E-commerce retailers can improve customer experience with anomaly detection

How often have you experienced frustration while shopping online? ?sn?t it disappointing to abandon your shopping cart because the transaction returns an error? Worse, disappointed customers are lost opportunities for the business.

This is an opportunity for retailers to streamline the online strategy to provide a good customer experience and boost revenue. Given the sudden surge in traffic, are e-tailers geared up to deliver a good buying experience to customers?

The COVID pandemic has changed our lives in fundamental ways including the way we live and buy things with many shoppers flocking online for the first time to get their daily needs. The lockdown forced people to stay indoors and order online which is subsequently becoming a good hygiene practice as people are avoiding going to physical stores and markets and gradually switching to online purchases.

According to a report by credit card bill payment platform, CRED, increasing number of people are moving online with discretionary and non-discretionary spends during the lockdown and these trends are continuing well beyond the lockdown indicating a larger behavioral trend.

The report noted sharp spike in online grocery and e-commerce demand surpassing even pre-COVID-19 levels, while spending on physical grocery and shopping has fallensubstantially. The data?which takes February 2020 spending as a baseline?found that Delhi spend grew to 135%, while Mumbai was at 133% and Bengaluru at 124%.

E-tailers are faced with a problem of plenty?the increased online activity is a boon but managing operations smoothly to ensure a complete and fulfilling customer experience so a happy customer returns again is a process fraught with complexities as Cloud systems work in a distributed environment with extensive automation creating challenges for operational visibility. However, e-tailers can overcome this challenge by deploying anomaly detection tools which help to keep a close track of real user-behavior by providing visibility into every aspect of the user journey including how much time a user spent on a particular page, what was the page load time, whether the transaction was smooth and whether all steps could be fulfilled in a single attempt, etc.

In the case of an event, e-tailers are able to pinpoint the exact nature of the problem and resolve it before it affects customer experience. This is because anomaly detection is able to use intelligence to monitor behavior of a user, application, or a Cloud resource to detect and establish a pattern in time series and raise an alert when there is a variation.

For example, the average time a user takes to complete a transaction during peak hours may be higher than the average time taken during off peak hours and any variation in the pattern alerts the operations team to investigate whether the delay is due external factor such as a promotion campaign, or whether it is due to slow response to database query, or whether there is an error in the application code.

The upside is that discovering each business incident presents an opportunity to interact and engage with the customer. Knowing which customer abandoned the shopping cart and having the insights into the reason provides the retailer to reach out to the customer with a customized message or to make an offer to come back and complete the transaction.

Anomaly detection can be applied to any number of scenarios including plugging revenue loss. For example, there is an unexpected increase in the purchase of gift cards yet this is not reflected in increased revenue. This anomaly should raise the red flag to investigate the cause and plug the error before it causes revenue loss to the business. 

Share on

Leave a Reply

Your email address will not be published. Required fields are marked *