Sales Productivity Hampered By Poor Data, Lack Of Prioritization

Published: April 10, 2013

Are marketing-generated leads really full of dreck, or is sales just unable to close deals? It is an age-old battle of wills that is getting more heated as the pressure is on both sales and marketing to meet ever-rising revenue targets. Many organizations are looking to Big Data and predictive analytics to help identify hot sales prospects, but weaknesses in their databases are hampering sales productivity.

More than two thirds (68%) of companies report struggling with lead generation, blaming marketing for not providing enough quality leads, according to recent research sponsored by Lattice Engines, a data analytics platform provider, and conducted by CSO Insights, a sales and marketing effectiveness research firm,


{loadposition C2C13IAA}The survey of more than 1,200 corporate and sales executives also revealed that nearly half believe marketing-generated leads are lacking in quality and quantity. According to the survey respondents, 42% of sales reps feel they do not have the right information before making a call.

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To combat these drags on their productivity, some sales reps are going rogue, executing their own activities including lead generation with one-off email campaigns, building micro-sites and leading webinars, according to the study’s findings.

Observers noted that sales productivity is hampered primarily by three issues: The database contains bad or incomplete information, leads are not the right people or types of companies that the organization is targeting; and the leads are not prioritized.

70% Of Data Going Bad Annually

“There is no doubt there is a huge correlation between the quality of the leads being sent over to the sales team and the productivity of the sales staff,” said Jon Russo, Founder and CEO of B2B Fusion Group. “Some industry figures point to the fact that 70% of sales data goes bad every year. That’s a lot of wasted effort.”

Poor data quality has an impact on the productivity of the sales staff at Level 3, a B2B telecom provider, as the company moved from a wholesale provider to selling direct to mid-market firms. The firm is in the process of a large database project, including cleaning up its current records and bringing in new records to support its growth and expansion.

“As we began looking at the current database and how it would support our sales efforts going forward we uncovered some issues,” said Corey Livingston, Senior Director of Marketing Operations for Level 3, She added that bad or missing data were issues, along with duplication “With our history as a wholesaler, we needed to expand our database but wanted to make sure that we were paying proper attention to data hygiene as we brought in new records.”

If a salesperson spins their wheels calling bad phone numbers or having emails bounce back, they are not spending time closing deals, observers noted.

“You really don’t want highly compensated salespeople making calls to bad phone numbers,” said Michael Bird, President of NetProspex. “Say a sales person is making 50 to 75 outbound sales call a day and you have a 75% accuracy on the phone numbers in your database. All that does is take away from their active selling time. It also doesn’t build trust when they are making bad phone call after bad phone call.”

Pat O’Brien, VP of Field Operations for Leadspace, pointed out that even a small increase in sales productivity can have a huge impact on revenue. “If I have a company with salespeoeple selling $100 million a year, if I improve their productivity by 10% that is the same as improving revenue by 10%. Sales productivity has a direct impact on revenue. Every minute a sales person spends qualifying a lead means that they haven’t gotten one step closer to closing a deal.”

Another concern at Level 3 was that the sales team was going to start doing their own prospecting if they weren’t getting qualified leads, and “that’s not a good thing in general,” Livingston said. “Because the minute a sales person gets someone going from a prospect to a sale, their immediate attention goes to the sale, and prospecting going out the window.” Figures from the Lattice Engines/CSO survey back up Livingston’s concerns: Sales reps are spending 20% of their time doing their own research, diminishing the time spent selling.

Who Is Most Likely To Buy

In addition to ensuring that all of the basic data — name, title, phone, email, etc. — are in the records — sales productivity also slows down when leads are not prioritized. Nearly half (45%) of respondents to the Lattice Engines/CSO Insights survey reported that they need help figuring out which accounts to prioritize.

“Marketing needs to be sending sales the most qualified leads; people who are in an active buying window,” said Level 3’s Livingston.

Observers say that some of these issues can be addressed by making use of Big Data for predictive analytics.

ReachForce, a provider of data management systems for B2B marketers, recently acquired SetLogik, a vendor of cloud-based data and analytics technology, with an eye toward steering sales reps toward the hottest leads, among other functions.

The Connected Marketing Data Hub offers an integrated suite with continuous data quality management and predictive marketing capabilities, said ReachForce officials. Through its integration with a number of marketing and sales automation platforms, including Marketo, Eloqua and, it enables marketing professionals to more effectively collect, qualify, target, and convert leads throughout the buyer’s lifecycle.

“Better data makes for better decisions, including prioritizing sales prospets,” said Bob Riazzi, CEO and President of ReachForce, in an interview with Demand Gen Report. “High-quality data is the foundation for predictive marketing, which is where things are headed.”

Barry Trailer, Co-Founder ofCSO Insights, added: “Although progress has been made the past couple years to more closely align sales and marketing, there is still plenty of work to do. Big Data has the potential to begin closing this gap by providing sales and marketing with buying signals they may not even know exist.”

Big Data and predictive analytics are the next frontier for marketing, according to Shashi Upadhyay, CEO of Lattice Engines[GW1] . “Sales organizations have made it clear that they are not getting what they need to be successful in today’s environment. Businesses embracing Big Data are achieving higher levels of success by empowering marketing to deliver a previously unattainable level of insights to sales, focusing them on the opportunities with the greatest revenue potential.”

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