The Bullseye Framework

 
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Not using any structured approach for getting traction is one of the most common traction mistakes, and yet there are simply not many traction frameworks out there to help you make sense of the process. In our upcoming Traction Book, Justin and I present the Bullseye Framework for getting traction. It is a simple approach that is meant to act on the following premises:

  1. In any given growth phase, usually one customer acquisition channel (traction vertical) is largely responsible for really moving the needle for a startup. This is a consequence of the fact that getting traction itself is usually (though not always) a power law problem.

  2. There are about 20 different traction verticals that we see startups use to get traction. It is hard to predict beforehand exactly which traction vertical will work best for your startup at a given time. You can make educated guesses (and you should!), but it is hard to tell until you start running tests whether a given vertical is the best one for you right now.

  3. Most startup founders have a significant bias towards (or against) using certain traction verticals, e.g. for ones they're already familiar with and against ones they know little about, find icky or involve a lot of perceived shlep. A corollary of this premise is that there are far too many startups focusing on the same traction verticals and that many potentially promising verticals get overlooked and are therefore under-utilized.

Our framework for approaching traction uses a bullseye metaphor (see picture). At any given time, the inner circle contains your most promising traction verticals; the next concentric circle contains the next most promising, and the latter rung contains the rest.
Using the Bullseye Framework is a five-step process:

Step 1: Brainstorming. Go through each traction vertical and brainstorm how you might use it effectively for your current situation. This first step is meant to help you systematically counteract your biases by forcing you to take each vertical seriously. As such, it should take a while. First, you need to have a basic understanding and appreciation for each vertical, which our book is designed to give you. Second, you should have mapped your space to know where others have succeeded and failed at each vertical and why. Third, for each vertical you should spend at least an hour thinking up plausible paths to traction within it, and more specifically possible cheap tests to run in that vertical. The whole process should be spread out over days or weeks.

Step 2: Ranking. Place the traction verticals into three columns:
  • Column A (Inner Circle): what traction verticals seem most promising right now?
  • Column B (Promising): which traction verticals seem like they could possibly work?
  • Column C (Long-shot): which traction verticals seem like long-shots?

Step 3: Prioritizing. Go back through your columns and critically re-think your choices. Try to place your top three traction verticals in column A, the next six in column B, and the rest in column C.

Step 4: Testing. Your top three traction verticals in Column A comprise your inner circle. Devise cheap tests to experiment with them in parallel.

Step 5: Focusing. If one traction vertical from your inner circle shows significant signs of early traction, then you have your winner (for now). Double down on what's working, and wring as much traction as you can from it. If none of the three traction verticals from your inner circle proved successful enough to focus on, go back to Step 1 and start over, incorporating your new-found knowledge (from the other steps).

Why three? Why test in parallel? There are a bunch of nuances in here that we expand upon in the book, but the basic Bullseye framework is pretty straightforward.

We argue you should spend about half your time pursuing traction (as not spending enough time is another common mistake). Whether you use our framework or another, it is strongly advisable to take a structured approach to getting traction.
I'm the CEO & Founder of DuckDuckGo, the search engine that doesn't track you. More about me.
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