Understanding Attribution Reports
To generate attribution reports in Poplar, transactional (order) data must be shared with the platform by one of three ways:
- Manual CSV Upload
- Poplar's Shopify App
- Orders API Integration
If you haven't shared transactional data using one of these methods, Poplar will not be able to calculate attribution metrics. If you did not set a Holdout group for your campaign upon mailing, the platform will not be able to calculate Lift metrics. Attribution reports are updated as transactional data comes into our system. If you change your attribution window at any point after setting up your campaign, it will take time to refresh and reload your new attribution data.
Poplar measures customer response to mailings using the last-touch attribution model. This means that we attribute orders to the most recent mail piece (within the attribution window).
IN THIS ARTICLE
The attribution window is the length of time after customers have received your mailing for which you want orders to count towards your campaign. You can set a custom attribution window when you create a new campaign, and adjust the window by editing an existing campaign. This is the period of time for which you wish to credit a customer's transaction to the mailing. By default, Poplar uses the recommended 90-day attribution window with a minimum option of 30 days.
Before your attribution window has fully passed you may begin to see results populate, but because these are incomplete, we suggest waiting until the attribution window has fully passed before evaluating the performance of the mailings.
Typically 60-70% of conversions will occur in the first 30 days, 20-30% in the 30 days following that, and around 10% in the final 30 days. The 90-day window is a Direct Mail industry standard, and is the best option to see the full scope of the numbers.
Adjusting this setting after reports have been generated will result in a wait time for re-calculation. Your attribution reports are updated as transactional data comes into our system. If you change your attribution window at any point after your set up your campaign, it will take some time to refresh and reload your new metrics.
The attribution window begins when your mailings are in-home. To provide a direct comparison across postage types and holdouts, there is a slight nuance to this rule.
Mailing B used First Class postage
For all mail pieces from A and B, including any holdouts in A and B, we would consider January 5 as the in-home date. This allows you to directly compare the results from all mailings on January 1.
You may select a reporting window to filter and see only mailings that were sent in that time period. In Poplar, reporting window refers to the date a mailing was sent (created manually or triggered). Please keep in mind that this is different from the attribution window. To view reports by day instead of by week, simply adjust the Reporting Window to only show the past seven days:
The Orders API allows you to specify whether transactions came from a new buyer (customer) or not. If you are using Poplar in any customer acquisition campaigns, or if you just want to filter your attribution reports by new customers, we recommend including this metadata through the Orders API.
We assume that all New Buyer data sent to our system is correct. Therefore, if Jane Doe made two orders and both orders were marked with the flag new_buyer: true your attribution reports would count Jane Doe as a new customer, twice.
Per campaign, the first matching order from each customer is considered unique and any subsequent orders from the same customer that are also attributed to the campaign are not considered unique.
A customer should only ever be reported as a New Buyer once, but per campaign you send out, each customer has a new opportunity to be considered unique. We determine whether or not a customer is unique (per campaign) based on a couple of data points and the likelihood the data point is available.
- The data points we consider are customer_id and customer_email.
- If neither customer_email or _id are provided, the platform will not be able to determine a customer's uniqueness. Address data cannot be used to determine customer uniqueness as a single address could map to multiple individuals.
The holdout metrics allow you to compare activity amongst the mailed group vs. customers who did not receive a mailer but converted anyway. If you opted for a holdout group when setting up or launching your campaign, the holdout group performance will appear right below the mailed group's metrics for easy comparison. If you did not enable a holdout for your campaign, the platform will not be able to calculate lift metrics.