Sales make the business world go ’round, but data is the gravity that holds everything together to be cohesive and coherent. Data teaches us the most important lessons: what went right or wrong, what can be improved, and what path forward we should take.
Strong skills in managing, analyzing, and presenting data can even help predict what awaits us in the future. A good sales analyst will be able to create accurate forecasts within a 2 percent margin of error. This level of accuracy is not mere chance or luck; it’s the result of taking a data-first approach to sales.
Why is a data-first approach so important? Whether you’re getting your startup off the ground or running a global business, data is the fuel that will ignite your next round of investment or get you to the Fortune 500. Being able to understand the levers you need to pull and the reactions to your actions is crucial when you get to managerial positions. When in sales, predictability is the word that will grant you the hyper-growth you are looking for.
Data As A Sales Tool
I strongly believe that the first stage in the sales process is critical and can significantly benefit from the insights provided by valuable data. As you’re identifying leads and cold-calling, data can provide some much-needed intel about the person or business on the other end. This type of insight can be purchased or even culled from public sources (LinkedIn; Crunchbase etc.), and will give you a leg up and take you one step closer to building a relationship and closing a deal.
On the other end of the sales funnel is data from existing customers, which is generated internally. Product stickiness, churn alerts, up/cross-sell are the daily bread and butter to customer success managers. You should understand your churn trends, set alerts to certain user behaviors, and be able to maintain an active life line between what the data is telling you and what actions should be taken next.
Those who have just begun using data should focus on understanding and digesting the data available to them that will make the biggest difference in their day-to-day activities. As your comfort level rises, you will be able to master the data and crossmatch it to several variables and KPIs, eventually helping to predict sales results with high accuracy in no time. The one caveat here is that 2020 has seen a number of anomalies from economic disruptions due to COVID-19, and may not be the best baseline for future predictions. It’s even more important to track changes over time and use consistent data (which may date back to 2019) for forecasting.
Data As A Business Intelligence Tool
Many people believe the only job of the sales team is to control two metrics:
- Revenue
- The number of subscriptions sold each month
While those are two important data points, that is only a bird’s eye view to a much more intricate maze of data available to understand your business. As sales professionals grow in their careers, they must take a broader view of the overall business to understand what makes the gears turn in the right direction.
In SaaS, there is an endless list of KPIs to track, from the important abbreviations–MRR, ARR, ARPA, ARPU, LTV–to conversions, engagement, retention, churn and more. What’s more important than each individual data point is understanding that these decisions are taking place in a 3D maze; when you move one part, the others move in conjunction as well.
To put this in practice, imagine you are assigning more leads to your top sales reps. An increase in leads alone doesn’t mean they will maintain the same engagement or conversion rate, but by having a bigger pool of opportunities, they should be able to find more monthly recurring revenue to convert. The trick is to study the movement of sales in your business; learn seasonality, understand when changes in product were deployed, when the team hired more reps, or when you lost that superstar from your team. Compile everything into a spreadsheet to get an in-depth view of how certain events, even unpredicted ones, impact results and use it to plan ahead.
Managers can also use data to track performance among their teams. I believe it’s more effective to track a sales rep’s performance based on KPIs than by monitoring their MMR conversions. If they are putting the effort in and meeting targets like talk time, number of calls, number of demos, and participants per demo, results will eventually match up. This type of data allows you to make decisions at a management level. You’ll understand which downturns are a result of seasonality or factors outside of a salesperson’s control, and which may indicate a team member needs more training or coaching on certain products.
The Bottom Line
Data can be the crystal ball predicting next best actions and results for salespeople. But to really make the most of what data has to offer, managers have to build a data-driven sales team. Individuals can track and monitor their own numbers, but it’s much more valuable to share data across people and teams. Not only will that identify trends and anomalies, it will help motivate the team as each person will want to be showcased as a top performer. It’s also important for managers to not only share the raw data, but help break down the numbers, explaining any context and actionable insights that come out of the data. This will help underscore the value behind the data and encourage each team member to track and understand their own metrics.
While instinct is a great quality in sales, a hunch is only a hunch until proven true. Salespeople should be using data to back up their hypotheses and improve the decision-making process throughout every part of the sales process.
Raul Perdigão Silva is the global head of inside sales at Pipedrive, the first CRM platform built from the salesperson’s point of view. Connect with him on LinkedIn.