Adding more features to a failing product is often a tempting solution, but it's rarely the right one. This is especially true in the startup world, where new products often face a “Trough of Sorrow” after initial launch. In this stage, features get added haphazardly, leading to a “Frankenstein product” that lacks focus and tries to do too much.
Eric Ries, in his book "Lean Startup", proposes a powerful solution called the “Zoom In Pivot”. This strategy involves focusing your entire product on a single feature that demonstrates significant user engagement.
The process of identifying the feature to zoom in on mirrors the approach of choosing a new product for a startup.
To determine the best feature to zoom in on, carefully analyze your current usage metrics. Look for features with the highest engagement and usage. This data will provide valuable insight into what aspects of your product resonate most with users.
Based on your product strategy and usage metrics, formulate a hypothesis for the smaller, zoomed-in product. This hypothesis should outline the core features of your product and define your desired outcomes.
Testing your zoom in pivot is relatively straightforward. You can easily modify your user interface to highlight the feature you're focusing on. The following approaches can be implemented:
A/B testing is crucial for optimizing your zoom in pivot. Test different variations of your user interface and landing page to see what best drives user engagement with your highlighted feature. This process will help you refine your approach and maximize the effectiveness of your pivot.
After implementing your zoom in pivot, meticulously monitor your key metrics. Look for a significant increase in the usage of the highlighted feature and a decline, ideally to near zero, in the usage of secondary features. Also, evaluate aggregate stats such as frequency of use, time on site, and content shared to ensure they remain stable or improve.
The process of creating a successful zoom in pivot may require several iterations. If your key metrics don't move in the desired direction, it could indicate that the chosen feature might not be the right fit, or that your user base might not be receptive to the pivot.
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