Making sense of numbers: How to do quantitative analysis

Are you building the right product? It’s an important question whether you are a startup or a big company. Good research can help guide you. Doing it incorrectly and you’ll go down the wrong path.

There are two basic types of research: qualitative and quantitative. Qualitative generally involves asking people what they want or their experiences with existing products. Quantitative using hard numbers from your users.

Quantitative research can help you answer questions like “What features do I need to add to my product?” “What features can I remove from my product?” “How is my user base generating revenue?” “Where is there fraud and abuse?” (There is some overlap; I’ll do a separate post on qualitative research.)

Some caveats to look out for when doing quantitative analysis:

  • Data talk, but people hear it in different ways. Given the same set of facts, people can come to multiple interpretations.
  • Interpretation of some metrics can and should change over time. At the very least, acceleration will change over time.
  • A single metric can easily be gamed, either by accident or intent (conning investors).

These are some of my favorite things in quantitative analysis. This is by no means a complete list. 

A/B testing

This is commonly used to test different messages or designs. Two variants (A and B) are presented to different users. Marketing emails commonly use A/B testing. Take a small portion of your subscriber list and send one subject line to half and another subject line to another half. With the data on open rates that you get from these emails, you can send the one with the better conversion to the rest of your list. There can be more than two; you can have A/B/C.

1% testing

This is a variant of A/B testing. It’s commonly used to test different features, especially in complicated products or products so well established that you don’t want to change the experience overnight.

Take Facebook’s News Feed. This is a product that is used by billions of users around the world. Adding a new feature without testing can cause a lot of grief and negative feedback. Before you roll it out widely, you present the new feature to a tiny percent of the user and track how it performs. Do people use it? How often do people use it? Does it add or subtract from other features people use. (I call it 1% testing, but in Facebook’s case, it might be 0.001% testing.)

Market segmentation

One of the challenges with data is that averages can mask important differences. You can dig into data to identify segments that you want to go after. If you’re running a credit card business and find that 15% of your overall spend is travel, that tells you one thing. But when you look deeper, you find that a group of customers spend $50,000 a year on travel. This might lead you to create products for that lucrative customer.

You can also use data to figure out who your profitable and unprofitable customers are. In many products, you’ll find that some customers are unprofitable. They could be doing too many returns. (E-commerce.)

 Fraud/abuse analysis

Detecting fraud (illegal behavior) and abuse (legal behavior but not within your business model) is a great way to use data.

I worked for a company that sold long distance calls. When we looked at the usage data, we found that we had a very large amount of usage to Tuvalu. Given that it’s a tiny nation, this didn’t make sense. A closer look found that there was an error in our rate tables and we were selling something for 10 cents that cost us $2.00. As you’d expect, people from Tuvalu told each other about it and we became the calling service of choice for them. (Some of the details here have been changed.) 

Another use case is finding the outliers in all-you-can-eat plans. Think about cell phone data plans. In the AYCE model, some customers might use 1 GB of data and others use 100GB. Your business model and network capacity is based on average usage of 5 GB of data. The 100GB user hogs capacity and slows things down for everyone else. With data, you can develop new policies: the * that says data rates will be slowed down after 25 GB of use.

Search analysis

Looking at what people search for but you haven’t delivered is important to product planning and improving the experience. After all, they came to you for it.

Let’s say you run a ride app. When someone launches the app, they might be an area where you don’t offer service. Tracking those requests gives you insight on markets that you might want to look at when developing expansion plans.

It’s also a way to improve the product to suggest alternatives that the user might want. If someone is in New York City and searches for “In-N-Out,” you might respond “There are no In-N-Out burgers in New York City, but here are some McDonald’s.” Just kidding. I’d probably return Shake Shack, but In-N-Out is so much better.

Cohort analysis

The key to a successful business is that lifetime value is greater than customer acquisition cost. (Often written as LTV > CAC). You want to make sure that, on average, you make more from customers over their lifetime than it costs to get them.

Look at the customers that signed up for your service 1 year ago and how much they spent and when. For customers that sign up today, can you use the historical data to model what the new customers are likely to do?

When looking at data, you also have to weigh the cost of the analysis against the value of the data. If you’re using data to analyze how people navigate through your site, it may be sufficient just to track data on a small subset of users. Adding too much tracking can add to latency in your site or app.

Also, if you’re trying to decide whether or not to implement something that will take 2 days, it doesn’t make sense to spend 2 weeks to build a system to get the data.

There are a variety of tools you can use for quantitative analysis, depending on what you’re trying to get at. Marketing tools like HubSpot handle A/B testing for email campaigns. Google and Facebook have their own tools for ad performance analytics. Google Analytics and Adobe Analytics allow you to analyze user behavior. For complex feature-level data, you will likely have to create your own database and run SQL queries against it.

COIVD-19 Caveat: For most businesses, I don’t recommend doing quantitative research based on data beginning in March 2020, unless you’re using it to compare the impact of COVID-19. If you try to project based on data from March 2020 on, you’re likely to over or underestimate behavior post COVID-19. 

Grammar trivia: Data is plural, not singular. (Plural of datum.) It’s one of those weird English things that doesn’t seem right, but is. Like how a person who runs a restaurant is a restaurateur, not a restauranteur.

What it means to be a product leader

There has been a lot written about how to be a great product person. The skills for being a product leader are different. Here are some of the things I’ve tried to do in my time as a product leader. (Many of these skills apply to leadership in general.)

  • Represent product in leadership meetings. Any organization will have many competing priorities. This includes business strategy, customer needs, marketing campaigns and financial situation. All of these contribute to what the organization needs from the product organization. It’s your job to listen to these competing needs and provide direction to the rest of the organization to ensure that the expectations from executive leadership are realistic.
  • Go beyond buzzwords. The CEO wants AI in the product? Sounds sexy. But what does that actually mean? Delve into the details. If the CEO wants something that can’t be built with today’s technology, it’s the product leader’s job to say that.
  • Clearly communicate priorities. Once priorities are decided, it’s up to you to make sure that everyone on your team knows what they are and how they fall into the schedule and affect the roadmap. Priorities can and will change and the changes need to be communicated quickly to the team, with direction on what other work needs to be delayed or canceled.
  • Empower people. “Empowerment” is a buzzword too often used in job descriptions, with little to back it up. As a product leader, you can’t make all the  product decisions yourself — there are way too many. If you do, you will fail at the other aspects of your job such as working with company executives on overall strategy.
    Let product managers make decisions. Many decisions often have little consequence to the overall success of the product. Is the right timeout for a login 1 day or 3 weeks? In most cases, you won’t know until you try it. Clearly, the right answer isn’t 10 seconds or 10 months. The goal is to build it in such a way that you can change it later.
    Be prepared to step up into the weeds when something critical comes up, but don’t stay there. I’ve had to do QA when time was tight and we needed to get things out. That should be the exception. You’re being paid way too much for that.
  • Make decisions quickly. Inevitably, there will be disagreement among the members of the product team or between product and design. When these come about, it’s your job to make a decision. It’s better to resolve these quickly with the knowledge that most decisions are reversible once you have more knowledge on how customers respond. Don’t let decisions drag out with weeks or months.
  • Elevate the skills of your team. Every team member will have strengths and weaknesses. Help your team members up their game. I’ve spent a lot of time teaching teammates on elements of product design, how to do customer research and how to communicate, among many other things. Some of this had been in the form of classes for the team, others have been in writings.  (You can also find a lot of my writings on product management and customer experience on this blog.)
  • Congratulate in public, criticize in private. You’ll have successes and failure. Celebrate the successes in public so that the team can share in the joy and excitement. When things go wrong, don’t criticize or berate people in pubic. Things will fail; that’s the nature of launching products. Failure is great, if you learn from it.
    Embrace risk taking. If people are afraid of taking risks because they fear public flogging, your products may end up being too saccharine.
  • Hire great product people. If your company is growing, you’ll need to hire more. As important as skills are, fit is more important. You can teach someone how to do market research; it’s much harder to convince them to care.
    There are different types of roles in product organizations. Some are more structured and repetitive. Some require creativity. Put the wrong person in the wrong role and they will be unhappy and unproductive.
  • Say “No.” This is probably the most underrated. Humans generally want to make others happy. Product leadership requires balancing every aspect of the organization. It’s easy to string people along, but it’s a bad idea. It’s better to clearly say no. It’s not possible with the schedule. The technology doesn’t exist. You’d need to spend a lot of money on AWS. Whatever the reason, put it out there. If someone doesn’t accept your “no,” then take it to the executive team for a resolution. You’ll get more done faster and are less likely to burn relationships.

These are, of course, general guidelines. You need to be aware of the specifics of your situation. If you’re in a highly regulated industry, it may have serious consequences if you fail; it’s the product leader’s job to understand that.

How to keep customer feedback from destroying your startup

You’ve launched your product. You’re getting some adoption. People seem to like it. You start to get some feedback. TechCrunch does a write up on your site. You get lots more feedback.

Sounds great, right? In many ways, yes. But feedback can destroy your company, if you let it causes you to thrash in what you are doing.

Your earliest adopters tend to be the most geeky, the techies who probably don’t represent your target customers. (Unless your target customer is techies.) The feedback they give you isn’t going to matter to the general market.

I heard Stewart Butterfield, the founder of flickr, talk about this early on. Some of his users wanted that ability to geotag photos by uploading tracklogs from Garmin hiking GPSes and syncing their timestamps with the timestamps on their pictures. Great idea. I loved it and would’ve used it. But me and 10 other people. It turned out not to be necessary in the long term because cell phones (which are the source of the vast majority of pictures online) automatically embed GPS information.

In the short term, geeks like me found tools like GeoSetter and iTag to embed GPS date into EXIF fields on photos.

There are a few other problems with customer feedback:

  • It’s not prioritized, even by the person giving feedback. Generally they don’t tell you whether it’s really important to them or just an “it would be nice.” Would it affect their likelihood of sticking around? Would they pay more for your service? Would it help you get the word out to more people? Who knows? Most feedback doesn’t come with that level of detail.
  • You don’t know who they are how they use the product. Without understanding the customer’s persona, feedback is less valuable.
  • It’s rarely the case that more small features will make or break your product. There are rapidly diminishing returns on many features. In a lot of cases, there are negative returns.
  • They are unlikely to know what your business model and goals are.

In order to make the most of the feedback you get, you need to organize it. See how much of a certain type of feedback you get. Group similar feedback. Have your product and business teams decide where it falls within the business goals.

This is especially true of business-to-business companies. You’re having one-on-one interactions with the buyer. He’s giving you some interesting ideas. Sales tells you that if you had “one more feature,” they’d close the deal.

Wait. When there are a small number of big customers, you risk becoming a captive development arm. You definitely don’t want to be that. It makes it easy to lose track of your other customers. If your product becomes too specialized for a specific customer, it can hurt your valuation.

You want to take in feedback and harmonize it with feedback you get from other customers and potential customers.

It can be hard when you’re working closely with someone to say “no.” Your sales team might keep nagging you for that feature. (In a future post, I’ll discuss how to deputize your sales team and sales engineers into mini product managers.)

Stay strong. Make sure what you’re doing aligns with your roadmap and will appeal to other customers.

There are somethings early customers will ask for that are no-brainers. Examples are GDPR compliance and SSO. You don’t have to do these right away, but be sure to have an answer prepared on how you will solve these problems.

Yesterday, I sent some feedback to the CEO of a company I’m looking to invest in. It’s an incredible feature. I know it will help them sell to new customers. Of course he should take my feedback: I’m a potential investor, reasonably well-known writer, have decades of product experience and I run UX quizzes on Twitter that people seem to value.

His response?

Sounds like a good idea.

That’s something that we can think about adding to the system. Thanks for the feedback.
That’s exactly the right response. It increases the likelihood that I will invest.

A startup’s guide to doing research on the cheap – usability testing

User research is an important part of the product design process. It can help you make sure you’re building the right thing for the right people and to continue to learn from what you’ve built.

I divide companies into two types: those that are driven by users and those driven by features. User-driven companies pay intense attention to the needs of their users and build products for them. Feature-driven companies focus on what they can do with technology and build those products. You don’t want to be the second.

Needs can be expressed or unexpressed. Some needs that users express may actually be counter to what they want. Important needs may go unexpressed because users don’t know exactly how to express what they want, or the research tools are poor.

There are many types of tools that you can use for research: usability testing, focus groups, ideation sessions, ethnographic research, user feedback, survey research, eye tracking, etc. Too often product managers confuse the roles of these tools and end up with bad interpretations.

Research can cost from nearly nothing to tens of thousands of dollars. In this series, I’ll go through research tools I think provide the biggest bang for the buck for startups.

Today’s topic: usability testing.

You need to assess whether people can understand what your product will do. Ideally, you’d do this shortly after the user flows have been built. Bring people in 1 by 1 and watch them accomplish a series of key tasks. Have the designer and product manager sit with the interview subject.

I like to just give the subject a task and see what happens. (After all, no one is going to be sitting with them while they are actually using the product.) “Order a large pepperoni-mushroom pizza and have it delivered to your house.” Then watch as he goes through the user flow. Have the interview subject articulate their thought process as they perform the task. Where did his eye go first? What was the overall flow?

Only when the subject gets stuck should the interviewer intervene. “Where did you expect to find it?” “Maybe try scrolling further down the page?”

Although ordering a pizza is a relatively simple task, there are a number of steps: finding the restaurant nearest your house, selecting your pizza, adding toppings, special instructions, delivery information, payment, etc.

Some people like to do the testing one step of the process at a time. I prefer to do it all in one pass. There are two primary reasons:

  • Time to completion is a key part of user success. If you stop the subject at every step, you aren’t going to be get a sense of how long he would have taken with your user interface. If it would have taken him 10 minutes to order a pizza, your interface has failed.
  • You get a sense of what other flows the user might see. That’s not necessarily a bad thing, but it’s important to get that sense.

Once the first pass is done, you can repeat the test step-by-test and ask for detail on what was confusing or not.

Usability testing can be done with static images linked together, but I really prefer doing it with live or close to live code.

You can also test a couple of different flows.

It’s important that the subject is told at the outset that he is not the one being tested; it is the user interface that’s being tested. There is no right or wrong answer.

Whom you choose to participate is key. On HBO’s Silicon Valley, the initial response to the compression tool was amazement. All of their friends loved it. Except for Monica, who hated it. Then, we saw the user interface:

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The people who loved it, the initial test group, were friends of engineers who were also engineers. They loved this type of interface because it gave them control over every little detail of the compression. Most users don’t want this.

You want to get people who don’t do tech for a living, if at all possible. You want to get people who are as close to your target audience as possible. If your product is designed to be used by senior citizens, don’t have millennials do the testing. (In this example, you’ll miss things like font sizes.)

Usability testing doesn’t need to be a formal process and doesn’t require special equipment.

You can recruit test subjects via craigslist. $75 to $150 for 40 minutes is a reasonable amount to pay. If you sell a product, some of this could be in service credit. For example, a $75 AmEx gift card and $50 to use on your app. I’m also comfortable asking friends and family, if they would be in the target user group.

Usability testing isn’t survey research; you don’t need to interview 1,000 people. With ten people, you should be able to identify the biggest obstacles in your interface.