After we have successfully laid out the online and offline channels, a common question arises: What should we do when the customer data on the two channels cannot be integrated and it is difficult to identify and make better analysis and predictions due to data fragmentation? This is also a big challenge for retailers: having a lot of data but not being able to analyze it well. Therefore, the focus of virtual and real integration (OMO) is: "turning data into valuable information". After properly using data, we can understand the preferences and purchasing behaviors of offline consumers and master their online behaviors, which has become the basis for today's creation One of the key elements of a better customer experience.
As one of the major retail channels in Taiwan, Quanlian Welfare belgium phone number data Center uses the AIXON customer data science platform to integrate offline store transaction data to strengthen its digital strategy and instantly convert Quanlian's offline transaction data into usable structured data or tags. Integrate with consumption data from the official website and App to improve customer profiles and generate consumption insights in real time. For details, please refer to: Appier helps Quanlian strengthen OMO digital strategy deployment .
When the database is more complete, it will be able to provide suitable product recommendations and services based on each consumer's attributes and preferences. Based on the precise "consumer-centered" marketing strategy, we will create a better customer experience and let consumers No matter which channel it is, it can meet his needs and effectively improve shopping guide opportunities.
In the post-Cookie era, if brands want to grasp the whereabouts of consumers and spend their budget wisely, they are limited by the inability to identify cross-device data. We need to maximize the full potential of first-party data while respecting Under the premise of consumer privacy, it helps brands collect complete consumer profiles and make more accurate predictions.
Use AIXON to construct the user's Intelligent User Profile (Intelligent User Profile) based on the user's browsing time, device, location, events, keywords, interests and other information after entering the site to identify anonymous visitors and their potential behaviors. It can extract user characteristics for probabilistic matching and establish a comprehensive customer profile without recording personal identity information; at the same time, it can automatically mark preference tags and predict customer interests, make up for the shortcomings of historical and behavioral data, and help brand owners improve their segmentation. Strategies to accurately grasp customers’ intentions and achieve the purpose of personalized and precise marketing. For details, please refer to: Appier’s Guide: Showing Up in the Post-Cookie Era .