Data Collection
Data Extraction
Data Store
Data Transformation
Data Sets Delivery
Our project is implementing a multi-channel data collection system to gather real-time pricing information. We will collect data via SMS, image uploads, email, and a web portal.
SMS Data Collection: Users will install a mobile app that automatically identifies and forwards SMS messages containing invoice links to our servers. These links will be processed to extract relevant product data.
Picture Data Collection: Users can upload photos of physical invoices to our web portal or through the mobile app. Image recognition technology will extract product information from these images.
Email Data Collection: Users can manually or automatically forward relevant emails to our system. The email content will be processed to extract product data.
Our mobile app offers a win-win solution for both consumers and our data collection efforts.
In today's digital age, consumers are inundated with countless SMS messages, making it difficult to identify important information like invoice links. Our app addresses this challenge by automatically filtering and extracting relevant data from SMS messages.
Additionally, by centralizing online invoices within our app, we provide users with a convenient way to manage and access their purchase history.
All collected data undergoes a standardized process of parsing, filtering, and categorization based on product SKU, price, and retailer. Personal information is omitted during the data insertion process. The processed data is stored for analysis and made accessible to users through both scheduled data exports and a real-time API.
The project will gather data from various sources, clean it up, and organize it into a usable format. This processed information will be available to users in real-time through an online service or in regular reports.
This data aids to it users with:
Time-series analysis:
Track price changes over time for specific products or retailers.
Identify price fluctuations due to promotions or seasonality.
Forecast future prices based on historical data.
Competitive analysis:
`Compare price positioning of different retailers.
Identify price wars or aggressive pricing strategies.
Analyze market share based on price competitiveness.
Product lifecycle analysis:
Track price changes over a product's lifecycle.
Identify optimal pricing strategies for different product stages.
Sure!
Dealavo
Repricer.com
Competera
Minderest
Price2Spy
More: https://dealavo.com/en/price-monitoring-tools/
Realy? - NOT!
Our data can be sold by offering it as a third-party data feed to competitors mentioned above. We can provide access to specific local market datasets defined by geographic boundaries and/or language.
Our prepared datasets are our core product and will be delivered to clients, including wholesalers, manufacturers, and consulting firms, via API, download, or email.