Most product managers are not short of data on the performance of their products. Reporting tools such as Amplitude and Mixpanel allow access to product insight more quickly and at a bigger scale than ever before. The biggest data-related challenge faced by product people today is actually cutting through the noise created by this avalanche of data to focus on what is really important.
For a product company to be truly data-driven in it’s decision making, it’s essential to create and socialise a team-wide understanding of the KPIs that are the most meaningful. The best way of doing this in my experience is to create a ‘Product Data Map’ for your product. A Product Data Map is a visual representation of the data hierarchy for your product, and the relationships between the various KPIs you want to target.
Doing this has multiple benefits:
It creates a visible framework for solution design
Designing features that target the ‘lever’ metrics that have the biggest impact on your product means less hunch-driven development and more alignment between user research and key business objectives.
It increases the ‘democratisation’ of data within your company
The more people in your team who have visibility on what is important, the more support you will get to achieve your goals, and more empowered individuals will feel in helping develop solutions.
It increases stakeholder alignment
A product data map helps frame your prioritisation decisions in terms of value to the business, and reduces the number of people asking “why are you working on this?”
The Product Data Map places your KPIs into one of three categories:
Primary Business Objectives
These are the fundamental measures of success that determine whether your business is successful. They are the metrics that shareholders and board members will be focused on. The Primary Business Objectives will usually include revenue or a similar proxy, and might include the KPI that best represents customer growth for your business. These measurements will rarely change in your Product Data Map, unless your company pivots into a very different business.
Success Indicators
Your success indicators are the most important of your leading metrics. This type of KPI offers insight into the future performance of your primary business objectives (which are lagging metrics - they describe what has already happened). For example, user retention is a success indictor for Monthly Active Users. If you improve user retention it’s a strong indicator that overall user numbers are about to grow.
Lever Metrics
These are the product behaviours that have an impact on your success metrics (and therefore ultimately your primary business objectives).
For example, email opt-in rate is a lever metric as it improves the effectiveness of your product marketing, driving up customer sessions. Lever metrics are useful because they help focus solution development on moving numbers that will deliver value to the business. It’s easier to target a solution or feature improvement with the objective of increasing email opt-ins than it is to be told to “build a feature that increases user numbers”.
Your lever metrics will almost always include core product actions that drive customer value. For example - for Pinterest, the number pins made in the first few days of use is the primary lever metric or ‘habit forming metric’ that drives retention for new users. For a social media app, the number of likes or followers that a new user receives in their first few days is likely to be a key lever metric for driving retention.
Ideally you will have a high level of confidence in your Lever Metrics positively impacting your Success Indicators. This confidence in Lever Metrics can be built in a number of ways but experimentation is the best mechanism available. Out of the three levels of the Product Data Map hierarchy, it is the Lever Metrics that will most likely change over time as your product matures.
Once you have identified your KPIs and where they sit in the Product Data Map hierarchy, you can work from the bottom up and add connections that show lever metrics impacts which of Success Indicators, and which success indicators are leading metrics for which Primary Business Objectives. You will also likely make connections within a category - for example some Lever Metrics will impact on each other, and a customer-number or growth related KPI which is a Primary Business Objective will almost always impact upon revenue or sales.
Product Data maps will be applicable to any type of business model, but they will almost always be unique to your specific product. Let’s have a look at a couple of different business types and a hypothetical product data map for each. First up, a classic e-commerce business.
For a business in the retail space the number of sales and the amount of total revenue are likely candidates for the Primary Business Objectives. The Success Indicators for sales (the main leading metrics) could well be ‘conversion rate’ and ‘total user sessions’. A Lever Metric for conversion rate, one that is easy to target with a feature solution, could be the ‘cart abandonment rate’.
For a ‘freemium’ subscription business, the Product Data Map would look very different. Subscriber numbers are likely to be focused on as a Primary Business Objective, as could the total number of ‘free’ users that comprises the conversion funnel.
For a 'freemium' business, the first step in creating a paying subscriber is to get the customer hooked on the free product. To this end, there would be a big focus on Success Indicators like ‘new user retention’ and on identifying the most impactful Lever Metrics that will create an engaged and active user. The ultimate Lever Metric for retention is often called the Habit-Forming Metric, and will be the primary focus of product teams in businesses that are prioritising growth.
Do you use anything like Product Data Maps to embed data-driven ways of working in your business? I’d love to hear from you if you do. Drop a comment below or get in touch, I’d love to hear your thoughts.
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