That depends to some degree on the particular goals and challenges of your organization. Other factors include the type of product or service you’re selling, your pricing relative to your competitors’, and the average length of your sales cycle.
Certain aspects of sales analytics are fairly standard, however, including the proper cadence. Typically, you track results by week, by month, and by quarter.
Examples of typical weekly sales analytics include:
Number of contacts: What is the target number of contacts (phone call, email, etc.) you would like your reps to make in a given week? What is the actual number? If the latter exceeds the former, you can probably set more aggressive goals. If it’s the opposite scenario, you might want to dial back the target number so your reps don’t feel the need to start spamming prospects just to hit a quota.
Response time: Depending on which source you cite, response time is either incredibly important or seriously overrated. One study famously found that conversions drop off significantly when a rep takes longer than five minutes to respond to an inbound lead. But as The RAIN Group’s Trish Bertuzzi pointed out, “It can take longer than five minutes to not sound like an idiot.” So the objective should not be to set some arbitrary standard; it should be to compare the lead response time of your most successful reps to that of your least successful reps and see if there’s a correlation. If there is, set the bar accordingly.
Examples of typical monthly sales analytics include:
Marketing qualified leads (MQLs): Not all leads are created equal. MQLs are the ones your marketing team has determined have the highest probability of conversion among your sales team. If the percentage of MQLs that result in actual conversions is low, that indicates a disconnect between your marketing team’s approach and the on-the-ground reality for your sales team.
Win rate: This is the percentage of deals a given rep managed to close compared to the number of deals they attempted to close. What’s a good win rate? A RAIN Group survey of 472 organizations found the average win rate is 47%. But the truly revealing finding was that win rate broke down into three basic groups: elite performers, top performers, and “the rest.” Elite performers, which comprised just the top 7% of respondents, produced an astounding win rate of 74%. Top performers, which comprised the top 20%, produced a win rate of 62%. Everyone else produced a win rate of just 40%. Knowing which of your reps are producing top win rates, as well as where and how they’re succeeding, can be extremely valuable.
Percentage of reps making quota: While other metrics provide a more precise measure of financial impact, an increase in quota attainment reflects the success of sales enablement, signifies greater team stability and job satisfaction, and correlates with lower turnover.
Examples of typical quarterly sales analytics include:
Customer lifetime value: This is an important metric because it accounts for the short-term cost of acquiring a customer as well as the total value that customer is liable to provide over the long term. A rep who’s producing high win rates could be relying too heavily on prospects that require a lot of ongoing customer support or are difficult to retain. Quarterly analytics can help surface these important insights.
Time to first deal: On average, what is the length of time between when you hire a new rep and they complete onboarding and training and close their first deal? It might be longer than you think. Once you start tracking this metric, you can work on shortening that interval — which will reduce your cost of hiring and increase your first-year revenue per rep.
Content contribution: How effective is your sales content? Get the answer by tracking the use of sales content by each rep, tagging each opportunity, and tying content to pipeline and deals closed. That lets you measure the revenue contribution of specific assets.
Content lift: This is an even more precise measurement. By calculating the difference in average deal size in a given quarter between closed opportunities that had shared content and those that didn’t, you can determine the revenue lift of a content piece.