What is the Media Spending Influence tool?
The Media Spending Influence tool is an interface for media that doesn’t have a business manager (such as Meta Business for instance). That is the case of Influence.
Without a business manager, it is impossible for Quantic Factory to collect influence data automatically through an API. The data collection has to be done manually. This is what the Media Spending Influence tool is for.
We can only measure paid influence (influencers you paid to make content about your products), not organic influence. Two methods can be used to measure paid Influence:
through an UTM analysis, if there is a link in the influencer’s content that we can track,
through promo codes (you give a discount, through specific promo codes, to people seeing the influencer’s content). Thanks to the Media Spending Influence tool, we can include promo codes in customer journeys. This is a unique feature that brings insights into influence attribution.
Where to find the Media Spending Influence tool?
The Media Influence tool is located in the Parameter menu, in Quanticfy.
How to upload your data?
Step 1: put together your promo code data
We need your promo code data to be uploaded following this structure: one column for the cost, one for the date (DD/MM/YYYY format), and one column for the promo code. It should look like this:
You can download a valid example and an invalid example from the Media Spending Influence tool page. We accept data as .csv, .xlsx, or .xls files.
Step 2: Upload your file
Once your file is ready, click on Upload the Cost and choose the file from your device.
Our tool will check if the data submitted has the right format. If not, you will be able to see, in red, which cells are causing the problem. From there, you have the possibility to edit your data directly in the interface. You can also add new lines of data.
When all is in order, press Next.
The last step is column-name and content verification. To do so, we ask you to confirm which column of your file matches the date, cost, and promo code information.
Once this is done, you can click on Submit.
Precisions about your data
Empty values will not be accepted
Use a dot (.) and not a coma (,) for the decimal values (cost column)
The data you submit through the Media Spending Influence will be displayed in a few minutes in the “My uploaded costs” section rig. Then this data will be integrated into your dashboards the next day. For the upload of your data to be successful, each promo code must have only one cost per date. If the same promo code appears several times for the same date, it will cause issues preventing us from properly processing your influence data.
If you submit a file with multiple lines for the same promo code on the same day, one of these lines will be randomly picked as a reference and others will be ignored
If you submit the same promo code for the same dates with several cost values (for instance you first upload PROMO65 with a $20 cost on the 1st of February, then upload another file containing PROMO65 with a $30 cost on the 1st of February), we will only keep the value of the latest data. In this case, the PROMO65 promo code will be considered to cost $30. The latest cost value will erase and replace the previous value (here, $20).
How to delete your data?
If you want to clear your cost history, you may use two methods:
the Delete Costs form
uploading a new file with 0 values
The Delete Costs form (right under the uploaded cost table, on the Media Spending Influence page) is an easy way to clear everything between two dates. Pick a start and end date, and click Delete. Note that the days are included ( [from, to] ).
You may also upload a file cost with zero values. If you want to erase the existing cost for PROMO65 on the 1st of February, create a file with one line containing the following information:
Tips for your business
If your business relies a lot on Influence (more than 20% of your sales), we recommend you switch to another attribution model.
Quantic Factory uses a 7 days time decay attribution model by default (shown in the table below). In this model, hits are not weighted the same depending on when they occurred. This is relevant for most ad attribution through UTMs: ads seen (or clicked on) a week before the sale are considered less important for attribution than ads seen (or clicked on) the same day of the order.
This model is not suitable for Influence.
It makes promo codes overweighted in the attribution, as they are always used on day 0 (the day of the sale), with no prior appearances in the customer journey. This creates a recency bias that we can eliminate by switching to a flat attribution model. In this model, the coefficient for all days (D0 to D7) is 1:
To request an attribution model change, please open a ticket (using our chatbot).