People.ai

Venketesh Iyer and Dan Zhang have deep experience in leading analytics and strategy teams at prominent companies including Salesforce.com, Facebook, Amazon, and Expedia, and have shaped best practices in GTM optimization, Planning & Segmentation, and built an operational engine to support global multi-billion-dollar scale sales organizations. Dan has also seen the hyper-growth possible by creating a critical operational foundation to scale the Pre-IPO SaaS company AppDynamics that led to one of the highest value acquisitions in history at AppDynamics/Cisco. 

(Sales) Data is like garbage. You’d better know what you are going to do with it before you collect it. – Mark Twain

You don’t have to search too hard to find endless articles that tell you running a sales organization nowadays needs a data-driven approach. Every sales operations and revenue operations team is tasked to track and report on a giant set of sales metrics.

But it gets overwhelming, very quickly. After reading this and applying our framework, you’ll be able to execute your Go-to-Market strategy, achieve your sales targets, and build a scalable sales engine.

With the rise of instrumentation and data visualization technology, we went from “only measuring win” to “measuring anything possible” in the last few years. As a consequence, leaders don’t have a clear sense of what is really driving sales in their business, while salespeople, who are inundated with dozens of metrics, get lost in the day-to-day noise. The result is poor control of the data that matters. Knowing what to measure is the most critical step to set up your Sales Analytics successfully. Sales analytics leaders need to set a vision for what they want to achieve and then work out the best data and metrics to help the team do it. Most companies have dashboards that just vomit dozens of charts, most of which are there just because they are easy to drag and drop.

As GTM analytics leaders, we’ve implemented Sales Analytics Rationalization projects at multiple companies to shift the organizational focus from data dumping and reporting to storytelling and action-driven insights. We have found that in our collective experience, implementing an analytical framework by different levels is critical to deconstruct the sales performance and quickly zoom in to the metrics that really matter. From our own experience, reviewing decks and pages of sales KPIs can actually bury and dilute the real performance signals. 

In order for you to implement this, we’ve created this proven framework as a reference guide to most effectively analyze the health of a scale-up sales organization. We believe that by defining the right audiences across the sales organization is the most important data strategy the Ops & Analytics leader can set for the team. It is like when launching a rocket into space, you have a team to monitor the crew’s activities, a team to monitor the spacecraft systems, and a team to monitor the weather and plan accordingly. There is no way you can serve all three teams with one big report or dashboard. Precise and consistent sales analytics creates accountability, reveals insights about your business gap and hedge, the traits of top-performing sales reps, and more aspects that will improve your bottom line. Let’s get started!

1. Sales Rep

It is a common misconception that “Planning” is only a sales manager’s or sales operations’ job. However, the top sales reps are usually very strategic in terms of planning their work, including planning territory penetration, planning how they spend their time, planning how to hit their number through series of ‘land and expand’ motions across multiple quarters.

Top performers constantly reflect back on their personal performance throughout the sales process. What helped them succeed last quarter? What caused them to have a light pipeline coverage next quarter? Which accounts are getting hot or cold? How should they adjust the time allocation to take down more new logos? Sales reps need a very precise lens in order to continuously improve and drive more predictable, consistent performance.

In order to create a Sales Rep lens, we recommend the following metrics: Book of Business, Performance Trending, and Forecast.

Example of Sales Rep Lens:

  • Book of Business
    • List of accounts/customers that the sales reps own enriched by statistics including Lifetime spend, TAM estimate (usually provided by Sales Ops & Analytics team) and Engagement Indicator (computed by sales activity platform like People.ai)
  • Performance Trending
    • 4 By 2 Trending: Typical sales performance analysis uses the last 4 quarters of bookings and next 2 quarters of Open Pipeline to paint a holistic picture. For a ramped rep, is she consistently closing business and building the new business? For a ramping rep, is she starting to build enough pipeline when she comes out of the ramp? 
    • In addition to that, having an Engagement score as the main indicator of the pipeline health can drive insights on which pipeline are just “comfort pipeline” with a lack of real customer interaction
  • Forecast
    • A good Forecast is usually a combination of human judgment (Art) and predictive model (Science)
    • Human judgment: each sales rep or manager has the ability to override the forecast of their next level direct reports (or their own as a sales rep)
    • Predictive model: In basic forecasting models, one can associate a probability of closure on the deal dimension such as forecast categories. In sophisticated predictive modeling, each deal could have an individual score as Propensity to Close based on attributes like Deal velocity, Deal size, Deal stage,  Engagement level, team/regional attributes, etc. 
  • Other critical deal statistics:
    • ASP and Win rate: These two are good lagging indicators to show how the rep stack up against the others on sales execution fundamentals.
    • Average Days to Close – This metric can help zoom in to the sales motion issue (is this rep taking too long to close deal comparing with his peers?)  also indicates if the rep has enough time to build out the future pipeline

2. Sales Manager

For the Sales Manager, quota capacity planning is critical to their success. A common mistake we saw is sales managers let Sales Operations or Finance take the wheel when it comes to the quota planning process. The Sales Ops team is usually well-intentioned, but they don’t have the same understanding of the rep’s potential, candidates pipeline, or the marketing opportunity that the sales managers do.

It’s not just the sales operations job to set the quota and carve the territory once a year during the annual planning. It is up to the sales managers to continuously monitor their teams’ capacity and run scenario analysis based on the latest personnel movements and actual team performance.

In order to create a Sales Manager capacity lens, you’ll need the following metrics inputs: Sales Quota, Ramped reps, Ramping reps, Open HC, Potential attrition

Example of Sales Manager Team Lens:

All of the other Sales Rep lens metrics are applicable for Sales Manager lens but reported on 2 levels:

  • Detailed: List of Sales reps with their ramping status, rep skill/will profile and Rep Performance cards for a full performance summary. 
  • Aggregated: For example, Average Quota attainment across the whole team and 2 year total historical Open Pipeline across territory sub-segments.

3. Leadership: 

On the leadership level, the role of sales analytics focuses more on informing the company strategy setting, guiding the priorities, running QBRs and reporting to the board, etc. The sales analytics on this level serves as a compass to adjust the execution of the strategy throughout the year. What excites the most visionary leaders today is the strategic value of sales analytics: the ability to enable and inform broad commercial growth and transformation, not just incremental efficiency gains.

At the leadership level, there are 2 primary pillars: An aggregate pillar (by team) and a dimension pillar (by business attributes)

  • A CFO might want to look at Historical trending of Sales Productivity By GEO in order to determine the country strategy
  • A CRO might want to look at the average pipe coverage across the territories to get more insights into regional marketing or channel partners’ Return On Investment
  • A General Manager of a Business Unit might be most interested in a Product Performance to Goal Matrix (%) cut by vertical in order to determine the investment into the product portfolio. Insights gleaned from sales data can help businesses shape their growth strategies, focusing on entirely new segments of a market or moving away from unprofitable areas. 

Example of Leadership Lens:

As a closing thought, there are other two important investments the company needs to make to set up sales analytics successfully: First, the company needs to identify a leader who is both responsible and accountable for centralized, consistent data that sales leaders can rely on to build the analytical powerhouse. Second, committing to data-driven sales culture can go a long way. The most sophisticated insights in the world will sit on the shelf and get stale fast if the sales team doesn’t use them. Leaders in the company can influence the sales team to base their decisions on data rather than on just “gut feeling”. The Operations team plays an integral part in insights democratization through designing a frictionless process and putting tools in sales hands at the right moments.

Successful sales analytics is a journey. It is critical to measure what matters in sales and it is so much more than just a data dump. Carefully picking the right sales metrics to prioritize and then optimize will put you ahead of the game — you’ll be able to execute your Go-to-Market strategy, achieve your sales targets, and build a scalable sales engine.We’d love to hear more about what data or metrics work well for scaling your operations, especially when it comes to sales. Questions or passionate about this subject? Drop us a line to Dan dan@people.ai and Venky venketesh_iyer@berkeley.edu