Claire Vo, VP of Product at Optimizely, shares her approach to boosting conversion rates and running experiments that deliver value.
Claire provides a succinct definition of the role of a modern product manager: taking ideas and customer insights and building solutions that drive value for your customers and your business. She then says that conversion optimization and experimentation ties those ends together. Experimentation validates that ideas meet customer needs.
Claire shares the exact steps that she takes to run experiments and improve conversion rates. The first step is mapping out your conversion funnel. What is the user’s journey from visiting your website for the first time to receiving value from your product and delivering value to your business?
The last step in the conversion funnel is often an action that drives revenue, such as purchasing items on an e-commerce site. However, Claire says that, depending on the product and business model, there can be many more important conversion points. These can include email sign-ups, product engagement, and advertisement views.
Claire recommends analyzing your conversion points using your in-product analytics tool. If users aren’t converting at important points, you could be hindering your ability to achieve a positive ROI on your marketing and product development efforts. Claire then recommends forming a hypothesis about how to improve a given conversion point, choosing the right metric to define success, designing and deploying the improvement, and analyzing the results.
You’ll learn a lot from this episode about running experiments and improving conversion rates.
Here at the Highlights:
Claire describes how conversion optimization fits into the ever-evolving role of a modern product manager (5:40)
Claire pinpoints the conversion points that product managers need to focus on (7:50)
Claire walks through how she designs experiments for improving conversion rates (13:01)
Claire provides insights on how B2B product managers can improve conversion rates (17:46)
Claire highlights common pitfalls to avoid when running experiments (20:18)