Data is no longer a level playing field. Companies that leverage AI and machine learning software have a leg up over competitors who are still only using data to look backwards. Research shows that 77% of high-performing customer service teams rate their ability to leverage artificial intelligence as excellent or above average. Companies that get predictive analytics right can greatly improve their customer experiences.
There are seven types of analytics we can pay attention to when it comes to customer experience. Each type helps gain better understanding of customers and improve the overall brand experience.
https://www.forbes.com/sites/blakemorgan/2019/01/16/7-kinds-of-predictive-analytics-for-customer-experience/
The ability to collect massive amounts of data represented a huge leap forward in customer service and communication when customer relationship management first hit the market as a marketing, sales and data management tool.
However, CRMs weren't a holy grail. Data management is one thing. Using data to understand what customers really need (not just what you think they do) and how to engage them is another thing entirely.
CRMs were not built to be nimble. Times change, customer expectations change, and the technology needs to change with it.
Currently, predictive analytics and artificial intelligence promise the potential to revolutionize CRMs in truly meaningful ways, but rather than be hyperbolic about that potential, it's important to be pragmatic -- and that's not the same as being negative.
https://www.crmbuyer.com/story/The-Trouble-With-CRM-Data-85616.html/
