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    Categories: Tech & Trends

Three Lessons to be Learnt from Global Retailers

Retailers are under constant pressure to use emerging technologies like analytics and big data solutions to design marketing strategies. Here are the key lessons to be learnt from global retail giants
– Mihir Kittur, Co-founder & Chief Innovation Officer, Ugam

The rise of technology and mobile devices in India is changing the way consumers interact with retailers. Thanks to the information transparency and shopper empowerment, consumers today expect more than just discounts and promotions – even in a price-sensitive market like India.

Are retailers matching expectations or prices?
India’s retail landscape is very dynamic and competitive, owing to factors such as the rising middle class, India’s youth demographic, and a burgeoning online retail environment. With the growing mobile and Internet penetration, consumers today can compare prices on their phones while shopping in a store. This has shifted the power from the retailer to the consumer, and puts pressure on the retailer to meet consumer demands, and offer the best ‘deals’. Hence, retailers try to match prices with their competitors.
Price-matching guarantees seem to be the first line of defence for many retailers because it is ‘easy’ to do. While it gives retailers a sense of action, it also drains the profit pool very quickly and tends to permanently change the shopper’s behaviour to react primarily on price. This phenomenon has been played out in the West and, while there is always a different local nuance, the business results for retailers who resort to price-matching solely has not been good. Global retailers today, are adopting more sophisticated strategies such as Dynamic Pricing, Product Intelligence and Custom Analytics to be more responsive to price, and use customer signals to better understand shopper intent and respond with a relevant ‘offer’ at the right time. There are, therefore, important lessons to be learned.

1. Get your pricing strategy right
It starts from here and this requires a commitment from the top, right down to the category managers. Many retailers don’t invest enough time and resources to understand their consumers, competition and market trends, and are presently just reacting to the price war. Of course, it’s easier said than done, especially in a market where new VC funded start-ups are prioritizing marketshare over profits. Thus, before choosing to match price, retailers must ask themselves these questions:
Should they be price-matching, at all? If yes, should they do it for all or only specific products?
Can they match prices in exchange for some value? For example, the Walmart Savings Catcher app checks if a local retailer is offering a lower price. If so, Walmart credits the difference plus doubles the credits if customers redeem it using an American Express Bluebird cards.
Should they price-match only for certain categories? For example, brick and mortar retailers selling consumer electronics will find it extremely difficult to compete and sustain on price-matching alone.

2. It’s not always about price
There are several other factors such as customer service, shopper experience, and a unique assortment that can influence purchasing decisions. For instance, physical stores carrying consumer electronics are often subjected to high attrition rates, limited retail space, and poorly-informed staff. Hence, they often struggle to offer a meaningful shopping experience to their customers. However, by applying advanced analytics and big data technology, retailers can identify existing gaps to improve the store experience for shoppers. Best Buy is a great example of a multichannel retailer that has adopted big data analytics to know ‘when’ to resort to price matching.

3. Knowing everything about your customer is not enough
Retailers need to invest in analytics and technology solutions to better understand what their competitors are up to, what their key value items are, how they are pricing them etc. Big data solutions such as pricing and assortment intelligence can help retailers sense, shape and respond to consumer and competitor signals. Making content improvements such as providing detailed product information, adding better images, and carrying user reviews and ratings can also drive conversions and provide better price-realization.
By using data-science, retailers can identify the products unique to their store and ones that are high in demand, how competitors are pricing products, study consumer signals and mark down or up accordingly. In a nutshell, retailers need to look beyond price-matching to be successful in the long run. Think about it, if every retailer offers the same price, there has to be something that differentiates them from their competitors that makes their customers stay with them.

PCQ Bureau: