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  • Matt Lamb

Sales Needs Data Science, too.

One may be curious: Is data science impacting sales processes and methodologies? For a function spearheading enterprise revenue generation, herein stands an opportunity for applied machine learning, an infrequently discussed application; it is not the headline-grabbing AI stuff we see so often in today’s social outlets. This doesn’t diminish the impact machine learning is having on enterprise sales.

Machine learning has come a long way from its origins in the early 1950s, when Arthur Samuel wrote the first computer learning program for, ironically, the game of checkers. Since then, we’ve witnessed advanced statistical models (a primary foundation for data science) establish lasting imprints in lean manufacturing, engineering, and quality control, to name just a few. These early applications laid the groundwork for machine learning to take leaps going forward, spawning Smart Factories and Smart Manufacturing practices which are transforming these industries.

Today, machine learning has penetrated nearly all our digital experiences. Uber, Lyft, Netflix, Amazon, PayPal, Facebook, and Google all use machine learning to elevate and deliver value within their services. It looks like tech has joined the machine learning party, and so has healthcare, banking, transportation, education, professional sports, pharma….. the list goes on. Within these industries, machine learning is getting the work done better, more efficiently, and creating competitive advantages.

Consider one day in the life of a sales representative:

emails, calls, meetings, conference calls, Outlook invitations, notes, follow-ups – prospects, market research, due diligence – contracts, up-sell and cross-sell pollination – solution fits – demonstrations – quotes – negotiations – discounts, goal acquisition, meeting quotas, commitments, refining forecasts,...

Nearly all of the above may be applied for a single sales opportunity. Now let’s rinse and repeat this, every day, for N number of opportunities spanning multiple accounts. This exposes a clear problem-statement to address: how to become more efficient, making each customer encounter more meaningful, influential, and impacting to enhance rep performance. Machine learning directly tackles these issues and unlocks the power of sales and customer data.

Thanks to advancements within CRM systems, sales dilemmas have the ability to be captured and organized digitally. Today’s sales organizations are fundamentally changed for the better through machine learning. Through their use in models for sales, representatives now have algorithm generated opportunity scores to better understand where to invest their time and how to more accurately predict forecasts and future outcomes. Additionally, machine learning informs reps what their customers will buy (with statistical certainty) and how to best price these offerings. These tools can inform reps the best time to contact a customer, the best method of communication to use, and what step within the sales process to initiate.

This science is creating substantially competitive advantages across industries. Enterprises that understand their data as a differentiator will continue to win more. Check out Smart Cart and Smart Score to see how you can harness the power of machine learning and analytics to increase your win rates and profitability.

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