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3 Major Things Big Data Can Give Retailers

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As brands continue to attempt to find ways to increase their sales within stores, big data is a primary contributor to brands learning more about people and personalizing their shopping experience. Big data is datasets that are much larger than traditional databases and can process data quickly to provide reliable and specific information. As the use of big data continues to increase, retailers are using this data to gain knowledge in a variety of ways. Retailers who use big data to its full potential “could increase its operating margin by more than 60 percent” (McKinsey). Customer segmentation, personalizing the experience, and price optimization are three things big data can provide retailers and they all should be utilized by brands. Unlike traditional market research, big data allows more specific information to be collected while also utilizing technology to be able to collect this information.

1. Customer Segmentation

Big data allows retailers to identify the specific customers that will make them the most profitable and can target them with products they will buy based on their past behavior. Gathering people’s individual trends from social media, e-commerce, and in stores, companies can combine all this data before analyzing it and placing people into customer segmentations. When people are placed in these segments, stores can then give precise offers to the different segments so more purchases are made. Understanding what these segments prefer can lead to higher conversion rates among consumers because brands now know what each person is consistently purchasing and can target specific segments with promotions they are interested in. Once retailers have consumers in their segments, then they have the ability to personalize the experience.

Official WeChat accounts as well as other Chinese social media allow retailers to gain consumer information, understand shopping habits, and overall interaction with the brand. After more consumer data is obtained, retailers gain a better understanding of which products their target consumers are more likely to purchase thus allowing retailers to optimize their retail inventories.

2. Personalizing the Experience

Big data uses a multitude of factors to help personalize the experience and increase shopper retention rates. The use of websites, cameras, and shopper information allow retailers to analyze the data to provide a better experience. Companies can analyze data on what users are doing on their websites and therefore create unique offers. They can follow what people are searching for or putting in their shopping carts, and use the information to promote related offers to the consumer. Cameras used within retail stores give valuable shopper trends for companies to analyze using big data. Every shopper and their needs are unique, which is why identifying each individual helps retailers understand what they are looking for and give them a personal experience.

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Pop-up stores are taking on a new role in China. Easy implementation allows retailers to create a unique and exciting new experience for consumers while also driving traffic to physical locations and gaining access to their data through interaction. This Tory Burch pop-up store in Shanghai seamlessly integrates new experiences to increase brand awareness for a spring line released earlier this year.

Upon entering, guests can hear the sound of waves and birds over the ocean. They can look through binoculars to see a video of models wearing the new products on a boat.

Passing through that room, guests are led through a tropical walkway that leads them to an interactive VR photo booth where a tropical bird flies in and lands on their hand. The photo can be saved through bookmarks on WeChat.

The last interactive element was a matching game where guests could match different material swatches. After each match was made a picture of the product made from the material or a description about the material would appear on the screen. If the game was completed within the time limit, guests could follow their official WeChat account and receive a coupon for a free gift if they went to their official store in the shopping center.

Giving the consumers the opportunity to interact with the new fabric collection and follow their official WeChat account, the retailer can correlate the most popular items purchased from the new collection to the followings from the specific retail location. This correlation will allow the retailer to streamline their inventory in specific retail locations.

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3. Price Optimization

Retailers no longer have to guess when the demand for a certain product has decreased or struggle to discover the market price for goods in their stores. Big data allows companies to track each transaction that occurs and use it to predict the demand for the products. This allows them to select a price they know is correct and can be changed at any minute if demand were to change. In addition to this, retailers to optimize their inventory which can lead to big savings. Big data also allows retailers to keep track of competitors and follow their pricing so they can respond accordingly, whether it is lowering or raising the price. Retailers everywhere are optimizing price using big data and it is creating more competitive pricing strategies in the market.

McDonald’s utilizes price optimization through testing of different markets. The use of instore kiosks, mobile apps, delivery help them to determine the right prices for the right market while also curving consumer habits.

 

Results

Ultimately big data gives retailers more realistic views of their consumers, target market, and purchasing habits. This data allows retailers to build stronger connections to their consumers to increase sales. Additionally, big data allows retailers to optimize their inventory in each location, allowing them to save millions by only ordering products that their consumers want. Strategic implementation of big data tools through marketing and retail operations can make retailers more successful in China.

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