Top salespeople used to be thought of as something of a breed apart. With their killer instinct for the close and sky-high commissions, their methods were a mystery and often regarded as something innate and intangible. Attempts were made to analyse their secret sauce, to model the behaviours which produced success, but for decades fundamental attribution errors were made as to the source of their outcomes.
Some of this enigmaticism stems from the way in which sales conversations have always taken place, face to face, and one to one. This makes them particularly difficult to analyse and dissect, and for the success factors to be learned or even taught: the very act of having an apprentice or junior shadowing a sales conversation implicitly changes the dynamic, the relationship between the salesperson and their customer. Frequently those brilliant at closing sales are not best at explaining how and why they do the job so well – perhaps being genuinely at a loss to articulate the critical factors, or finding subconscious avoidance of overthinking something which is working just fine as it is.
Fortunately today, many of the top sales interactions are now taking place online. Still one to one, face to face – but thanks to today’s unified communications technology, they’re digitised in real-time, in top quality recordings.
This obviously has benefits for contractual reasons, but a further huge plus is the ability to listen back and learn from what is working. Like many aspects of human behavioural psychology from teamwork to management, top sales behaviours can now be analysed and codified and general rules and principles drawn from observed actions, so they can be reapplied elsewhere.
Even more excitingly, smart applications are now being developed with precisely this kind of analysis in mind, embedding machine learning directly in the tool itself.
If 100 sales execs each make 20 customer calls to sell the same piece of complex B2B SaaS, the artificial intelligence built into the smart platform can analyse each conversation against its outcome, break it down into its different elements and components, and draw conclusions from common patterns of behaviour on both sides. For example, if there’s a particular objection that customers frequently raise, and it turns out that 60% of customers who raise this objection fail to go on to complete a sale… Analysis of the other 40% of calls, those who raised the question but had it satisfactorily resolved, can prove incredibly useful. Which form of words did the salesperson use, in what context, at what phase of the process? Which supplementary questions arose?
In the past, an individual representative may have reflected on and tried to learn from their own 20 previous calls, whether positive or negative, but the application can learn from all of the calls, and just get smarter each time. It won’t dwell anxiously on its commissions, obsess about its mistakes, or blame the quality of the leads it received – it will simply analyse the data, then offer actionable insight as a result.
Such insights will identify what happened, where things are going wrong – is there a product feature which must be sorted, or simply better explained, to improve conversions?
And sales teams – and their leaders – will be able to use these insights to change their behaviours, test assumptions, evolve new scripts… and ultimately, make more sales.
You can see the latest sales analytics tools in action at the UC Summit, and explore the potential benefits for your conversion rate. So sign up now, for unprecedented insight into sales success.