Don’t look now, but the end of 2016 is nearly upon us. So, too, are the articles and blogs summarizing the best and worst of 2016 and making predictions of what’s to come next.
I overheard one such prediction at the SiriusDecisions Technology Exchange earlier this month in Austin, Texas. In a room full of B2B marketing and sales technology practitioners, more than 75 percent said that predictive analytics will have the biggest impact on their team in the future. Pressing on the topic, a future poll discovered that 55 percent of attendees are not currently using predictive in their organizations, while 16 percent used predictive analytics in marketing, only 2 percent in sales, and 27 percent of attendees are using predictive analytics in both marketing and sales.
This room validated what research firms like SiriusDecisions, Gartner, and others have been telling us – we’re at the precipice of major disruption as companies turn to predictive analytics and artificial intelligence for new ways to create value exchange opportunities. In the most recent market guide, “SaaS-Based Predictive Analytics Applications for B2B Sales and Marketing," Gartner forecasted* the predictive analytics space to experience “rapid growth within the next two years” due to the compelling ROI that these solutions deliver. But, to date, the truth is most adoption is around predictive lead scoring.
“The range of predictive analytics offerings and capabilities will continue to evolve as AI begins to impact sales,” said Steve Silver, senior research director at Sirius Decisions.
As this disruption continues to take place, companies are going to turn to predictive analytics, machine learning and artificial intelligence in other, perhaps even all, parts of their business. For instance, Zilliant MarginMax and SalesMax introduce artificial intelligence (AI) algorithms that think and act like a pricing and sales expert. For companies that derive most of their revenue and profit from repeat purchases from existing customers, Zilliant AI helps them to better manage, optimize, and grow these existing customer relationships.
So what should you do to embrace the disruption instead of being disrupted?
SiriusDecisions presented one model to consider that starts with an evaluation of your demand waterfall. It starts by identifying the problem that needs to be solved:
- Too few leads and the need to source more
- Too many leads and the need to better prioritize the good ones
- Leads that aren’t converting and the need to better engage them
By identifying the problem, you can then map the appropriate predictive applications to address the problem.
This is a good approach, but I’ll also submit and encourage an alternative approach – one that considers a different paradigm that doesn’t begin with marketing leads. Instead, consider looking at it from a customer-centric view.
Outside of your employees, your customers are your most valuable asset as a company; in fact, some may argue I have those reversed. Yet, many companies first look to predictive analytics to help serve new prospects instead of customers they already have. At the same time, global sales organizations are restructuring to better address the needs of top customers, and marketing teams are adopting more customized and targeted, account-based marketing strategies. What are these companies to do about all of the other hundreds if not thousands of customers that do not make the “top” tier list?
With an AI strategy centered around customers first, organizations can know every customer like their best. They can turn their CRM into a growth engine that delivers actionable, revenue-based insights to their sales and service teams. And they can provide a tailored, scalable, and highly-informed experience to each one of their valued customers.
I completely agree with the prediction of the room. I’ll go further and predict that the companies that win figure out how to first optimize the value of every customer relationship.
Contact Zilliant to learn how hundreds of companies use Zilliant to deploy a customer-first AI strategy.
*“SaaS-Based Predictive Analytics Applications for B2B Sales and Marketing," Gartner, September 7, 2016