How AI powers churn prediction and helps in smart customer engagementSudeshna Datta
Let’s get down to simple economics. Acquiring a new customer may cost up to 25 times more than retaining an existing one. No business in the world is immune to the risk of suddenly losing many customers at one time. So, you can imagine the impact – both financial and competitive – that losing customers can have on any business. It’s like losing to the competition outright. Customer retention has been a key challenge for almost all businesses across all industries. On one hand, aware and empowered customers are controlling their interactions and relationships with brands.
On the other, businesses are in a fix because many of their tried-and-tested methods of attracting and retaining customers stand ineffective today. To match up to the changing customer-brand dynamics and competitive pressures, forward-thinking brands are resorting to Artificial Intelligence (AI) for controlling churn and enhancing customer interactions.
Churning towards improved customer experiences with AI
In a study conducted for Pegasystems by Forrester, Artificial Intelligence and Improving the Customer Experience, results show that deploying AI-based solutions for customer management can lead to up to 10-50 percent reduction in customer churn. AI-powered churn prediction tools compute the likelihood of a customer to discontinue their transactions with any business. Hence, with the help of such a tool, companies can be ready with their strategies (and deploy the right solutions) at the right time instead of depending on warning signals.
AI-powered tools also help in cleaning and assessing data, building a predictive model to test, and identifying the customers prone to churn risk. This information can indicate what stage of churning the person is in. While early-churn customers (users who abandon a product shortly after using it) are difficult to retain and engage, late-churn customers (those who have a long-lasting relationship with a brand) can be incentivized to continue their association with the brand.
How can AI help predict churn and enhance customer experience?
AI can lead to intelligent, informed, and smarter customer experiences along each stage of the customer journey. But how does it do it all? AI performs better as it feeds on more data. Most of the data is available in different forms and from various sources inside the organization. To ensure that an AI-based tool helps with accurate predictions of churn rate and delivers the best solutions for enhancing customer experience, businesses must integrate the AI layer with all the organizational data points. Further, integrating AI with customer relationship management can have the following benefits for the business:
Machine Learning algorithms can help gather data about disengaged customers and apply predictive models and techniques to find out which accounts are at high risk of churn. In addition, they also pinpoint when they will switch and what offers will most likely encourage them to stay. AI-powered churn prediction, then, can keep more customers engaged, leading to the higher lifetime value of each customer.
Marketing teams can use predictive AI tools to generate personalized email content, campaigns, or messages aligned to the customers’ past behaviour. As the messages will be more targeted and relevant, it will involve lower spending but generate higher returns. An intelligent AI tool can be integrated with the company’s CRM system and send contextual messages at scale. AI systems can help present relevant promotions to customers based on their individual needs rather than the needs of the business, driving higher conversion rates and better customer satisfaction.
Know your customer with social AI
With a majority of the customer base found online, social AI, the fusion of AI and social media, can be beneficial for companies who adopt it. Social AI can provide enterprises with better insights after analyzing data centred around the customer’s online and social media activity, preferences, and buying patterns. It is useful in monitoring and analyzing social communication, as well as guiding marketers with strategizing and tailoring their marketing activities and promotions accordingly.
Provide real-time recommendations
Predictive intelligence and analytics tools process customer data such as purchase history, patterns, intent and preferences, priority status, and usage patterns to identify the right selling opportunities. AI tools are helping marketers understand customer behaviour and preferences and suggest the most suitable offerings for each client. AI-powered tools provide product, offer, and action recommendations tailored for each customer by identifying what kind of plan to offer these customers, and which accounts might require special attention (i.e. focused sales approaches) to increase the likelihood to purchase.
Enabling smart customer interactions
AI-powered customer support solutions can help organizations understand a customer better. The customer data which is captured during interactions can be analyzed using AI, analytics, and Machine Learning, and the insights derived from them can be used to develop highly-personalized solutions for every customer. This can improve customer delight and turn a customer into a loyal, high-value asset driving repeat purchases. Moreover, such insight-driven interactions can assist customer-facing employees to focus better on tackling the issues that have the greatest impact on customer experience.
The AI imperative for customer delight
The need of the hour is for enterprises to evaluate their current engagement model and see if it is still relevant in the present scenario and if it will work in the long term or not. Consequently, companies must come up with marketing campaigns which are ultra-personalized for each individual customer in order to optimize customer engagements. At the same time, they must empower their salespeople with insights on customers, while customer support agents should be equipped with the business intelligence required to delight customers during every interaction. The integration of AI into various processes like sales, marketing, and customer relationship management is imperative for enterprises to ensure smarter, proactive, and delightful engagement with customers.
AI-driven technologies using smart data sources can help companies and their teams understand where each customer is in their unique journey. As a result, businesses can easily identify the gaps in customer experience and present relevant actionable insights and solutions to retain customer interest, while ensuring their overall satisfaction with the brand.
Sudeshna Datta is Executive Vice President and Co-founder of Absolutdata, where she leads global client operations, developing partnerships across Europe and beyond.
(Disclaimer: The views and opinions expressed in this article are those of the author and do not necessarily reflect the views of YourStory.)