On this page:

Basic Requirements

One item per product group or ad group.
To use the Shopping Attribute Bidder, the shopping campaign needs to have a structure where each item id has its own product group or ad group. This is the lowest level at which the feed can be split and enables us to aggregate data at any level. To set up this structure you can use one of the following options:

Use the Shopping Campaign Builder to create one product group or one ad group per item id. It takes less than five minutes!
Use GRIP Structure tool to convert existing shopping campaigns into the GRIP (Group of Individual Products) structure without losing historical performance data.

Getting Started

Select the shopping campaign you want to get information for and select the date range. You can select multiple campaigns from the same feed to be considered in the analysis. Custom Date ranges are also available.

If your merchant feed has not been recently synced, you’ll need to re-sync it to Optmyzr so we can get the most up-to-date version of the feed.

Note: The Bids by Attributes tool only shows product groups for which bids can be changed. These are products that have their own product group. The lowest level at which a bid can be set.

Select Attributes

Select the attributes you want to aggregate data by.

Select Optimization Strategy

Show All: All active product groups irrespective of performance.

ROAS < 100%: All product groups with less than 100% return on ad spend (ROAS).

ROAS > 100%: All product groups with more than 100% return on ad spend (ROAS).

Custom Strategy: Create your own custom filters and save them as optimization strategies.

Reviewing Results

Review performance data aggregated by attributes like color, age, gender, etc, and set bids for selected product groups. You can also change the attributes selected for aggregating data.

Sorting Results

You can sort the table for any metric by clicking on it, and easily get to identify the Brand with the highest ROAS or category with the most clicks.

Sorting will also work when you do 2 - level aggregation, for example, if you aggregate performance for Brand > Product Type → and sort for ROAS, you'll see the Brand + Product Type combination that is getting the highest returns.