Customer relationship management (CRM) solutions have solved some of the most important problems for companies in the last decade. They helped companies manage disparate data sources about the product, services, customers, etc. They enabled companies to access and manage all their customer data in one place. The better visibility into this data enabled executives and employees to be more efficient in responding to customers’ needs, and drive more sales.
In this digital age, companies face a different set of problems. The capabilities to collect, verify and analyze the huge amount of data being generated, the ability to understand different forms of data and being able to offer personalized solutions to customers are now mandatory. This is where artificial intelligence comes into play. Artificially intelligent CRM solutions help all the customer-facing departments improve customer experience.
- Natural language processing systems can dig through the text of emails exchanged with customers to estimate the likelihood of a potential sale, detect the best possible deals, identify deals a team is at greatest risk of losing, and provide recommended actions to improve the sales process. They can help sales reps to focus on the most promising leads based on the engagement data analysis, and shed light on their purchase triggers.
- AI-powered sales CRM can suggest the sales agents the products that they should upsell or cross-sell to any specific customer. This information can be deduced from the purchase patterns of thousands of customers. Such a CRM is especially useful in an e-commerce scenario, which has thousands of products in any particular category.
- While pitching to a prospect, the CRM engine can inform the sales team about the expectations of the customer, and his previous bad experiences (if any). This information can be obtained by crawling the net and analyzing his online reviews, posts, etc. The salesperson can then tailor his pitch to increase the chances of the customer converting.
- AI can also help your salesforce find the right person to approach in a company. It can go through social media profiles and find executives who are more likely to try out new solutions (ex: early adopters or who are moving up the career ladder).
- Intelligent training solutions for sales agents help them increase their productivity multifold, compared to a blanket training solution for everybody. These training solutions can build on customer feedback specific to an agent.
- Using natural language processing tools, email or chat communication from customers regarding their issues can be directly routed to the appropriate customer service agent.
- Chatbots and virtual customer assistants can help companies address a large number of customer service requests without increasing the load on agents. Enabled with natural language processing tools, chatbots can give the appearance of an agent to a customer on chat or mail, and make him feel valued. Chatbots are also available 24×7, increasing the brand’s reachability.
- Intelligent lead scoring: Machine learning software can intelligently score the probability of a customer opening an email, signing up to a newsletter, or making a purchase. You can then tailor your marketing campaigns to have better reach and engagement.
- Using deep learning algorithms, your CRM software engine can analyse images across popular social media platforms such as Facebook, Twitter, Instagram, Pinterest, etc. and suggest the kind of communication that works the best for your target audience.
- NLP can also be used for sentiment analysis on text to understand how customers feel about your brand and offering. Such an add-on can continuously crawl the web, and social media platforms to glean the content posted by your customers and leads for raw data.
- CRM add-ons, available in the market, scrape the data on the net to enrich your company’s customers’ profiles. These software can then identify potential customers and provide you tailored prospect lists.
- Intelligent CRM can combine existing customer data with his information available on public platforms to extract contextual insights into individual customer behaviors. They can combine third-party data with real-time analytics to optimize decisions and recommendations in various domains.
- Using predictive analytics tools, you can categorize your customers into high value and low value. You can then tailor your offerings, marketing communication based on the value they bring to your business.
AI-based CRM start-ups have been on a rise and so has been the funding, with companies offering AI-based marketing automation solutions alone raising more than $500M in funding till date. By 2021, AI-powered CRM activities could increase global business revenues by $1.1 trillion and create 800,000 net-new jobs, according to predictions in a new study.
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