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  • Writer's pictureAmel Mechalikh

The pitfalls of sales-led product discovery and how use AI to avoid them

Updated: May 4

In our latest user research, we identified a common error that many sales-led companies make: putting their sales team at the helm of product discovery.

Artificial Intelligence (AI) can help your teams focus on sales, product discovery, and more.

What is sales-led product discovery?

Sales-led product discovery is a scenario where the majority of customer insights and virtually all product decisions, such as the product vision and roadmap, are determined by the sales team. While this approach can provide valuable insights into customer needs, it can also lead to bias and incomplete data.

The problem with sales-led user research is that sales teams may lack the specialized skills and training needed to conduct user research effectively. While some salespeople are intuitively skilled at drawing out customer pain points and needs, many others lack this skill and may quickly shift into their sales pitch. This can lead to a biased understanding of the customer, with a focus on what the sales team thinks would make the product more easily "sellable", rather than what the customer actually needs.

User research requires a specific set of skills, including knowledge of research methodologies, data analysis, and an ability to separate personal biases from objective findings. Sales teams may not have all of these skills, and they may also be focused on meeting their sales quotas, leaving little time for in-depth user research.

How can my team avoid this pitfall?

In companies where sales drives the product decision-making process, it is crucial to involve other teams, such as product management and design, in the user research process. This ensures that the product is developed with a well-rounded understanding of customer needs, rather than a biased understanding based on the sales team's perspective.

A collaborative approach that involves multiple teams and stakeholders can lead to a more comprehensive understanding of the customer. By bringing together sales, product management, design, and other teams, companies can gather insights from multiple sources and create a more complete picture of customer needs. This can lead to better products that meet customer needs and drive sales.

How did this insight inform our product?

At, we encourage our users to collaborate with their sales teams and all customer-facing teams. We believe that a product discovery tool should be the hub of any customer qualitative data, including not only user research interviews but also sales and customer success calls. By gathering data from multiple sources and analyzing it with the right tools, companies can identify patterns and insights that can inform product decisions without missing important customer knowledge.

When patterns automatically emerge from all of these channels, it’s a strong sign that further investigation may be needed or that the decision-making process should start. This is where tools like can be particularly valuable, as they can help companies identify these patterns and analyze the data coming from all departments to make informed decisions.

Final Thoughts

While sales teams can provide valuable insights into customer needs, they should not be the sole driver of user research. A collaborative approach that involves multiple teams and stakeholders is necessary to gather a complete picture of customer needs and build products that meet those needs. By leveraging tools like, companies can gather and analyze qualitative data from multiple sources to make informed product decisions that drive sales and customer satisfaction.

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