Product Analytics and Frameworks for Growth for Startups
The outcome that every organization expects to drive through the adoption of product analytics is about scaling customer empathy by understanding exactly how users interact with their product and use these insights for data-driven growth and innovation. Irrespective of whether your organization is involved in making a Software as a Service (SaaS) product or is into retail or consumer goods in today’s market of digital natives there usually tends to be a trace leftover of that behavior.
In order for product analytics to be effective, it needs to be real-time, collaborative and support the paradigm of self-service for teams who work on it so that the goals and outcomes of the analytics effort can be aligned to the product vision, especially in the case of startups when it comes to rapid cycles of iteration. It also needs to be easy to use in order for a data-driven culture to thrive within a startup’s operational and technical ecosystem of operations.
Product analytics can give you a deep understanding of a businesses’ customers. The better a company understands its customers, the better it can meet their needs. The better and more effectively an organization meets its customers’ needs, the more it will grow and gives rise to the domino effect of synergies.
Product analytics typically provides insights that are hard to gather from qualitative data — sources such as customer surveys, support tickets, or focus groups. It should be kept in mind that people aren’t always the most reliable narrators. While direct feedback from customers can be very useful, it should be taken in context with data analytics and situational intelligence.
There are lots of important metrics you can track as part of your product analytics method, such as Lifetime Value (LTV), Monthly Recurring Revenue (MRR), and Customer Acquisition Cost (CAC) which are much more important than other vanity metrics which are not directly tied to the growth of your organization. But to makes sense of this information and formulate insights or hypotheses for growth the numbers alone are not enough. It is here that some frameworks such as the following help organizations to understand what is relevant and makes sense for them:
- Pirate Metrics (AARRR)
- The Google HEART Framework
- North Star
Pirate Metrics (AARRR)
Dave McClure of 500 Startups and PayPal introduced the concept of pirate metrics in 2007 to get startup founders to think about metrics as a reflection of the customer experience at five points in the customer journey:
- Acquisition: People visit the companies website or app for the first time.
- Activation: Users have their first valuable experience with the companies product.
- Retention: Customers come back and continue using the product.
- Referral: The customers like it enough to tell their networks.
- Revenue: People take actions that make your organization money.
The Google HEART Framework
Google developed the HEART framework as a way to organize metrics around the user experience. The acronym stands for:
- Happiness: Users feel good about the product, and they experience value.
- Engagement: People interact with the product in meaningful ways.
- Adoption: Customers try new features or new users’ complete key actions for the first time.
- Retention: Users continue to come back to the product over time.
- Task Success: People complete important events without problems.
North Star Framework
The North Star Framework aligns the product team and strategy around one key metric, the “North Star Metric” or the “One-Metric-That-Matters”. That metric should incorporate three things:
- A measure of customer value
- A representation of product strategy
- A leading indicator of revenue
When an organization aligns with the value of product analytics and begins to implement it, it is possible to see a domino effect where the customer insights uncovered from product analytics will lead to dramatic improvements in the product which in turn translates to better and sustainable growth.
