According to a report by analytics major McKinsey, some leading retailers are turning the promise of Big Data into reality. An analysis of more than 250 entities over 5 years has revealed that companies that have established Big Data at the core of their sales and marketing efforts have managed to improve their Marketing Return on Investment (MROI) by 15-20%. That adds up to $200 Billion of additional value based on an estimated global marketing spend of $1 Trillion!
Companies that are at the forefront of retail are forever searching for new ways to boost customer engagement. The promise of Big Data has been around for some years but its only recently that the potential has started turning into real-world gains for some early adopters.
New technologies, channels and platforms have created a tsunami of customer data and an unprecedented insight into customer preferences and behaviour. This has led to the use of analytics to identify valuable opportunities, influence the customer decision journey, and personalize the product or service offerings to customers.
It has become a veritable gold mine, with marketers digging in to any and every available piece of information that could help catalyze higher revenues and greater customer satisfaction.
Below we have compiled a list of what we think are some leading retailers who have benefitted from this technology. Feel free to participate in the list:
“We want to know what every product in the world is. We want to know who every person in the world is. And we want to have the ability to connect them together in a transaction.” These were the words of Walmart’s CEO of global e-commerce, Neil Ashe.
WalMart’s attempts to use data to predict customer behavior reportedly date back to the year 2004, when USA was stuck by Hurricane Frances. The data was used to inform stocking decisions and led to strong sales. This realization of the powers of predictive analysis eventually led to the creation of @WalmartLabs. Since its inception in 2011 it created the Big Fast Data Team with the purpose of finding pioneering uses for data in retail.
They also created the Social Genome project, which guesses what products people are likely to want to buy, based on their conversations with friends. Another service called The Shoppycat suggests gifts that a person might like to buy for his friends, based on their interests and Likes. They also experimented crowd-sourcing new products with “Get On The Shelf”. Proposed products are put before a voting public to determine whether they should be stocked by the chain nationally.
They now have their own search engine, Polaris, which uses sophisticated semantic analysis to work out what a customer wants based on their search keywords.
eBay is quite busy with its gigantic search data. Because insight into search data allows its users to broaden or narrow searches, leads buyers to related products and optimizes the overall experience on eBay. In essence, what eBay does is use intelligence from advanced users and apply that to help what they call ‘the naive user’ (a user who’s not good with queries). A lot of effort goes into the first step of cleaning the data. De-duplicating user-associated data provides better suggestions for related searches. After that, eBay goes six years back in time to analyze user behavior. And it does this pretty much in real time.
Another example is eBay’s new data-driven homepage, “the Feed.” Consumers can “follow” categories of items — from Ray Ban Wayfarers to vintage typewriters to costume jewelry — and stay on top of the newest listings, whether they’re collectors or simply in search of something specific.
eBay also recently announced Pulsar – an open-source, real-time analytics platform and stream processing framework. Pulsar can be used to collect and process user and business events in real time, providing key insights and enabling systems to react to user activities within seconds!
Amazon has been using Big Data to determine everything from what a customer has placed inside the shopping cart to which items they’ve viewed and purchased in the recent past. Amazon has christened this technique as, “item-to-item collaborative filtering,” a method that utilizes data sources to personalize a customer’s buying experience. It provides Amazon shoppers with a convenient shopping experience by presenting consumers several merchandise options that either they have considered in the past or that are suitable for them. This way, they are able to decrease the time a customer spends on searching, and shortens the buying journey.
Neil Lindsay, Vice President, Marketing at Amazon, explains: Amazon doesn’t only record the browsing history; rather it knows what people want to purchase. Amazon has traditionally invested in its own customer data analytics rather than in usual paid marketing opportunities such as TV ads.
Over the last 3 years or so, Netflix has graduated to being a content creator, rather than just being a distribution channel for movie studios and other media networks. Its strategy to do so was firmly driven by viewership data, which showed that its subscribers had an enormous appetite for anything that was directed by David Fincher and starring Kevin Spacey. After outbidding networks, including HBO and ABC for the rights to House of Cards, Netflix even went to the extent of predicting what it called a “perfect TV show”.
Every aspect of the production under the control of Netflix was informed by data, including even the range of colors used on the cover image for the series, to draw viewers in.
It was so confident that the entire series was immediately commissioned without going for pilot episodes, thereby breaking a long-held convention. The series has been running for 3 seasons and the 4th is on the production line. The 1st season received 9 Primetime Emmy Nominations and 4 Golden Globe Award Nominations, being the first online-only series to do so!
6. Rent the Runway
The analytics team at Rent the Runway uses data to make all important decisions, from sales & marketing to operations and stock buys. Data has always been an invaluable asset to this innovative retailer. Early on, their data illustrated that almost one fourth of their customers were adding an accessory to their designer dress orders. Jumping on the trend, Rent the Runway actually launched an entire upsell program on the site because of this strong data.
Birchbox is a subscription service for beauty products, that was launched in 2010. It sends out boxes every month to subscribers with various kinds of cosmetics samples and allows the customer an opportunity to buy the ones that they like.. They have coined it as the “try, learn, buy” model of selling beauty products.
Since Birchbox started as an online only retailer, it already knew how to use data to personalize offers and increase sales. Online subscribers enter in personal data like skin tone, hair color, and style preferences to determine what they receive each month. The data also helps in driving product recommendations and search results.
“From the beginning, data has been an essential part of Birchbox’s growth and strategy … we use it to make important company decisions, and use it to guide us towards creating the best possible new products for our customers,” said Deena Bahri, VP of Marketing of Birchbox.