Combatting customer churn or attrition for brick-and-mortar stores has become increasingly important especially in an age where big-box stores and retailers are ambushed by the likes of Amazon (significantly deepened its presence in India), Flipkart and Paytm. While customer churn is not a new phenomenon for retailers, ecommerce giants, known for luring customers with jaw-dropping discounts, have made mapping the churn the most important metric of late. Also, the lines between offline and online are blurring. For example, Seattle-headquartered, Jeff Bezos led Amazon has taken an omni-channel route (deepening offline presence) in India to consolidate its market dominance. Case in point – it recently picked up a 5% stake in leading department chain Shoppers Stop and will soon open “experience centres” in Shoppers Stop.
So how can retailers thrive in this dynamic market? The key factor for churn could be the price game kick-started by e-commerce players who have taken it to a new high. Another key factor is that e-tailers have a mature tech backbone with AI and ML systems in place, while retailers are still battling to consolidate their data sources and integrate ML models for better execution.
So, in a hyper agile market, how can retailers and big box stores battle churn, especially in the festive season wherein digital giants are hard at work to woo customers with great promotions. Globally, retailers are definitely losing the edge what with upmarket department store Toys R Us filing for bankruptcy even before the holiday season. However, we believe in India, retail vs e-commerce scene is still not so grim. After declaring bankruptcy in US, Toys R Us launched in Bengaluru recently, a clear indicator how India is a potential market.
Analytics India Magazine examines the customer churn in retail, why it matters and why it is an important metric to track:
- An old marketing principle is that the key to driving deep customer engagement is matching customer journeys with insights about the customer. E-commerce players with deep tech muscle have advanced analytics and machine learning algorithms to understand user behavior
- E-commerce players leverage apps – the first point of contact for customers which helps marketers get the right insights and convert first-time buyers into repeat buyers, thereby achieving their marketing goals
- In contrast to e-tailers, retailers often track engagement rates, click-throughs, items in the cart and unsubscribed rate which is not the real indicator of customer churn
- According to Brett Robbins, Head of Business Development at Custora, New York-based customer analytics firm that spun off from Wharton, customer churn in a way helps predict how the demographics will behave in the future
- Understanding how the churn rate varies each week, month can help in better customer segmentation
- Customer churn rate is an indicator of where the retailer is going wrong and how you need to step up your efforts before you lose a major percentage of sales to rivals
- Robbins cites the “Early Repeat Rate” the percentage of customers who made a second purchase in a stipulated time-period a good way of building loyalty and driving conversion
- He believes that retailers are looking at the wrong metrics in the Customer Lifecycle Value
- For the churn rate to be captured effectively, one must combine different sources of BI information, user logins from complimentary Wi-Fi, data from beacons and online surveys
Winning the battle for eyeballs
With the holiday season upon us, retailers and e-commerce players have rolled out aggressive marketing plans to woo your pockets. In this scenario, reducing customer churn means one thing – ensuring repeat customers and acquiring high value customers that leads to a wide customer base. It all starts with the buzzword – omni-channel retailing which translates into understanding the customer, what he/she wants and recovering the money back on the marketing costs. Industry analysts believe for retail businesses to gain an edge again, big box stores will have to re-establish consumer interest.
In this case, predictive analytics can help prevent churn:
- By analyzing historical data from click stream and catalog data and unstructured sources (social media, surveys), one can get a sense of shopper behavior
- Social churn factors can be obtained by adding social media data to the mix which can lead to richer predictive models
- Merging all the siloed data together is crucial to arrive at a score for potential churners
- Analysts arrive at scoring models for potential churners
- The churn scoring model dictates the marketing strategy – whether to retain churners or focus on loyal customers by segregating high-value and low-value customers
- The model can further analyse the net campaign gain for each set of churners by factoring in the cost of reaching out to a segment of customers and the discount rate offered that customer
- Insights gleaned from predictive churn management models can serve as massive inputs for the BI strategy
The Indian retail market is expected to reach 1 trillion USD by 2020, making it one of the fastest growing markets across the globe. It is because of this reason that US toy giant opened a new store in India after reporting bleak sales on the home front. However, if Indian big box stores want to win the race for eyeballs, they will have to leverage predictive analytics to reduce customer churn rate, increase customer retention, speed up customer acquisition and convert their one-time buyers into repeat buyers. Legacy retail chains have a long way to go before they can bridge the gap between offline and online sales.