Tips to Avoid Drowning in Data

After establishing clear reasons for collecting the data, the next step is to ensure that you are only collecting data that will provide the necessary information (such as the reasons for churn), Nicholson says. Too often, companies collect data that won’t provide the knowledge for actionable intelligence.

This might not always be easy, because the type of data needed for actionable intelligence has changed, points out Lauren Bakewell, chief product officer for sales and marketing solutions at Dun & Bradstreet. Years ago, marketers and salespeople needed data to help them with customers at the top of the sales funnel, to entice people to respond positively to different sales offers. Today, buyers have conducted their own research on company websites, have read product reviews on social media, and might have even gone into physical stores to examine products and services. They’re much deeper into the sales funnel before they ever come in contact with sales and marketing personnel. Because of that, company employees need actionable intelligence to close sales more than to start the sales process.

Intent data is very valuable in that context. Knowing how and why a potential customer came to the company website, for example, could help marketing and sales teams close the sale by crafting and delivering the right message, at the right time, through the right channel, and in the right context.

TECHNOLOGY-DRIVEN

Though data collection is typically technology-driven, the actual conversion of raw information into actionable intelligence via analytics is a much more multifaceted, heavily nuanced process with many more moving parts.

Data analytics, Bergh says, “is not about the meal; it’s about the kitchen that created the meal.

“There is lots of talk in the data science and analytics world about what should be on a stellar plate of insight. But the real focus should be on the kitchens and the staff that innovate and create excellence with data,” he continues.

To take raw ingredients and turn them into “gourmet analytic insight” requires an intense focus on operations, error rates, and the ease of getting new ideas into the right hands, Bergh says.

That sounds simple enough, but current research suggests that the vast majority—some reports claim upwards of 85 percent—of all current data science projects will never make it into production or deliver desired business outcomes.

A big reason for that is the persistence of data silos at most organizations. The problem of confining data to specific departments or data collection systems is something that has plagued businesses for decades, but little has been done to change it over the years. Despite wide acceptance of the need to centralize all company data, actually doing so is still more of a future goal than a reality today.

Many silos continue to exist today because many of the legacy CRM systems that are still in use weren’t designed to work with many of the new data sources, such as social media commentary, intent indicators from speech applications, and several others, Bakewell argues.

Particularly problematic for many larger companies is the fact that as they acquire other companies, they often keep those entities’ CRM, enterprise resource planning, and other back-office systems in place. What they end up with is a collection of disparate systems that were never designed to communicate or share data with one another.

Even when companies do make moves to break down the silos, they face challenges with matching data across systems and centralizing it.

Then, too, it’s not just system silos that need to be eliminated. Even if the systems produce cohesive data that can be shared, too often marketing, sales, and customer service personnel disagree on what the results mean, according to Adam Honig, CEO of Spiro Technologies, a CRM system provider. “You need to have a foundational understanding of the results,” he strongly recommends.

KEEP IT CLEAN

Another huge challenge with turning data into actionable intelligence is ensuring the data itself is good. That means keeping it relevant and up to date.