Transforming Sales From An Art To Science

The Company
13 March 2019

Experience, intuition, and the ability to forge relationships are still important elements defining a successful sales person. But these days, where new technologies are integrated into every aspect of our lives, it would be naïve not to accept that the old “tried-and-true” methods of selling are perhaps more tried, and less true.

Make no mistake, selling is still very much an artform, but in this new era of selling, introducing data science means setting your sales team up for success through more efficient and effective customers interactions and a whole new way of approaching sales process.

Automate non-selling tasks

Tedious and frustrating as they may be, data entry, quote generation, and other administrative tasks are part and parcel of the sales role. There’s no escaping that fact. But when your sales professionals spend 66% of their time poring over spreadsheets and emails, that accounts for plenty of wasted time, talent, and opportunities to build relationships with prospective customers.

It is no surprise then, that according to a Salesforce study, 57% of sales professionals expect to miss their quotas in 2019.

The solution? Automate these tasks and allow your sales professionals to focus on what they do best. Automating not only saves time but also reduces error rate. Through data science techniques such as machine-learning, your business can reduce critical errors such as missing or incorrect contact phone numbers in your B2B database.

According to ZoomInfo, 62% of businesses rely on prospect data that’s only between 20% to 40% accurate and 40% of business objectives fail due to inaccurate data. From a cost perspective, it costs $1 to verify a record as it is entered, $10 to scrub and cleanse it later, and $100 if nothing is done.

These statistics only serve as proof that automation techniques such as a model capable of analysing and extracting updated information is the key to successful selling.

Improve objection handling

A veteran sales person may be all too familiar with objections and have honed his or her ability to turn objections around to ultimately close a deal. But for newer sales reps, data science can provide much-needed real-time guidance and identify coaching opportunities to improve selling effectiveness.

By using machine-learning to automatically identify specific types of objections and collecting responses from top-performing sales reps who are able to turn objections around, data science can automatically present the best template responses for each scenario.

This ensures uniform communication across the entire sales team and more importantly, reduces the response time of sales objections because leaving sales objections unaddressed, ultimately makes it harder for you to change the opinion of the buyer (Hubspot).

Reduce the time it takes to generate more accurate sales forecast

Estimating future sales allows your business to make informed decisions and better predict short and long-term performance. Sales forecasting also provides insight into how your sales team should distribute its resources.

So, it’s safe to say that sales forecasting is a crucial process to successful selling. But as any sales person will tell you, putting one together is a slow, expensive, and time-consuming endeavour. The knock-on effect is that sales teams are not given enough time to action on leads generated.

This is where the field of data science comes into play. Using a fast, scalable, open-source machine learning and deep learning technology called H2O, large businesses such as PayPal and Cisco were able to analyse all their data and get accurate predictions faster without resorting to sampling.

For Cisco in particular, the use of H20 meant that it can run its collection of 60,000 propensity to buy (P2B) models that help its sales teams focus on the highest-yield initiatives in just a few hours rather than months. This allowed its sales team more time to better equip themselves to engage prospective customers.

Despite being relatively new, there is no doubt that the benefits of data science far outweighs the commitment of time and resources it requires. But as selling becomes more about the customer, data science is the way to transform sales from an art into science – one that focuses on action, revenue, and people.

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