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Abstract: Everyone has their own traditional scene of "Pro-Orange". Consumers come to a super mall and are very excited and lost. Why? There are too many brands gathered in a mall, the area is too large, consumers are very excited and lost. After entering the venue, they don't know anything about the brand and event information in the venue. They can only build their cognition of the mall in fragments during the process of "going around".
Everyone has their own "Orange"
In the traditional scenario, consumers come to a super mall, excited and lost. why? There are too many brands gathered in a mall, and the area is too large. After consumers enter the mall, they don’t know anything about the brand and event information in the mall. They can only build their cognition of the mall in fragments during the process of “going around”. We often see consumers in shopping malls, open group buying/takeaway apps, first search for information, and then open AutoNavi indoor navigation to go to designated stores. Therefore, in offline scenarios, the intelligence and personalization of consumer experience have not been realized.
▲Personalized recommendation by word of mouth
In Pro Orange, consumers stand in front of the "Thousands of People, Thousands of Faces" advertising screens, and they will get on-site recommendations matched by user preferences and needs. Or open the Koubei App to get a personalized "Qianchengli" based on the user preferences of [Youmeng+] and LBS data, which is the connection and connection between the online App and the offline consumption scene. From this extension, consumers can get a portable "shopping assistant", which can pre-match the brands and consumption routes in the mall according to the user's preferences and recent needs, so as to improve the shopping experience.
Light deployment highlights core data capabilities
Regardless of the "Thousands of People, Thousands of Faces" advertising screens or personalized "Word of Mouth App" recommendations, they are all improving the matching efficiency of consumer demand. The core behind this lies in the underlying data and technical capability support.
▲ "Thousands of people and thousands of faces" advertising screen
Taking the "Thousand People, Thousands of Faces" advertising screen as an example, the deployment method is very simple and only requires four steps:
1. Configure intelligent hardware: the cost of the interactive screen is very low, only need to modify the hardware and add a data acquisition module;
2. Personalized materials: establish a library of advertising materials, and classify the brand and activity information in the mall;
3. Back-end data docking: The back-end API is docked with the data of 700 million real active consumers of [Youmeng+]. From the technical level, [Youmeng+] can achieve second-level user preference matching and dynamically call advertising materials;
4. Data optimization and precipitation: In the actual operation, through the data monitoring background, the user behavior data is accumulated, and the material content is dynamically optimized, such as the design style/type of event information, etc., to better meet the needs of shopping mall passenger flow
The whole system is based on the global data capabilities of [Youmeng+] and Oplus' offline intelligent recommendation engine. The front-end display is low-cost and light-to-deploy, and the back-end heavy data and technical capabilities have been packaged. Two major abilities are tested:
1. The breadth of group coverage and the depth of individual identification. That is, whether the data covers the users of the entire network, and whether the interests and preferences of a specific user group can be described in a fine-grained manner.
2. Data access, intelligent identification and computing capabilities. When a consumer stands in front of the interactive advertising screen, the millisecond-level calculation and recognition will simultaneously display the product information.
The value of data
The value of innovative black technology is to empower consumers and brands through data, improve the matching efficiency of shopping needs and the efficiency of obtaining information. For brand owners, offline dataization and online and offline data integration can enable consumers to be online in all scenarios.
1. Gain a deeper understanding of consumers and accumulate data assets.
2. Improve store operation efficiency, organize goods, and customers self-service shopping.
For example, through the thermal dynamics of passenger flow, we can grasp the popularity of the store and optimize the layout in the venue; according to the preference of passenger flow, we can optimize the categories. In short, it is based on user preferences to promote in-store conversions.
3. More accurate investment strategy to realize the survival of the fittest in stores.
Same as the previous point, the investment promotion is scientifically supported by the user preference and store popularity, and the floor effect is improved.
4. Offline traffic operation and activation of remote stores.
The traditional retail industry emphasizes location/location, because affected by physical factors, the direction of passenger flow determines the popularity of the store. And when we divide the passenger flow into different groups by means of data and personalized recommendation methods, we can reduce the physical impact, activate remote stores, and make the traffic distribution in the mall more uniform, which also improves shopping. environment.
Black technology, can I have a dozen?
I am an ordinary brand retailer without a huge budget. I want to maintain steady growth in performance, and I also want to try some new retail as soon as possible, and I hope that I can get operational help after I try it. Is this the Arabian Nights?
Judging from the maturity of the industry's development, offline big data operation tools already have a mature system, and the cost of many data black technologies is affordable. For example, interactive advertising screens and smart shopping guide screens are priced in the range of 1,000 yuan to 10,000 yuan. Brand owners can start with a few stores, start with marketing scenarios, make them more refined and implemented, improve the efficiency of a single store, and then quickly replicate the experience.
In the process of choosing a new retail data service provider, to avoid some misunderstandings, we can start from two points. New retail emphasizes data reconstruction of people and goods yard. The data here is not only the brand owner's own data, but also interacts and opens up with external data, otherwise it is "closed-door big data". Then, whether the new retail data service providers have enough data volume and quality, and whether they can connect with business data, this is the first key point. Second, the offline retail industry is very different, and the business models are also different. We should try our best to choose partners that match our own industry or have basic data platform capabilities.
It can be said that Qinchengli has once again refreshed the industry's perception of new retail. So, are you ready to meet these data black technologies?