CPQ: Boost Selling Performance and Accuracy

CPQ: Boost Selling Performance and Accuracy

By Denis Pombriant • CRM BuyerECT News Network

Apr 17, 2017 3:37 PM PT


They say it can take a product idea 10 years to go from concept to mass-market appeal but that might be only an optimist’s viewpoint. Some of the best ideas in CRM right now have been marinating for at least that long — and some for much longer. Two great examples are analytics and CPQ, which companies like Oracle, Salesforce and others have embraced with passion. Interestingly, each technology has traversed a path that needed other technologies to become fully mature.

“Analytics” — that is, business intelligence and data mining — is an old term for what we now call “machine learning.” Analytics and big data needed a lot of hardware improvements to become prominent.

For example, way back in the 1990s, Kendall Square in Cambridge, Massachusetts — next door to MIT — became known as “AI Alley” for all of the startups there that were going to enable us to know customers’ minds before they did. Most of those pioneering companies are gone now, but their ideas generated big R&D throughout the tech sector.

One of the major drawbacks of any kind of advanced analysis is the need for processing power on specific data. To do that, you need fast CPUs — but also, your data can’t be static and sitting on a disk. So, the AI movement influenced not only speedups for CPUs, such as multiprocessors and federated computing, but also in-memory databases and very dense memory.

Of course, it took 20 years, but today we’re reaping the benefits of the investment and research necessary for all of it to happen. Now we really do have the ability to know probabilistically what customers in the aggregate will think, and we can act by putting next best action suggestions on a smartphone. That’s pretty cool.

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