Excited by my email update from ShopAkira, a Chicago based store selling brands similar to that of UrbanOutfitters, I immediately started my online shopping escapade after reading about their 50% special going on that day. After filling my cart with 3-5 items, however, my conscious began to regain control of my shopping frenzied brain. A quick glance down at the table where a copy of last month’s bank statement lay, further pushed my conscious mind to the forefront, as I regrettably forced myself to close the ShopAkira tab. Thank goodness…crisis avoided…or so I thought.
You can image my surprise the next morning when I opened my inbox and found another email from ShopAkira. The email not only provided a reminder of the items in my cart but further egged me on to finish my transaction by giving me and extra 10% off if I finished making my purchases with in the next 24 hours. Needless to say online retailer 1, broke student 0… well played big data analytics…well played indeed.
As mentioned in Precision Marketing, companies looking to take advantage of big data need to use “relevance to retain current customers, maximize revenue potential per customer, help to acquire new customers and build long-term customer loyalty.” Gone are the days where customer loyalty could be built on mass e-mail spams and high general awareness. In today’s fast-past, high tech world, online retailers need to send relevant, personal messages to their target segments, in order to build any credible kind of relationship that will result in brand loyalty and increased life time customer value.
Not only can big data help drive brand loyalty and increase customer value, but it can also help to streamline retail practices/decisions and cut costs. I recently read an article that talked about how ModCloth, another online clothing retailer, is using big data in new ways to personalize their consumers’ shopping experience. For instance, their “Be the Buyer” program allows customers to vote on certain products with high-ranking products tagged as “Be the Buyer Picks.” Each “Be the Buyer” poll generates an average of 6,700 votes and helps ModCloth more accurately predict what new product items will sell or what type of product should be reduced in future inventory purchases by product buyers.
The article can be found here: