“Everyone is talking about it, but very few are doing it.” The phrase can be applied to all sorts of cultural, comedic, and business scenarios, yet the concept of marrying the highly technical nature of the “big data” frenzy to the Wild West environments of professional sales and marketing cultures seems relatively far-fetched. Or does it? Aberdeen’s Sales Effectiveness research practice has frequently covered sales forecasting with the perspective that more analytical approaches toward deal management are directly correlated with both better forecasting accuracy and stronger business results.
This post is guest authored by Peter Ostrow, VP & Research Group Director of Customer Management and Sales Effectiveness at AberdeenGroup.
In fact, Aberdeen research published in Sales Enablement: Fulfilling the Last Frontier of Marketing-Sales Alignment showcases how marketing and sales leaders can most effectively reduce sales cycle friction, specifically by collaborating around the content used to entice and close B2B customers. Offering survey respondents the opportunity to indicate whether big data solutions were in play on either side of the relationship, we find that deployments are relatively few in number – predictable, given the relative youth of the big data marketplace – but that Best-in-Class enterprises were much further along in supporting both marketing and sales activities with these technologies: reporting 27% adoption rates (and rising) among the strongest sales teams, versus low single-digits among under-performing organizations. Another way to slice the data is by comparing the sales effectiveness KPI’s of adopters against non-users, which tells a clear story of performance-enhancing data:
When we speak of the predictive analytics referenced in these data, the topic focuses on software solutions that help line-of-business leaders use historical data to better anticipate future customer acquisition and service results. From the marketing perspective, this is actually not radically new. Aberdeen’s Marketing Effectiveness and Strategy research practice has long covered marketing automation solutions and related technologies, which can superbly track the digital behavior of prospective buyers, and help sellers understand when a company or individual has become warm or hot enough to engage directly. Big data muscle furthers this awareness by providing faster, more accurate lead scoring abilities: how does the prospect’s online behavior, represented by data both structured (web site visits, downloads, webinar attendance) and unstructured (social media and other user-generated content), map to other companies who became customers, or even lost opportunities? Marketers can provide a more customized experience for potential buyers by refining campaign content and delivery in real-time, with big data-driven analytics that help take out the guesswork inherent in their line of work.
From the point of view of sales, big data tends to be focused on the sales forecast. Once a notorious magnet for derision and jokes, the anticipated sales activity published internally by Best-in-Class companies has become a data-driven, trusted picture of a firm’s short-term health, especially among those using predictive analytics to understand which deals are more likely to close, which are at risk, which ones it might be worth walking away from, and which ones are the most deserving of eleventh-hour discounting or executive fly-by’s.
Traditionally, B2B organizations have regularly pressured their front-line sellers to report, up the food chain, on all of their current and pending deals, particularly regarding the size and timing of each anticipated closed opportunity. Unfortunately, all too often, reps tell their superiors what they think the bosses want to hear. They also tend to overly rely on their gut instincts, "happy ears," and "sandbagging" when communicating such information. Influenced by pending commissions, spiffs, and President's Club vacations, reps and managers alike unfortunately let their emotions dictate the contents of the sales forecast. The problem with this scenario is that it involves too much Capt. Kirk, and too little Mr. Spock. A sales forecast based on gut feelings – "I've got a really good feeling about this deal, so I'm moving it to 90% likely to close" – is far more likely to yield an ineffective estimate of near-term sales results compared with a data-centric forecast that is devoid of emotion.
This blog series has been dedicated to the notion that sales enablement can be optimized by better data management: connecting, analyzing, and leveraging the enormous haystack of customer-centric information that allow B2B sellers and account managers to find just the right needle, create better conversations with their counterparts, and beat quota in a content-rich, untethered Workstyle that maps to the Best-in-Class results Aberdeen’s research promotes. I hope you’ve benefited from the lessons you’ve learned from your peers and contemporaries during this process.
Interested in learning more? Watch our On-Demand Webcast Aberdeen Group research reveals how best-in-class organizations enable Sales here.