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Industry Leading Blog for Manufacturers

Machine learning has come a long way from its origins in the early 1950s, when Arthur Samuel wrote the first computer learning program for, interestingly, the game of checkers. Since then, we’ve witnessed advanced statistical models 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. 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. And now manufacturing is ready to take part, driving sales opportunities, new revenue, and improved customer experiences.

Consider one day in the life of a sales representative:
emails, calls, meetings, conference calls, Outlook invitations, notes, follow-ups with 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 the above may be applied for a single sales opportunity. Now let’s rinse and repeat this, every day, for opportunities spanning multiple accounts. This exposes a clear problem-statement to address: how to become more efficient, make each customer encounter more meaningful, influential, and impactful – while enhancing a sale rep’s performance. Machine learning directly tackles these issues and unlocks the power of sales and customer data.

Thanks to advancements within CRM systems, sales dilemmas can be captured and organized digitally. Today’s sales organizations are fundamentally changed for the better through machine learning. 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. In short, reps can be told what to sell, who to sell it, and when, and even know how likely they are to buy.

This science is creating substantially competitive advantages across industries.  Enterprises that understand their data as a differentiator will continue to win more. Check out one of our offering using this technology, Pinpoint Sales for Aftermarket, which harnesses the power of machine learning and analytics to increase win rates and profitability.

Pinpoint utilizes cutting edge machine learning techniques that equip sales reps and leaders with the data intelligence to create competitive advantages that leads to better customer interactions and more revenue attained.  Through this offering, reps get prescriptive information about all of their accounts: which accounts to call, when to call them, and what their accounts have a statically driven propensity to buy. Pinpoint Sales for the Aftermarket is true AI and becomes smarter and more powerful as its used.  It learns from your interactions and always optimizes where you put your sales efforts toward.


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