E-Commerce: How AI-driven customer engagement helps to improve customer retention?
Posted On November 5th 2020
In the early days of online retailing, there were just a bunch of key channels that retailers had to focus on to attract customers. Dawn of the century witnessed a huge increase in the number of channels and choices for a customer to make purchase decisions.
In later years, it immediately got simpler for a customer to bounce between channels, and to move brand loyalties in a matter of seconds. Along these lines, by giving attention to keeping those one-time purchasers faithful, returning customers started to advance. Additionally, online retailers started to see customer acquisition costs going through the roof, impacting their unit margins. Multi-channel customer acquisition strategies soon proved to be costly affairs if the customers were left only to make one-time purchases. Hence, the focus shifted towards customer lifetime value and retention strategies.
Maintenance of existing customers was less expensive than the picking up of new ones. However, market studies revealed that only 32% of customers really returned for more business within the given timeline. This emphasized the need to connect with current customers all the more frequently and find avenues to increase repeat businesses and increase the lifetime value of a customer.
Few manual techniques are implemented to improve the customer retention in an e-commerce business which includes sending targeted emails, offering reward points, customizing customer encounters depending on their purchase history, offering more delivery and return options to the customers, etc.
“Aa a pivot of all such customer retention initiatives lies customer engagement.”
In today’s fast-moving and highly competitive marketplace, customer engagement plays a vital role in retaining the customers for the long run. Industry information uncovers that more than 50% of customers are bound to do business where the experience is personalized. With more customers presently shopping online than ever, retailers are taking a look at trend-setting innovations to automate customer engagement and personalization with the power of AI.
A Salesforce survey on how hyper-connectivity impacts customer behaviour reveals that:
● Personalized customer engagement is the key to customer retention.
● More than 50% of customers are likely to switch brands due to a lack of personalized engagement.
● Customers are willing to share a certain degree of behavioural data for businesses to provide personalized experiences.
● 53% of customers expect personalized product recommendations and shopping experiences.
● 62% of customers expect personalized offers and discounts based on their past purchase history.
The survey also extends to discuss effective usage of technology and data in offering such personalized customer experiences. It happens to be:
● Customer interaction data and technologies, enabling companies to provide personalized experiences are very much under-utilized.
● With an increasing number of online users, customer behaviour data collection and drawing out personalized inferences warrant for automated intelligent systems.
● On web technologies, high performing teams are 7.2x likely to use intelligence-driven personalization than the underperformers.
● On customer communications (emails), top-performing teams are 4.2x more likely to leverage intelligence-driven personalized communications to their customers.
It is imperative to the point where customer engagement and personalization has to be automated to manage volumes of interaction data. Artificial Intelligence makes automated personalization more brilliant and more compelling than ever, which drives both engagement and conversion rates for retailers. Businesses who are incorporating artificial intelligence record higher effectiveness and lower operational expenses. Through AI, e-commerce businesses can provide personalized experiences by taking into consideration various qualities and behaviours of their customers, including buying patterns, shopping motivations, and purchasing tendencies.
On the other hand, intelligent systems such as AI and ML algorithms are cost, time and resource-intensive to establish and maintain in the long run. Also, the effectiveness of such intelligence infrastructure depends on a lot of iterations in fine-tuning both data and algorithms to suit each individual business. Hence, the total cost of ownership (TCO) of such systems are generally high.
How can Datsy help the e-trailers in customer engagement and retention?
Datsy bridges the gap between the need for intelligence infrastructure and high cost of ownership. Datsy Suggest provides AI-driven hyper-personalized recommendations for eCommerce applications on a pay-as-you-go SaaS model. This relieves e-commerce businesses of any entry/exit overheads and liberates them to experiment on various engagement strategies through personalized product recommendations.
Datsy Suggest facilitates customer engagement through contextual product recommendations. Context can be configured for customer personas, calendar timeline, seasonal products and behavioural patterns. Personalized experiences motivate your customers to return to your e-commerce platform and over a period of time, makes your platform their first choice for any shopping need, thus, converting “customer retention” from being a problem statement into a business outcome.
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