Executing automated shopping tasks

A system comprising one or more computers and one or more storage devices storing instructions that when executed by the one or more computers cause the one or more computers to perform operations comprising:

• extracting one or more line-item purchase information data elements from an image of a purchase receipt, each data element comprising an item name, a quantity, a unit price, and a tax, wherein the image of the purchase receipt is a scanned image of the purchase receipt, or a digital image of the purchase receipt generated by using optical character recognition (OCR);
• retrieving, for each data element, expected item pricing data and expected tax data from a retailer-specific database indexed by region and date;
• identifying a data element having a difference between a unit price represented in the corresponding data element and an expected unit price represented in the corresponding expected item pricing data, the difference meeting a configurable threshold, wherein the difference is a corresponding purchase price discrepancy;
• constructing a discrepancy report having a structured data format, wherein the discrepancy report comprises receipt metadata, itemized differences, and recommended claim language;
• and
• transmitting the discrepancy report to a retailer system over a preferred communication channel determined by a retailer profile associated with the retailer.

An apparatus comprising one or more computer storage media that stores instructions that when executed by one or more computers cause the one or more computers to perform operations comprising:

• extracting one or more line-item purchase information data elements from an image of the purchase receipt, each data element comprising an item name, a quantity, a unit price, and a tax, wherein the image of the purchase receipt is a scanned image of the purchase receipt, or a digital image of the purchase receipt generated by using optical character recognition (OCR);
• retrieving, for each data element, expected item pricing data and expected tax data from a retailer-specific database indexed by region and date;
• identifying a data element having a difference between a unit price represented in the corresponding data element and an expected unit price represented in the corresponding expected item pricing data, the difference meeting a configurable threshold, wherein the difference is a corresponding purchase price discrepancy;
• constructing a discrepancy report having a structured data format, wherein the discrepancy report comprises receipt metadata, itemized differences, and recommended claim language;
• and
• transmitting the discrepancy report to a retailer system over a preferred communication channel determined by a retailer profile associated with the retailer.