From the course: Data-Driven Product Management

Defining your product analytics strategy

From the course: Data-Driven Product Management

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Defining your product analytics strategy

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- [Instructor] The most important part of any successful product analytic initiative is having a good strategy. In order to ensure that you are capturing the right data, you zoom out so that you can set priorities, assess risks, set goals, and otherwise prepare so that you can get your analytics set up correctly. So we're capturing the right information and providing the necessary views to support your strategies. Setting an analytic strategy is really a matter of asking questions, the right ones, and with the right stakeholders. Through these questions, you should be able to identify gaps, opportunities, and pitfalls, which will provide the scaffolding for what data you'll need to capture and visualize. The first question is, at what stage is your product? Is it slated to be created? Is it built already, but needs to grow? Has it been around a while and now needs to be competitive? We'll discuss each of these in future videos. What is your product vision? What are the ideals that are set out for this product, both in terms of what it does and for whom, but also where does it stand within the business? Is this a flagship product, an internal one, a sideshow? The product vision changes and morphs over time, so this is a good time to reanalyze. What are your business goals for the year? Are you a fast growing company, slow growth, maintaining market lead? Are you restructuring or making acquisitions? Are there any business goals within your particular group? Maybe you're looking to integrate AI or maybe your CTO wants to get rid of technical debt, know any and all of these. What then are your product goals? These will oftentimes be in service of the business goals, but not always. If you've had a goal you were working on, will it be the same moving forward? Do you need new product goals for any reason? Do you have any of your own initiatives you might want to kick off that will affect how you approach your product analytics, like assessing the effectiveness of your mobile app or hitting some specific revenue numbers or KPIs? If you don't know what these terms mean, don't worry, We'll discuss them in another video shortly. What issues are you having with your product? Any user issues? Is your churn rate acceptable? Do you have bugs, bad app store reviews? Are there areas where customer support is getting hit heavily? Be honest and use data from sales, marketing and customer service to make sure you really understand this, even if you think you already do. What risks do you have? Any new competitors? Any risky assumptions you have about your new product or feature? Do you know or can you think of any data that might be missing to make good decisions? Do you understand how users are using your app? Where are they dropping? Where do they spend most of their time? What is their satisfaction for certain features? For now, don't worry about being able to get that data, just think about what would be nice to have. Are there any business cases or decisions that you'll need to support with data in the near future? And lastly, what is your bandwidth? Do you have some developer bandwidth to add events and integrate the data you need? Do you have bandwidth on the product ops side to create visualizations and track this data? Keep in mind, coming up with your product analytics strategy, requires proper diligence, talking to people across the organization, and taking the time to get the real answers to all of your questions. When you're done though, you should have a pretty good idea of what you're going to need, and then it's a matter of making a plan and putting it into action.

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