It is not the strongest nor the most intelligent company that survives, but the one most adaptable to change![i]
No doubt there is sensational change coming in a tsunami-like fashion to sales and marketing departments in both B2B and B2C companies. These marketing and sales environments are especially under pressure because as technology gallops ahead, the companies that adapt to change will survive, while those that lag behind in adopting new ways of selling and marketing are slated for the trash heaps of failed businesses. And the driver of this change is Business Intelligence (BI).
Why it’s important
“The companies that lag behind in adopting new ways of selling and marketing are slated for the trash heaps of failed businesses.”
Yes, fears of change have been expressed before, but none are as urgently as those occurring in today’s marketplaces. The
Business Intelligence, the Driver
BI is another name for Artificial Intelligence (AI), which is an older term; some believe they’re interchangeable. Machine Learning (ML), some contend, is a subset of BI (but not really).[ii] Confused yet? Press on and it will become a little clearer.
Machine Learning is not just business intelligence, but the ability for a system to take BI knowledge (data), learn from it and take action. We experience this already, most typically for instance, in customer service. From machine learning we already have the development of new intelligent apps in sales, marketing, service, finance and manufacturing. Read Gartner’s Top 10 Strategic Technology Trends for 2017 for some insight into what is occurring at breakneck speed.
The beneficiaries of business intelligence are database platforms, which interpret the signals of BI and ML and guide us to an action in marketing and sales, or to a process that helps us sell more than our competitors. Warning: for those who hesitate on the threshold of sales and marketing change driven by ML apps, there will only be short- lived pity, because those who adapt will be too far ahead to remember those who failed.
Why it matters
“Warning: for those who hesitate on the threshold of sales and marketing change driven by Machine Learning apps, there will only be short-lived pity, because those who adapt will be too far ahead to remember those who failed.”
In marketing and sales we see these changes already in demand generation, prospect qualification, and personal productivity applications for salespeople (and almost everyone else), and in the data platforms that are necessary interpreters. The emergence of predictive marketing agencies, departments and software is a result of ML applications.
The database platforms reading the results of wide-ranging BI information from department silos are growing exponentially because an interpretation of the data is required. Too much information is meaningless without a summation of results. Presenting the information is the first step in ML for information that leads to action on its own, with a minimum of human intervention. All of this begs the question: is there now, or will there be a replacement of salespeople in the near future? The answer is yes.
The Sales Lead Management’s parent company, Funnel Media Group, and its internet radio program hosts interview executives who walk the talk about BI and ML, but this is only the tiny beginning of what lies ahead for sales and marketing executives and their companies.
My advice? Every sales and marketing executive has to search out BI/ML apps and become an expert in what is new and possible to give his or her company a competitive advantage. Sales managers, don’t assume this doesn’t include you. While human intervention and face-to-face, voice-to-voice interaction is needed, it may not be needed in all instances. Plus, BI and ML already offer apps that help salespeople become better informed, faster, and more responsive to their prospects than their competitors. Your choice is clear, adapt or fail.
Radio program/podcast replays about BI and ML applications:
- How Predictive Lead Gen Solves the Mystery of Revenue Shortfalls by Finding Qualified Prospects Sean Zinsmeister, Infer
- How to Find Qualified Prospects to Drive the Forecast Sean Burke, Kitedesk
- How a Personal Sales Assistant App Increases Sales Using Humor Adam Honig, Spiro
- Are BI Apps Confusing or Improving CRM and Sales Revenue? John Golden, SalesPipeliner
- Why Sales Managers Need Instant Business Analytics Mike Saliter, Qlik
- What is the Difference Between Artificial Intelligence and Machine Learning?
- Artificial Intelligence vs. Machine Learning: What's the Difference?