For fast-moving consumer goods enterprises, the most direct way to influence consumers' choice is to let consumers see your products at first sight when they want to buy products.
Therefore, every year, brand owners will spend a lot of marketing expenses on occupying the layout and secondary display, so as to establish more contact points between products and consumers. But it is worth thinking about, brand owners have invested a lot of money, how is the implementation of market launch? What aspects of the sales plan could be improved? How to achieve a more efficient, accurate, and cost effective sales process?
A leading food and beverage brand in China is facing this challenge. They find that in the process of business management of 2 million + terminal stores across the country, the store data submitted by sales representatives in different retail channels (modern channels, traditional channels) and different retail scenarios (main shelves, secondary displays, etc.) face challenges of authenticity and efficiency.
They need to address three areas immediately:
How to get real store data?
How to effectively evaluate the performance quality of sales representatives through objective data?
How to write off market expenses intelligently and plan market expenses reasonably?
AI enablement improves the efficiency of retail execution in the whole scene
The improvement of store execution efficiency and the intelligent write-off of market expenses have always been the difficulties faced by the brand business department. Did the rep go to the right store? Is the product positioned where it should be? How can I sell more? How to convince store managers to order more products and increase awareness?
Enabled by AI and machine learning technology, the food and beverage brand changed the traditional methods of data collection and statistics and marketing expense verification through the cooperation with Trax, and helped the brand's 8,000 + sales representatives in China to upgrade the business ability of visiting stores in a short time through the digital control of store implementation standards.
With Trax store number intelligent solution, sales representatives only need to enter the store to take pictures of display, and these pictures will be transmitted to Trax cloud through API docking for intelligent scene identification and segmentation. No matter for shelves, vertical freezers, or special scenes such as end shelves, floor piles and box cutting, accurate identification can be realized. Then, through product identification at SKU level, KPI information such as distribution, number of layers, number of rows, product location and so on can be quickly obtained. In addition, the built-in anti-cheating detection system of Trax can greatly reduce the possibility of cheating in the remake, thus ensuring the authenticity and effectiveness of the pictures.
The brand owner not only quickly grasped the real data of the stores, but also quickly checked the real use of special display expenses through the identification of secondary display scenes by Trax, reducing the manual audit manpower and improving objectivity.
By completing more than 6 million picture recognition per month, the store execution efficiency of the brand has been improved by 59%. Meanwhile, the brand has gained insights into sales blind spot and distribution blind spot data, refined store operation and management, and improved the brand's overall shelf share and spread rate.
To learn how this national leading food and beverage brand quickly realizes store execution efficiency improvement and intelligent business management, please add Trax wechat public account to obtain Trax "AI Enabled Full scene Retail Execution" food and beverage industry best practices, to add power to your retail execution.
