The value of business data has greatly grown and will continue to expand in the rise of the Internet era.
To better target customers, most businesses would establish an online presence or establish physical stores for their businesses. And effective data integration from different commercial channels is vitally important for today’s retailers – online retailers who are opening physical stores or local retailers who are opening online stores for gaining valuable insight more accurately and comprehensively, thus creating greater economic efficiency and consumer benefits.
1. Provide a personalized brand experience and a coherent brand experience.
It’s vital to build a seamless channel experience across all channels. For example, beginning in early April 2013, Uniqlo achieved transformative and rapid growth in mainland China using full channels including local stores, the official Uniqlo site, flagship stores on the Tmall B2C platform, and the mobile App. Uniqlo used its mobile App to support the features such as online shopping, QR code scanners, coupons, offline store inquiries and etc. You would redirect to its flagship stores on the Tmall B2C platform if you used the “online shopping” feature, while the coupons and QR code were only available when you used the mobile App and shopped in its physical stores. Therefore Uniqlo achieved the goal to attract its customers from the mobile Apps to physical stores. By scanning the QR code, you can get the product description and real-time inventory and Uniqlo-supported mobile payments such as Alipay(zhi fu bao) and WeChat Pay in all the physical stores.
Thanks to the data integration from all channels and quick action, Uniqlo has created a seamless brand experience. Through a customer-focused transformation, Uniqlo establishes a unified customer data profile and positively meets the needs of customers for a good shopping experience at any time with the right big data technologies. Besides, Uniqlo narrows down the focus of its target customers to provide rich and accurate messages that resonate with smaller accurate groups during the process of distribution, production, and services offered.
2. Optimize inventory deployment across all channels.
If the retailers don’t understand the inventory situation and the correct channel inventory allocation by using real-time internal data, their businesses cannot survive long. Previous inventory deployment strategies cannot deal with the issues of storing data collected from all channels, data integration, and data application.
When the Nexus 4 smartphone(LG Nexus 4 or LG Mako) was released, Google did not hold any pre-sale. This means that the demand is almost unpredictable. Those who want to be the first to use Nexus 4 had to wait in a queue for a long time at the physical stores and most of them eventually left gloomily because the smartphone was out of stock in mere minutes. In the meantime, Google’s online ordering had been paralyzed for the big traffic and was restored two days later, while the customers were told to wait a few weeks to buy a cell phone.
To solve the problem, it’s necessary for retailers to check the overall actual performance from all sales channels in real-time, integrate the data in time for better feedback and prediction for all sale channels and thus accurately deploy inventory resources through the channels in advance and improve inventory management.
3. Better identify and adapt to customers’ needs.
It is important for retailers to understand the way customers shop across channels, which is conducive to heightening brand awareness and making arrangements for inventory development. In cross-channel retailing, the ability to understand and adapt to customers’ needs ultimately depends on the ability of each channel to extract data from all channels and integrate and understand the data extracted.
For example, you can track online consumer behavior with the help of advanced technology – exactly a customer’s movements across the Internet and analyze the data collected. Thus you can present them with the right, relevant goods and therefore better understand your potential customers.
Data is generated every time shoppers visit and interact with shopping sites, and the data is usually unstructured which is hard to extract and sometimes some data is not even collected. When the data collected is not comprehensive, you cannot correctly understand what causes a click on your site and what content has been clicked and viewed. Without extracting and integrating data, you cannot make good use of online channels to optimize the sales process.
When Amazon realized that shopping cart abandonment is a big problem, it found out the reason – a tedious search process with too many steps when trading on the site. Then Amazon analyzed the customer behavior data and then created a new feature that enables its customers to checkout in only one step. In short, it’s essential to take advantage of your customer behavior data extracted across all channels for optimizing your online sales.
Multi-channel retailing takes time and effort. To enhance the chances of success in business, it’s vital to extract data from all these channels, integrate the data and then make a detailed analysis before making a prediction. For example, the success of Uniqlo hinges on its digital content marketing and key opinion leaders. Meanwhile, Uniqlo makes good use of historical data integration and establishes its own brand and reputation for product innovation to combine the customer’s in-store and online experiences.
In short, it’s very important for retailers to integrate data from all their channels – consolidate their online data and offline customer data that is distributed across different databases, and build more accurate customer profiles.