Daily or weekly data feed of all relevant logistics and shipping data in raw form delivered via AWS S3 bucket. Our data feed provides our client's the ability and flexibility to leverage our e-receipt dataset to answer their business questions. We train you on the nuances of transaction data and provide client support to make you successful in using the dataset on your own. Edison's data feed includes a few components: 1) User level data (user panel) - We provide a user panel dataset to help understand panel level metrics, make adjustments for panel growth, and extrapolate from our sample. 2) Receipt data - Each email receipt we observe is parsed based on the most advanced approach combining deep learning and human coding. We follow a standardized structure when categorizing values in receipts and try to account for edge cases. Each row in this dataset represents a unique item on a receipt.

Daily or weekly data feed of all relevant grocery purchase data in raw form delivered via AWS S3 bucket. Our data feed provides our client's the ability and flexibility to leverage our e-receipt dataset to answer their business questions. We train you on the nuances of transaction data and provide client support to make you successful in using the dataset on your own. Edison's data feed includes a few components: 1) User level data (user panel) - We provide a user panel dataset to help understand panel level metrics, make adjustments for panel growth, and extrapolate from our sample. 2) Receipt data - Each email receipt we observe is parsed based on the most advanced approach combining deep learning and human coding. We follow a standardized structure when categorizing values in receipts and try to account for edge cases. Each row in this dataset represents a unique item on a receipt.

Daily or weekly data feed of all relevant travel purchase data in raw form delivered via AWS S3 bucket. Our data feed provides our client's the ability and flexibility to leverage our e-receipt dataset to answer their business questions. We train you on the nuances of transaction data and provide client support to make you successful in using the dataset on your own. Edison's data feed includes a few components: 1) User level data (user panel) - We provide a user panel dataset to help understand panel level metrics, make adjustments for panel growth, and extrapolate from our sample. 2) Receipt data - Each email receipt we observe is parsed based on the most advanced approach combining deep learning and human coding. We follow a standardized structure when categorizing values in receipts and try to account for edge cases. Each row in this dataset represents a unique item on a receipt.

Daily or weekly data feed of all relevant food delivery and restaurants data in raw form delivered via AWS S3 bucket. Our data feed provides our client's the ability and flexibility to leverage our e-receipt dataset to answer their business questions. We train you on the nuances of transaction data and provide client support to make you successful in using the dataset on your own. Edison's data feed includes a few components: 1) User level data (user panel) - We provide a user panel dataset to help understand panel level metrics, make adjustments for panel growth, and extrapolate from our sample. 2) Receipt data - Each email receipt we observe is parsed based on the most advanced approach combining deep learning and human coding. We follow a standardized structure when categorizing values in receipts and try to account for edge cases. Each row in this dataset represents a unique item on a receipt.

Daily or weekly data feed of all relevant retail and apparel data in raw form delivered via AWS S3 bucket. Our data feed provides our client's the ability and flexibility to leverage our e-receipt dataset to answer their business questions. We train you on the nuances of transaction data and provide client support to make you successful in using the dataset on your own. Edison's data feed includes a few components: 1) User level data (user panel) - We provide a user panel dataset to help understand panel level metrics, make adjustments for panel growth, and extrapolate from our sample. 2) Receipt data - Each email receipt we observe is parsed based on the most advanced approach combining deep learning and human coding. We follow a standardized structure when categorizing values in receipts and try to account for edge cases. Each row in this dataset represents a unique item on a receipt.