4 Ways AI Will Revolutionise Sales Operations

At the heart of every high-growth B2B company is a sales operations team. (or maybe person !). To use a race car analogy, think of sales reps as the drivers and sales ops as the guys in the pit lanes. Both are mutually dependent.

Sales ops covers many functions from hiring, to sales enablement, to strategy and much more. As a cost centre, sales ops needs to be a well-oiled machine if it’s to drive-down costs, improve sales productivity and allow a business to stay ahead of the competition. This is all very important in today’s world. Sales ops allow a business to deliver a better customer experience. They enable reps to turn orders around without delay and sales execs to become trusted advisors, well-versed in products, while providing extremely valuable customer intelligence to help generate future applications.

The reality is, as organisations grow, the pressure mounts on the sales ops team. They inevitably have to do more with less. The good news is, advances in artificial intelligence will make drastic differences to the productivity of sales ops teams in the not-too-distant future. I’m not talking about an extra head on an 8-man team. Over time, AI fuelled technology could replace 7 out of 8 sales ops professionals. Here are 4 examples of how AI will deliver unparalleled advances to sales operations.

Semantic Territories

Territory formation and allocation is one of the most delicate functions of the sales operations team. Sales executives and managers are never happy with their territory. Territories always appear to be cut unfairly. Failing that, there are always technical problems. Companies are routinely misallocated to the wrong territory. For example, healthcare businesses end up assigned to the financial service teams, enterprise accounts are allocated to the mid-market team, subsidiaries are assigned to the wrong parent… and the list goes on! Picture a future where a territory understands the companies it’s meant to contain. The territory is smart enough to differentiate between the companies that should and should not belong to a patch. At the heart of these smarter territories is the semantic web. The semantic web is comprised of a set of languages that give meaning to data. The territories and the data in them are converted to ontologies, using languages such as RDF, OWL and SWRL. In doing so, the territory can better understand if businesses belong to it or not. It will allow AI-powered applications to pull data from multiple sources to better illustrate the provenance of an organisation. This will allow inferences to be drawn, e.g., is Smart Tech a subsidiary of Smart Group? It will also remove vagueness, e.g., is Financial Software Inc a tech company or a financial services company? The net result will be sales teams executing better, happier customers aligned with the right teams and more consistent revenues for organisations.

Predictive Forecasting

Getting forecasting right is incredibly important for businesses, particularly public companies whose stock price hinges on the accuracy of forecasts at each earnings call. It’s not uncommon to hear stories about company ABC whose stock price declined after missing sales estimates. The problem starts with frontline sales teams. We all know sales managers who routinely sandbag deals, under-commit and then overdeliver or routinely miss their calls altogether. This is a nightmare for sales leaders judged on their ability to forecast accurately by their over-expectant CEOs. The good news is, we are very close to sales applications being able to decipher between the bluffers and the straight-shooters. Say goodbye to hail Mary forecasts and hello to AI-powered predictive forecasting. With the power of machine learning and predictive analytics applications, we will be able to combine inputs from sales reps, managers, deal activity, past performance, customer behaviour and data about the target businesses to arrive at a far more accurate forecast than humans can produce. This will be particularly important for businesses selling to the mid or SMB market where there are often hundreds if not thousands of deals in each forecast.

Sentient Hiring

Hiring is notoriously difficult for fast-growing sales operations. Each hire can potentially add millions if not tens of millions to the top line. A few bad hires can cause a business to go under. Determining “fitness for a role” is nearly impossible to do in a few interviews. Companies invariably must take calculated risks with any new hire. This seems crazy though…. We live in an era where data is the new oil. Each hire, in that case, is rich in oil with most people having multiple social media accounts, websites, blogs and so on. By scanning the internet, including photos of frat parties in Cancun, to stag parties in Berlin, AI-driven applications will be able to determine if a candidate is the right fit for your business or not before you even read a C.V. As scary as it may be seem, computer vision can determine your intelligence just by looking at a photograph. The humble paper C.V., or even a PDF C.V.. is disappearing into the rear-view mirror. The future will be completely digital. AI-driven hiring will be at the forefront of finding star talent.

Self-healing Data

Data is the life blood of any sales organisation. For businesses to improve adoption of sales productivity tools such as CRMs, businesses need to ensure data is curated and maintained to ensure the sales team remain confident in the applications they are using. Picture a world where an application knows its data is in bad shape. A bit like a health-tracking app on a smart watch, AI-driven applications will be able to sense when the quality of data in an application is degrading and will itself be able to make the necessary changes to bring the quality back up. Sales ops can restrict and control the data being pushed in and out of application by the sales team. However, it’s hard to predict when that data is stale, for example, when a person changes jobs, gets married or changes their name. Applications with the right APIs and links to rich internet datasets will be able to spot the changes in the data and adapt accordingly. Maintaining data is the bane of Sale Operations. The good news is in the future, there will be no need as AI will act as a data valet for your business to allow sales ops to focus on more valuable work.

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