Are you talking to wrong users for your product research?

A wrong user is someone who’s neither a benefiter, nor a hacker, nor an expert.

Do I look ripped or what 💪 😎 How’s my new dress 👗🥰 We often ask rhetorical questions that lead us to answers we want to hear. More importantly, we tend to ask those questions only from people who would give us the answers we want to hear. We take those people and their answers as confirmation to our preconceived notions. In real life, that might work in our favour but when it comes to building products, it’s a disaster. Product decisions end up being made based on flawed user input. When product hits the market, we wonder where we went wrong.

Before we start building a product, it’s critical to discover deep and sometimes surprising insights related to the problem we are solving. These unique insights make a product unique.

Starting with wrong users makes us skip this step entirely. Any later attempts to define a “unique” offering feels forced upon.

To hit upon unique insights and make new discoveries, it’s critical not to start with wrong users.

Who’s a wrong user?

Imagine you are building an app to help people remit money. In search of users, you send a quick note to your friends asking if anyone has tried to remit money recently. You find out that your neighbour Alisha sent money to her sister overseas few months back.

You feel lucky to have found your first user.

“Alisha can help me understand her experience and challenges in remitting money. She’s a helpful neighbour after all and a good friend.”

She would answer all your user research questions. To help you further, she might even turn into an early adopter and test your prototype.

There’s one problem though — She isn’t a benefiter, someone who will get the most benefit from your product.

She rarely needs to remit money. It won’t excite her even if you build your product with all her suggestions. She might try your product for few weeks, even months but she won’t stick around. She would escape as soon as the novelty factor fades away.

Now imagine Amar, a blue-collared worker in your office. His family lives back in his home country. He needs to send them money each month. He keeps trying various means from wire transfers to bank transfers to see what works best. He compares the time it takes, costs involved, and convenience with which his folks back home receive the cash.

Amar is a hacker, someone who tries various means to solve the problem because it’s too important for him to be left unresolved.

Also, he’s always looking for the most efficient ways to pay bills back home, send school supplies to his kids, get medicines delivered to his parents, etc. His friends in similar situation see him making smart choices and aspire to emulate him.

Others see Amar as an expert, someone who researches and uses best products and services to save time and gain money.

If you build an app offering the most efficient means to remit money, Amar will be the one benefiting the most from your product. As his friends trust his choices, they will follow suit.

Amar is a benefiter, a hacker, and an expert. He is a 3-in-1 customer called the high-expectation customer (HXC for short).

Alisha, on the other hand, is none of those things.

A wrong user for your product is someone who’s neither a benefiter, nor a hacker, nor an expert.

3 magic questions to reveal the wrong user

When we introduce our clients to the concept of the high-expectation customer (HXC), they love it❣️ They are excited by the idea of defining their very own HXC. In the past, we made the mistake of asking the team for input at this early stage. We wanted to know what they think their customers expect from their product. We ended up with what looked like a “desired” feature set or a wish list from “potential” customers.

That’s when we figured we need to take a step back.

At this point, the idea is not to zero in on features, or even think about features. At this point, the idea is to rope in users for whom this product means a big deal. More importantly, filter out those for whom it doesn’t.

Following are the 3 magic questions we use to filter out the wrong users. You can include these questions in your initial survey to your potential/current users.

Question 1:

How disappointed will you be if you can’t remit money/become richer/organise your day better/learn piano/the thing your product is helping them do?

1. Very much. It’s a high-priority in my life.

2. Not so much. I can live with or without it.

3. Not at all. It doesn’t concern me much.

The first question comes directly from this great article by Rahul Vohra of Superhuman. In this article, he explains how he managed to measure and achieve the product-market fit for his company.

For us, question 1 is a filter for a benefiter. If the problem your product is trying to solve doesn’t mean much to this person, she’s likely to not get the most benefit from your product. We are most interested in the users who select option 1.

We drop the users who select option 3. The users who select option 2 are pursued only if they turn out to be both hackers and experts from the next two questions.

Moving on to question 2:

What are you currently doing to remit money/become richer/organise your day better/learn piano/the thing your product is helping them do?

Question 2 is about understanding if this user is a likely hacker. Someone might answer “Very much. It’s a high-priority in my life” for question 1 but isn’t doing much towards it. It means either the problem is not too important for them to resolve or they are clueless on where to begin. Hold on to these users.

Question 3:

Do your friends or family or others look up to you when they need to remit money/become richer/organise your day better/learn piano/the thing your product is helping them do?

The last question helps us understand if this user is looked upon as an expert by others. Can this user help scale the product organically?

You’d hit a jackpot if you find your 3-in-1 customer but that’s not always the case. Even if you get a 2 (benefiter + hacker or benefiter + expert), the user is worth pursuing further.

Building upon your HXC profile takes time and effort. Filtering out wrong users from the start will steer you in the right direction.

When the wrong people leave your life, the right things start to happen.

A shoutout to undraw for the open-source images!

Thanks for reading! I am Prachi, co-founder of Bayzil, a product strategy and design studio based in Singapore.

We help teams innovate and build digital products that customers love. To work with us or just to say hi 👋, get in touch at prachi@bayzil.com.

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Prachi Nain

Prachi Nain

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