5 Ways Artificial Intelligence Is Transforming CRMs

by Falon Fatemi

 

2019 has already unfolded as a banner year in terms of the union between artificial intelligence and sales. While 2018 saw the artificial intelligence sales revolution beginning to gain momentum, the applications were limited. In 2017, 51% of enterprises leveraged some form of artificial intelligence. In 2018, the percentage increased by a mere 2% to 53% adoption.

This year, artificial intelligence will increasingly play a vital role in sales organizations. One of the most profound implications will be in the context of CRMs. CRMs have long struggled to gain the favor of sales professionals. Less than 40% of businesses report a CRM adoption rate in excess of 90%. This year and beyond, we’re sure to witness a marriage between artificial intelligence and CRM systems, a transformation that amplifies the capabilities and effectiveness of antiquated CRMs.

1. Data ingestion and retrieval 

Many individuals have predicted that artificial intelligence’s foray into the sales landscape poses a threat to the human sales profession. Yet the belief that artificial intelligence signals the demise and replacement of the human sales function entirely, is tremendously short-sighted.

Artificial intelligence promises to enhance, not replace, the human component of sales. The sales professionals of the future will use artificial intelligence to complement their efforts and skillsets. When it comes to CRMs, this starts with data ingestion and retrieval. As it stands, sales professionals spend 17% of their time entering data—the equivalent of nearly one work day per week. Indeed, manual data entry is the primary obstacle that inhibits CRM adoption.

Artificial intelligence not only empowers sales professionals to eliminate manual data entry, it also bolsters their ability to centralize disparate customer databases and, in turn, capture the complete customer lifecycle—whether it has transpired via email, phone conversations, chatbots, etc. CallMiner Eureka, for example, uses artificial intelligence and machine language to capture and transcribe customer interactions. Transcriptions are tagged according to key topics and a rich categorization schema. When this data is ingested into a CRM, it can surface key insights, including objections, specific data with respect to competitors, and ideal use cases. Salespeople can search transcript metadata for keywords, phrases, or even acoustics such as increased voice intonation that may signal excitement and increased interests. With the air of topic clusters and frequency maps, salespeople are equipped to detect vital customer trends.