Why product teams overestimate revenue from sales feedback

Using sales reports to figure out which features will have the most impact? Avoid these pitfalls when prioritizing by "business value".

Jul 3, 2024

Jul 3, 2024

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0 min read

โ€œWe lost a $100K deal to [competitor] because we didnโ€™t have [feature] yet.โ€

Why using lost deals to estimate business impact is messy

Product marketers and product managers know this story well. When using customer requests or deal feedback to prioritize product investments, opportunities (deals) like this sounds like a good way to grow revenue. So what's the problem?

The example above assumes three things:

  1. The deal your competitor won was $100K

  2. You could have won the deal at $100K.

  3. Having the feature would have changed the outcome.

Best case scenario, all three are true and you now have a compelling data point. But if youโ€™re looking at lost deals and interviewing sales reps without understanding how their process works, you may also overestimate the value of a feature.

In this post, weโ€™ll talk through scenarios you will encounter when researching the potential โ€œbusiness impactโ€ of a feature. This includes four common reasons product teams overestimate feature value, and how to avoid them.

Why do we overestimate a feature's business impact?

The story goes something like thisโ€ฆ

For the past two quarters, youโ€™ve considered finally building a feature youโ€™ve heard about from a few folks on your sales and customer teams. You know what the feature requires, but arenโ€™t sure about business impact yet. Before changing the roadmap, itโ€™s time to research! You go to the sales and customer teams for details.

โ€œHow has this affected your deals?โ€

You hear stories of six figure opportunities that evaporated, and how this feature was critical to the customer. After totaling the results of your internal roadshow, you now have what looks like strong data.

โ€œWe lost over $800K in deals to competitors because we didnโ€™t have this feature. And there's another $500K potential from existing customers who expressed interest.โ€

Now you have a way to tie the feature to potential new revenue. As far as product management is concerned, this sounds like a compelling business case for prioritization. And who would blame you? Youโ€™re leaving MONEY ON THE TABLE! This sure feels like an obvious win.

On first glance, prioritizing the feature seems like a good move โ€” but how do you know if the estimate is reasonable? Here are four mistakes to watch out for as you're researching data from sales and customer teams.

Mistake #1: The deal doesnโ€™t have realistic scope or pricing terms

Most people won't buy everything at once, up front, at full price. Iโ€™ve seen situations where reps cited $M+ deals as the value of an opportunity, because technically thatโ€™s what a full global rollout at list price might be. It is an optimistic view, but misleading for folks in product management and product marketing who may not have the context when researching.

Expect discounts

Contract negotiation is one of the later stages of the sales cycle. During this stage, you establish the commercial terms, often with trained folks from the customerโ€™s procurement team. Until this happens, the value of a deal is subject to change. One especially important side effect of this is that the earlier a deal is lost, the more likely the opportunity is overvalued.  This is not always a sign that your sales team is doing something wrong, just a reality of how typical reporting and deal cycles work.

If a sales rep did a demo with a prospect and filled out a preliminary opportunity in Salesforce, that number most likely reflects the potential value if they paid full (โ€œlistโ€) price. In large deals, expecting full price is not realistic. Especially when the customerโ€™s procurement team is involved, you should expect some kind of negotiation or volume discount applied to the final amount. Discounting can be 10-20% minimum, but may go much higher depending on scale. The scope of the deployment may not be firmed up either, so the # licenses or estimated usage can reflect potential future upside.

To get a realistic estimate, ask your sales team for the average discount with similar sized customers. You can use this to adjust estimates which may be too optimistic.

Weight revenue by stage

Within revenue-facing teams, itโ€™s normal to weigh deals in the sales pipeline differently based on how far into the deal cycle they are. This adjustment makes forecasting more accurate. Essentially, a dollar is less valuable at earlier stages and more valuable at later stages. A $100K opportunity might reflect $50K (or less) in weighted pipeline in the initial phases.

The thinking is that as you move through the process, you can consider more of the opportunity realistic. A brand new deal might start weighted 30% of total $$, and a deal thatโ€™s awaiting final signatures could still be weighted 95% of total value. Your companyโ€™s approach may vary.

Mistake #2: Using lost deals to estimate potential revenue

The dreaded big deals lost report in Salesforce

This issue happens when you base research on on reports like "Top 10 biggest deals lost" from Salesforce. Just like #1, the problem starts when you include revenue from lost deals at face value, without considering if it is valid. If a deal hasn't gotten to negotiation or budget discussions yet, you don't yet have confirmation that the customer is willing to pay the amount you quoted. The real opportunity is closer to whatever they spent with a competitor, and often within an existing budget. The amount they spend with the winning solution may not be anywhere near your quote.

What to do instead

Ask the rep if they established the customer's budget. It doesnโ€™t have to be precise, and even a range helps. Benchmarking the deal against similar sized customers you already have is another way to verify youโ€™re using realistic numbers. Ask what the average sale price (ASP) was for similar deals in the past, and if it is a good benchmark for this estimate too.

Mistake #3: The revenue estimate includes expansion potential

Future potential, before discounts applied

"They plan to start with 100 people, but have 10,000 people if this goes well."

This happens with deals may have long term expansion potential, but the initial purchase has a smaller scope. Especially for products with usage-based billing, you also need to separate initial adoption versus future potential opportunity. This is true for both customers and prospects. When youโ€™re early in a deal, itโ€™s harder to know the realistic starting point compared to potential upside from growing the account long term.

For example, if you have a product which bills by # of users and youโ€™re working on a deal with an enterprise company spanning multiple countries. You want to be sure the opportunity size is grounded in reality vs. assuming 100% of global employees at the company will need licenses immediately. The customer might consider their initial deployment a pilot with an intentionally limited group of users for the first year.

What to do instead

Try asking โ€œWhatโ€™s the value of this deal in the first 1-2 quarters?โ€ or โ€œWhatโ€™s the smallest deployment that would still make sense for their initial goals?โ€ The goal is to anchor initial value instead of overly optimistic estimates.

If you find the largest deals were lost in early stages, you might also want to apply the forecast weighting to your own estimates for clarity. When you skip this step to evaluate potential revenue from a new feature, you risk overestimating the impact and prioritizing the wrong things.

Mistake #4: Attributing a lost deal to a single feature

We only need one feature to close the deal

In B2B, itโ€™s rarely just one thing. Decisions around large deals are complex, especially as you move upmarket and into enterprise. This means you canโ€™t always neatly attribute a specific lost deal to a specific feature. Itโ€™s more likely to be one of a few factors, and perhaps the other three gaps on the list were more important. And saying no to customer feature requests is hard.

For example, if your product was disqualified from an RFP (request for proposal) process due to missing a feature, you donโ€™t have confirmation that the quoted price would be valid if you had the feature. Only that you estimated the deal at a certain size. You're guessing.

What to do instead

In these cases, you want to understand the conviction that the deal hinged on the specific functionality. If you arenโ€™t sure, have your product marketing team interview prospects from lost deals. Your goal is to learn, not change their mind. Target 15-20 minutes max, and do not include anyone involved in the sales process. You will get more honest feedback.

Itโ€™s OK to reward the person willing to give the feedback, if needed. Keep incentives simple, like a $50 gift card or a small donation to a charity of their choosing โ€“ some companies have policies against accepting gifts from vendors.

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