As little as 10% of data errors cause 1,000 wrong decisions for 10,000 SKU products. High-quality data is essential for any analytics, automation and optimization system to work correctly and ensure the best results. Competera allows monitoring data collection at all stages while factoring in the business logic and goals of the retailer, as well as the peculiarities of the competitive environment.
Does your business receive competitor data in a convenient format, on schedule with a guaranteed quality and freshness level (SLA)?
Customer Success Team
Customer Support Team
We support our clients with full-scope data orchestration and aggregation for quick and seamless integration of Competera in your IT infrastructure.
We adapt the system’s integration to the retailer’s current operations. Our platform is compatible with any data regardless of its format and source, as well as of where it is stored and how it is processed, etc.
Multidimensional matches: title, EAN, UPC, images, units of measurement, etc., with two levels of verification, confidentiality scoring system and manual QA. Our clients could choose automatic, manual or hybrid product matches: Competera’s multilevel checking algorithm will ensure the best-in-class data quality.
Any data dimensions
Any type of stores and platforms
Any amount of products
Any speed velocity on-demand
High-score matches group
Low-score matches group
Low-score matches check-up
High-score matches check-up
Our human-guided matching algorithm and dedicated scraping system ensures the best-in-class dataset and data freshness
How Competera Competitive Data Scraping Powers Retail Enterprise
Your company can choose automatic, manual or hybrid product matches: Competera’s multilevel checking algorithm will ensure the best-in-class data quality
Our team fully manages a seamless and straightforward integration basing on the retailer’s technical and business expectations. A dedicated manager acts on behalf of the retailer inside Competera
We daily collect and deliver over 10 million data points about prices, product availability, promotional activity, among other metrics — any data available on a competitor website with custom logic, frequency, and freshness
Transparent delivery and matches: the percentage of product intersection by category and store, the time of product matches, the ratio between the delivered and planned data amount, the current scanning status, etc.
We guarantee the data accuracy and freshness, matching speed, integrating new stores and addressing daily inquiries. We are financially responsible for failure to fulfill the obligations
We scan websites and deliver data by the time the retailer needs it to react properly to the market changes and seize every opportunity to increase revenue
Competera helped us monitor the prices on our products at different markets, price aggregators, and marketplaces. Prices variations of our products are quite frequent in the market. Competera provides very useful tool for eCommerce purposes to monitor the products pricing across the online channel. Show more
I’m a current user of the Competera pricing software. I’d say the big task is done for the managers of product categories in the online channel. Online fully automated competitor’s price tracking helped us significantly reduce the time for data processing and product pricing. After the integration with the service our prices got protected from possible human errors. Show more
Having more than 7000 products in our range can be difficult to monitor from a pricing perspective. In the gift retail sector, prices change every day and for us to deal with all that new data is a real challenge. We wanted an accurate and reliable pricing solution that could help us be more price competitive and gain more profit per product. Show more
To increase revenue, we have adopted a mechanism within the pricing engine which can calculate demand elasticity while factoring in product cannibalization and seasonality. The solution has suggested the best promotional products and set the optimal prices based on competitive data, among other tasks. According to our estimations, the mechanism alone has incrementally increased revenue by 1% over the period of three months Show more
We were looking for an algorithm-based solution which could scale and consider all the factors which influence prices and which we usually neglect. We realized clearly that our managers would not be able to handle all of these variables, including all our historical data spanning 24 years, and offer optimal prices in real time. We could put together a whole department of data scientists instead, but it would take a long time and cost a lot. So, we preferred a technological solution from Competera and raised our revenue by 16%. Show more