The days of going through a phone book cold calling every name in there to flog them toner are over. In its place, we now have a system that relies on predictive analytics and machine learning. This is good for the general public, who are no longer bombarded by unwanted calls, it’s good for companies, who can make better use of their resources by targeting actual leads, and it’s good for sales staff, who don’t get quite so much abuse. However, is predictive analytics everything it’s cracked up to be, or do sales teams need to be wary before leaping head first into the technology? Many of today’s sales teams are at the base of a steep learning curve around its adoption, and they will need to work fast to avoid falling behind.
Salesforce’s recent State of Marketing report found that 79% of high-performing teams currently use predictive analytics. It used to be that only the largest companies, like IBM and Amazon, had the data and expertise required to use it, but the technology is now available at a price where it is more affordable to companies of all sizes, and insights can be garnered by business staff without the same degree of expert knowledge.
Predictive analytics in sales looks at past behavior of customers and leads in order to discover patterns that suggest whether they can be considered prospects. It is not the same as marketing analytics, which looks at creating demand as opposed to creating revenue - two things that often get confused. For example, if a business has always sold furniture, predictive analytics can look back at when the last purchase was made and the average life expectancy to see if they will be looking for something new, alongside past customer interactions to determine what style of product they will most likely be enticed by. They could even look at whether someone has recently changed address as an indicator that they may be looking for something new. By doing so, salespeople are no longer wasting time on the phone to dead-end leads and can focus only on the most viable leads. The additional ease for reps to prioritize the right prospects and plan their outreach also means they are likely to follow-up more consistently, leading to better sales.
Another way that predictive analytics can help sales teams is in establishing how best to approach each prospect. When sending sales emails, they can judge which subject line will be most impactful on open rates, which format will elicit the most engagement - all the way down to the choice of wording. Sales teams presenting their product or service to buyers can use predictive analytics to get an idea of which combination of slides, length of the presentation, and tone of voice will lead to the most conversions. Predictive analytics is essentially just giving you an idea of what techniques are most likely to work, helping even the most experienced salesman hone their abilities by using empirical evidence rather than intuition.
However, there are also limitations. Predictive analytics tools are, in the main, only capable of going on information that has been seen before, which restricts it in terms of looking for new markets. In a recent article in Forbes by Donal Daly, founder and CEO of sales solution Altify, he argued that predictive analytics will ‘be correct some of the time, but some of the time they will be wrong.’ It could be from a competitor, or you could be targeting an existing customer, perhaps with a better deal than the one they currently have. This is true, but it’s equally true of any other available system. You need salespeople to work with the tools and to understand the data they have. They need to understand the context around the data - how current it is, anything that could mean that it is wrong. Knowing how to use predictive analytics effectively requires a different set of skills than the kind salespeople may be used to, leaders don’t necessarily need to nurture a Glengarry Glenn Ross type atmosphere anymore. In the future, it is likely that the Alec Baldwin’s of this world are driving Hyundais to work, and the data-driven salesperson is driving the $80,000 BMW.