341: Using the data warehouse to make better product decisions – with Jeremy Levy

How product managers can use data to understand customers and create value Today we are talking about making better product decisions that create customer value using the data you already have. A PR person contacted me about a company that received the 2021 Products That Count award in the Operate category. The award recognizes products that help product managers and are pushing for better ways to accomplish work now and in the future. The company is Indicative and they help product managers leverage insights based on data already in their data warehouse, build their product roadmap, optimize user engagement, and reduce churn. I’m interested in learning more about this area in general because it brings together several important aspects of product management—the customer journey, data science, data-driven decision making, and reduced time to market. Our guest is Jeremy Levy, the CEO of Indicative. Summary of some concepts discussed for product managers [2:00] What problem in product management drew you toward your work with Indicative? Our mission at Indicative is to help businesses build better products through data. The first company I founded provided location-based dating for iPhone and Android, and my second company was the first mobile-based CRM for enterprise. In these companies, we struggled with leveraging the data we collected from our customers in a cohesive way for our product teams to make informed product decisions. We created Indicative, the only product analytics platform build specifically for modern data infrastructure. Indicative allows product teams to easily synthesize and use information and ask thousands of questions about their product, roadmap, or day-to-day decisions. [5:36] What is a data warehouse? A data warehouse is a repository of a company’s business data. It’s separate from a traditional transactional database that runs your application. The data warehouse keeps your data in one place and allows the rest of the company to easily interface with the data. Data warehouses have become available easily and inexpensively; now a startup has access to the same hardware as a Fortune 500 company. [9:02] How can we do a better job creating products for customers using data? Can you take us through an example? One example is Prezi, which makes virtual presentation software. Customers don’t use their products in a linear flow; there’s an infinite number of journeys the customer could take when they use the product. Any manual analysis of those journeys is impossible, so Prezi built a data warehouse to collect and store all their data. Using our platform, they isolated the individual journeys customers take as they create presentations. They found friction, the most effective paths, and the features that people were and were not using. Understanding the nuances of how people use their products allowed Prezi to better understand their users and inform their roadmap to reduce friction and help people create better presentations faster. [12:24] When you brought Prezi onboard, did you instrument their product to collect data, or was there already data available for you to leverage? Prezi already had their own data. This is often the case. Companies retain ownership of their data and use a variety of available tools to collect and analyze data, storing it in a single data warehouse. Storing data in a single warehouse makes data collection and analysis safer, more reliable, and less expensive. [17:25] How do customer journeys help us make better products? Customer journeys include all the paths that customers take when they interact with your product and all the touchpoints like email, registration, and phone calls. We created a product called Journeys that visualizes many possible journeys and allows you to filter the ones that are most effective and visualize them with a Sankey diagram,