on if you A/B test for the entire lifespan of the product, which defeats the point.”

These are excellent points, and they are a drawback of A/B testing. It’s sometimes tough to tell what the long term effects of a particular design change are going to be from A/B testing. Also, A/B testing doesn’t easily account for design changes that are a part of a larger design strategy.

In other words, sometimes you’re going to make changes that cause problems with your metrics in the short term, because you strongly believe that it’s going to improve things long term.

However, I believe that you address this by recognizing the potential for problems and designing a better test, not by refusing to A/B test at all.

Just because this particular tool isn’t perfect doesn’t mean we get to fall back on “trust the designers implicitly and never make them check their work.” That doesn’t work out so well sometimes either.

An Argument I Didn’t Hear

There’s one really good argument that I didn’t get, although some of the above tweets touched on it. Sometimes changes that individually test well don’t test well as a whole.

This is a really serious problem with A/B testing because you can wind up with Frankenstein-style interfaces. Each individual decision wins, but the combination is a giant mess.

Again, you don’t address this by not A/B testing. You address it by designing better tests and making sure that all of your combined decisions are still improving things.

How I Really Feel

Look, if I’m hiring for a company that wants to make money (and most of them do), I want my designers to understand how their changes actually affect my bottom line.

No matter how great a designer thinks his or her design is, if it hurts my revenue and retention or other key metrics, it’s a bad design for my company and my users.

Saying you’re against having your designs A/B tested sounds like you’re saying that you just don’t care whether what you’re changing works for users and the company. As a designer, you’re welcome to do that, but I’m not going to work with you.

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5 Fun Ways to Ruin Your Startup

So, you’re interested in ruining your startup. At least, that’s what it seems like based on a lot of decisions I see some companies making.

Let’s talk about some of those terrible decisions that really hurt startups.

Hire Big Thinkers

Here’s the thing about Big Thinkers or people who describe themselves as Big Picture People. They don’t execute. At least, they don’t execute in any way that is helpful to a startup.

Sure, there are a few people who can both lead and get their hands dirty with details. If you find one of those people, hire them immediately.

But more often, I see startups stall out because they’ve got somebody making decisions who doesn’t have to actually implement any of those decisions. They’re delegators. And the problem is, at very early stage startups, there just aren’t enough people to delegate TO.

If you’ve got a team of four or five people (or even ten or fifteen), every person should be spending the majority of his or her time actually building, making, designing, writing, testing, selling, or some other verb that isn’t “setting direction” or “planning” or “establishing policies.”

Want a successful startup? Hire Big Doers, not Big Thinkers.

Talk About Awesome Features All The Time

Yes, yes. You have this fantastic idea for the next big pivot that’s going to make you all rich. But you know what? That idea that you had 2 months ago that you still haven’t finished building was also fantastic. So is the one you’ll have 2 months from now. Also the one you’ll have 2 minutes from now.

Startup people are incredibly rich in ideas. Unfortunately, they tend to be broke in every other conceivable resource.

A great way to ruin your startup is to spend all of your time in meetings discussing in detail all the wonderful features you’re going to add in the future. Instead, capture the broad outlines of the idea quickly, put them in your backlog, and, when you’ve actually built something and need to move on to something new, see what ideas you’ve collected that would solve a real customer need. THEN design and build them.

Want a successful startup? Sure, you need to dedicate a little bit of time to thinking about the future, but spend a hell of a lot more time working on the present.

Wait To Ship Until It’s Perfect

It can be tough to release something into the wild before you think it’s perfect. But the thing is, it’s never going to be perfect, and the faster you get it out there, the faster you’re going to start learning which parts are the least perfect.

The longer you put off getting something in front of users, the more money you’re going to spend on something that might very well fail. Wouldn’t it be better to find that out early enough to turn it around and make it awesome?

Want a successful startup? Release small pieces of your product often, and get over worrying that it’s ugly or doesn’t work exactly the way you want it to. You’re just going to end up changing it all anyway.

Work 40 Hours a Week

This one may not be what you expect. It’s not some diatribe about how startup employees need to work 24/7 and not have outside lives and eat all their meals at their desks. If that works for you, great. Personally, I enjoy going outside.

But you do need to acknowledge that work at a startup doesn’t follow a strict 9-5 routine. Sometimes you need to check on things over the weekend or answer customer complaints late at night. Sometimes you need to make a final push to get something out the door quickly. Sometimes decisions need to be made outside of regular business hours, and there isn’t anybody else to make them.

Want a successful startup? You don’t need to live at the office, but you do need to be aware of what’s happening and be able to react when necessary. If you want to turn your phone off at 5pm on Fridays, you might consider working someplace where you’ve got more people to back you up. 

Make A Lot of PowerPoint Decks

Sure, investors love them, and you’ve always got to show something to your board, but I’ve seen this get really out of hand. If you’re spending an hour or two a week building slides to share information with five other people, you are wasting everyone’s time.

I get that there’s important information that you need to share with the team, but the problem with PowerPoint is that people start doing things like tweaking display and finding funny pictures to make their points. A whiteboard works just as well for writing a few bullets, and it’ll get you out of meetings faster, not to mention taking far less prep time. 


Want a successful startup? Consider creating a simple dashboard of all the metrics that everybody in the company should be monitoring so that they can see the pertinent information at any time. That way, nobody’s waiting on you to build graphs and paste them into a deck once a week.

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User Research You Should Be Doing (but probably aren't)

Startups know they should get out of the building and talk to their customers, but sometimes they’re a little too literal about it. There are tons of ways to get great information from your customers. The trick is knowing which technique answers the questions you have right now.

Sure, you’re doing usability tests and trying to have customer development interviews, but here are a few slightly unusual qualitative user research techniques you should be employing but probably aren’t.

Competitor Usability Testing

Have you ever considered running a user test on a competitor’s site?

This one’s fun because it feels a little sneaky. It also gets you a tremendous amount of great information, since chances are somebody is already making mistakes that you don’t have to make.

For example, when one of my clients, Crave, wanted to build a marketplace for buying and selling collectibles, we spent time watching people using other shopping and selling sites. We learned what people loved and hated about the products they were already using, so we could create a product that incorporated only the good bits.

The result was a buying and selling experience that users preferred to several big name shopping sites that will remain nameless.

Bonus tip: There’s always the temptation to borrow ideas from a big competitor with the excuse, “well, so and so is doing it, and they’re successful, so it must be right!” Guess what? Sometimes other companies are successful for a lot of reasons other than that thing you’re stealing from them. Make sure users like that part of a competitor's product before using it in your own.

Creating a Great Design and Research Culture

I led a conversation recently at Web 2.0 Expo about creating a great design and research culture at your startup. To be clear, I didn’t offer to run it because I’m an expert, but it’s a topic I’m extremely interested in. I wanted to find out from other people what their problems have been and see if we could help each other solve those problems.

The most interesting thing to me was how similar many of the problems were, which leads me to hypothesize that too many companies are making the same mistakes over and over when trying to integrate design and research into their organizations.

Here are a few of the common complaints I heard and some of the solutions that were proposed.

Keeping Design in a Silo

The most common problem was bad communication between the design team and other teams within the company. One participant said that, in her company, the visual designers were on another floor from the UX designers, and the designs didn’t always translate correctly.

Another participant talked about a company where the engineers, designers, and strategy people were all in different countries. The cultural differences between the different teams led to even more communication problems.

Solution: Our proposed solution to this problem was to blend teams whenever possible. A participant told us that, when they embedded designers with the engineers all sorts of good things happened. Not only did communication improve because they were all sitting together, but they actually became friends, which made them all more willing to listen to different points of view.

What Makes UX Lean - My Talk from SXSW

If you couldn’t make it to SXSW this year, there was a fantastic, all day lean startup track with talks from lots of lean startup experts. I was lucky enough to be asked to be on the Lean UX panel, along with the always awesome Janice Fraser, Ian McFarland, and Dan Martell.

I gave a short talk on what makes Lean UX Lean. Since I’m a blogger at heart, I wrote down pretty much everything I was going to say first, which means I can now publish a draft of the talk here! If you didn’t get to hear the panel, or if you did and want a quick refresher, please enjoy!

I’ve been a user experience designer for a lot of years, and I’ve worked with a lot of lean startups, which is part of the reason why I got a call last year from Manuel Rosso, the CEO of Food on the Table.

Now, Food on the Table is a very lean startup here in Austin. Because they’re a lean startup, they measure absolutely everything. And because they measure everything, Manuel knew immediately when the product developed an activation problem.

The whole project has been written up in a post for Eric’s Startup Lessons Learned blog, and I strongly recommend that you go read it if you haven’t already. It has a lot of tips about how to incorporate design into your startup that you’ll hopefully find helpful.

But today, I want to go a little deeper into what made that project a good example of Lean UX. Because, during that project, we did a lot of things that you might do in any sort of a UX project for any sort of a company.

For example, we did qualitative user research to understand why users were having a problem. We made sketches and built interactive prototypes, and we tested and iterated on them.

These are wonderful, helpful things to do, but they’re not unique to Lean User Experience Design. They’re part of User Centered Design, which I’m a huge fan of, and I’ve done all of those things in waterfall projects at giant companies that were anything but lean.

So, what are a few things that made this a lean ux project and not just a regular old redesign?

Integrating Quantitative Research

I think the first hallmark of Lean UX is using quantitative metrics to both drive and validate design changes. What does that mean? Well, it means that the reason we were working on the first time user experience was because a specific metric, activation, wasn’t as high as the team wanted it to be.

Quantitative metrics didn’t tell us exactly why we had a problem - we needed to do our qualitative research to understand that - but it did tell us what our most immediate problem was, which helped us to understand where we should start improving our user experience.

In that way, the metric drove the product decision.

Quantitative metrics also meant that we knew, at the end of the project, we’d be validating our work with an a/b test against the original design. That quantitative validation of design really helps improve the design process over the long run, because we can see what sorts of changes have the biggest positive impact on our end user experience. That lets us improve the ROI on future design projects.

When Is a Design Done?

I was talking with a designer about Lean UX. I was explaining that one of the hallmarks of Lean UX is to get a good, but not complete version of a product or feature designed and built and then iterate on it later. She thought this sounded like an interesting approach, but then she asked, “When do you know you’re done?”

Figuring out when you’re “done” is tricky for any design or redesign project, unless you’re a consulting agency, of course, in which case the answer is, “when the client runs out of money.” But I realized that, in Lean UX, figuring out when you’re done is actually incredibly easy.

You’re done when your metrics tell you you’re done.

Let me explain. No product is ever actually “done.” There is always something you could do to improve it. However, projects can certainly be done. The trick is that you have to choose your projects correctly.

What’s the correct way to choose a Lean UX project? Every Lean UX project should be chosen based on a metric.

This may piss off a lot of designers who want to make wonderful, exciting, super cool designs just for the sake of design or user happiness, but when it comes down to it, unless you’re independently wealthy, every design change you make should move a number that is important to your business.

Now, it is a lucky break for those of us who care deeply about our users that improving the overall user experience of the product frequently improves some number that the business people care about. But not every single thing you can do to make a user happy has the same ROI for the business. And not every improvement makes the right people happy at the right time.

That’s why the UX projects you choose should be based on metrics.

Let me give you an example. Whoever it is at your startup who is in charge of running the business should have a pretty good idea of what your various metrics have to be in order for you to all retire and buy yachts. For example, your Activation number may have to be 20% and your Retention may have to be 70%. (Please note, I made these numbers up. Your metrics may vary.)

They pick these numbers because they know that having, for example, a 99% retention rate and a 1% activation rate may lead to retaining 3 incredibly happy users forever, which is suboptimal from a business perspective.

So, if your activation number is at 10%, your business folks may come to you and say, “we need to turn more of our acquired traffic into regular users because we have identified this as the most important problem to solve at this moment.” You respond, “Great! How many more do you need?” They explain that you need to get activation from 10% to 20%.

You will notice that the metrics are not driving your design decisions. Nor are they driving your feature requirements or any other product changes. They are simply telling you what your biggest business problem currently is.

Now, it’s up to you as a designer or product owner to figure out what is keeping the activation number low and then come up with some ideas of how to fix it. You do this with what I like to call “research and design” or alternately “that thing you are paid to do.”

You may have dozens of wonderful ideas for how to fix the problem, and you may love and believe in all of them. You may not, however, actually execute every single one of them.

This is where the Lean part comes in.

Ideally, you will design and execute as many of the fixes as necessary in order to move the number to where you want it to be. Maybe you’re awesome (or awesomely lucky), and you move that activation number on the first try with a very small bug fix.

Does that mean you never get to implement the super sweet, but somewhat complicated, feature that you know will make users incredibly happy and improve activation even more? No! Unfortunately, you may not get to implement it just yet.

You see, once you got your activation number to where it needed to be, it stopped being the most important problem to solve. Now, maybe you need to work on getting retention higher or improving revenue or referral.

On the flip side, maybe you redesign the first time user flow and improve activation, but not by enough. That means you should continue working on it. Figure out why your changes didn’t have as big of an impact as you thought they would, and then try some new things.

You’re not “finished” until your metrics are where you want them to be.

Why is this important? Startups have a ridiculous number of things to do, and they typically have limited resources. It can be incredibly difficult to prioritize when to keep working on a feature or an area of the product, and when to move on.

By setting the goals ahead of time based on metrics that are critical to the business, it becomes much easier to know when you’re “done,” and when you should keep optimizing or redesigning.

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Like Lean UX but hate reading? I'll be on the UX panel at the Lean Startup track at SXSW. You should come see it and then say hi to me afterward.