4 Ways AI can help you better understand—and serve—your customer
When the concept of CRM first began in the 1970s, companies were forced to rely on little more than annual surveys and phone calls to complete their Rolodex and spreadsheets. Today, artificial intelligence has brought the industries lightyears forward, empowering businesses to streamline the process of gathering, organizing, and even analyzing customer information. At the forefront of this technological revolution are software based systems and AI-powered tools like machine Learning (ML), predictive lead scoring, and natural language processing (NLP) that garner automated insights in minutes.
Businesses can leverage AI-based CRMs to organize and access valuable customer information like demographics, contact details, and communication history. With this data, companies better serve customers, automate business processes, and create future opportunities with more accurate sales forecasts, recommendations, and lead conversion. Ultimately, sales representatives can use this intelligence to nurture their customer relationships and better target future clients.
Here are four ways AI can help you become better at customer service.
Alleviate busywork so you can focus on the customer
Some experts claim that AI poses a threat to sales professionals. However this belief has proven to be short-sighted; because AI solutions reduce time-consuming administrative functions such as data entry, teams now have greater bandwidth to help customers and focus on the more meaningful aspects of their jobs, including creative thinking, problem solving, and client support. In one poll conducted by the research firm Opinion Matters, it was found that sales reps who used a CRM system spend 15 days a year just recording client phone numbers. The best AI-based CRMs support and complement a worker’s skills and job, freeing them from manual data retrieval and analysis. Today, chat and email bots ensure that customers get quick answers, while other AI technologies analyze voice and text in real time to help agents more effectively serve clients.
Create more personalized and efficient customer engagement
Bots and other AI-based CRMs don’t only serve to open up employee bandwidth. They also empower businesses to personalize their customer interactions by mining and analyzing customer data like purchase history, demographics, and browsing behavior. This data can then be used to tailor interactions such as marketing messages, product recommendations, and customer support to better suit each customer’s unique needs and preferences. In turn, AI-based CRMs often employ chatbots to provide instant customer support and improve response times to answer frequently asked questions and even process simple transactions.
Gather critical data
In 2023, data is the most valuable resource a business can own. By capturing a centralized record of high-quality customer sales data and communications, AI-based CRMs ensure increasingly accurate and insightful AI predictions, which accordingly strengthen your business. In this way, AI-based CRMs become a self-sustaining cycle; customers provide their own data, which is in turn used to improve the customer’s experience and overall fulfillment. AI also solves the pervasive problem of bad data. According to a study conducted by business information and research firm Dun & Bradstreet, 91% of data in CRM systems is incomplete, while 18% is duplicated and 70% is rendered stale each year, resulting in disasters such as a disrupted sales pipeline. AI tools, which are more immune to human error, are able to detect irregularities, anomalies, duplicates, and other mistakes that compromise CRM data—and reputations.
Learn from and respond to the customer
Think CRMs are only good as data repositories? Think again. With AI powering them, CRMs are taking on a new, powerful role as data scientists, providing targeted recommendations for salespeople, including sales and marketing collateral to be delivered at specified times. Without AI, disparate customer data might be lost or delayed in analysis. According to the International Data Corporation, many businesses are not effectively leveraging their information assets; only 2% of the data created in 2020 was retained and used in 2021. Rather than waste it, generative AI promises the potential to turn these assets into gainful information. In practice, one of the best applications of this is detecting vital customer trends, capturing the complete customer lifecycle, and segmenting consumers based on factors like demographics, behavior, likes, and dislikes. Once customers are identified and appropriately grouped, it’s easier to respond on the fly to their changing variables like economic factors and competitor activity.
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