Building for enterprises is a unique rollercoaster compared to building for typical consumers. While B2C PMs have the luxury of millions of users, making it easier to do things like A/B testing and see clear trends in the data, a B2B PM must marry scarce quantitative data with qualitative feedback to make sense of things. It's not an easy endeavor. 

As a B2B PM, you're caught in constant a tug of war. On one side, the sales team pressures you to build that "one more feature" to clinch a major customer. Meanwhile, your CPO urges you to adopt a strategic, less reactive stance towards the relentless wave of customer feedback. You barely have time to do both.

The best product managers aren't the ones constantly reacting to the feedback, but rather, they have a good sense for picking up on what users don't say directly, but might need. They identify the additional puzzle pieces they need and seek out the information, allowing them to paint a complete picture and chart a strategic course. This is especially challenging in an environment where people are only tuned into one thing: “Our biggest customer just asked for feature X. Let’s build it.”

For example, let’s say you’re a PM at Slack collaborating with a customer success manager responsible for their client, Spotify.  The customer success manager, in monthly meetings with a Spotify representative, conveys user feedback, complaints, and feature requests. But this Spotify representative, often an IT manager doubling as Spotify's Slack admin, may try to relay the input of the day-to-day Slack users at Spotify, but not fully grasp the nuances or severity of issues, leading to mischaracterizations and deprioritizations.

There’s a lot of information that gets lost in these conversations – it’s easy to just see a small sliver of the entire user experience without realizing it. Whereas if you understood the long tail feedback from actual users, you could work on launching the right features with fewer complaints. 

Most B2B PMs tend to rely heavily on customer success managers for insights, creating a bias in their product development. But the best PMs are proactive in constantly gaining a perspective on what customers are experiencing, without creating a large tax continually speaking with their customers.

Here are some ways to gain an edge.

1. Make it easy for users to give direct feedback instead of going through internal company representatives and then to the customer success manager. 

Talking to customers can be time-consuming for both parties. A quick way to collect feedback is to institute feedback portals into your B2B channels. This way, you widen the aperture of feedback you receive from a single representative to anyone who’s using your product. 

One way to accomplish this is to add a “provide feedback” button at key parts of your product. You can also do it off the shelf, using products like Sprig’s in-product surveys, Medallion’s product feedback management, or Bucket’s Live Satisfaction, which allows you to implement a UI on the front end and provides an easy-to-understand visualization on the back end.

By asking customers for feedback at the right time and integrating the survey tool directly into your product's interface, you enable a direct line of communication with your users – with a low barrier of entry for them. With Bucket for example, real-time customer feedback is combined with the quantitative user data, essentially giving you one place not only to see what features customers are using but also their sentiment and feedback for these features.

One example of where this chart was useful would be for a PM director at a B2B SaaS company with $6 billion in revenue. After introducing an upgrade to an analytics dashboard, she received qualitative feedback that customers were initially excited to try the feature but few were retained. The satisfaction score for the new analytics dashboard was low, so she married the qualitative feedback with quantitative feedback to diagnose the root cause. She discovered that users were attempting to click on the analytics dashboard for a detailed view of the data, which did not exist. Combining quantitative and qualitative feedback, she gained insights into what was lacking in the current product and successfully advocated for the development of a more comprehensive data view accessible after clicking on the graph.

Bucket’s Live Satisfaction and products like Amplitude (with integration) give PMs a way to get a more holistic understanding of how the product has been received on the ground, without imposing a significant burden on customers.

2. Contextualize the feedback. Did the feedback come from a target segment that we care about?

Once you've collected customer feedback, instead of immediately taking action, it's important to consider the context by understanding the type of user providing the feedback. Is it coming from a user within a segment that is relevant to us? Is it from a new user who is casually testing our product, or is it from a dedicated, daily user who advocates for our product? This context helps you prioritize and address the feedback effectively.

To effectively manage and act on user feedback, it's beneficial to categorize the feedback into specific buckets. To determine which bucket, you can ask your customer success manager or if you're directly receiving feedback from users interacting with your product, you can analyze their usage history to make this determination. 

Tools such as Amplitude’s Funnel Analysis or Bucket, for deeper analytics on a per-feature basis,  help you slot in feedback into these buckets. Bucket, for example, utilizes a framework for evaluating feature engagement, STARS, which stands for Segment, Tried, Adopted, Retained, and Satisfied – representing these categories in an easy visualization:

A "segment" refers to a group of users who belong to the specific target audience intended to use the product features. For instance, it could be small businesses generating $1 million to $10 million in revenue. “Retained” means that a user has become a repeat user, indicating that the feature has gained acceptance and success within that particular user segment (i.e. reached product-market fit).

Let’s take an example of a Group PM working at a $1b ad tech unicorn. The company uses ML to optimize ad campaigns, and the PM received feedback from customers that advertisers were struggling to determine the appropriate cost-per-click (CPC) value for their advertising campaigns.

To address this issue, the PM had to figure out if this is a problem experienced by their target user segment, which, in this case, is serious advertisers. It's important to recognize that there will always be a small group of non-serious advertisers who lack expertise in advertising and have no intention of ramping up their advertising spend – however, these customers are not the target segment.

The PM eventually confirmed that this feedback was genuine, that there was a long tail of serious small and medium-sized business (SMB) advertisers willing to invest substantially in advertising, but were hindered by their inability to select the right CPC. As a result, the PM decided to take action on this valuable feedback and launched a new feature that offered guidance on the appropriate CPC input.

3. Take action on the feedback.

If you want to do something about the feedback, it better be about a feature that many people are using all the time, rather than just some of the time. I find it useful to think about plotting a feature on a chart, where the x-axis is the number of people using it, and y-axis is the frequency of use per person, which Bucket offers a chart template for: 

You can generate this view in a few different ways. You could either write a custom SQL query, make use of Amplitude Starter templates, or opt for a tool like Bucket, which automatically provides this view when you integrate it with your product. Bucket can be particularly handy if you lack access to data scientists or if you simply want a rapid, hassle-free way to extract insights without investing an excessive amount of your own time in creating elaborate visual representations. The key is to streamline the process of pulling the right data.

Take, for instance, a Senior PM at WhatsApp who oversees features for online stores for businesses. Her main goal was to reduce feature bloat. Early on, the team had dedicated time to crafting custom features based on early customer requests, but they were transitioning towards a more standardized product. She aimed to remove features that were no longer strategically significant or had low usage to drive a cleaner customer experience and allow her to allocate her engineering team's time more efficiently.

At the time, her primary focus was on boosting sales for WhatsApp's online stores and optimizing the checkout process. While a few businesses had requested a post-checkout product review option for customers, it had very low usage and created unnecessary friction in the checkout process. To build a case for this issue, she used a chart detailing feature usage frequency to make a compelling case for eliminating certain features to reduce feature bloat.

In conclusion, succeeding as a B2B Product Manager involves navigating a unique set of challenges. Unlike B2C counterparts who often benefit from a large user base for A/B testing, B2B PMs must skillfully blend limited quantitative data with qualitative feedback. This balancing act involves resisting the push for endless feature requests while striving for a strategic vision. The most successful B2B PMs don't merely react to customer feedback but actively seek a complete understanding by capturing a broad range of user insights. To gain an edge, consider implementing direct feedback channels and leveraging tools like Bucket to make feedback actionable, helping you decide whether it’s worth taking action on.

If you want to check out Bucket, visit them at Bucket.co.

This piece was written as part of PM’s at Works partner program. You can read about the guidelines we adhere to in the link above. We always note partnerships transparently, only share my genuine opinion, and commit to working with organizations we consider exceptional. Bucket is one of them.