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Data Analysis To Focus on the Right Sales Metrics

Many sales managers have a laser-like focus on tracking their goals and progress against these goals, but to be most effective they should be tracking different metrics.

shutterstock 117313246 300x199 Data Analysis To Focus on the Right Sales MetricsThat’s according to a blog post from Scott Edinger, founder of Edinger Consulting Group, who notes that sales professionals and their managers too frequently focus only on numbers when accessing performance.

In his post, Edinger points to a recent study by the Sales Education Foundation and Vantage Point Performance that identifies 306 different metrics that sales leaders are using to manage their businesses.

The metrics fall into three broad categories: sales activities (number of accounts assigned to reps and number of calls made by reps), sales objectives (the number of customers acquired and retained) and business results (revenue, profit and customer satisfaction).

“Even though managers were spending more than 80% of their time focused, as I had been, on the second two categories, the report found that sales management could affect only the first – the sales activities,” Edinger notes. “The other two couldn’t be directly managed since they’re outcomes, not the process by which the outcomes are gained.”

He draws on advice from the authors of the new book “Cracking the Sales Management Code” to suggest four sales activities that companies should focus on to be more effective, depending on what they sell and where they might have organizational weaknesses.

Quality of interaction: Sales managers who need to drive improvements in the quality of the interactions between salespeople and prospects or clients should use data analysis to help them focus on metrics like call plans completed, coaching calls completed or number of calls that are reviewed.

Coaching in the area of call management is particularly valuable when the seller needs to make only a small number of calls to greatly affect the outcome of a given deal. In selling professional services, for example, the ability to create value in one or two interactions with a senior executive often makes or breaks the deal,” Edinger adds.

Opportunity management: Sales managers who need to boost the abilities of their sales staff to pursue and close multistage sales should use data analysis to help them focus on the number of opportunity plans completed or the percentage of early-stage opportunities qualified.

Edinger says this will allow managers, “to confirm you are really reaching the right customers, that these customers have the potential to generate a reasonable amount of business for the effort it will take to gain it, and that they are in fact willing to budget sufficient sums to purchase your offering. Identifying bad deals in this way and getting them out of the way early may be the simplest way to increase your odds of success.”

Account management: For increasing the long-term value of a single account, managers should work with their sales representatives to adjust account plans so they define overall strategies for the customers, Edinger notes.

I have a high-tech client that tracks the amount of time executives spend each month with a single account that generates $65 million a year,” he says. “Account management metrics are vital when a substantial portion of your organization’s revenue is concentrated in small number of key customers.”

Territory management: Sales managers who need help allocating sales reps’ times among various clients in their territories can use data analysis to identify metrics like the number of customers per rep and the number of sales calls made, Edinger suggests.

“Many sales leaders have been inadvertently micromanaging through revenue or profit numbers, which is counterproductive,” he concludes. “This is your chance to provide your sales team with a new context to succeed in. By closely managing the things you can control, you will give your organization the best chance for success.”

Another issue that many organizations struggle to pinpoint is how to attribute the value of a customer or what channel to attribute a sale to, notes a recent article from CMO Australia. The magazine points to the conclusions of Nicolas Chu, president of online booking site, about using data analysis to pin down customer lifetime value.

“The traditional metrics we use are based on short-term vision [30-day metrics], meaning you can’t see the customer who then comes back in six months to buy something,” Chu notes in the article. “We’re starting to model our investments to recognize if someone comes back through another channel six months later to purchase something. We also try to give some credit for new customers. You might be willing to spend more to acquire new customers in the first place, because you can increase your repeat rate long term.”

The firm has learned that customers who first purchase a lower margin product might have more value than originally thought.

“We realized people are trialing us with a product, but after a certain period of time and if the experience was good, they were coming back to our site and the length of stay was longer, so the value was higher,” Chu says.

“Without big data it’s extremely difficult – you can look at the purchase history and what they’ve spent with you, but it’s difficult to predict what their future value is. We now use this model to understand whether we should spend 15 minutes, 20 minutes or an hour to retain you because we know if you’re most likely to book with us in the future, or if at the end of the day you won’t be a loyal customer,” he adds.

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