Sales Data Analytics: Momentum Keeps Building

Lead optimization and customer lifetime value calculations are the new frontiers.

Sick of those emails and telephone calls from sales people "following up" on a vendor-provided white paper you downloaded out of curiosity and not due to an immediate need? Those calls and emails are a huge waste of your time, and theirs, and everyone knows it.

Fortunately, the growing need for – and popularity of – lead optimization and customer lifetime value analytics may provide some relief for the unproductive calls as well as the put upon victims of these efforts.

A lot has changed in the two years since I last reviewed survey data on the use and effectiveness of sales force automation. New surveys done last fall and some recent discussions with experts and marketing and sales officials indicate that a combination of these new tools and new attitudes can dramatically improve the productivity and success of sales people. And they certainly need the help.

Surveys by IDC found that only half of sales people say they have good access to external information about clients and prospects. In addition, less than half are using social media to identify and qualify sales prospects.

External information and social media data are crucial to lead optimization. Rather than just contact everyone who downloaded a document, lead scoring analyzes a variety of actions to identify the "best" leads. For example, an individual who registered and attended a webinar is scored three or four times higher than someone who merely downloaded a document. Combine that webinar attendance with prior contact information from internal CRM systems and then overlaying public information – company skill searches and new product or marketing initiatives and even social media activity – can yield a more realistic and lucrative buyer profile.

The obvious challenge for the sales operations departments, and the IT opportunity, is in figuring out a way of integrating those various internal and external data sources into an analytics engine that can deliver the right information to the right person at the right time.

And that's why integration is the number one sales technology investment line item for companies, according to a mid 2012 survey of more than 300 executives from large and medium-sized companies. Notice that sales analytics is also a top priority:

sales data analytics

Integrating enough internal and external data into a useful lead scoring application is a non-trivial task and the ROI will not appear quickly.

"Due to the long sales cycle for ERP, BI and CRM projects it may take a few years for marketers of these solutions to see hard dollar returns on their marketing automation investments," Gerry Murray, the research manager for IDC's CMO advisory service stated. However, as he noted at the IDC Directions 13 event this month, "a modest investment in analytics can show dramatic improvements in processes such as lead scoring by overlaying external sources of customer intelligence with data from sales and marketing systems."

While lead scoring can provide an immediate and substantial impact on sales productivity and success rates, a longer term strategy to develop a complete customer lifetime value (CLV) analytics tool is considered the ultimate goal by many leading edge sales executives. Relatively few companies have reached this level of maturity, Murray notes. But recent discussions at the IDC event indicate that many large companies know they need to get to this point and realize that it is a multiyear process.

Understanding the value of a customer is not just knowing how much money was spent and overall profitability of that customer, but many other metrics as well. How much customer service and support is required? How much product customization? How much sales and pre-sales effort is involved? How fast do they pay their bills?

Gathering all of that data requires major silo busting – the CLV analytics need to access multiple modules from finance, customer service, sales force automation and production systems. A 2012 IDC survey found that most marketers from large high tech companies rated as ineffective their ability to use CLV data to drive marketing decisions. Indeed, this survey found that few marketing organizations were effectively using sales qualification, forecasting and proposal data.

Integrating the various internal and external data and applications and delivering the lead scoring and CLV analytics is a classic example of how the business side and the IT department need to partner. While sales technology has not received the same level of support as finance or production in the past, providing valuable tools to the front line revenue generators is a higher priority these days. And now that the sophistication of the tools is far better than in the past, along with the sophistication of the users and their executives, the time is right.




Tags: business intelligence, Data Analysis, lead generation


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