With AI and machine learning underpinning accelerated and better decisions, I wonder how long before the impact becomes systemic throughout the sales profession and most specifically, sales managers.
A Point of View
Sales Gets a Machine-Learning Makeover is an interesting article from MIT’s Sloan Management Review that discusses areas where automation can enhance interactions and also deliver operational productivity gains with the following two examples from their survey:
- 38% of respondents credited machine learning for improvements in their key performance indicators for sales – such as new leads, up-sells, and sales cycle times – by a factor of 2 or more.
- Another 41% created improvements by a factor of 5 or more.
Each of the examples show enticing business benefits.
But how many selling organisations are at a level of proficiency that this is the next logical step? A step into massive and accelerated business process improvement? A step being demanded by your customers?
It is this last point that is the inhibitor and the opportunity.
If a selling organisation is a leader and all metrics are channelling in the right direction, it would be a brave executive that would tamper with a winning formula. As with all industries, there will be those that look a little over the horizon and build to compete in a changing landscape, if not change the landscape themselves.
The over the horizon competitor has a digital DNA, much more than a technology zealot. That competitor is unencumbered by legacy mindsets and infrastructure and lives to not only embrace, but constantly create change. Or “make a ruckus” as Seth Godin would say.
A simple illustration is to splinter off a sales person or team and equip them to run their own Facebook (FB) ads to see if they can personally attract an audience. The evidence from Gary Vaynerchuk amongst many others is that FB ads deliver an incredible ROI with tight targeting.
If this is appealing, you can then start to move your experience to include video as a next step in customer access and engagement.
You can be left with a decision – embrace the algorithm economy or not. Fortunately, the decision isn’t binary and there is a lot to be learnt from the online world where A/B testing and experimentation are the norm.
A traditional selling organisation can create their own learning with measurable experiments. Test new methods. Don’t fall for the aged jargon of Proof of Concept” (POC) but call your experiments just that.
Learn from the successful experiments as much as the failures and let every experiment advise your future strategy. The outcomes are not an end in themselves.