UX Strategy: How to Devise Innovative Digital Products That People Want (2015)
Chapter 3. Validating the Value Proposition
“To know what a business is we must start with its purpose. Its purpose must lie outside of the business itself. In fact, it must lie in society since business enterprise is the organ of the society. There is only one valid definition of business purpose: to create a customer.”
— PETER DRUCKER, 1973
AT THE BEGINNING, YOU DON’T JUST DEFINE YOUR PRODUCT VISION. Rather, you first need to figure out what problem you’re going to solve and what kind of customer needs it solved the most. That’s a lot to figure out, and getting one part wrong could turn your vision into a delusion. So, to stay grounded, you’re going to really dig into Tenet 1, Business Strategy, and Tenet 3, Validated User Research (see Figure 3-1 and refer to Chapter 2 if you need a refresher on the four tenets of UX strategy). In this chapter, you will learn how to create a value proposition, which is the magical thing that you must make tangible for customers. Then, you will go over how to validate it through experiments to prove whether that hypothesis is correct.
Figure 3-1. Tenet 1 and Tenet 3: Business Strategy and Validated User Research
The Blockbuster Value Proposition
When I was in the eighth grade, I used to pretend I had a stomachache so my mom would take me to work with her. She was a legal secretary at Burbank Studios, and I loved wandering the back lots, hiding on sets and watching crews shoot television shows and movies. Once, I even had a chance to meet Ricardo Montalbán on the set of Fantasy Island! The younger me of 1978 just couldn’t imagine a cooler job. And that’s why the older me of 2012 was particularly excited when a blockbuster movie producer arranged a meeting with me at a bungalow on the same lot. He wanted to consult with me on an idea for a product to see if it “had legs.”
EXT. BUNGALOW – MORNING
The shot starts long and then pans up through the
window of the bungalow.
INT. BUNGALOW – MORNING
A production assistant leads our UX strategist
JAIME into the room. The movie producer PAUL is
seated behind his desk. He stands up to greet her.
They shake hands and then settle into their seats.
The assistant leaves the room.
So I have an idea for an ecommerce site, and
I'm hoping you can help me with it.
Let's hear it.
It's like an Amazon.com Wish List for the
Busy Man who needs help shopping for his wardrobe.
Can you tell me more about this "Busy Man"?
Paul gets really excited. He leans forward and ges-
ticulates a lot while describing the Busy Man to
He's the guy whose life is his work. He makes
good money but doesn't have time to spend it.
He loves high-end products but hates shop-
ping for them. He's sick of repeating himself
to salespeople but still wants to get the VIP
Jaime leans forward, hands resting on her knees.
She takes a beat before speaking.
That's very specific. But do you think this
is a problem for most busy men? Do you think
they need it solved?
Absolutely! I certainly do!
In Los Angeles, it’s easy to run into both Hollywood types who pitch movie ideas and tech entrepreneurs who pitch Internet product ideas. What’s funny is how similar they are. Both want to create something original and compelling that makes lots of money. Both need to raise a ton of cash to make their ideas into reality. But, this requires “spinning” a good story in order to convince potential stakeholders and investors that there is an audience out there who will want the idea.
Most investors know that the odds are not in their favor because the market is constantly being inundated with schlock — crappy movies and crappy apps. Then again, when something is truly great, the payoff can be major. And not just in terms of the money. Having a “hit” is also what gives us fulfillment as content and product creators. We want to create something that people find useful and meaningful — something maybe even our mom will like!
However, there is one major difference between making movies and making digital products. With films, regardless of the strategy — casting big-name actors, sequels to board games, well-worn plots and tropes — there are hardly any opportunities in the process of making the film to “de-risk” it through empirical feedback. Sure, filmmakers can test early cuts on their target market, but typically at that point, reshooting is an unaffordable option. With digital products, you can “test market” your concepts on your target audiences much earlier and with much less fidelity to the intended idea. You can reality check your team and ensure that everyone is on the right path. There is no reason to live on Fantasy Island unless you enjoy the risks of big gambling.
§ Just because your stakeholders (or you) really want your product, doesn’t mean anybody else will. Most startups fail because the market doesn’t necessarily need the product.
§ You need to ground your stakeholders and team in reality with empirical evidence. You must turn assumptions into facts.
§ Don’t take what your stakeholders or team says at face value. To learn what potential customers want, hunt them down in person.
What Is a Value Proposition?
Generally, a value proposition takes the form of a statement and is usually the first sentence out of the mouth, as it was for my movie producer client. Think of it as an elevator pitch — when you distill something into a discrete, easy-to-remember, compelling, and repeatable phrase. Its primary purpose is to communicate the benefits that the customer can expect from your offering. Here are examples of value proposition statements for a few well-known products:
§ Airbnb is a community marketplace for people to list, discover, and book unique spaces around the world through the Internet.
§ Snapchat is the fastest way to share messages, photos, videos, texts, and drawings with friends for a limited amount of time.
§ Waze is a social traffic and navigation app based on the world’s largest community of drivers sharing real-time road information and contributing to the “common good” while driving.
No matter what environment you work in as a product maker, you are constantly getting pitched or pitching value propositions. Before their products became household names, just imagine how many times the teams at Airbnb, Snapchat, and Waze had to repeat their value proposition statements with investors until they finally “clicked.”
All this is to say that the little sentence, “It’s like Avatar meets Die Hard!” is really important. But, you might be thinking, how hard could it be to come up with one? It’s not, actually. In fact, there’s even a website called itsthisforthat.com, which generates random value propositions as fast as you can click the refresh button. I generated the one shown in Figure 3-2.
Figure 3-2. A machine-generated value proposition that says “Airbnb for Wedding Venues”
Let’s deconstruct the website’s value proposition formula:
It’s <famous platform or app goes here> for <type of customers or customer need goes here>!
The “this” essentially describes the magical powers of the product. The “this” for the dating app Tinder is how you can immediately let someone know you find them attractive with a swipe interaction. The “this” for Waze is how you can find a driving shortcut because other people around you have their Waze app open and are providing you with real-time data to maneuver around traffic jams. The “this” is the mental model; it’s how people understand the interactive dynamics of a product and how it affects the outcome of how they use it.
The “that” describes either or both the specific customer segment and its need or goal. The “that” for Tinder is people looking for an easier way to “hook up” instead of having to fill out a time-consuming dating profile. The “that” for Waze is drivers who want to avoid getting stuck in traffic even if it means taking routes off the beaten path. The “that” clues us in on who might want or need the “this” and why. What this formula does is give us a fast way to articulate the solution.
But value propositions are not valuable if they do not solve a real problem. I’m not talking minor problems like a scraped knee; I’m talking about painful broken-leg problems. I’m talking about those problems that hinder a certain set of people from doing what they need to do in a timely manner. By solving this kind of problem, a solution would give relief or joy to this large set of people. You need to know everything you can about those problems and people before you build out those solutions, because building software takes time and money. Thus, it’s a risky endeavor to just begin building a new innovative product based on a hunch.
Because what if you are wrong?
Or your boss is wrong?
Or the client is wrong?
Or even the successful movie producer guy is wrong?
Or this digital value proposition that we generated in .05 seconds is wrong?
The answer is simple. If the person with the big hunch is wrong and your team doesn’t find out until after the money is gone, everyone has failed in making something with a true value proposition. Everyone involved has only succeeded in wasting their resources. And because this is the infancy stage of your product vision, you don’t want to get too attached to any ideas — especially without proper validation that real customers will really want the solution.
If you don’t want to live on Fantasy Island...
Just follow these five steps, which I will walk you through in detail:
Step 1: Define your primary customer segment.
Step 2: Identify your customer segment’s (biggest) problem.
Step 3: Create provisional personas based on your assumptions.
Step 4: Conduct customer discovery to validate or invalidate your solution’s initial value proposition.
Step 5: Reassess your value proposition based on what you learned!
(Rinse and repeat until you have product/solution fit.)
It’s that easy! We just need to be empirical in our process.
Step 1: Define your primary customer segment
Because you and your team are launching an innovative product, you are starting with zero customers. Therefore, if you think your customer is everybody, think harder. Otherwise, you’re facing an uphill battle in customer acquisition. Which is easier: getting everybody to use your app, or getting people who really need it to sign up? Many hit digital products have done just that. When Facebook launched, it was exclusive to students at Harvard University, not the entire world. Airbnb tested out its product on the 2008 Democratic National Convention, and even Tinder did its initial pilot project by focusing on college students at the University of Southern California.
The customer is a group or segment of people with a common need or pain. Your primary customer’s pain point must be severe, because there is a lot of risk involved in trying to change how people do something in a familiar way to an unfamiliar one in an uncontested market space. Examples of customer segments are international college students in Los Angeles who have a hard time making friends with native students, aspiring musicians in big cities who want practice gigs, or busy suburban moms who can’t manage their kids’ schedules. These segments can be identified by a combination of demographic and psychographic attributes, but what is most essential is that they describe in 10 words or fewer a set of people on whom you can zero-in.
So, let’s go back to the computer-generated value proposition and imagine the most obvious primary customer. Who the hell needs to plan a wedding on a budget? Hmmm... As Figure 3-3 demonstrates, maybe a bride-to-be? Yes, let’s go with it!
Figure 3-3. Mock-up of typical first page of a pitch deck
Step 2: Identify your customer segment’s (biggest) problem
The problem should be a specific one that a specific customer segment is having. Nonetheless, you need to acknowledge that you and your team are working solely on assumptions, and that’s just the reality of where you begin when making a product. You make assumptions about your users, their needs, and how to solve them. You just need to be very honest about the assumptions you’re making and to take them for what they are: facts people take for granted. Or, as the great Coach Buttermaker (Walter Matthau) in the movie Bad News Bears said to his baseball team, “When you ‘ASSUME,’ you make an ASS out of U and ME.”
At the beginning of the chapter, Paul the movie producer stated that he understood his customer’s problem because it was his own: he was a busy man with money who didn’t have time to shop. Therefore, all busy men needed an online shopping experience to build a high-end custom wardrobe. If that logic worked for every value proposition, I could easily look at the digital value proposition and say, “When I planned my own wedding, I was a bride-to-be on a limited budget, and my biggest pain point was finding a wedding venue in Los Angeles that I could afford.” Which was true for me, but is it true for every frugal bride-to-be?
This is where you want to write out the customer and problem hypothesis in a statement. Here’s what it could look like:
Brides-to-be in Los Angeles have a hard time finding wedding venues that are affordable.
Which, if proven true, would validate an important need for the value proposition:
Airbnb for Finding Wedding Venues.
It would seem, then, that the next logical step would be to start dreaming up the entire feature set for this much-needed solution, right? No. Not yet.
Remember the software engineer from Chapter 1? He jumped straight into building out the solution for his startup. He assumed that customers like him (addicts’ loved ones) would be interested in a digital platform with which they could negotiate prices with treatment centers. He also assumed that there would be a lot of customers like this or at least enough to help keep the business model afloat. Yet, these assumptions were just that: assumptions. He could not pinpoint the reason why his product was unsuccessful until my team ran validated user-research experiments. The experiments exposed the fallacy to him, which was that customers, including those with a decent budget, were highly unlikely to book a treatment center over the Internet the same way they would book a hotel room. He heard directly from the potential customers what he initially didn’t want to believe: booking a treatment center was just too much of a highly emotional decision to be done entirely online.
Here’s a pro tip:
Don’t build your product’s UX around a value proposition unless you have tangible evidence that people will want the product!
If you are a problem solver (which is instinctual for UX designers, product makers, and entrepreneurs), this process at first feels backward. That’s because it is. We are reverse-engineering the solution to validate the assumptions about the customers and their problem. This approach is particularly important for those of you who have produced dozens of products, including ones that have been very successful. Don’t believe your own hype. Instead, approach every new product or project like an experiment.
As I mentioned in the Preface, I’ve been a part-time college professor for more than 20 years. I have always run my courses the same way. The first week, the students have to think of problems they would like to try to solve using technology. Each week, they build toward the final course project, which is to pitch a real product that they’ve tested using the methods I’m teaching you in this book. In the spring of 2014, I offered UX apprenticeships to my students Bita and Ena to take on the “Airbnb for Weddings” product vision. I’m going to present their methods and results to show how you can give any value proposition a real shot to see if it is viable. This was their first assignment: the provisional persona.
Step 3: Create provisional personas based on your assumptions
Personas can be a helpful tool in giving stakeholders and the product team an empathetic sense of what the end user’s needs, goals, and motivations are. In this way, they can make a product more “user-friendly.” However, the concept of provisional personas has had a tumultuous history with advocates on both sides of the table, so I’m going to give you a little lesson on it to explain why I’m using them here and now.
In the early days of software design, the engineers who developed and programmed the products were also typically the designers of the product interfaces. These product interfaces were rarely “user-friendly,” because they were not tested on the end user of the product. Too often, interfaces were pasted together in a hurried fashion to meet a shipping date.
Alan Cooper, a widely recognized Bay Area software designer and programmer, knew this problem all too well. In 1988, Cooper created the visual programming language that would become Visual Basic, an innovation that ultimately enabled an open marketplace for software companies that wanted to build applications for Microsoft Windows. In 1995, he invented personas and wrote books to help software teams to embrace his goal-directed design methodology. Personas were also a critical tool to inspire product stakeholders to make more user-friendly interfaces. But to achieve this kind of persona, it meant that months of qualitative “ethnographic” research had to be conducted to create an authentic model of each end user.
By 2002, personas were a popular tool in the designer toolbox, but they weren’t often used to achieve their original purpose. Instead, big interactive agencies such as Razorfish or Sapient used personas to upsell the research/discovery phase to clients. When used in this way, personas were often laughable caricatures packed full of stereotypical details based on nothing more than marketing data. In fact, this is what happened with the three personas conducted for the Oprah.com redesign I talk about in Chapter 2. The personas that made it to the discovery brief were depicted as three people from different minority backgrounds but only because Oprah had a massive multiracial following. In reality, ethnicity had little to do with the UX of the product. Did African-American Oprah fans need a different interface or feature set than Caucasian Oprah fans? In this way, the personas failed in informing the UX strategy process in a basic way, such as when Cooper writes, “Don’t confuse persona archetypes with stereotypes. Because personas provide a precise design target and also serve as a communication tool to the development team, the designers must choose a particular demographic characteristics with care.”
By the third edition of Cooper’s book About Face in 2007, he added a new section called “When Rigorous Personas Aren’t Possible: Provisional Personas.” The concept was geared for product makers who did not have the time, budgets, or corporate buy-in to perform the fieldwork necessary to gather detailed qualitative data. They were a simple collaborative group exercise for designers and nondesigners to create quickly. In fact, the product designer and author Jeff Gothelf also reintroduced them as a Lean UX technique to help align teams on how they think about the customer before doing customer discovery. This is where personas become useful to you in this book, because a provisional persona will be a helpful communication tool to depict your hypothesized customer and align your team. It also gives everyone a starting point for the validation process. Thus, you can think of a provisional persona as a “back-up” or “low budget” persona, which is better than having no persona at all. (Also see what the long-time UX executive Peter Merholz has to say about profiles in Chapter 10.)
Provisional persona layout and breakdown
The provisional personas will collect and present the assumptions you are making about your primary customer segment. Therefore, all information will be contextual to the hypothesized customer and relevant to the value proposition. Specifics such as demographic details or user goals aren’t necessary unless they are essential to the product. Instead, you want to focus your personas on what you assume is important to customers and how they are currently dealing with the problem.
The provisional persona is made up of these four parts:
Name and snapshot/sketch
What is the customer’s name? What does she look like? If you’re going with a certain gender or demographic — in this example, perhaps a woman in her late 20s or early 30s — search for popular baby names of the early 1980s. If you can sketch, draw her. If you have a photo of someone who fits the part, just paste it. If not, find a good reference photo using Google Images or Flickr.
What factors personally motivate the customer? The description should be a composite archetype of the customer that is relevant to the product idea rather than a stereotype of psychographic or demographic details. For example, your team only cares about the customer’s taste in cars if you are solving a problem related to cars.
This category can be answered in several ways. The first is how the customer is trying to solve the problem now. Is it via a workaround on the Internet? In the real world or a hybrid of both? Is the customer tech-savvy enough to use the Internet to solve his problem? Is he using social networks to do it? Or are there general behaviors for customers who are using similar types of digital products that are relevant to your solution? The second is how the person’s personality affects his behavior. For example, if the person is professionally successful, does that make him a good problem solver? Is the customer trusting or skeptical?
Needs and goals
This category explains what motivates the customer and causes her to act a certain way. For example, what is she missing from the current solution? What specific needs or goals aren’t being satisfied by the customer’s current behaviors? What are the deal-breaker issues she faces? What are compromising points?
Because you are using the provisional persona purely as a thinking tool to get a sense of your primary customer segments, you and your team want to keep the layout and content simple. In the provisional personas that follow, Bita and Ena use a two-by-two grid with a section for each part. They’ve pasted the image of their primary customer in the upper-left section, and they’ve created five to six bullets in each of the other three. Observe how the assumptions about their customers seem relatively easy to prove. You only want statements in your provisional personas that can be externally verified.
Figure 3-4 shows the provisional persona that Bita did for her first homework assignment, for “Airbnb for Weddings.”
Figure 3-4. Bita’s provisional persona for a bride-to-be
Figure 3-5 shows what Ena developed.
Figure 3-5. Ena’s provisional persona for a bride-to-be
What’s most telling about the personas is how different the customers are even though each student worked on the same value proposition. They each assumed the primary customer was a very different kind of bride. Bita assumed that her customer was a professional woman named Jennifer in her late 20s or early 30s. She earns a decent income and is value conscious. Ena, however, assumed that her customer was a younger 20-something bride named Stephanie. This younger bride is in a very different place in her life than the more established and professional Jennifer. This creates more distinctions between the two brides. For instance, price is an issue for the younger Stephanie, but she wants people to have fun. She’s willing to compromise and not have fancy food or that big of a wedding. However, Jennifer is efficient and a problem solver. She has high expectations that everything will be perfect. She needs a solution that will help her save time and get good value.
Which persona is the right one? It doesn’t matter right now, because Bita and Ena are just working with assumptions anyway, and what they’ve built in the provisional personas are just more assumptions. Perhaps in the final product they might be able to suit the needs of both personas, but until then, everything in the personas remains an assumption until proven true or false. Regardless of who ends up being more “correct,” though, the provisional personas helped Bita and Ena paint a clearer picture of their hypothesized customers. Now they just need to find those customers in real life and see what the brides really think!
Step 4: Conduct customer discovery to validate or invalidate your solution’s initial value proposition
In 2005, Steve Blank, a long-time Silicon Valley entrepreneur, published The Four Steps to the Epiphany: Successful Strategies for Products that Win. Although his methodology revolves around four phases, I’m going to ruminate on the first one, customer discovery, as part of your UX strategy.
Customer discovery is a process used to discover, test, and validate whether a specific product solves a known problem for an identifiable group of users; it is essentially conducting user research. However, you don’t want to just watch people, empathize with them, and then make judgments. Instead, you want to “get out of the building” and get customer validation, which is foundational to the Lean Startup business approach (and Tenet 3). You want to actively listen to people and engage them because your goal is to uncover the specific problem that they need solved.
This might sound like an obvious thing to do, but shockingly, the majority of stakeholders whom I work with in startups and enterprises don’t talk to customers. In fact, before Lean Startup, the norm was that companies would just build the product without talking them. Much like Paul the movie producer, the stakeholders or product team assume that if they have the problem or associate with it, this means that they understand it. I think the real reason stakeholders don’t talk to customers is fear. Product visionaries are like screenwriters sweating away at a script that they never show anyone. They’re frightened of what their real customers might think — nobody wants to hear that their baby is ugly.
In an ideal world, customer discovery is a collaborative process involving as many members of the product team going out into the field as possible. Collaboration will also help organically build consensus on what exactly the vision is for the product. If the people you work with don’t want to do customer research, do it for yourself. Do it on the sly without waiting for permission from your boss, the client, or any naysayers. What is crucial is that it is attempted. You can come back from your research and share your discoveries anecdotally with your team. If nobody wants to listen, you can decide at that point if you want to continue working on that project or with your current team, or with your current employer. But at least get out there and discover evidence that might make your product better in the time that you have to work on it. Own your destiny.
We’ve already touched on some reasons why product makers become very protective of their ideas. They put a lot of energy and love into them. If you’re a UX designer, you know exactly what I’m talking about. Clients such as Paul typically come to you with an idea for the product that they want to build. They’ve assumed that customers want their product. But as I’ve already stated, the UX strategist wants to know whether those assumptions are correct. As you’re learning in this book, you don’t want to get too attached to any ideas, especially without proper validation that real customers want the solution.
Fortunately, Bita and Ena aren’t emotionally attached to the value proposition I generated off the Internet. They just need to validate their initial assumptions. And that’s exactly what they’re going to do. They’re going to get out of the building (office or classroom) to conduct problem interviews.
The problem interview
During customer discovery, the goal of the interview is to talk to real people. My students have personas, and they need to talk to the people who match those personas.
Let’s remember Tenet 3: Validated User Research. You want to use the approach of the Lean Startup, which means research should be meaningful, effective, and swift. You want to get into the Build-Measure-Learn loop as quickly as possible (see Figure 3-6). That loop begins with the smallest build of an idea. This build leads to some form of data that can measure what the customers say. Based on that, you then learn from that feedback about how to make the build better. And at this infancy stage of a value proposition, this means getting out of the building to validate provisional personas.
Figure 3-6. The Build-Measure-Learn feedback loop from the book Lean Startup by Eric Ries
You need to identify two or three nearby locations where you can make direct contact with your proposed customers. You can’t hide behind your desk. Think creatively about where your customers lurk by focusing on the types of activities they might be doing. If you can’t find them in the real world, you need to find them on the Internet (more on that in Chapter 8).
In the case of Bita, her provisional persona was of an upper-middle-class yet value-conscious bride-to-be. Bita decided to hit the malls of Los Angeles where she thought she could find people who matched her persona. Her first stop was the Westside Pavilion in West Los Angeles. This mall had plenty of kids’ clothing stores such as Gymboree and Baby Gap where mothers with babies shopped. This was certainly different than what I was thinking, which was that Bita would find women in the midst of shopping for wedding gowns.
Bita’s assumption was that these new mothers might give her insight about planning a wedding because they probably had a wedding before starting their family. And because they had very young children, their wedding was most likely recent. Bita dressed professionally and appropriately. She carried a notebook on which her questions were written and always approached her targeted customer with a smile and only if the timing was right (typically, their baby was asleep in a stroller). This was her script:
Hi, I’m Bita. I’m conducting research on a product idea for an Internet startup. Can you spare a few moments to answer questions related to wedding planning?
The problem interview is actually made up of two parts: the screener and the interview. A screener is a list of questions used to qualify potential participants for a study. You need these questions because you cannot assume that every person you approach is in fact the customer you need and want to validate your persona assumptions. The screener questions will identify the “control group,” on whom we will ultimately validate our hypotheses.
Therefore, good screener questions must help you quickly weed out the wrong people. They should seem nonintrusive to the participant, but you know they are deal-breaker questions. It might be helpful to work backward. What are the exact answers you must hear from someone to qualify them for this mini-experiment? Sometimes, it takes a few iterations of your screener questions to truly ensure that you are talking to the right people. Be okay with fine-tuning your questions on the fly to either make them more general or more specific, based on what happens “in the wild” as you begin talking to people.
Let’s get back to Bita. If the woman she confronted seemed open to chatting, Bita immediately launched into her screener questions.
Phase 1: The screener questions
1. Were you married within the last few years?
o Yes (continue to question 2)
o No (kindly end the interview)
2. Did you happen to get married here in Los Angeles?
o Yes (interview the person)
o No (kindly end the interview)
Based on Bita’s persona, the goal of her screener questions is to identify if the woman she’s interviewing recently planned a wedding in Los Angeles. She needed participants with fresh memories about what happened at their weddings. Also, she needed them to be married in sunny Southern California, in which they probably had an outdoor venue like a park, beach, or fancy backyard. This detail was crucial to validating the Airbnb for Weddings value proposition, because she assumed that these outside locations (such as someone’s fancy backyard overlooking the beach) would have solved this potential participant’s wedding venue woes.
Phase 2: The interview
If a woman passed the screener test, Bita was able to move on to her actual interview questions.
Typically, this is when product makers and tech entrepreneurs like to extol the virtues of their awesome value proposition. But, if you just start pitching ideas at strangers, they tend to just nod their heads in agreement to quickly get the hell away from you. That’s not the validation you need or want. Remember customer discovery is about listening and not selling. Let’s take a look at how Bita handled it in her interview questions:
1. How did you go about planning your wedding?
o Prompt for both ceremony and reception locations
o Prompt for tools/means, such as Internet, word-of-mouth
2. Did you have a budget for venues and were you able to stay within that budget? (If not, by how much more?)
3. How many people were you planning to have at the reception (for example, 50 to 200)?
4. What were some of the challenges you faced in finding the venues (Prompt: e.g., finding the ideal location, such as by the beach)?
5. How did you overcome these challenges? Did you end up having to compromise on your ideal wedding?
These questions actually set up the context for our solution. Now that the participant has that context, it’s time for Bita to ask her money-shot question. Bita:
Excellent, thank you so much for all this great feedback. I have two last questions for you.
6. Have you ever heard of or tried a website called “Airbnb”?
o Yes (continue to question 7)
o No (quickly explain what value prop is of Airbnb with respect to the part about short-term subletting and continue to question 7)
7. If there were a website, like Airbnb, that gave you a numerous choices of gorgeous homes with big backyards in LA that you could rent specifically for a wedding event, what do you think?
You end with your money-shot questions, which are when you actually pitch your hypothetical value proposition. Again, you want to listen and not sell. See how open-ended Bita’s questions are? She’s just pulling the trigger on the solution to see what response she gets without trying to bias the participant in favor or against it. When you ask the money-shot question, just capture the essence of the person’s response and, if they apply, ask any relevant follow-up questions. Then that’s it! Thank the person profusely and let him go on with his day. Ideally, you will try to collect 10 complete interviews from screener to money-shot.
Now, it’s time to do a serious reality check about your primary customer, because this book is talking about digital products for twenty-first-century consumers. Therefore, you need to think about all of your potential customers. Sometimes they are paying customers, and sometimes they are customers who use the product for free. As you probably already noticed, I use the terms “user” and “customer” interchangeably, because users who don’t pay for a product such as Facebook or YouTube are still customers. Facebook and YouTube need buy-in from these nonpaying customers so that paying customers — advertisers — will want to engage with the product. All this is to say that sometimes you only have one primary customer segment for which you need to validate a UX. Here are some examples:
§ A video-streaming website such as Netflix needs movie viewers.
§ An online publication such as the New York Times needs news readers.
§ A financial website such as Citibank needs customers with bank accounts.
But, what if you need two distinct user types for your product to have value? Two-sided markets are what make the Internet go around. They drastically affect the UX strategy because they require two distinct user experiences — one for each customer segment — to be validated and created. eBay has buyers and sellers. Airbnb has hosts and guests. Eventbrite has event producers and event attendees. These digital products are insanely good at providing value to both of these customer segments through their feature sets, and that’s something that you might also need to do.
The real Airbnb is a digital platform that facilitates one set of customers (hosts) subletting their properties to another set of customers (guests). Airbnb then collects a small percentage of the transaction from both “sides.” Bita and Ena’s value proposition is based on Airbnb’s innovative business model, which is based on the peer-to-peer sharing economy. For them to solve the problem of helping brides find an affordable venue for weddings, they must match them up with the other side of the market: people who are willing to rent their homes out for a wedding event.
Ena realized this during her customer discovery. Consequently, she took a step back and created a provisional persona of her other primary customer, which you can see in Figure 3-7.
Figure 3-7. Ena’s provisional persona for a wedding venue host
This is the customer segment that also must exist to make her value proposition work. Ena needs people like John and Susan: people who own nice homes in Malibu and are open to innovative solutions for taking advantage of their home’s value. They are probably older than our brides-to-be and quite concerned that their homes don’t get trashed, or so Ena’s persona assumes.
I asked Ena how she planned to validate this provisional persona. Where would she find people of this type? Would she knock on big fancy doors of homes by the beach? Good luck. Maybe she could ask people who were shopping at the high-end grocery store in Malibu if they would rent their home? I was concerned that she was chasing a persona that wouldn’t be easy to verify. So I sent her out to do more customer discovery.
The following week Ena came back with some pretty cool validation, which is shown in Figure 3-8. She had put on her bride-to-be hat and contacted some real hosts on the real Airbnb. She asked them if they would consider renting their homes out for a wedding event. She even asked how much they might charge. As it turns out, people are already doing this.
Figure 3-8. Example of a positive response from hosts on Airbnb for Ena’s inquiry about renting their home for a wedding
Hosts on Airbnb were already bending the system. They were creating pricing packages totally separate from the Airbnb business model and UX, and the responses showed Ena how familiar hosts were with wedding inquiries. So, how did this information affect Ena’s value proposition? Let’s find out!
Step 5: Reassess your value proposition based on what you learned! (And continue to iterate until you have product/market fit.)
As you can see, conducting validated user researcher does not need to be costly or time-consuming. For Bita, it cost her one Saturday to validate whether her assumptions were right, which she then compiled into the results shown in Figure 3-9.
Figure 3-9. Bita’s customer discovery results
Yes, she only talked to 10 people who passed her screener questions, but she found that 9 of them had a huge problem finding an affordable venue. Obviously, the value proposition’s hypothetical problem was real. However, she also learned about how much those people spent on their weddings and how many people they invited. This knowledge affected how she thought about her value proposition because it meant the detail of venue size was actually more important than she originally assumed. It made her question whether there were homes large enough in Los Angeles to accommodate the needs of her personas. It was a reality check.
In contrast, Ena’s customer discovery revealed that there is already an existing solution for Airbnb for Weddings, and it was...Airbnb! Moreover, she also learned that Airbnb is not designed to address the purpose, problems, or perspectives faced by the host or bride-to-be. For example, you currently can’t search for homes that will allow private parties. You have to look at each house, one listing at a time, and then contact the owners individually just as Ena did. Yet people (both hosts and brides-to-be) are currently using Airbnb as a Band-Aid solution because there is no better alternative! It’s when you stumble on evidence like this that your “value innovation” creative juices should start flowing.
Now that we have feedback, you and your team, like Bita and Ena, need to make some decisions, because one of three things should have happened:
§ You did not validate your customer hypothesis. Therefore, you need to pivot on who you think your customers really are. Go back to Step 1.
§ You did not validate the pain point your customers were experiencing. Therefore, you need to pivot on the problem. Go back to Step 2.
§ You validated both your customer and your problem hypothesis and are feeling pretty good about your solution’s value proposition. Go on to Chapter 4.
At the beginning of this chapter, I talked about great value propositions from amazing companies like Waze, Airbnb, and Snapchat. Some of these value props are very different from what their founders started with before their products had substantial traction. Value propositions of products evolve with a great understanding of customers’ needs. Not to quote Peter Drucker ad nauseum, but he did say, “Strategy requires knowing what our business is and what it should be.”
By mashing up customer-discovery techniques with traditional user-research tools such as provisional personas, you now have a cost-efficient way to determine if you are on the right track with your product. Even if you are intimidated by users, new to research, locked in by a requirements document, fighting a looming deadline, or staring at a two-line vision statement, you want to reach out to users when you are at the starting point for a product development cycle. Because doing so is always far better than making an “ASS out of U and Me.”
 Drucker, Peter. Management: Tasks, Responsibilities, Practices. HarperBusiness, 1973.
 Cooper, Alan. About Face. Wiley, 1995.
 Cooper, Alan. About Face 3. Wiley, 2007.
 Gothelf, Jeff with Josh Seiden. Lean UX. O’Reilly, 2013.
 Blank, Steve. The Four Steps to the Epiphany. K&S Ranch Press, 2005.
 Drucker, Peter. Management: Tasks, Responsibilities, Practices. HarperBusiness, 1973.