A campaign runs in March with three interest-free installments, and in April, same targeting, same creative, with twelve. April average order value comes out well above March, and the team reads it as an improvement in ad targeting. What actually changed was how much the same buyer could afford per month, not who the ad reached.
Buyers choose by monthly installment, not total price
When interest-free installments expand, the buyer is not evaluating the product list price: they are evaluating what is left of their paycheck each month. A product that was out of budget at three installments becomes affordable at twelve, and the sales mix shifts toward pricier items. That shift raises the campaign average order value without anything actually changing in how the campaign is built or targeted.
This is not exclusive to electronics or branded apparel. It hits any category where product price is sensitive to the available monthly installment: furniture, travel, appliances. The pricier the category average order value, the more visible the effect when financing changes.
Where the comparison gets misread
The most common mistake is comparing ROAS or average order value across two periods with different installment offers and crediting the whole difference to the campaign. It happens often around seasonal sale events, when the number of interest-free installments expands beyond what is offered the rest of the year: the seasonal campaign will always show a better average order value, and part of that gain is financing, not media.
How to separate product mix from real performance
- Log how many interest-free installments were active in each period you are comparing. Without that data, any AOV comparison across months is a blind one.
- Split average order value by the number of installments chosen on each sale. If overall AOV rose but AOV within each installment tier stayed flat, the change is a mix shift, not a targeting gain.
- Compare campaigns against periods with the same financing offer when the goal is to measure a real media gain, and keep the comparison across different installment offers for measuring the financing effect itself.
- If the goal is selling a higher ticket, expanding installments is a pricing lever, not a media one. Measure its result as such, separate from campaign performance.
It is the same logic behind why attribution models can credit the wrong channel: before crediting a campaign for a number that improved, rule out that the number improved for another reason. It is also the standard we apply in performance marketing for Argentina: reading a campaign result starts with controlling for the variables that are not the campaign.
If your average order value rose right when you expanded interest-free installments, you probably have less of a media gain than the dashboard suggests.