Over the course of the past few decades, the organization and structure of B2B sales teams has settled into a nice, predictable pattern. The best, most tenured reps are out in the field, making the daily donut drop with the very best customers, building relationships and taking orders. An inside sales team mans the phone banks, taking and processing incoming orders for everyone else. Perhaps in branch-based businesses like auto and trucks parts or electrical products distribution, this includes counter reps consulting with local walk-in business, taking and fulfilling orders. Over time, an eCommerce channel is included to enable self-service for customers online.
Of course, the impacts of the COVID-19 pandemic have heavily disrupted this sales channel mix nirvana. eCommerce is now an essential channel with companies racing to make it easier for customers to buy from them online, inside sales teams quickly adjusted to performing their jobs from home, and shops stayed open if deemed essential. The field sales reps did their best to quickly adjust their normal jobs on the fly to be available to their customers without being able to call on them in person.
According to McKinsey, “almost 90 percent of sales have moved to a videoconferencing/phone/web sales model, and while some skepticism remains, more than half believe this is equally or more effective than sales models used before COVID-19.”
The future of the sales landscape has shifted quickly under the burden of COVID-19 disruption, but savvy company leaders are adjusting in-step, utilizing predictive sales analytics to blend inside and outside sales and better serve each customer.
Untapped Opportunity in the Long Tail of Customer Accounts
Typically, within a B2B company, 20 percent of the customer base is in the “strategic account” category, and for good reason. It’s not uncommon for 80 percent of revenue to be derived from this top tier of accounts. Rightfully, the most knowledgeable sales reps are appointed with maintaining and growing those relationships.
Over time, through product line proliferation or mergers and acquisitions, companies have grown to a complex scale that simultaneously asks sales reps to cover more accounts while accepting that, by doing so, a significant amount of customers aren’t receiving the dedicated attention needed to maintain and grow wallet share. However, in the face of COVID-19 disruption, it begs the question: How much revenue are you missing in the long tail?
Findings from our global benchmark report indicate that the total available opportunity of empowering sales reps to retain and grow the accounts within your existing customer base is significant. In terms of customer churn, measured at the product category level accounting for both decreased purchase volume and outright defection, most companies fail to capture between 4.5% and 16.1% of available revenue. In terms of cross-sell to actively grow wallet share, companies miss 3.2% to 14.8% of available revenue annually for product categories they sell — and their existing customers need — that are not bought at expected levels.
The Future of B2B Sales: A Blending of Inside and Outside Sales
As noted by McKinsey, outside or field sales reps are operating more like their inside sales counterparts. The time saved travelling and visiting their top accounts presents a new, reimagined opportunity for this highly-skilled sales team: Turn their white-glove sales style toward the long tail of customer accounts and empower them to treat every customer like a strategic account.
This long tail of customer accounts, sometimes referred to as house accounts in distribution, are typically served when visiting a branch or calling in when they need something. Utilize the newly available bandwidth of outside sales teams by giving them growth and recovery actions to take with these customers. Predictive sales analytics can quickly deploy these insights at scale, accounting for all customers and product categories.
Predictive sales analytics generates growth actions with advanced data science to create ideal purchase pattern profiles based on your best customers, considering spending patterns, total spend, and breadth of products purchased. Utilizing clustering and affinity-based algorithms, it matches each customer to the closest purchase pattern profile to guide reps directly to the items customers are not currently purchasing, but should be.
It also uncovers recovery actions by identifying “at-risk” customers that are showing early signs of defection on one or more product categories using advanced, patented algorithms to serve up specific areas where revenue is declining or has been completely lost. Contrasted with traditional business intelligence reporting, this approach eliminates noise by accounting for buy-cycle patterns, seasonality, one-time purchases, or volatile buying behavior, to exclude false positives from the recovery insights.
Predictive sales analytics is already widely in use in B2B companies with high order velocity and replenishment, such as foodservice distribution. If you have predictive sales analytics in place today, prioritizing these insights across the long tail of accounts for outside sales reps is easy to do. If you don’t yet have predictive sales analytics in place, getting started is straightforward and can be live in your business within a minimum of four weeks.
The future of sales will be a blend of inside and outside sales due to COVID-19 disruption in the traditional sales team structure. Reimagining how to utilize your highly skilled outside sales team to serve the long tail of customer accounts can have significant revenue potential. Predictive sales analytics can help pivot these teams to the most significant recovery and growth actions to simultaneously capitalize on their increased bandwidth while increasing organic growth across your business.