The 4 Problems with B2B Sales Analytics — and How to Solve Them

But for a technology that’s been around for nearly two decades — since Siebel Sales Analytics launched in 2003 — it hasn’t changed much. Yes, Qlik, Tableau, Looker, and other BI dashboards provide great visibility into sales performance, helping sales leaders understand the performance of each member of their team. But as helpful as these offerings have been, overall sales performance in B2B companies has not tremendously improved.

According to the CRM vendor Hubspot, sales teams achieve close rates of 19%, whereas best-in-class companies can close 30% of their deals and more. Forrester analyst Seth Marrs noted that average sales quota attainment has dropped from 63% to dismal 43% by some estimates.

With all this visibility, why haven’t we managed to achieve real breakthroughs in our sales performance?

The limitations of today’s sales analytics tools

At Celonis, we spend a lot of time helping organizations look across all the systems involved in the end-to-end Sales process. Here are the four biggest and most common issues we’ve encountered:

1. Sales analytics show you problems — but not where these come from
   Sure, most popular sales analytics tools can highlight that gaps in your pipeline exist. But in most cases, that’s where the insight ends. You’re unlikely to get any insight into where the gaps have come from, the real impact they’re having on your sales performance, or the next best steps to fix them before a future quarter falls through.
2. Actionable insights aren’t always very actionable
   Most of today’s sales analytics tools and platforms claim to deliver ‘actionable’ insights. In reality, these tools still mainly rely on the manager’s own ability to identify gaps and skill to execute. The result: subjective, non-data-driven judgments at best. Even the strongest analytics insights need to be effectively translated into actions that sales reps, managers and ops teams can start taking immediately to deliver meaningful value.
3. Sales analytics need to look beyond CRM
   CRM sits at the center of the sales process today. But in modern organizations, valuable sales and customer data can be found across a whole host of other systems — marketing automation, and CPQ, to name but two. When sales analytics are generated purely from CRM data, they lack context. To build up a complete, contextualized view of your sales process, you need to look beyond CRM and integrate any and all relevant data sources as well.
4. Poor data quality
   Essentially, as with any data-driven tool, you only get out what you put in. So if the quality of your CRM data is poor, the quality of your insights will be too. And without any visibility into where data is inaccurate, false, or no longer representative of current conditions, you could end up with weak sales insights without realizing it — seriously impacting your sales performance. Until your salespeople see CRM hygiene as an essential step in helping them hit their quota, you’re going to have a hard time changing that and your sales analytics will suffer.

Going from sales reporting to sales execution

Today’s sales analytics platforms simply aren’t fit for purpose. If we really want to hit the numbers we’re aiming for, we need to mature from insights to action, from sales reporting to sales execution. Let’s give you some inspiration on how you can get there.

1. Know exactly what's causing gaps in your pipeline
   Even though Sales analytic tools give you great insights into common sales KPIs, they are black boxes when it comes to understanding what exactly is going wrong when you miss your targets. Which specific actions should your sales reps take to close the deal? When is the best moment to send a follow-up email to opportunities? Is there a partner who helped you close a similar deal before and could support? What proof point (value assessment, POV, customer reference) is the most effective to seal the deal with one specific opportunity? Technologies like Process Mining can bridge the gap between reporting and execution. Visualizing your sales process end-to-end and adding relevant business context, the technology helps sales organizations focus on the most important issues and impactful actions.
2. Take the right action at the right time
   What most sales analytic solutions have been missing so far is the opportunity to go further than insights. Just like Google Maps doesn’t only show you how to get from A to B, but proactively adapts your route in real-time based on different factors (weather, traffic, tolls, etc), industry leaders have realized they need a tool that ensures they’re taking the right action at the right time. Fortunately, the sales technology market is undergoing a renaissance. Adding technologies like Process Mining, AI, Machine Learning to their tech stack, the most forward-thinking companies have started to identify pipeline gaps early at all levels, close gaps with automation and guided action, and deploy resources on the most promising accounts.
3. Improve CRM hygiene
   If sales reps are struggling to stay on top of their admin, the quality of data entered into CRM systems can quickly fall, directly impacting the analytics it’s used to generate. Keeping the CRM clean can be a tough task, but one that’s well worth your time if sales analytics aren’t delivering the results you want to see.