Competitor monitoring case study: Pricing automation for food delivery company
Discover how a $1 billion food delivery service boosted its income by using pricing automation and price optimization strategies.
About the Client
The client provides a fast delivery service for food and FMCG products, utilizing the 'dark store' model. Their main focus is fast delivery, where orders are fulfilled from a warehouse that assembles goods specifically for online requests, which are then dispatched for delivery. These warehouses are located in more than 100 cities, and in each city, the retailer competes with local 'at home' format stores and other large retailers.
0 regions
0 dark stores
0 orders per day
Client Challenges
• The requirement to promptly re-evaluate a large product catalog of over 100,000 SKUs
• The necessity to compete with different delivery services in each city where they operate
• The need to collect competitor pricing across different sales channels
• The need to quickly match new products within their catalog with all competitors
• The requirement to rapidly scale price collection in case of launching in new cities or the appearance of new competitors on the market
The main details of the project
Data must be collected for millions of SKUs
Price collection solution needs stable functioning
Throughout the project, we prioritized rapid, large-scale data collection and system stability. We duplicated data from major competitors to reliably provide the client with essential analysis data.
Large catalog updates
Regular matching of new products is necessary
FMCG catalogs are highly dynamic, with products changing frequently.
This leads to the requirement for regular matching of product updates in client's catalog with product updates in competitors' catalogs.
New requirements frequently emerge
The customer often needs to include new competitors
To promptly address the customer's evolving needs, including adding new competitors and testing store in a new location, we assigned a skilled manager to ensure fast and efficient support.
Solution
• Setting up data collection based on customer requirements
• Matching the product catalog
• Configuring the repricing module
• Generating reports for managers from different departments
• Providing a dedicated account manager for prompt support
Project stages
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1
Customer requirements
We gathered customer requirements and reviewed the competitors' websites
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2
Scraper development
We developed a scraper that collects all the necessary data
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4
Product matching
We matched customer's products with the competitors' products
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3
Data processing
Setting up the repricing module and generating reports
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5
Testing and launch
System stability testing and commercial launch of the project.
Implementation
A few words about customer’s task implementation
Product Matching
One of the main tasks for the client is to obtain prices for a matched catalog of their products. This entails the need to match newly added products in the client’s catalog with those in the competitors’ catalogs before collecting prices.
To achieve this, we use a hybrid matching method that combines the use of unique identifiers and machine algorithms and the most complex cases are handled by content managers. The results of the machine matching process are subsequently reviewed and approved by the content managers.
Data Collection
The client needs to monitor large number of competitors in more than 100 locations across several sales channels. Ensuring the right volume of data arrives at the appropriate time is of really importance. To achieve this, we have done:
- Optimized our scrapers for efficient data retrieval
- Configured the advanced collection of data from key competitors
- Arranged for the collection of additional information that will assist the client in improving product procurement and making more informed business decisions
Repricing
In the initial phase, we conducted product catalog segmentation to kick-start the repricing process. Subsequently, we collaborated with the client to establish guidelines for repricing products. After conducting test runs and confirming the accuracy of the figures from the repricing process, we activated the repricing module to transfer the new prices to the customer.
Data Transmission
Multiple departments within our client’s company demonstrated a need for immediate access to competitor data. This included the repricing department, the procurement department and the analytics department. To cater to their specific needs, we developed customized reports and set up data delivery channel.
