Five Ways Organizations Can Leverage AI-powered CRM to Boost Success

Arun Gupta
Published 07/08/2024
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Five Ways Organizations Can Leverage AI-powered CRMArtificial intelligence (AI)-driven success in scaling business growth and boosting profit margins using customer relationship management (CRM) involves leveraging the capabilities of AI within the CRM platform. The process includes enhancing various aspects of customer service, sales, marketing, and decision-making. Fortune Business Insights reported that the global CRM market size was projected to expand to over $157 billion by 2030. Many major companies in all industries, from financial to healthcare and beyond, employ AI in their CRM systems. One example is Coca-Cola, which leveraged AI to target campaigns and identify where customer service could improve with its CRM system. Its customer satisfaction increased significantly based on these insights.

AI-powered CRM systems enable predictive analytics, personalized and automated customer engagement, data-driven insights, and automated business flows. Focusing on these five key areas significantly boosts chances for long-term organizational success.


Predictive Analytics

One of the more significant benefits of utilizing AI is its unmatched ability to gather, process, analyze, and report big data in a fraction of the time any group of humans can. Proper programming and supervision make it less likely to make errors and can identify patterns that people miss, including traceable behaviors, sentiment analysis, and visual and audio recognition. Integrating AI into these business processes and taking advantage of its rapid and accurate predictive analyses allow for a wider range of diversified information in a shorter period, saving time and money.

By leveraging CRM data and trends, companies can glean valuable insights to accurately predict customer behavior, sales, and revenue. This helps businesses inform decision-making, innovate new or improved products and services, and meet the specialized needs of their consumers. By utilizing pattern recognition, AI can identify potentially fraudulent activities, protecting the business and its customers from financial losses.


Optimized Sales and Marketing

AI-driven marketing campaigns can target consumers with demands that match a business’s supplies or services, allowing budget allocation that optimizes the return on investment (ROI) and decisions that drive additional sales. Because AI excels at filtering and categorizing purchase histories and browsing patterns, businesses can suggest relevant products and services.

Developing a honed sales funnel is critical to success. AI can automate tasks, personalize customer interaction, and enable data-driven insights, which are crucial in the five stages of a sales funnel (awareness, interest, consideration/evaluation, action/purchase, and loyalty). AI provides an efficient solution for social media monitoring, website traffic analysis, and market trend prediction. This helps marketing teams effectively segment target audiences, identify the most effective marketing channels, and create personalized messaging and campaigns.


Customer Service

While customer service expectations continually evolve, the recent influx of AI-related services and products has dramatically expedited demands. More than ever, consumers are looking to companies that provide reduced response times and tailored products, services, and purchase options. This shift will continue to grow. AI can optimize case routing and management by automatically classifying and assigning cases based on topic, urgency, and expertise required. This ensures customer queries are handled by the most appropriate agent, reducing response times and improving resolution rates.

In 2022, Gartner, Inc. projected that AI-automated responses through chatbots and voicebots will grow from an estimated 1.6 percent to approximately 10 percent by 2026. AI’s customer segmentation skills are critical in extracting relevant data and discerning subtle patterns, providing more customization for consumers. Personalized marketing increases conversion rates, leading to improved customer loyalty and revenue. Equally as important, AI models can operate 24/7, catering to consumers in every time zone.


Enhanced Decision-Making

Through automated insights, AI streamlines data analysis by processing enormous amounts of data much faster than humans can do on their own. With appropriate machine learning (ML) and training with applicable information, AI can provide concise, accurate data in time-sensitive situations when handling consumer problems. It also saves money by opening opportunities that would have been lost due to the inability to meet an extreme deadline when handling customer issues.

Data democratization enables an organization’s workforce to make data-informed decisions, which is crucial in successfully integrating AI into a business model. Because big data is complex, those unfamiliar with technical terminology or unable to scrutinize statistics can develop decision paralysis—the inability to make decisions due to overwhelming information. AI eliminates the challenge of interpreting vast amounts of customer data for relevant results, enabling faster and more effective decision-making.


AI-Powered Workflow Automation

AI tools can analyze collected data to pinpoint opportunities for improvement, providing valuable insight to decision-makers, who can also implement AI tracking for regular monitoring, keeping one step ahead of any further areas that can be streamlined or improved to meet ever-growing consumer demands.

Using AI only to remove select repetitive, routine tasks from staff can save time, allowing staff to focus on jobs that require the human element. Applying AI technology to the entire customer-service cycle—like scheduling appointments, providing confirmations, and sending follow-up emails—instead of individual tasks can increase efficiency and productivity, leading to improved customer satisfaction and loyalty.


Best Practices

The first step in developing an AI-powered CRM implementation plan is to map out current processes to see where AI can best fit the organization, starting with use cases, whether designing a custom CRM or procuring a ready-made CRM platform. This could be time-consuming, but once AI is integrated, it can speed up the process in the future. Designating a team or an individual with knowledge of AI expedites the research phase; the collected data is used to identify applicable tools, focusing on quality, that meet company and stakeholder goals.

Data privacy and security are paramount in selecting AI-powered CRM models. Concerns abound regarding consumer information privacy, but customers who feel their data is secure are more likely to stay loyal to the companies that provide this. Security breaches are detrimental to organizations when customer information and the organization’s internal data are hacked. Another best practice is involving those who will be interacting with the AI model early in the process to allow time for adjustment and learning. Proper communication and ongoing training are key.

The successful integration strategy includes adopting AI models that integrate with existing infrastructure, if possible. Many types of custom software struggle to cooperate with some AI applications, so starting with systems that require minimal changes to incorporate AI will help. Once the model has been implemented, regular testing and continuous monitoring ensure issues can be resolved quickly, and improvements can be developed.

When utilized efficiently, AI goes beyond cutting costs; it leads to revenue growth through a business’s evolution in customer service and internal processes. As ML and language models continue to improve, processes powered and generated by AI will be faster, less biased, and more nuanced. AI’s ability to grow and adapt assures long-term relevance, fostering market competition and sustained business growth. Leveraging AI’s unique skills, combined with human interaction, is the first step to success.


About the Author

Arun Gupta is a solutions architect with over 12 years of experience in the IT industry, focusing on Microsoft Dynamics 365/CRM/Power Apps. His expertise spans the entertainment, financial services, and non-profit sectors. He holds a Bachelor of Technology in information technology and a Master of Science in information technology from UNC Charlotte. For more information, connect with Arun on LinkedIn.


Disclaimer: The author is completely responsible for the content of this article. The opinions expressed are their own and do not represent IEEE’s position nor that of the Computer Society nor its Leadership.