"What you measure is what you manage", this sentence was proposed by Peter Drucker, the father of modern management, in 1954 and has become a widely quoted quote. However, Drucker's full statement is actually more powerful: "What you measure is what you manage—even if it is meaningless or even detrimental to the purpose of the organization." Drucker's insights highlight that while collecting and measuring data is necessary, the real challenge is identifying and prioritizing the key metrics that will drive the business in the right direction. By focusing and prioritizing the right metrics, you can ensure that what you measure and manage is truly impactful.
A company's most important metrics change over time. Focus on rapid growth in the early stages, rather than making profits right away. The company prioritizes metrics such as user growth and user retention. As businesses mature, their focus shifted to profitability and financial sustainability. Linking its metrics to the stages of the product lifecycle should prioritize them based on the stages of the product lifecycle.
Product life cycle phases
The metrics that should be focused on at each stage help address the pressing issues presented at each stage. Tactical questions may vary, but here are the strategic ones:
- Introduction: Have we achieved product-market fit?
- Growth Period: How Can We Scale Effectively?
- Maturity: How do we make money?
- Recession: How can we keep users interested and slow down the recession?
Introduction period: Has the product-market fit been achieved?
The first and most critical phase in the product life cycle is the introduction phase, where the primary focus is on achieving product-market fit. At this stage, the product owner must determine if their product meets a real market need and resonates with the target audience. Understanding product-market fit involves assessing whether early adopters are not only using the product, but also finding value in it. Confidence in product-market fit sets the stage for future growth and scalability.
There are three metrics that clearly show whether a product-market fit has been achieved, listed in order of importance as follows:
- Retention: Do users find the product valuable? Example metrics: D30 retention rate, queue retention curve.
- Active Users: How many users does the product have? Is the number of users increasing? Example metrics: Daily Active Users (DAU), Monthly Active Users (MAU), Growth Accounting.
- Stickiness: Is the product attractive and frequently used? Example metrics: DAU/MAU, activity frequency histogram (sometimes called L28 histogram).
Using these three metrics together, it is possible to quantitatively measure whether product-market fit has been achieved or to point out the most critical product issues. You may encounter one of the following five scenarios:
- No long-term retention and low user growth (worst-case scenario): No product-market fit in this scenario. Users are no longer using the product and the market size is small, requiring significant adjustments to the product and/or target market.
- No long-term retention but high user growth: It's a funnel problem. Users are attracted to use the product for a short period of time, but eventually all of them are lost. The focus should be on fixing retention and slowing the rate of growth.
- Long-term retention but low user growth: In this scenario, the acquisition funnel should be adjusted to increase user growth, or if the market proves small, move to a larger market.
- Long-term retention, high user growth but low stickiness: This is when users find the product useful but don't use it frequently. Examples include tax preparation apps, travel websites, and ticketing websites. The focus should be on exploring new features to make the product more engaging.
- Long-term retention, high user growth, and high stickiness (ideal): Users keep coming back to the product, use it frequently, and the number of users is growing, which shows the product-market fit.
Once an organization is confident in product-market fit, the focus can turn to growth. This approach avoids spending a lot of money on user acquisition only to have to change the product or market, or churn most users.
Growth Period: How to Scale Effectively?
The growth phase is the stage where the product has the potential to change from promising to dominant. The key question at this stage is: how to scale effectively while maintaining product quality and user satisfaction?
The analysis at this stage should include the following three types:
- User Journey Analysis: How to Optimize User Experience? Example metrics: Conversion rate, conversion time, funnel analysis.
- Experimentation: How do we determine if a change will positively improve key metrics? Example methods: A/B testing, multivariate testing.
- Aha Moment (Aha Moment) analysis: What moments lead to significant changes in user retention and stickiness. Example metric: A combination of user journey analytics, experiments, and product-market fit metrics.
When implementing user journey analytics, you should follow the principle of "less is more". There may be an urge to record every page and every button, but this is often onerous and difficult to maintain for engineering implementation. Instead, start by recording only the start and end events, which will allow you to calculate the conversion rate and conversion time. Include only the critical steps in the user journey. Ensure that events capture user segments such as device, operating system, and location.
Experimentation is a skill that needs to be exercised. You should start building this capability early in the product and company lifecycle, as it's more difficult to implement than a set of metrics. Practice this capability by involving product, engineering, and data teams in the design of experiments. Experimentation is not only critical in the "growth phase", but should always serve as the basis for analysis throughout the rest of the product life cycle.
'Aha' analysis helps identify key moments that can accelerate growth. These are the key interactions in which users realize the value of the product, leading to loyalty and stickiness.
Maturity: How to make a profit?
In maturity, the focus shifts from rapid growth to optimizing profitability and long-term sustainability. This phase is about optimizing the product, maximizing efficiency, and ensuring that the business remains competitive. By focusing on cost management, increase user revenue, and explore new revenue streams.
The focus shifts at this stage to:
- Monetization Metrics: How to Achieve Profitability While Maintaining High-Quality Products and Happy Customers? Example metrics: Customer Acquisition Cost (CAC), Customer Lifetime Value (LTV), LTV Ratio, Monthly Recurring Revenue (MRR).
Monetization metrics have a clear goal, which is to try to increase revenue and reduce costs. Marketing and marketing teams are typically responsible for reducing CAC, and product teams are typically responsible for improving LTV and MRR. Strategies may include optimizing ad spend, reducing sales deal completion times, and cross-selling and bundling products to existing users.
Recession: How to keep users interested and slow down the recession?
"Your profit is my chance" – Jeff Bezos. As the product matures, margins inevitably decline. Competitors discover your opportunities and increase competition, existing users migrate to alternatives and new technologies, the market is saturated, and there is little to no growth. At this stage, it's crucial to maintain your existing user base.
During the recession phase, there is a broad set of useful indicators to adopt. Some of the key types are:
- Churn Prediction Modelling: Can you identify and intervene users who are likely to churn? Example models: logistic regression, tree models, neural networks.
- Power User Analysis: What can you learn from your most active users? Example metrics: stickiness, feature usage, volume.
- Root Cause Analysis: What are the root drivers of key metrics? Example analysis: Quarterly Business Review, Problem-Driven Tree.
By creating a churn prediction model and analyzing feature importance, you can identify user traits that are likely to churn and deploy interventions. As new user growth has slowed, it's critical to retain existing users. This analysis may also be helpful in recovering previously churned users.
High-value user analytics aims to understand the most active users and their characteristics. These users are the highest priority to retain, and their product usage behavior should ideally be shared across all users. Look for users who are active every day, spend time in the product, use the most features, and spend the most. Deploy measures, such as loyalty programs, to retain these users and identify ways to increase the number of high-value users.
Root cause analysis is essential to drill down into specific problem areas in a mature product. Given the complexity and scale of the product at this stage of the life cycle, the ability to perform customized, in-depth problem analysis is critical. This analysis helps uncover the underlying drivers of key metrics, provides confidence in implementing costly product changes, and helps unravel interdependent metrics in the product ecosystem.
A product or company at this final stage may choose to create a new product and enter a new market. At this point, the cycle starts again, and the focus returns to product-market fit.
"Focus is rejection" – Steve Jobs. Product analytics is a bottomless pit full of potential metrics, dimensions, and visualizations. In order to make effective use of product analytics, companies must prioritize metrics for a handful of focus areas at all times. These indicators can be supported by a range of other measures, but must have the following characteristics:
- The team agrees on which metrics should be prioritized
- The team has a strong understanding of the definition of key metrics
- Metrics are related to key product issues
- Specific actions could be taken to improve the indicators
This can be achieved by prioritizing the right metrics at each product life cycle stage (introduction, growth, maturity, and decline). From achieving product-market fit to scaling effectively, optimizing profitability, and maintaining user interest, each stage requires a clear focus on the most relevant issues. Remember, it's not about measuring everything, it's about what matters.