The Evolution of Sales Metrics in Modern Business
Sales is a fast-paced industry where numerous deals, lead qualifications, and messaging activities happen simultaneously. This high volume of activity generates an overwhelming amount of data. Many sales departments track the wrong metrics, obscuring their path to revenue. To navigate this complexity, organizations must focus on the right sales metrics that provide a clear view of performance.
Data tracking strategies have evolved significantly with technology. Key metrics include activity metrics, product metrics, revenue metrics, and conversation intelligence. Activity metrics track rep actions like phone calls, emails, and meetings. Product metrics relate to success indicators such as purchase rate, churn rate, or revenue attributed to specific products.
Revenue metrics encompass total revenue, changes in company or product revenue, and the percentage of revenue from new versus existing customers. Conversation intelligence involves patterns and insights from conversations between reps, prospects, and customers. Before joining Gong, Annelies Husmann, Head of Enterprise Sales at Gong, focused heavily on activity metrics and how they married product data and revenue data. She notes that while these three metrics can give a great snapshot of business health, they only answer surface-level questions.
Activity, product, and revenue data can tell you that a rep is having three times as many conversations as other reps, but they cannot tell you why he is winning the deal. To solve the mysteries behind why deals close and how to replicate best practices, Husmann says her team leverages conversation intelligence and revenue intelligence data recorded by Gong’s software. Conversation insights can include words used by prospects or sales reps, conversation length, or other verbal themes that solutions pick up on.
Leveraging Conversation Intelligence for Strategic Insights
Conversation intelligence allows sales teams to answer vital questions that traditional metrics cannot. For example, how often are competitors coming up in deals? Which prospects are most engaged on the buyer side? With conversation data, teams can review recordings of sales demos and lists of discussed topics that AI-powered tools have picked up from the audio. This data provides a deeper understanding of the customer journey and the factors influencing buying decisions.
When a sales rep has a data tool to track how well their deal is going, they can determine what is needed to convert a lead into a customer. If conversational analytics show a prospect asking questions about integrations, competitors, or pricing, reps can add those to the agenda for the next meeting. Reps can also learn from tenured colleagues about how they address potential customer needs and pain points.
Sales teams can use conversational insights to identify gaps in their sales calls and discover what is working for other reps. They can track progress using KPIs, such as whether they are asking enough questions in discovery and if those are the right questions. This approach enables reps to refine their strategies and improve effectiveness in engaging with prospects. By focusing on the quality of conversations rather than just quantity, sales teams can drive better outcomes and close more deals.
Identifying Coaching Opportunities Through Data
As a sales leader, Husmann leverages conversation data and other KPIs to determine if reps are positioning the value proposition accurately. Sales enablement leaders or VPs of sales can also use this data to verify if reps are using the company’s designated sales methodology, such as Sandler or MEDDIC. Strategic initiatives will be reflected in the words or phrases used in calls, allowing conversation intelligence to pinpoint which reps have adopted new messaging or methodology and which have not.
When sales leaders find inconsistency in sales rep data, they can determine the best way to train or give strategic feedback to ensure effective tactics. Husmann says, “We’re really good at strategizing and moving jobs forward for our team. I think having this full picture of insights into what’s going on in your pipeline frees you up to do more of that. And that’s why we’ll close more business.” This data-driven approach to coaching allows leaders to focus on high-impact activities rather than administrative tasks.
Even though sales teams aren’t expected to be marketers, they need expertise around their ideal customer. Understanding the voice of the customer benefits the sales team, sales enablement, and the overall company. Sales orgs can use this data to hone in on the voice of the customer, market feedback to a new product, and new messaging effectiveness. From there, sales teams can develop the best sales strategy around their ideal buyer and share the voice of that customer with marketing, product, and customer success teams.
Using Data to Strategize Without Disruption
With various data tools, leaders might be tempted to over-monitor rep activity, which could be disruptive. Instead, Husmann says tools like Gong are meant to help sales leaders strategize, strengthen their overall pipeline, and train reps more effectively. She believes that reps and frontline managers can use analytics insights productively, without being disruptive in daily processes. It affords them deep insights and complete visibility into what is truly going on in the pipeline.
Husmann explains that in one-on-ones, she no longer spends the first 20 minutes of a 30-minute meeting asking, “What’s going on? Who’s involved? What’s our next step?” Because she can already answer that question using data. Instead of catching up, she spends 30 minutes strategizing with her team, asking, “How are you moving the ball forward? How is our value prop resonating with their executive staff? And most importantly, how are we going to close more business together?” This shift in focus allows for more meaningful and productive conversations.
Determining When to Pivot Strategy
In 2020, many sales teams, including Gong’s, used data to recognize shifts in sales. When companies chose to pivot their strategy, they also adjusted their KPIs and progress metrics accordingly. Husmann explains, “Throughout the year, we’ve seen a couple of different changes in our sales process. And that naturally affects the different KPIs and data that we’re tracking. Historical data the team had tracked was really no longer relevant because everything had changed.”
What the team focused on in Q2 was different from Q4. In Q2, they focused on building relationships because things had slowed down. Deals that used to be signed by a VP of Sales now had to go to the CFO or CRO, elevating the buyer. Gong also adjusted sales processes when they determined that more prospects were budget-conscious due to the pandemic and looming recession. Having a clear, definitive ROI tied to a value prop affecting the entire business became table stakes.
Now, as Gong’s business has sped back up, its sales teams have pivoted tactics and data tracking again. People realize they need complete visibility into the voice of their customer and what remote teams are doing when speaking to customers. A nine-month sales cycle was sometimes shortened to three. Now, Husmann says the metrics she tracks focus less on small sales activities and more on improving productive time management. She uses data to answer questions like: Are the potential sales commitments real? Are we driving to close as fast as possible? Are we focused on making sure we have the largest land as possible so we can get in and get out of deals?
Balancing Data with Human Instinct
As a sales leader or rep, it might be tempting to think sales intelligence and data tools will always lead you to deals. But, because selling products involves soft skills, like emotional intelligence and relationship building, even Husmann notes that there are times where reps and leaders will want to follow their instincts rather than data. Instinct comes from understanding the human aspect of the relationships you’ve built with your prospects and understanding the unspoken feeling of an opportunity. Most importantly, instinct typically comes from understanding the context of the conversations you’ve been having. Data doesn’t always pull that through.
While sales reps might run into times when they need to trust their instincts on a call, sales leaders should also use their instincts when working with or training reps. Even though data is a large part of Husmann’s coaching, she says one of the things she always tells reps is that they are always allowed to go and make their own decisions. Using your instinct and listening to your instinct is part of that ownership of your sales cycle. Everything should be based on science and data, but the human aspect should not ever be taken out of the equation. At the end of the day, relationships are important. The art of sales is important, and those instincts will eventually need to be listened to.
Collecting and Leveraging Sales Data Effectively
Sales metrics can be an amazing way to get insights on your sales process, where it’s leading to deals, and where it needs work. But, collecting, organizing, and analyzing all of this vital data takes work. If this post has persuaded you to leverage data in your sales strategy, but you don’t know where to start, you can look to your sales ops teams, as well as managers and reps, to collect and clean key data. The ultimate goal for any strategic sales operations or revenue operations team is to provide real fantastic sales analytics from the sales force or other systems of record.
That being said, there is some responsibility on everyone from the rep to the frontline manager, all the way to the revenue operations teams, to make sure that they believe in the power of data and that they’re all doing their part to make sure that dataset is as clean as possible. By working together to ensure data quality and relevance, organizations can unlock the full potential of sales analytics to drive decisions and speed up deals. This collaborative approach ensures that data is not just collected but effectively utilized to inform strategy and improve performance across the sales organization.
Sales analytics provide a powerful lens through which to view the sales process. By focusing on the right metrics, leveraging conversation intelligence, identifying coaching opportunities, using data to strategize without disruption, determining when to pivot, and balancing data with human instinct, sales teams can drive better outcomes and close more deals. The key is to use data as a tool to inform decisions, not to replace human judgment and relationship building. As the sales landscape continues to evolve, organizations that effectively leverage sales analytics will be better positioned to succeed in the long term.
