To build your data analytic models we do need to take data from your e-commerce (and offline) sales records, we will analyse your data, propose & validate 9 customer lifecycle stages using Recency, Frequency and Monetary classifications for each buying persona.
The technical specifications to provide us with your transactional data file are set out below:
- We recommend at least 3 years of historical transactions data.
- The file presented must be a CSV file
- The filename must match the format “transactions_[unique suffix].csv”
- E.g. “transactions_march2020.csv”, “transactions_20200310.csv”
The file must contain the header row as follows: “Transaction_ID,Email_Address,Purchase_Date,Purchase_Amount”
The file must consist of the following columns of data:
- “Transaction_ID” – These must be unique and numeric
- “Email_Address” – as per standard format of an email address
- “Purchase_Date” – We can accept purchase dates in the formats stated in Table 1 below
- “Purchase_Amount” – This must be in a single currency and should not present a currency symbol. It should also be a plain formatted float, eg 9999.99 without any commas or other separators
Required Date Format
The following are accepted date formats, but the internationally recognised standard ISO-6801 format is preferable:
2020-03-03T13:38:11 (preferred) 25/04/2012 14:14 25/04/2012 14:14 2012-02-22T11:47:34.874
- We require a sample file of at least 1 transaction initially, to validate the field formats – Your Onboarding Project Manager will provide you with a link to our encrypted transfer method ‘Owncloud’ for you to drag and drop your file into. They will then confirm receipt and confirm if the data formatting is acceptable.
- Our Sysops team will then create & provide you with an SFTP location so you can transfer us your full transactional history file, and setup the e.g Daily recurring delta changes from then on.
- Drop all your historical transactions on the agreed first drop date
- Then only delta changes from the 2nd drop onwards, based on the agreed frequency, weekly is preferred.