Companies often struggle to identify market changes early or respond quickly to competitive dominance. Additionally, they face challenges in successfully launching new products into the market.
Why we’re better
shopeyeQ Upsell Recommendation conducts a weekly benchmark analysis that compares the performance of sales locations and translates it into a category benchmark. This process continuously identifies and leverages market opportunities. If predefined thresholds are not met, automated upselling workflows are triggered, such as targeted store visits.
Empower Your Retail Success
Discover how our platform's advanced features—like dynamic clustering algorithms, real-time insights, and predictive analytics—empower you to drive smarter growth.
Data Utilised
This use case explores how POS clustering can reveal insights into retail performance by grouping similar points of sale.
Must be acquired.
Must be acquired.
Unemployment rate, inflation (provided by seQ technology).
Purchasing power index by postcode, age in the region (provided by seQ technology).
Map the customer journey
You provide us with your data, which we cluster in the background. We identify lookalikes for you and perform value-based segmentation.
1- Initial Data Collection
- Nielsen ID: The user provides their Nielsen ID.
- Data Review: We check if the correct data, such as Historic Sales Performance Data, is available or needs to be acquired.
- Data Provision: The data is provided to the customer’s cloud (S3, Azure, Snowflake, etc.).
2- Data Processing (Case 1)
- seQ Pipeline: Our seQ Pipeline processes, enriches, and clusters the data using machine learning, accessing current and historical performance data from the last two years.
- seQ Value-Based POS Clustering: Creation of a list of sales outlets with their respective cluster labels (value-based labels from 1 to 20).
- Ranking: This list is ranked based on our seQ score, which is reviewed weekly.
3- Benchmarking
- Weekly Sales Performance Comparison: We compare weekly sales performance per point of sale (POS) and translate it into a category benchmark for your product’s performance.
- Upselling Workflow Trigger: If the benchmark falls below a predetermined value, a predefined upselling workflow is triggered.
- Example: A store visit is assigned to the responsible employee.
Explore Similar Solutions
Do you often feel like you’re not noticing when a competitor becomes dominant in the market, or struggle with launching new products successfully?
To address these challenges, shopeyeQ Upsell Recommendation proposes the following solutions: First, we implement a category benchmark analysis that continuously compares your products with others in the same category. This gives you early insights into market changes, allowing you to respond quickly to dominant competitors.
An additional crucial step is the automated provision of upselling options to users. These options go beyond simple assignments, including new product offers and shelf securing actions. They are triggered individually based on various indicators like shelf audits or other performance metrics. Even when performance is good, the analysis continues; the results of shelf audits are fed directly into the AI, ensuring ongoing, precise action recommendations.
Furthermore, with Upsell Recommendation you can use defined thresholds to quickly respond to issues with specific products in supermarkets. For instance, if a product is struggling, the response time for similar products is accelerated by lowering the thresholds. This allows for a more flexible and effective market strategy that can quickly adapt to changing conditions.
These integrated Upsell Recommendation solutions enhance your market presence, improve competitiveness, and optimise the introduction of new products in an efficient manner. They ensure that you continuously identify and capitalise on market opportunities, solidifying and expanding your market position.
Optimizing Retail Insights
This section presents a series of case studies that demonstrate the transformative impact of POS clustering on retail operations.
Explore Similar Use Cases
Turn Insights into Impact with shopeyeQ
