Making Sales a Science: Sales Analytics

The story of Moneyball, General Manager Billy Bean’s use of analytics to create a continually competitive baseball team in Oakland on a shoestring budget, is famous in business circles as an analogy to explain the fascinating use of big data to drive results. But just what do you measure when it comes to improving your sales, and how exactly do you do it?

Today’s Sales Metrics

The age old business axiom is, If you can’t measure it, you can’t manage it! Never has this been more true than in sales. I defy you to find a company that isn’t tracking sales, and most of them are doing a bang up job of segmenting sales by geographic region, timespan, division, and salesperson, to name a few. Increasingly more firms are tracking other things along the path to a sale, such as number of outbound calls, appointments, presentations, and proposals. Great! These are valuable indicators, but there are a couple of key shortcomings that every CSO or VP of Sales in business should recognize:

• In most cases these are trailing indicators, meaning you’re looking back after the fact to provide a post mortem on what went right or wrong with last period’s sales, and
• Rarely are any of these metrics tied to prospect behavior, excepting again, if that prospect buys something and becomes a customer.

These weaknesses can lead to performance of sales teams that remain stagnant, and often leads to errant conclusions about what is succeeding and what is failing. When that happens, you get poorer sales performance from your salespeople, as in less revenue per salesperson. To make sales goals you play the numbers game and hire more salespeople, all at significant cost considering that there is a given percentage that won’t work out and will need to be cycled out of the organization.

Measurement Revolution

It’s too costly to just keep hiring new salespeople and hoping for them to make rain. Most cannot, regardless of how big their Rolodex or LinkedIn connections pool is.

There is great news, however. We’re living I the world of analytics and measurement. Erik Brynjolfsson, the Director for the Center of Digital Business at MIT, relates how most great revolutions in science have been preceded first by revolutions in measurement, and in the past few years technology has created such a measurement revolution in the world of business analytics. Customer Relationship Management (CRM) tools like Salesforce are not just contact managers any longer, they are repositories of big data that other applications can mine to determine relationships and trends and reveal insights about buying patterns, customer profitability, other customer behaviors.

Measuring Sales Effectiveness and Improving

So, as a business sales leader you have two challenges:

1. What to measure, and
2. How to use the data to improve.

When it comes to what to measure, the choices are abundant, depending upon how much data you have collected and how standardized and accurate it has been collected across the organization. For sales and other trailing indicators, those numbers are in the accounting system and are hopefully tied into a system that can extract and parse with the previously mentioned demographic filters. Separating out analytics by region, customer verticals or top performers in the company certainly can lead you to some insights for decision making. Depending upon your business, you just may be able to come up with success models to propagate across the firm.

For instance, what if you found out that the profitability of sales sold by Jerry Smith from Austin was 6% higher than anyone else in the company? What would you do with that information? It depends, of course. It could mean that Jerry is a superior negotiator who can train others, or perhaps he defines scope better than everyone else, eliminating early stage problems in the delivery cycle of the business. Doing more digging and responding accordingly could be worth big returns to your company.

Personalizing the Sales Process

What if you could extract data that was more than just aggregate trends, but got down to the individual customer level, allowing you to respond with a unique offering to each prospect, served up to her the way she wants it and in the timeframe needed? That’s what marketing automation programs do with online campaigns, landing pages and website traffic. They test what works based upon where people click on online pages, various offers and other content, and how well they convert to a desired action, such as opening a report or, a best case, buying something online.

In a complete online environment this has gotten relatively simple to do. In the give and take that occurs between salesperson and prospect over the phone or in face to face conversations, tracking becomes tougher. Emotion is involved in both the potential customer’s responses during a sales encounter and in the salesperson’s interpretation of them. In performance analytics, the old standard of GIGO (garbage in, garbage out) rings true.

Here are two bankable ways to help put some hard science to these soft encounters, promoting a reliable, standardized data set and individualized sales process for each prospect:

• Sales Lexicon – Create a list of possible customer responses in a given selling situation such as “requested more information” or “reference check needed.” This should be done collectively by the sales leaders in your company with different divisions represented. If your firm is small, that makes it easy since it may just be you. Set these terms up as standardized inputs in your CRM or tracking system so that reporting salespeople have to select one from a dropdown list and not just wing it with free form text in a comment field. This is the difference between a forced choice test like the SAT versus an essay exam. It minimizes interpretation and gives sales analytics something to work with.
• Force a measurable Customer Response – A salesperson just had a telephone conversation with a prospect. It seemed like it went well but he’s not so sure. Suppose he knew exactly the most optimal time to follow-up in the next stage of the sales process with every prospect? John Cousineau, President and Founder of Amacus, suggests that salespeople document the conversation with notes to confirm understanding, always a good practice in sales, and then upload them to the analytics online environment. The salesperson sends an email to the prospect linking the notes right after the meeting. Now you not only can track opening of the email, but exactly when the prospect read the notes, how long he spent, etc. The Amacus software notifies the salesperson in real time when that happens, and he can magically re-connect with the prospect within minutes of that encounter, striking when the iron of prospect interest is hot. Think that might shorten your company sales cycles (as opposed to just following up in 2 weeks with everyone)? According the Cousineau, one of the chief benefits is to avoid wasting the salesperson’s time diligently chasing down suspects who were nice during the conversation, but didn’t show the interest to review the notes and next steps.

The Sales Net Effect

Look, there is still a great deal of black art involved in the sales process, particularly for complex products and services. A salesperson’s contact list and her gift of gab are still important to be sure. Sales data analytics help to bring the sales process out of the dark ages and refine it, standardize it where necessary, and customize it to individual targets at the same time.

Is it easy? No, but neither is sales. The measurement tools are available to create a revolution in your company sales if you’re willing to make the investment in dollars and time and actually learn. The sales brass needs to be able to look into the mirror and see that the Emperor may have no clothes, and be willing to correct things in his or her sales process that may have been totally ineffective. Leveraging the power of increased margins, decreased sales cycles and performance improvement for all salespeople should provide the motivation to get in the game.