According to Accenture (see link to article at the end of this blog), the new world of B2B selling requires several imperatives to survive and thrive in this new world in which we live. The first of these imperatives is to “rediscover your customer.” The prevailing theme is that historical customer insights are irrelevant. What matters is now. But the challenge is how to go about the task of gaining real insights into what our customers want now.
This idea of disregarding historical customer insights is a scary one. Sales and marketing leaders and salespeople have been doing this for their entire careers. Now we’re told “throw it out.” Well, you might ask, “what do we do in lieu of historical insights? How do we get our arms wrapped around the now?”
As Accenture suggests, the leaders of tomorrow are modifying their organizations sales priorities using predictive analytics and AI engines to derive key customer insights critical to surviving and thriving today, and in the days ahead. But how? Which AI engines, and what data are being used? Therein lies the rub. We all want insights and are becoming increasingly reliant on data, but are there rich sources of data that we’re missing? Are the best, most useful insights closer than we think?
At VantagePoint we offer a resounding yes to that question. Yes, there are rich sources of data that lead to incredibly precise insights. The question is “what are they and how do we leverage them?” These rich data sources are the very people that make up your sales force. Your salespeople. They are the ones interacting with your customers. They are the ones experiencing the changes that take place over time. The hard truth is that there is gold to be mined in the heads of your salespeople. You just have to find a way to get at the information so that you can analyze it and use it to make better decisions.
As Accenture suggests, throw out the old rule book. Get to know your customers again. This is intuitively appealing, but how do we do this? How do we get a handle on the changes with our customers? What replaces the old rule book and how do we develop a new one? These questions are real. Important. Critical. But the path to the answers may look illusive; however, it is even more straight-forward than you think.
Accenture suggests that we need to equip our sellers with situational awareness, to equip our sellers to best respond to changing customer conditions. Again, sounds like sage advice, but how? How are customers behaving now that is different than how they behaved 12 months ago? Who knows this better than your salespeople? What organizations need is a mechanism to extract vital customer behavior details out of the minds of their sellers and use that information to develop recent, relevant insights to changing customer behavior.
The best, most accurate way to accomplish this is by examining deal level data. Real details related to real deals sellers are pursuing. So, do we just extract the information from our CRM? Well, to say that CRM data has questionable hygiene is an understatement. This is a problem that organizations have been struggling with since the introduction of CRM. Sellers are notorious for putting the minimum amount of deal level information into their CRM when they log their opportunities. It may be getting better over time, but it is still falling far short of adequate. With highly questionable CRM hygiene, where do organizations go to mine the data? To their sellers.
So, do we need to hire an expensive consulting company to interview our sales force? Is that the best path forward? No. It is not. That well-trodden path is very expensive and slow and relies heavily on anecdotal information. You need insights that are current. You can’t wait six months for a big consulting engagement to produce customer insights. By then, things will have changed again. What is the alternative?
What if you had a mechanism for gathering very detailed information about the deals your sellers are facing? What if you could get very granular about what buying attributes are changing and to what degree? What if you could analyze that information to form accurate pictures of the changing buying situations your sellers face? What if you could then have a reliable way to determine the best sales approach to lead to a win in each buying situation? Well, you can. And it is quicker, easier, and less expensive than you think.
The big question is “how do you glean customer information from your sellers in a way that is reliable, accurate, and timely? How do you separate opinion from fact? How do you turn seller experience into actionable customer insights? The first thing you must do is develop a reliable way to gather very detailed deal-level customer information. You need a way to pull information out of your seller’s heads that favors fact over opinion, allowing you access to details that can be used to produce insights.
What kind of information do you need and how do you get it? Our research has revealed that there are over 25 buying factors that influence buyer behavior. That’s a lot to consider. What organizations need is a way to narrow the field and identify what matters most. That is where AI and machine learning come into play. By gathering seller-provided forensic information of won and lost deals, machine learning can be used to spot patterns in buying factors and how those factors influence unique buying situations. Sellers have very detailed information in their heads about deals they’ve pursued. Getting that information out of their heads and into a database is the first start.
If you are interested in further reading about buying factors and buying situations, read “How to Build an Agile Sales Force…”
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