Starting and growing a new product could be an intimidating process for Product Managers. This could be due to n number of challenges like what to prioritize, how to measure progress, how to make decisions which would lead to growth, etc. In the book Lean Analytics, Alistair Croll and Benjamin Yoskovitz provide us with five major learnings on how to navigate through such complex situations.
#1 Identify the North Star Metric
Identify a core metric which would be in alignment with the product’s goal and current stage. This metric should be used in each meeting and document to guide a PM’s decision-making and measure success. For example: after an e-commerce business matures, they would move their north star metric from delivered GMV (to be increased) to cost per ordered GMV (needs to be decreased).
#2 Follow the correct flow
- Empathy - Identify the target audience and understand them to identify their pain points. Measure user feedback diligently. Eg: feedback on Google Playstore, surveys, CSAT, etc.
- Stickiness - Once you start observing customer targeting fit, start focusing on user engagement and retention. Eg: for Cred, what is the daily active user? What is the retention of the user after 1 month, 2 months, 3 months? (is the user coming back to pay credit card bills?)
- Virality - Once we observe that the acquired users are engaged, start focusing on acquiring more users. This is the time to primarily track user acquisition and referral metrics. For example: Number of daily acquired users through referral from existing users.
- Monetary: Once you identify the product-market fit, start focusing on revenue and cost metrics. This is the time to track the customer’s lifetime value (CLV), customer acquisition cost (CAC) and monthly recurring revenue (MRR). For example: Daily commission from the sale of merchandise on the Cred App.
#3 Focus on actionable metrics
Identify the metrics which would directly impact our decisions and actions for the product. Try to be away from vanity metrics - the ones which look good on paper but don’t provide meaningful insights. For example: For a Social Media Advertisement, the number of likes would be a vanity metric and the click-through rate (CTR) would be an actionable metric.
#4 Create a feedback loop
Create a “Build - Measure - Learn” feedback loop. Begin with building a hypothesis -> build an MVP -> measure the north star metric -> learn from the results -> re-iterate. For example, how can Netflix solve the problem of password sharing without decreasing DAU? They will have to identify the reasons for the scenario, identify a few solutions, run MVP, measure metrics, re-iterate solutions as per results and then re-build and re-run.
#5 Utilize A/B testing to try out strategies
Use A/B testing as a tool to build and decide incremental improvements. A/B testing provides flexibility to test various product strategies which can be used to gain learning through the feedback loop. This helps in identifying the correct solutions for our target audience and making data-driven decisions. For example, a platform can run an A/B to check the efficiency of different login mechanisms - login form (control), Truecaller (test 1), WhatsApp (test 2) and Google sign-in (test 3). Depending on which group of users showcase a higher login success rate, the respective login process could be scaled to the targeted user segments.