The year is 2008. A man steps out of out of London Bridge Station, and the December rain pours down in sheets. He checks his watch – he only has twenty minutes to get to his meeting, and delays on the Underground rule out any chance of getting there by public transport. But he sees a light in the darkness – a black cab with its orange sign blazing out through the haze. His heart lifts, and he raises his arm to hail it. He’s going to make it on time.

His faith was well placed. London cabbies spend years studying the “Knowledge of London”, a process that imparts an unparalleled understanding of London’s streets, and involves about two years driving around London on a moped. Mention any street in central London, and the driver will know exactly how to get you there in the shortest time based on traffic, roadworks and the time of day. This training is so extreme, it produces noticeable differences in the brains of black cab drivers, resulting in a distinctly larger hippocampus – the part of the brain dealing with space. Without a doubt, the black cab driver doesn’t just work a job, but practices a craft. However, only a few months after our scene in London Bridge, something would happen that would change the place of the black cab in London forever. One New Year’s Eve, Garrett Camp, a Canadian programmer, spent $800 on a private driver.

This led to him wondering how splitting the cost with other Silicon Valley friends could have saved him money. “UberCab” was founded in 2009, and the rest is history. By combining several recent technological developments, Uber created a situation where a taxi driver didn’t need to know the city they were in – they simply needed to be able to drive. The app includes a map of where they are now, what route to take to their destination, even where to find their next fare. Most of the necessary knowledge to get a customer to their location is handled by technology. The impact of Uber on the taxi ecosystems of cities the world over has become the textbook example of disruption by technology.

The fact that anyone with a car can now work as a taxi driver has resulted in a sharp drop in average cost of a journey, as more and more drivers join Uber and its competitors. Black cab drivers have a complex and implicit understanding of the city in a way that technology is unlikely to ever be able to replicate. However, if technology can provide a route that is 75% as efficient, and this results in the customer being able to pay 50% less for the same journey? The popularity of Uber and other “ride sharing” apps shows this is a trade-off many customers are happy to make. It is also worth noting that traditional taxi drivers often pay large amounts to local authorities for their licence to operate – something a nominally “private” individual doesn’t have to do. So, what does this have to do with salespeople? For starters, sales is another craft. Certain innate qualities tend to be associated with salespeople – they are outgoing, confident and energetic. But this is only part of the story. More experienced salespeople often trust their “gut feelings” when courting potential customers. These instincts are honed from repeated experience of similar sales situations. Particular wording or timing of an email from a prospect may lead to a salesperson deciding that they need to take an entirely different tack, or give them a sense of who their competitor is.

These instincts are what distinguishes successful from unsuccessful salespeople. This is not knowledge that can be taught in the classroom – instead, it is gained from years of immersion in the task – not dissimilarly to the cabby’s “Knowledge”. Recent developments from the major players in the Customer Relationship Management (CRM) software space (such as Microsoft Dynamics and Salesforce) have focussed on supporting salespeople with Analytics and AI/Machine Learning. For example, Microsoft has recently released “Relationship Analytics” functionality, which analyses volumes of communication with customers to measure “relationship health”, allowing salespeople to see trends in how effectively they are maintaining relationships. Similarly, this spring Microsoft released Lead and Opportunity scoring, designed to use historical data to estimate which opportunities are most deserving of our time and attention, all of which works out of the box. This is only be the beginning of this type of development, and we can expect to see more and more AI designed specifically for supporting salespeople. What effect is this type of innovation going to have on the craft of selling? Does this have the potential to have an “Uber effect”, changing not just how, but also who does the job? Without a doubt, this will be especially useful for less experienced salespeople – those who have the talent but haven’t yet had the experience to navigate sales unsupported. As AI Sales functionality becomes more widespread, businesses may find that junior salespeople can generate more revenue than before. This could mean that hiring practices will begin to lean towards more junior salespeople with their lower hiring costs, and lower expected commissions compared to senior salespeople. Based on this, we might expect to see some disruption to the traditional craft of sales.

However, there are several other things we need to bear in mind. For one thing, AI has the potential to further increase the performance of experienced salespeople, not just novices. While some AI functionality will serve to replicate the pattern recognition of veteran personnel, much of it will give insights that weren’t previously easy to obtain – for example, by alerting users that a customer has opened an email, or actively notifying the user about what is going on in a customer service case. Furthermore, AI has the potential to free them up from non-value adding activities, enabling them to spend more time face to face with prospects and customers. Secondly, Sales as a craft is much more than knowing where you are going and how to get there – unlike driving a taxi, the social aspect is a core part of success, rather than a nice way to pass a taxi ride. The experience that a “craft” salesperson has in connecting with customers, engaging them, and selling the message of your company and product is not something AI is anywhere near being able to replicate.

Finally, it is worth noting that even in competition with Uber, traditional taxi models such as the black cab still exist. While some customers are happy to take a slightly lower quality taxi for a lower price, others aren’t happy to make this trade. We can expect to see the same in sales. For businesses that have a long sales cycle, high product price and low product sale volume, the relationship with their customers will likely be too precious to fully entrust to inexperienced salespeople. So, it would be an exaggeration to say that technological development is going to completely end the era of “craft” salespeople. However, it is no exaggeration to say that innovations are going to change how we sell – and may, instead of bringing about a gap between novice and veteran salespeople, divide those organisations that give their salespeople the latest tools from those that don’t.

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