Supercharge Your Sales Team with Actionable Product Usage Data

Sales teams are hungry to close deals but starved of the data they need to do so: product usage data they can take action on. This data exists, of course, but it’s often siloed inside tools that belong to other teams like marketing– and almost all of it is too old to be useful. Marketing and product teams need data that looks backward to understand how users are interacting with products and features to refine their roadmaps and strategies. 

But all of that happens post-sale. 

Sales teams need real-time usage data to understand how users interact with products and features while the sales process is still underway. There is no shortage of tools available to collect all kinds of product usage data, but almost none of these enable sales teams to understand and close complex deals. Sales teams need product usage analytics that live in sales dashboards and CRMs, not in tools primarily used by other teams. 

A lack of ready access to this kind of real-time data means sales are being lost. Existing usage data is either never translated in a way that makes it actionable for sales teams, or it’s trapped inside a tool that feels like it requires an advanced degree to use. 

The future of high-performance sales lies in teams that have access to real-time product usage data on how users interact with products and features throughout the sales cycle. These tools readily translate product usage analytics into actionable tasks with AI-powered automations that drive everything seamlessly. 

That future might not be as far away as you think. 

The Problem with Product Usage Data

Sales teams know that they need product usage data and they know what to do with it. The difficulty is either in accessing the product usage analytics from that data, or having to do so much work to understand it that it slows down the process to the point of killing sales. Any seasoned salesperson is intimately familiar with these pain points– usage data is being captured, it’s just rarely specifically for sales. 

If sales teams can access the usage data that is being collected, they often need advanced training to use the tool being used to collect usage data and store it. Even then, the data is rarely translated into something that’s easily actionable from a sales perspective. Something that spells out, at a glance, who the power users are, overall feature usage, and other key metrics around user behavior.

This leads to a loss in sales, which ultimately leads to a loss in revenue. It's one of the biggest issues affecting teams today, but it remains unsolved because it seemingly requires so much change to resolve. 

Translating Product Usage Data into Customer Insights

When it comes to upselling and cross-selling, sales needs the right product usage data at the right time; key product usage metrics that give sales team members insight into user behavior in actionable ways. That includes being able to analyze trends in feature adoption, identifying points of friction and drop-off, and the ability to segment users by behavior personas. 

Ideally, all of this is available in an easy-to-use dashboard that quickly translates if a customer or prospect is using a product or is active in a trial. If so, what is their usage frequency? Are they power users? Sales teams should be able to easily spot where prospects are confused by a certain feature and whether that results in them avoiding that particular feature or dropping out of the trial altogether. 

Analyzing product usage data can also help sales teams learn which features can help them upsell or cross-sell other customers. Heavy usage of a particular premium feature and what it enables them to do can be used as an example for other customers and key prospects, especially if they fall into the same user segments.  

This kind of usage data can also help teams identify overuse, translating into potential renewal or upsell opportunities. Depending on how a team’s particular offerings are structured, this could mean a customer needing more seats or access to premium features. 

It's not something you're always going to find in basic customer feedback, which is sometimes aspirational for how a customer wants to be using a product. Analyzing product usage data tells the story of true usage frequency and which features users interact with most vs. which are simply nice to have.

Building Actionable Dashboards for Sales

One of the best ways to combat customer churn is with proactive outreach. Sales teams armed with real-time product usage data have what they need to do informed outreach with a personalized touch. A customer who hasn’t been active in the product in a while is much likelier to respond positively to outreach that’s centered around helping them understand a key product feature vs. a generic “we haven’t seen you in a while, how can we help?” type of message.

Most product usage metrics available are geared toward product and marketing teams; they look back so that these teams might look forward. Sales teams live in the present moment and need usage data tailored to their processes. 

The key to making this data actionable is designing account overviews and activity feeds that are easy to read and use, at a glance. New sales team member onboarding should be as quick and painless as possible so they can be ramped up and contribute to increasing revenue as quickly as possible. Tools that don’t require extensive training are key to streamlining this process. 

The ready availability and readability of this kind of data likewise enable sales teams to surface renewal opportunities alongside red flags– like usage drop-off as an early warning sign of potential customer churn. Personalizing these alerts and notifications on a simplified dashboard would give sales team members the product usage data they need when they need it to take action. 

It would also give customers and prospects a much better experience throughout the sales and customer lifecycles. That leads to higher customer satisfaction and lower churn rates over time. 

Contextualizing Insights with Qualitative Data

This customer and prospect usage data becomes even more powerful when paired with market research. This enables sales teams to build those behavior personas they want to segment users by. Simply looking at usage data alone can identify friction points and drop-offs, but it’s even more valuable to know if that behavior is more likely in certain user segments. 

Suppose certain entry-level job roles are the ones that struggle with the same features, as seen in user behavior again and again. In that case, sales teams will be able to flag this in advance and smooth out the trial and onboarding process accordingly by either directing them to necessary resources or making sure the customer success team does. 

Sales and product teams can also establish productive feedback loops based on customer interviews, each getting a slightly different perspective on customer experience that can help inform the other teams’ goals. The richest, most actionable data lies in the ability to link the quantitative signals seen in usage data with the qualitative insights available from market research, customer interviews, and other customer feedback. 

Market research gives organizations the starting point for understanding their ideal customer profile (ICP), but customer interviews help teams narrow down the exact quirks of the actual users interacting with products and features regularly. 

Enabling Sales with Usage Narratives

The other advantage to investing in a product analytics tool that translates this data directly for sales is how much it streamlines workflows; the sales team no longer has to reach out to other teams to get the usage data they need or spend time getting that data translated for them. It’s already right there in a dashboard just for them, in an actionable format. 

A single source of truth for teams to operate from across an organization is crucial to streamlining workflows and increasing productivity. Further customizing that data– in an automated way– for each team means everyone can work even more seamlessly, driving progress toward team and organization goals with the least amount of friction possible. 

This kind of access to clear, actionable usage data allows sales teams to craft compelling narratives around key behaviors that can be used during calls with prospects and current customers. Conversational frameworks can be built around key metrics instead of “vibes”, allowing the newest team members to be trained in the most impactful way possible. 

These narratives and conversational frameworks are the tools sales teams need to help overcome the challenges regularly faced in the sales process. Being able to tell new customers and prospects relatable stories about how other users have successfully navigated friction points in a product to great success makes the process more personalized. 

Having the quantified data aggregated and anonymized also helps sales teams overcome any resistance stemming from data privacy concerns or ethics. Any personalized touches in customer and prospect stories should come from qualitative data, like customer interviews or approved case studies done in conjunction with customer success. Quantified data can be used in the aggregate to build a story of the "everyuser" while qualitative data adds personality, color, and relatable detail. 

Designing the sales dashboard and internal process in this way helps ensure internally secure data practices and compliance measures sales teams can also discuss with prospects and current customers who may have a new security officer who joins the team with questions. 

All of this helps foster a culture of transparency and an ongoing practice of clear communication with customers. That in turn fosters trust, leading to longer-term relationships, reduced churn, and increased revenue. 

Best Practices for Implementation 

If this all sounds great and you can’t wait to get started with your team, let’s break down the best practices for the implementation of product usage data for sales. We’ve already touched on a few of them, but it never hurts to get into the details. 

Make the product usage data easy to access and actionable 

The first key step is to establish a dashboard for sales with actionable, easy-to-read insights. The data sales teams need is real-time customer and prospect usage data. It can’t be post-sales data or real-time data that are essentially useless because it’s locked away in a silo or the tool it’s in requires a Ph.D. to use. 

To do proactive outreach, sales teams need to know current feature usage.

Create key communication feedback loops between teams

Sales, marketing, and product teams all have a vested interest in understanding customer and prospect usage of products and features (alongside customer success). Create a system that works for your organization that’s essentially a continuous feedback loop between these teams, so each can use the insights they get from their work to inform the others. 

Product teams need to know what to prioritize on the roadmap or for the next product launch. Marketing teams need to know what’s going to hook more ICPs. Customer success teams need to know enough to keep current customers happy.

Sales teams need to know how to talk to customers and prospects in a way that feels personalized, informed, and helps close deals to keep everyone else's workflows running smoothly through continuously building revenue. 

Run on data-driven insights 

Strategies should continuously evolve in your organization based on data-driven insights. Revisit the workflows teams have built regularly to see what’s working and what could be tweaked or refined. Ensure everything that’s vital information continues to live in a single source of truth all teams can access, but that’s also tailored to their specific needs. That includes all of the product usage data!

There’s a constant balance that’s needed between the firehose of usage data that can be collected around prospects and customers, how to keep that data safe, and how to make it tailored and actionable for teams without violating any customer privacy rights. 

Conclusion

Sales teams know what product usage data they need and they know what to do with it to close sales. Current systems that provide the wrong usage data– almost entirely post-sales– or silo that data mean companies are losing out on sales, negatively impacting revenue. 

The future is clear and easy access to usage data, with tools that have automations and AI to enable sales teams to do what they do best: close deals.