A killer sales dashboard is more than a conglomeration of metrics: it’s a tool custom-made to facilitate your SaaS company’s unique sales strategy. If you’re not sure what data to include on your team’s sales dashboard, there are lots of KPI lists out there to inspire ideas. Ultimately, though, it’s better to design your dashboard based on sales objectives, stakeholders, team roles, and organization hierarchies.
If that seems like a lot, don’t worry: it’s simpler than it sounds. We sat down with genuine sales fanatic Darryl Praill on a recent episode of the Data Talks podcast to learn how he as the CMO of a company specializing in sales engagement recommends designing sales dashboards. According to him, before you get to key performance indicators, it’s important to sync your team on the following three key performance initiatives so that everyone understands the game plan.
Understand what sales analytics are really for.
First and foremost, it’s crucial to communicate to your team that more than gamifying the sales experience, monitoring goals and quotas, predicting pipeline problems, and tracking trends, sales dashboards and the SaaS metrics on them are about accountability.
If you’ve ever worked for a company with rifts and resentment between departments, you know how important accountability can be. If Sales fails to meet its goals for a given quarter and doesn’t have data to demonstrate what went wrong, it becomes a guessing game — or worse: a blame game. Sales blames Marketing for failing to acquire good leads, Marketing blames Sales for neglecting to pursue them, and executives are forced to make decisions based on mere hearsay.
If you’ve ever worked for a company with rifts and resentment between departments, you know how important accountability can be.
With the right data on your sales dashboards, you can bring your teams together in a spirit of solidarity and collaboration. “What I love about reporting,” says Praill, “is that it takes the human element out of sales. It just says here’s the data. And you are so much more empowered and enriched [because] now you can make informed decisions that have a consequential impact on your output and on your future.”
This means that in addition to quota progress trackers and traditional SaaS sales KPIs — like CAC, CLV, ARR, and MRR — an efficient sales dashboard will provide insight into your lead lifecycle: how many leads were passed to Sales, which received touches, how many touches they received over what timespan, etc.. With data this granular, departments can work together to pinpoint weaknesses in the sales pipeline rather than argue over the facts. “That’s what so crucial about the data and reporting is that it becomes the arbiter,” explains Praill. “It becomes the truth, that single vision of truth.” With lead lifecycle metrics, drilldown capabilities become crucial, which leads me to my next point.
Get granular (but not too granular).
KPIs and other top-level summaries tell us where we are but not how we got there. To understand what Praill calls “the little numbers behind the big numbers,” we need to be able to drill into aggregates — sum totals, averages, counts — into data that might help explain those final tallies.
Praill likes using a sports analogy to explain the need for granular sales data. “A killer sales dashboard,” he says, “is both a scoreboard as well as a box score. When you equate the two, the scoreboard with the box score, you can start to see cause and effect. The box score influences the scoreboard.”
“A killer sales dashboard is both a scoreboard as well as a box score. When you equate the two…you can start to see cause and effect. The box score influences the scoreboard.”
In sales, conversation analytics are an excellent example of “box score” metrics worth including on sales dashboards. Let’s say a rep is making her sales quota for the month, and if we drill into that KPI, we see the number of calls she made and emails she sent. We could stop there and attribute her success to the number of calls she made, or we could drill further for insight into the quality of those calls. Conversation analytics, depending on the transcription engine your team employs, could include metrics like call duration, percentage of call spent listening versus talking, number of “trigger phrases” responded to versus ignored, number of filler words used, and more.
Praill advocates measuring behaviors and practices that will help you refine your sales technique but cautions sales managers not to “boil the ocean.” Teams that track too much and build too complex and inflexible a data model around those metrics invariably give up on the model altogether. The trick is to get just granular enough that your analytics ROI stays positive.
Track early warning indicators from outside sales.
Because SaaS relies on a subscription-based business model, churn and retention are important metrics, particularly for customer success teams. But Praill argues that Sales should be keeping an eye on them as well as early signs that Sales will need to redouble its efforts.
“If my churn starts to go up or my retention starts to drop,” he explains, “then chances are it’s one of two things going on. Either a) my Support and/or Customer Success teams are underperforming […] or b) my competition has done something new…which is causing my customers to leave me to go to them.”
In both cases, the company as a whole needs to respond to the pressure placing strain on Sales. If Support or Customer Success is struggling to accommodate customers, there should be investigation into the issue so that the company can continue to grow without overextending the Sales team. If the competition is drawing customers away, Marketing and Product need to investigate how and respond accordingly. SaaS sales dashboards should include retention and churn rates so that Sales can anticipate roadblocks and coordinate with other departments to clear them before they become costly.
An optimized SaaS sales dashboard should be more than a leaderboard for account executives and SDRs. It should foster cohesion between Marketing and Sales by tracking lead lifecycle, help explain sales rep performance through drilldown data, and prepare the Sales team to meet challenges coming down the pike. Pick metrics that facilitate these objectives, and you’ll be well-positioned to respond intelligently to changes in the market.
Article originally appeared on Software Business Growth.