Time to transform from CRM to Predictive CRM

Let’s imagine the world 25 years back. There was very less or almost no penetration of internet and email. The mobile phone was available only to the wealthier class of the society. It was during this time that we started hearing the term called ‘CRM’. Back then, CRM tools were sold more often as contact management software.

At the beginning of the 21st century, CRM tools continued to evolve. They started to focus on managing not just sales but also post sales data. This is what we today sales force automation and call customer support, but at its heart it still remains as a contact database. Since 2010, all the CRM tools have evolved sufficiently to keep pace with the changes that have taken place in the wider business landscape.

But today, when I compare these CRM tools, I see a lot of changes that have taken place from the UX perspective. A lot of additional features have been introduced to make it user friendly. But even now a few gaps exist between the tool's features and what the users expect from it.User adoption has been a challenge for CRM since sales personnel don’t find useful except for managing contacts using a single database. In some industries, sales people even hesitate to share their contacts with CRM tools.

What I feel is that today’s CRM should have more of predictability out of customer data than just manage sales or support processes. Thus, we can define an ideal CRM system as one that pulls together both internal and external data about prospective clients and help us to predict which customers are more likely to buy our products. Additionally, the system also helps us to identify other prospective customers, based on industry, size or other parameters.

Today, using the CRM tool, the management can get visibility into the pipeline and also do forecasting, but there is almost no value here for the sales reps. I think with predictive CRM, the sales reps will also want to use it because it will help them to close more business deals. The system will enable them to predict and generate more sales, thus earning more commission. The nature of predictability in CRM ensures that the sales users are calling the right customers at the right time instead of wasting their time with the wrong customers. This will ensure a very different attitude towards user’s adoption.

The conclusion is that the organization that has already deployed CRM will finally move towards predictive CRM. Thus CRM companies that do not embed advanced/predictive analytics, probably will partner with SAS, IBM/SPSS and other predictive analytic vendors.

In my next article, I will discuss POC solution on how we can use power of predictive intelligence correctly with the Salesforce CRM platform. See you there....