Transforming CRM information into effective sales insights

Superb customer experience is today’s top priority for fast-growing businesses. Customer focus is at the heart of any digital transformation initiative as forward-thinking organizations strategize. To ensure a positive customer experience from the start, technology must be agile and intelligent. And if you believe you have enough time to perfect your customer delight checkpoints, think again. Retail customers have repeatedly stated that they are willing to abandon brands after just one negative experience. Customer relationship management (CRM) is the ubiquitous starting point as enterprises revisit their tech stack to level up their customer experience, as it is a vast river from which millions of rivulets of information flow.

CRM: A system of record

In order to better engage with consumers and understand their preferences, we need CRM data to delve further into a customer story and provide signals to wrap it up. We see that sales teams can no longer rely on a formula based on this data when we look at the demanding customer profiles. Every engagement today requires personalization and curation and is more challenging.

Let’s take a look at some of the aspects in which CRMs fall short in modern-day sales and distribution.

Courtesy: As we try to understand how consumer buying behaviors vary with the economic landscape, CRMs fall short in tracking which sales actions and engagements are most productive across different client groups. These seismic shifts in consumer behavior are not addressed in sales playbooks.

Communication ease: BlackBerry’s spectacular downfall can be attributed in part to a failed CRM implementation. When its flagship messaging service was unavailable, it used Facebook (now Meta) as a communication channel instead.

Transparency and ease process: Since most CRM users update the systems irregularly, the data they receive is frequently erroneous, incomplete, or unreliable. A CRM should have complete visibility into customer information, playbooks that recommend next best actions, nudges for sales teams to take appropriate next steps, and complete visibility into team activity for sales team managers in order to create a seamless experience and transparency for customers. But how frequently are CRM platforms updated just after a sales engagement?

The need: A system of insight

A mobile and intelligent layer added to a CRM system can change it from a passive system of records to a contextual system of insight. Real-time data, AI, and machine learning capabilities will help a CRM become a recommendation system that will help sales teams close more deals more quickly and enhance the overall customer experience. The following characteristics, in addition to strong CRM data, can greatly enhance engagement and customer experience:

Auto-capture of activities: A feature like auto-capture eliminates the most significant barrier to a CRM: manual data entry. Automatic call and meeting detection, one-touch call sentiment, and note recording can all help with deep data capture.

Identification and imitation of winning behaviors: If intelligent platforms can identify winning behaviors from this comprehensive data capture, the identified behaviors can then float up as nudges for teams to imitate. Some examples include advising on the optimal number of touchpoints, tiering and prioritizing, and customization.

Nudges: Once the system recognizes winning behaviors, it should be able to nudge teams during sales and customer service. This gives sales teams very specific instructions for navigating different stages of interaction with a prospect or lead.