Modern technology organizations turn on the fulcrum of the partnership across product and field teams. Yet, in many organizations where product and engineering leaders are peas in a pod, that is not true of CROs and CPOs. But it can be, and I have now had the good fortune of seeing the magic that happens when it’s true. In organizations where this works well, three things stand out:

• There is a trusted method, linking product feedback to revenue data
• The field is a true partner and a source of insight, not a source of data
• There is a vehicle for making decisions together

A trusted method for linking feedback to revenue forms the foundation for the rest of the relationship between product and field teams.

Common Challenges

There are many ways that this can go awry:

• There is not a good source of specific product feedback, perhaps because sales team members decided it was not worth the time and effort.
• Product collects feedback, but sales does not trust the method. This can happen, for example, when feature voting systems favor not the most important ideas but those whose creators have the most time on their hands to campaign internally for their ideas.
• Product collects feedback, but it’s not linked to revenue. Product says, X has come up the most with customers, and sales says, yes, but that does not hold us back in deals while Y does.
• Sales gathers feedback, but product sees it as too anecdotal. When feedback is collected inconsistently or only anecdotally, product leaders find they have difficulty trusting what is shared, believing, sometimes rightly, that it is biased in favor of large deals, deals with the most vocal sales team members, or deals that have more executive visibility.
• Sales gathers feedback, but product sees it as too high level to be actionable. Prospect feedback that a product is not, for example, “enterprise ready” is a good starting point for investigation, but tells you little about what you can do by itself.

Success Factors

So what have we seen work well? You need a method that is agreed upon and trusted across both product and sales. That means four things in my experience:

• It’s consistent – Collect feedback on each deal and for each customer, allowing you to quantify the impact of improvements.
• It’s tied to revenue – The ranking mechanism is not based on internal votes but rather the amount of prospect or customer revenue tied to each piece of feedback.
• It captures the level of impact – Some feedback is nice-to-have, whereas other product issues will derail a deal entirely, and the feedback mechanism captures sales team judgment on this, which is often a sound leading indicator. In addition, it links to actual behavior. For example, you should know how much lower or higher than average the win rate is on deals with product gap X.
• It’s use case focused – The feedback focuses on the specific thing the customer is trying but not able to accomplish.

If you have this, it becomes an incredibly powerful shared language for product and sales. Sales can easily point out where product misses big opportunities from focusing on what customers are saying and not what actually kills new deals. Product can easily surface where the sales organization might overpivot on feedback from a large prospect that is not representative of the rest of the target segment. And both groups can focus on the relative merits of product choices instead of the extent to which they trust the data.

Considerations for Execution

Ensuring consistent feedback is no small feat. Product and sales leaders need to partner to emphasize to their teams the importance of both capturing and leveraging this feedback. In addition, they need to make it wildly easy to not only log feedback but also log in a way that is clean, de-duped, and well-structured. This is where having an AI-powered solution for capturing and structuring feedback is so valuable. By using LLMs to gather and structure feedback, teams can now dramatically reduce the effort and cost required.

Tying feedback to revenue also means making connections outside of your PLM system. An article of feedback needs to connect to the right Account and, if relevant, Opportunity in your CRM. That lets you tie feedback to the correct revenue numbers and understand how feedback relates to outcomes, like the decision to buy or not buy. Since we all know how quickly CRM data becomes messy, it’s important for field users to own linking feedback to the correct Account and Opportunity.

Lastly, train users on how to gather feedback appropriately:

• Defining severity yields much greater clarity for decision-making. E.g., all people involved in logging should know that ‘deal breaker’ means this issue alone was enough to derail the deal, no matter what else was done.
• Capturing as use cases also ensures that the focus is on the problem and not on the assumed solution. Achieving alignment on that usually involves some upfront training and occasional reinforcement, but is eminently possible with a little focus.

Conclusion

If you do these things, the lens you have on product opportunities is so much more useful. You can understand prospect as well as customer impact. You can leverage field judgment about severity as a leading indicator of revenue impact, and you can leverage actual customer and prospect behavior (buy or don’t buy, renew or don’t renew) as the ultimate arbiter.

The next step is to make it sustainable. For that, I believe you need true field partnership.

Vivun’s platform was purpose-built to foster seamless alignment between product and sales teams. To understand how, see this interactive demo.

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