Product Experience

The journey to product-market fit using Customer Experience data

The product-market fit (PMF) is one of the most important stages of a product’s lifecycle. Many startup businesses have tried to find it but failed. The reason? They didn’t understand their customers well enough, or as Bernadette Jiwa put it: “they didn’t manage to get close enough to their customers.”

We live in an age where businesses have all the means they need to get closer to their customers. Nevertheless, many businesses struggle to get feedback on how their customers feel, what they currently need and what they might need in the future.

This causes a gap between what customers need and feel, and what businesses believe those same customers need and feel. This is without a doubt the reason why most businesses fail to find a product-market fit.

How can you beat that? How can you use customer experience data on your journey to product-market fit? This is what we’ll be covering in this article.

The Importance of Customer Experience Data in Each of The 4 Stages to Product-Market Fit

The journey to product-market fit is not easy. It’s a journey full of challenges that must be overcome. Moreover, even when you get there, no one can guarantee that you’ll manage to grow as expected. Here are the 4 stages to product-market fit that you have to go through:

  • Initial idea
  • Idea validation & problem-solution fit
  • Scaling with a repeatable selling motion
  • Product-market fit

As you can imagine, the more customers you acquire and the deeper you dive into the process, the more customer experience data you’ll have. This doesn’t mean you won’t have data to work on in the beginning. However, it’s likely that you won’t have the infrastructure or the mechanism to gather all this feedback and turn it into actionable insights.

Let’s take a look at each of these stages in a bit more detail:

Stage 1: Initial Idea

This is the very first stage. Here, you generate ideas on what you can build. Remember: your product has to solve a real-life problem — a problem that many people have and are willing to pay money for. At this stage, you need to take the following steps:

  • Choose the problem you’re going to solve
  • Define your target audience
  • Create a customer avatar
  • Do competitive research
  • Come up with a value proposition
  • Decide on your minimum viable product’s (MVP) feature set
  • Build your MVP

Pro Tip: Make sure to take a look at these market research tools you can use in this very first stage.

One thing you need to pay particular attention to is the value proposition. Your value proposition has to communicate the value of your MVP in the best way possible.

Stage 2: Idea Validation & Problem-Solution Fit

At this stage, you need to identify whether or not there’s actual interest for the MVP you’ve built, which means you need to validate your MVP. You also need to discover who your ideal customer is and reach a problem-solution fit. Of course, if you can’t manage to do any of this, you’ll need to pivot. The steps you need to take here are the following:

  • Validate your MVP
  • Discover who your ideal customer is
  • Find a problem-solution fit
  • Pivot or persevere

One thing to remember is that many businesses make it to this stage but then fail to scale up. Why? Because reaching a problem-solution fit and a product-market fit are two totally different things. Both of them are important—however, as I hope is evident, only the second will keep your business alive.

Stage 3: Scaling With a Repeatable Selling Motion

At this stage you have to start scaling. Remember: scaling doesn’t mean that the founder of the business is making sales calls over the phone. It means your product is selling itself through different channels and selling mechanisms. This stage is characterized by:

  • A thorough understanding of who your ideal customer is
  • A core group of happy customers who continuously refer you to other customers
  • A mechanism that constantly generates new customers

At this stage, you also need to focus all your efforts on one single metric that reflects the overall growth of the company. This success metric is the reason why you need to build a feedback loop — in other words, a feedback collection mechanism that helps you constantly optimize the experience of your customers.

Stage 4: Product-Market Fit

According to Eric Ries, the author of the Lean Startup book, the PMF stage is:

When a startup finally finds a widespread set of customers that resonate with its product.

One common mistake among many businesses is the perception that product-market fit can protect you from competition, or that finding a product-market fit keeps you safe from market changes. If only that was true. The reality is that when you find a product-market fit, that’s when you actually need to get your gears turning and start seeking growth.

The Importance of Customer Experience Data in Each of the PMF Stages

As I told you earlier, the journey to product-market fit involves the following 4 stages:

  • Initial idea
  • Idea validation & problem-solution fit
  • Scaling with a repeatable selling motion
  • Product-market fit

Even though customer experience data is essential to get to product-market fit, businesses can use them only in stages 2 to 4. This happens because in the first stage, the initial idea, businesses don’t have paying customers. Thus, they don’t yet have access to data or any kind of feedback from customers.

Very often, startup businesses start charging for their products and services after finding a problem-solution fit. However, they can — and must — collect feedback from their users, even if they’re not yet technically paying customers. So, what data can a business retrieve and use in each of the 4 stages I just mentioned?

In the second stage, you’re trying to validate your product concept. Businesses in that stage rarely keep track of their validation efforts, partly because they miss the infrastructure, but mostly because they don’t have the resources to set up such a system. However, in this stage you should be collecting customer experience data for the following reasons:

  • You need to optimize your MVP so that every kind of feedback is useful
  • You need to validate your customer personas, so collecting data is critical
  • You need to decide if you’re going to pivot or persevere, and to take that decision requires data

Therefore, as I hope is evident, even though most businesses in this stage don’t pay attention to data, data is nonetheless essential for their future. Let’s quickly move to the third stage.

Businesses that want to scale up need customer experience data for the following reasons:

  • To know what makes their customers happy
  • To understand what their core group of customers need most
  • To identify hidden desires of their customers, and things that could be improved and optimized

Simply put, you can’t bring in new customers if you don’t know how — and are unable to — keep your existing customers happy. To do that, you don’t necessarily need to be a customer experience professional. You just have to get a step closer to your customers.

When a business finds a product-market fit, it’s ready to grow. To identify whether or not a business has managed to find a product-market fit, it has to conduct a PMF analysis.

Many people will tell you that a PMF analysis is unnecessary. However, a PMF analysis can help you get a 360° view on the performance of your business, and tell you how close you are at meeting customer expectations. Here are some of the metrics you can use to measure product-market fit:

  • Net promoter score
  • CSAT (customer satisfaction)
  • Retention curve
  • Churn rate
  • % changes in lifetime value

Of course, the metrics you’re going to use, as well as the ways you’re going to use to collect data, differ based on the type of business and industry you’re in. In the next chapter, I’ll be sharing with you how to set up a data collection mechanism, as well as what to pay attention to when setting up such a mechanism.

How to Set Up a Data Collection Mechanism & What to Pay Attention to

Is there a right way to measure the quality of a service? Is there a right way to know how your customers feel at any time using customer experience data? Is is important to set up a mechanism that collects data on autopilot? What are the things you need to pay attention to when setting up such a mechanism?

All these questions are critical when trying to find a product-market fit. Setting up a mechanism that helps you repeatedly gather feedback is the best way to understand your customers better and offer them the best possible experience.

How to Set Up a Data Collection Mechanism

The best way to set up a data collection mechanism is by using a feedback management software program or survey software. A feedback management software program is ideal for larger organizations, while survey software is better for SMBs. Some of the most common methods you can use to collect customer experience data are:

  • In-app (or on-site) messages asking for feedback
  • Emails asking for feedback
  • Online surveys

One of the most important aspects of collecting customer experience data is to choose which data collection techniques you are going to use. Yes, you can use more than one, but it’s better to focus on those which are closer to your customers’ habits. For example, if your email open rates are usually high, it would be wise to send an email asking for feedback on your products or services.

Things to Pay Attention to

What are the things you need to pay the most attention to when collecting customer experience feedback? Here are some of the most common:

1) Ask for feedback only when it makes sense

Should you ask for feedback when a user is inactive for months or hasn’t yet managed to experience the value of your product? Probably not.

This is why you should ask for feedback only when it makes sense, and only when you are sure that your customer has experienced the value of your product.

2) Focus on data collection techniques that are close to what your customers like

As I mentioned before, not all data collection techniques are equally effective. Your job is to find those that are most effective and resonate best with your customers, then use them in the best possible way.

3) Avoid survey fatigue

Have you ever heard of survey fatigue? This refers to a situation where your response rates drop, along with the quality of your insights. This can happen when you send many surveys in a short timeframe. This should be avoided at all costs.

4) Ask the right questions

To build an effective survey, you have to ask the right questions. Asking someone who hasn’t used Feature X what they think about it won’t help you to better understand your customers. In fact, it may harm your business rather than do any good. This is why you should focus on customer segmentation, and why you should ask the right questions to the right people.

Product-market fit - a long road but essential for growth

The journey to product-market fit is not easy. It’s a long road full of obstacles that need to be overcome. The truth is that by understanding your customers better, you will greatly increase your chances of finding a product-market fit and start growing.

The question is: how can you do that? By constantly gathering feedback from your customers, and by trying to understand their needs and pain points in depth. This is the only way to get closer to them and bring value to their lives every single day.

eBook: Introduction to Product Concept Testing