The Broad Scope of AI Implementation for Enhancing CRM Efficiency

Artificial intelligence plays a vital role in improving customer relationship management’s productivity and quality. It revolutionizes the strategies, processes, and technologies that help organizations manage and analyze customer interactions.

The challenge for today’s businesses is to put the rapidly advancing AI technology to constructive use. One company leading the way in helping organizations capitalize on this goal is marketing technology firm SAS.

SAS Customer Intelligence 360 is a multichannel marketing hub that enables organizations to seamlessly collect, enhance, extend, and activate customer data, he explained. Powerful audience targeting and management, comprehensive identity resolution incorporating online and offline data, and a unique hybrid data architecture enable marketers to create journeys to deploy messages and personalize experiences across the entire customer lifecycle.

Consumer demands are evolving, and customer service resolution expectations have increased significantly. To keep up, brands must ensure the technologies they adopt enable speed. AI-powered chatbots provide customers with a near-instant response, assisting them in self-serving and problem-solving no matter the time of day or what human resources are available.

“The most significant contribution to date is from a generative AI perspective. A lot of marketing technology/CRM vendors are doing really cool things with it. However, we will see more AI-related capabilities infused into CRM platforms for front-end customer experience in the future,” SAS Head of Martech Solutions Marketing Jonathan Moran told CRM Buyer.

Developing the Role of AI in CRM Efficiency

AI techniques to do this expand beyond generative AI. A variety of AI-powered tools are used in front-end CRM. These include natural language understanding (NLU) and natural language generation (NLG), beacons and geofencing, based optimization and customer routing, plus many more.

According to Moran, these AI-powered technologies make CRM more efficient across four key pillars:

• Automation and speed
• Scale
• Productivity
• Depth of insight

With generative AI, brands can automate CRM processes to deliver campaigns, content, messages, and interactions to market faster. The most obvious benefit of AI to CRM is increased productivity.

Demand for better customer experience (CX) is increasing, and CRM platforms and processes must scale to meet it. AI- and analytics-powered technologies like customer routing and enterprise decision-making enable organizations to process numerous engagements and interactions concurrently. These capabilities support businesses in delivering better personalized CX at scale across CRM engagement channels, he explained.

“AI and analytics drive CRM initiatives forward by collecting relevant customer data, applying insight to that data, and then leveraging the data to derive insights to provide an individual-based level of customer understanding. When leveraged properly, these technologies have the power to improve business metrics around revenue, profit, margin, loyalty, trust, and customer lifetime value,” Moran said.

Highlighting the AI-CRM Connection

AI-powered CRM features include text analytics, natural language processing, sentiment analysis, visual and voice recognition through biometrics, real-time decisions, optimization, and customer routing.

One of the pressing problems CRM has not overcome with AI solutions so far is that machine learning has not been as seamlessly integrated into CRM systems as it could be.

We asked Jonathan Moran to share his insight and lengthy experience integrating various forms of AI to improve CRM efficiency.

CRM Buyer: Why is this still a problem?

Moran: Many martech vendors are focusing on incorporating generative AI but are neglecting other types of AI. While generative AI solves many menial marketing tasks, it does not generate the level of insight that predictive analytics-based machine learning and other AI techniques can.

Aside from that stumbling block, how is AI fixing existing inefficiencies in CRM software?

Moran: AI can do several things to help fix inefficiencies in CRM software. For starters, AI can automate data entry but can also create data to augment data sets through the use of large language models (LLMs) and synthetic data generation.

Additionally, AI algorithms can enhance data quality by removing errors, inconsistencies, and duplicates. As we all know, improved data leads to better outcomes from CRM systems.

Artificial intelligence is rooted in predictive analytics. So, AI can be used to analyze CRM data to identify trends, patterns, and behavior signals that inform future actions.