CRM Problem- In the beginning of my career, I worked as an inside sales rep at a Canadian company by the name of Nstein Technologies. I was diligent about my work and used our CRM religiously — even though, like most salespeople, I hated entering my data into Salesforce (and to be honest, I did the absolute minimum I could get away with).
But not all of our salespeople were even that diligent about Salesforce, so one day our COO grounded the entire sales team for a week in a sweaty, windowless conference room so we could clean up our CRM. We spent five days manually updating Salesforce but didn’t even make a dent since the data was so incomplete and inaccurate. It felt like a complete waste of time to take the sales team out for an entire week of revenue-generating activities.
Fast-forward a few years to when I was building out the sales team at a company that I founded and was shocked to discover that in nearly a decade, nothing had changed. CRM data was still a mess, and now I was the one frustrated by not having this mission-critical data at my disposal and wasting sales time and capacity cleaning it up. At that point, I knew something had to change.
The CRM is an incredibly powerful tool that has transformed the way businesses store their data, interact with customers and forecast growth. But even though sales reps spend 30% of their time on manual, administrative tasks, according to a recent SiriusDecisions report (login required), Salesforce itself estimates that 91% of CRM data is incomplete and 70% of that data decays annually.
There has to be a better way.
AI To The Rescue
Artificial intelligence (AI) represents one of the biggest opportunities for enterprises to drive productivity and optimize operations. While AI isn’t necessarily new (after all, we were doing deep learning at Nstein all the way back in 2008), the technological advancements in recent years — made possible by massive improvements in data storage, raw computing power and sophisticated distributed algorithms — have opened new doors for adding long overdue automation and predictive capabilities to business processes like CRM.