Don't Let Data Be the Achilles Heel in Sales

Customer Strategy
All too often sales teams rely on outdated, unreliable, incomplete information. This makes for poor decision making,

All too often sales teams rely on outdated, unreliable, incomplete information. This makes for poor decision making, Gartner Research Vice President Tiffani Bova said during her presentation at Gartner Customer 360 this morning. Sales organizations need to improve data quality, validity, and quantity to improve their performance. Having the information and acting on it also means being consistent with how and why you use it, she said.Sales teams that leverage data can create a competitive advantage across the customer lifecycle, Bova asserted. This includes improvements across presales and marketing, pricing, sales interactions, implementation, customer support, and up/cross-sell, and renewal. Data can help understand and help improve everything from customer segmentation to price sensitivity, share of wallet, propensity to buy, service frequency, likelihood to repurchase or buy more.

"If you get 80 to 85 percent of sales from your existing customers, how do you do that more effectively?" Bova asked. Use data to drive costs out of service without decreasing service quality. Data can also help understand how to acquire more customers, grow profit per sale or account, grow new markets (industry, geography, demographic, etc.), and stop losing customers. "If you're trying to grow and do any of these things, data is the core of your decision making," Bova said.

Additionally, data can help companies determine whether they have the right partners in their ecosystem to provide the growth they're looking for. "Are those partners giving you the information you need?" Bova asked. Often partners feel they "own" the customer and fear disintermediation, so are hesitant to share data, she said.

When it comes to partner relationships, better data is the starting point for...

Recruiting new partners - determine how many partners, where should they be located, and what skills they should have
Communicating - open up two-way communication, and determine what messaging will resonate most with particular partners at specific times
Partnering better - use analytics to manage the partnership and business more effectively
Collaboration - create partner-to-partner collaboration based on complementary offerings, verticals, geographies, and the like

Unfortunately, Bova said, often there isn't enough data for sales leaders to make the right decisions. The data is often inconsistent and there may be limited visibility into the sales pipeline from certain channels. As a result, often the wrong partners are meeting with customers, sometimes lacking the appropriate skills at a time when customers are demanding more. It's essential that partners have a greater understanding of customers' needs and expectations.

The data-driven sales organization can better understand who they're selling to; what partners are doing in terms of driving new business, creating demand, expanding market adoption, and the like; communicate and share POS data, harness dashboards and POS data to track activity and results; and analyze performance across sales team, partners, and customer groups, as well as better understand metrics like retention and customer satisfaction.

This takes time. It starts by creating a cross-functional team that owns the design and implementation of sales and partner data efforts. Additionally, organizations should communicate the value of using data to improve the sales process, as well as leverage analytical expertise in the organization to make those improvements. Begin data-focused sales projects in a phased manner to show successes and keep it manageable. Finally, take the lead in creating a holistic view of the customer across operational, analytical, and marketing data sources. This includes understanding what data you have and what you need.

Sales organizations can drive significant growth and retention, Bova said; making that happen starts with having, understanding, and using high-quality customer data.