The retail industry is a complex field, where data has become an irreplaceable asset for achieving high sales rates and increasing profits. Precisely due to this continuous advancement, the total global retail sales are projected to reach $30 trillion by 2023.
However, apart from the financial advantages, the leading global retailers benefit in unique ways from integrating Big data: each of them using it for a distinct purpose and generating curious and creative insights from it.
So let’s see the real-life Big data examples of the biggest retail organizations.
Starbucks is one of the most popular coffee brands in the world. This American company has been on a top-ranking position in its sector for many years in a row, and the key to its continued success has always been the constant adoption of innovations, cutting edge technologies, and now: Big data.
According to research conducted by Forbes, Starbucks has achieved around a 26% increase in its revenues only for a period of three years (2016-2019). And Big data has a finger in that.
The brand uses data in terms of location, demographics, buying behavior, customer trends, and others, to predict the success and future performance of its new stores, which will open in different parts of the world. This way, the organization manages to mitigate the risk of opening a store in an unprofitable location and eventually to prevent any kind of store bankruptcy.
What is more, Starbucks uses the customer data it generates for marketing incentives and aftercare services to continuously engage with the clients even when they are not in one of their coffeehouses. And that has a double effect: provide personalized products and offerings, and achieve a higher level of customer satisfaction.
- In this particular example, Big data saves lives.
Costco is an American multinational wholesale corporation, which specializes in the retail of all kinds of alimentary products, as well as personal and household items.
The purpose for which this business entity uses Big data is quite impressive: Costco tracks each order in detail. That includes who had placed the order (and contact information), when the purchase was made, and exactly which item was shipped to the customer. This may sound not as impressive, but the following example will trigger you.
In 2019 Costco purchased and sold a batch of fruits, which turned out to be potentially contaminated with listeria. The integration of data gave the corporation the advantage to identify each of the clients who bought fruit from this particular batch and warn them about the possible threat. They not only did that, but alarmed the customers using two different means of communication: first by phone, and then by letter.
Amazon is a world-famous online retail company, from which you can order anything: from food to electronics. It is part of the Big Four tech companies, next to Google, Apple, and Facebook Group, which makes it a big fish and enormous factor in the tech world.
One of the most important and valuable strengths of Amazon is based on Big data integration: Their advanced recommendation engine.
It collects data from the purchase history of the customers, as well as from viewings, clicks, search queries, and in-cart items. Based on these data, Amazon gives suggestions with amazing accuracy and, at the same time, drives sales to slow-moving products and listings.
Interesting statistics related to this feature is presented by Martech and shows that 35% of Amazon sales are generated through recommendations.
This Swedish furniture retailer is well known for its constant innovation with the purpose of achieving a higher level of sustainability. The unique ways of manufacturing, packaging, and shipping and recycling make IKEA one of the few companies that have adopted a circular economy as part of the business culture.
But how this furniture leader uses Big data to its benefit?
Yet in 2013, IKEA launched a feature for image recognition and augmented reality in their app. The customers scan the items they like with their phone, directly from an IKEA catalog or from the store itself. The advanced analytics enable them to place virtually the furniture they liked in their own homes and see how it looks, as well as to change the color, sizes, and models.
Another use of Big data is in terms of item recommendations. Similar to the engine of Amazon, this retailer suggests related or complementary products to the items, which the clients viewed on the website, added to cart, or highlighted as favorites.
With such a personalization feature, IKEA is enabled to provide high-grade CX and satisfaction not only in-store, but in their webshop and app.
What is more, the use of big data for augmented reality and advanced analytics contributes to the company’s sustainability efforts by diminishing the people who actually drive to the store location to buy something.
This way, the organization is responsible for shipping a big part of the orders and has the freedom to optimize their transportation by organizing it in the least costly and most efficient way to diminish its environmental footprint.
ASOS in an enormous British fashion retailer who changed the game for clothes and accessories shopping.
The brand has introduced an image recognition feature in its app to allow its customers to scan any clothing item they like. Based on its characteristics, the engine generates a listing of similar products: for example, if you see a jacket you like, you can take a picture of it, and ASOS will show you their jackets with similar characteristics, such as model, color, accessories, etc.
Another use of those advanced analytics is the “Style and match” feature, where the app shows you suggestions on how to pair the clothes you have scanned and how to improve their fashion appearance.
With such use of Big data, ASOS becomes a preferred brand for shopping and fashion advice. What is more, those features are an excellent marketing tool for popularizing products and positioning the company in the mindset of its clients.