Sales management has always been a matter of analyzing data, analyzing human performance and deriving from those two activities a plan for market success.
Data Analytics in Sales
A recent article published by McKinsey and Company identifies four specific areas within the selling process where companies are finding moderate to considerable value in the utilization of data analytics. For sales managers, these include:
- lead generation
- pricing and discount management
- customer care
- selling opportunities
Each of these four activities are familiar, if not critical, to sales management. What has changed is the amount of available data, the currency of that data and the overall quality of data made available to the sales manager.
Let’s take a look at each of these four areas.
It used to be all about bingo cards in magazines, outbound telemarketing, cold calling and the analysis of high-level, vertical-market trends in relation to product features and benefits. Today, prospects screen out sales calls, mailrooms toss “junk” mail and buyers self-educate on pain mitigation, problem solving and product comparisons.
Smart companies understand this and facilitate the buyer’s knowledge quest with highly evolved websites that offer high-value content—content available in various formats and formatted to appeal to early, mid- and late-stage prospects. Marketing automation software tracks online behavior of visitors and accumulates historical records on those visits.
Sophisticated analytical software weighs assorted data elements collected including content accessed, length and frequency of the visit and then compares these elements with CRM-based demographic data related to the visitor’s company and their individual characteristics.
CPQ software, embedded into eCommerce products, allows the visitor to review specific product information based on certain inputs they provide related to their wants and needs.
For sales managers, what emerges is a complete picture of an opportunity based on high-confidence data. The buyers and tire kickers are automatically segregated, and the visitor’s online behavior drives the decision to watch, contact or follow up.
Leads are “real leads,” and opportunities are real as well. All contacts are at least warm, and a much higher level of receptiveness to contact and discussion can be expected.
Complex products almost certainly require complex pricing. Global-selling footprints for even small manufacturers place a heavy burden on sales management to ensure that pricing is correct in terms of special promotions, account status, price localization and taxing requirements.
For sales managers who deal with multiple sales channels, this can be an onerous management challenge. Back-office systems maintain critical data related to country, price, taxation and discounting parameters. However, the ability to capture those assorted factors and make them readily available to sales management requires more than monthly updates to a printed price list.
Configure price quote software has the ability to access and apply multiple pricelists based on customer location, demographics, GSA or national account status and many other controlling variables. CPQ can communicate with CRM and back-office systems to ensure that the proper price is quoted each time.
Discount management is handled the same way. CPQ can handle special promotional, volume and loyalty discounts just to name a few.
Sales managers don’t have to plow through reams of product and pricing memos to be assured that their reps are quoting the right price.
Sales Activity Data Powers Forecasting and Performance Evaluation
On a daily basis, sales managers are still asked about how much business they expect to close this month. Today, they have something besides their gut to call upon to find an answer to that question.
Documented online-visitor behavior provides an excellent source of data to power the predictive analysis of those visits. For example, this many touches correlates to this many return visits, or this many downloads correlates to this many product inquiries. The volume of data collected over time enables statistical inferences that eventually translate into closed business.
Sales managers are no longer required to maintain crystal balls or produce obligatory reports based on the vague promises of customers or sales reps.
For sales managers, one of the more difficult challenges has been the accurate appraisal of performance by individual sales reps. For most, this was simply a matter of looking at who sold last year and who didn’t.
Data provides a complete and accurate picture of what sales reps are doing and how they are doing it. Marketing automation, CRM and CPQ systems generate all manner of data that reflects the activities of sales reps and prospects.
Touches, contacts, phone calls, sales calls, visits, physical movements, quotes issued, proposals delivered and win/loss reports all provide actual records for sales managers of what their sales force is doing on a day-to-day basis.
A deeper analysis of this data enables managers to pick up on what phase of a selling transaction might be consistently more difficult for a given rep. The old rule, ask for the order, still applies. Sales managers need to be able to quickly identify these little problems to help the rep do a better job of selling.
Sales managers can help reps who demonstrate proposal problems or presentation issues. They can coach reps who are reluctant to talk price confidently or those who go in too early and push too hard. Mediocre reps can be elevated into good sales reps, and good reps can become stars with the proper counseling.
Customer Care and Matching Talent with Opportunity
Territory assignments used to be based on geographical factors, vertical industry classifications and sales rep seniority. Today, sales managers have a much more compelling set of criteria to drive the assignment of talent to opportunity.
The process of selling is changing. Customers are looking to Sales to help them in ways that previously were handled internally. The relationship has become the product.
Customers want more than features and benefits; indeed, features and benefits are almost instantly commoditized. Selling has grown beyond what the product can do into an assumption that the product works. They want sales reps who can provide insightful knowledge and advice to help them achieve success.
The consultative sale, the guided-selling process and customer-oriented selling all offer something beyond the traditional role of selling driven by the number of cold calls made, touches completed or quotes produced—but they do not go far enough.
Buyers want knowledge and insight, and sales managers are tasked with matching their human assets with those needs.
Data related to the individual sales rep’s history can quickly help sales managers identify who they have available with specific experiences and knowledge that most closely match the needs of a given prospect.
This is far more effective than leaving the success of a relationship to the chances of who happens to sit at what desk or who has been on staff for the longest time.
Sales management has not really changed, but the availability of data and the ability to use technology to help analyze that data has provided powerful tools to help the sales manager achieve their goals, the goals of the enterprise and most importantly, the success of their customers.