The core of product management revolves arounds asking the questions – What, Who, Where, Why, and How. For instance,

• What is the problem?
• Who is the user?
• Where is the user?
• Why does the problem exist?
• How do we solve the problem?

Data is the most important weapon in a PM’s arsenal. However, the value of this data is directly related to how it is curated and analysed. Exceptional PMs are those who are able to collect relevant data, mine and curate it to serve as valuable information. Harnessing this superpower helps them to prioritise correctly, successfully manage stakeholders, development teams, and users.

Becoming a data-driven product manager takes dedication and a systematic approach to research and data analysis.

PMs curate data along three key aspects – competition, industry, and users; all in relation to the market where they operate. Some of these terms are sometimes confused or conflated so let’s first clarify them in this context.

• Competition refers to companies that provide services or products similar to yours. Your competition serves the same market as you. For example, Paystack and Flutterwave offer similar products within the same markets.
• Industry refers to a group of companies that offer similar products, solving the same problems. For example, fintech industry provides financial services through technology. Flutterwave, Paystack, Interswitch, and similar companies make up the fintech industry in Nigeria.
• Users are the people who use your product. There are different categories of users. For instance, for B2C products, your users are also your buyers, while for B2B products, you may have users who aren’t buyers.
• Market is a combination of the industry and users. Economists define market as a place where value (good and services) are exchanged. Markets are typically categorised by demographics such as geography, age, gender etc., and quantified in relation to the general population. For instance, the Nigerian market.

Why should you invest time and money in research?

Here's a simple way to answer this question

Let’s say you have an idea for a product or feature. It solves a problem you’ve been experiencing for a while, and you haven’t found similar solutions being offered so you decide to solve that problem. You’ve answered the question – What.

Now you need to validate that idea, right? Does this problem exist for other people? If it does, who are those people? What’s their current alternative? Is this market big enough to serve? Are there any (remotely) similar products in existence? What are they doing wrong? What can you do better? What do you need to develop this product?

This is where research comes in. You need to understand the market you’re trying to serve, the details of the problem beyond the surface, why there are either no existing products solving this problem or why the existing products are not doing a good enough job. Are there infrastructure or regulatory constraints? You need to answer these and a lot more questions to help you define and articulate the value that your product / feature will deliver not only for your proposed users but all relevant stakeholders.

During your ideation process, you should be able to answer these questions –

Why should we do this?

How do we do this?

When do we do this?

How do we know it is done?

Who will buy this?

Let’s start with user research.

User Research: Uses Cases, Tools and Methods

User research is typically quantitative or qualitative. While cannot exist without the other, however, at different stages of your PLC, you lean more towards one than the other. For instance, at the early stages such as development and launch, you need more qualitative data to help you build a value-driven product while you lean more towards quantitative research which gives you more high-level data at growth and maturity stages.

Use Cases for User Research

1. Discovery : To develop value-adding products, we need to understand users and their needs. Who are the typical personas that will use this product? Beyond the what, we try to decipher the why. Why does the user have the problem? Why do they have their preference? Why is this product important to them?

2. Target market definition : Who is the user? How do we categorise them? What is the size of the market? How much of that market can we capture?

3. Product Launch : We need user confirmation that we’ve built the right product / features for them. Does the product solve the problem it was designed to solve? We have different versions of a particular feature, which do our user prefer?

4. Segmentation : Which features are more popular with which users? We’ve noticed a new demographic adopting our product for a purpose we didn’t originally plan for; how do we explore and grow this new user base?

Methods and Tools for User Research

Data from user research helps to

• predict user behaviour,
• forecast product metrics,
• determine market share and trends,
• measure return on investment,
• define pricing,
• develop roadmap,
• develop new markets.

Quantitative research tells us how much

Examples of Quantitative User Research include:

• Product data. The easiest and fastest way to get user data is by analysing already existing product data such as number of downloads vs active users, lead conversion rates, churn rate vs retention rate, LTV, CAC etc. Keep in mind that not all metrics are important for your product. We need to keep track of metrics that are important to the current product and company goals. For instance, if your current focus is adoption or market awareness, your key metric will be different from a product whose current focus is ROI or profitability.
• User Surveys. Surveys are another quick way to collect voice of customer. Carefully crafted survey questions and answers are a sure way of understanding user preferences.
• A/B testing. A/B tests may limit you to testing specific features, but they are a proven way of determining user preferences.

Qualitative research tells us how well.

Examples of Qualitative User Research include:

• Interviews. User engagement is one of the best ways to gather feedback. When interview questions are open and explorative, users share highly valuable insights.
• Focus groups. Combining interviews and observation within focus groups helps to understand user personas and their preferences.
• Leveraging existing data sources.

Analysing user data

On their own, different data types across multiple sources may tell different stories. However, analytics helps us understand and apply the data we’ve collected. Analytics helps us understand the why and determine next steps to achieve our desired results. For example,

• Why is churn rate high? Users drop off at a particular step because it’s complicated / cumbersome / does not properly communicate how the product solves their problem. What if we created a different flow and A/B test it with different user segments?
• Why is conversion rate low? Users have been recycling the trial version using different emails. How do we make our product stickier? Which features can we tweak such that users want to continue to the full version of the product?

Analytics tells us how users use the product, what their preferences are and how we can achieve better results with a few tweaks.

Great reads on user research

• https://www.aha.io/roadmapping/guide/templates/customer-research
• https://www.convert.com/blog/a-b-testing/how-to-use-data-in-ab-tests/

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