“We start to test the personas. We start to test different segments and markets. We try to test different go-to-market approaches. We’re always testing a new thing, but we’re refining who our audience is, who we speak to, what message resonates with them. And we keep getting more and more focused. This happens every single day, but it also happens at the macro sense. Every year, I look at what we’re doing as a company. On one end, the vision and the breadth becomes way bigger, but from a tactical standpoint, it becomes more and more laser-focused every year.”David Cancel

Solving Product – LinkedIn Sales Navigator Early Market Assumptions

When Sachin Rekhi began work on what would eventually become LinkedIn Sales Navigator, it was clear that they were going after sales professionals; they just didn’t know what kind of professionals.

They had an idea of the type of value propositions they wanted to bring to market, but they didn’t know who those value propositions would resonate with the most.

To work this out, they decided to do waves of customer interviews, and explore different customer segments, one at a time.

As the discussions evolved, the vision changed from ‘LinkedIn is building a sales tool for sales professionals’ to ‘LinkedIn is building a B2B sales tool specifically focused on B2B sales reps.

The market assumptions became clearer, but Sachin’s team didn’t stop there.

Clarifying Your Market Assumptions

Digging further, they decided to target enterprise sales reps. They wanted to build a product that would work with the largest sales teams and organizations on the market.

And by speaking to those teams, they realized that certain industries—tech and financial services—had stronger needs for the product.

Through series of customer discovery interviews, they iterated and clarified their targeting. The product was no longer for sales reps—it was for sales professionals working for enterprises in tech or in the financial services industries.

While their original hypothesis had been in the right ballpark, it wasn’t detailed enough to be actionable. But they successfully used research to increase precision.

Sachin says: “It’s super important to spend time on increasing precision, thinking about your iteration not as just validating and pivoting, but instead as adding meat and substance to the understanding of that hypothesis.”

The bulk of your time in product discovery should be spent on increasing precision, not diverting from your original market assumptions.

Don’t pivot unless you really have to.

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This post in an excerpt from Solving Product. If you enjoyed the content, you'll love the new book. You can download the first 3 chapters here →.

Categories: Case Study