3 Ways to Optimize with Google Shopping Dimensions
Gypsy’s Dispatches from the SEM Trenches
While bid management and negative keywords are the most important day-to-day management tasks for Google Shopping campaigns, the Dimensions tab gives data geeks like myself a number of additional opportunities to maximize performance. Here are a few of my favorites:
1. Identify Outliers in Spend, Impressions, or Conversions
The Dimensions tab provides a clean, exportable view that’s easier to sort than the data in the Product Groups tab. Additionally, data views in the Dimensions tab are not limited by the current campaign or product group structure. I use the Product Type, Category, and Brand dimensions to gauge performance of these product groupings without regard to where they live in the product group tree.
One outlier in the case above is the “hedge trimmers” category, with a CTR far below that of its neighbors. If you compare this data to what you see in the search terms, you can make more informed decisions on negatives or bid adjustments outside regular models.
Often, these findings lead into my second step:
2. Assess the Need for Product Group Breakouts or Restructuring
For most accounts, I base my product groups on category breakouts (either by product type or Google category) rather than brand. But if you see a particular brand driving a large amount of spend or disproportionate conversions, you can subdivide the groups in the current structure by that brand to better control performance.
In other cases, you can subdivide by a particular Item ID. In the case above, all three items are variants of an apparel product. The third product listed is the same as the first two but features a bright pattern instead of a solid color. In this scenario, it makes sense to break out the poorest performing item ID and assign it a lower bid, thus increasing the likelihood that the other two products will show on those queries.
If a particular product grouping shows drastically different performance metrics than others in the same adgroup, I will sometimes move it into its own adgroup in order to better tailor the negative terms. I may even create a separate campaign if the campaign controls for budget, devices, or location will assist in managing performance.
Of the Dimensions tab’s many uses, I saved the best for last:
3. Troubleshoot Google Shopping Data Quality
Sometimes I see results on Google Shopping that don’t quite fit. The search result in the image to the right did not involve any of my accounts, but is a good reminder that product data can be less predictable than keywords.
If you see an unusual spike in impressions (and sometimes clicks) without a corresponding increase in sales, dig deeper by comparing outliers in the Item ID dimension to the search terms. You can then look up the Item ID in the Google Merchant Center to see if you can figure out what terms in the title, description, or any other field might be leading to the disconnect.
For items of clothing, sometimes a unique color name (stainless steel, stop sign, snorkel) triggers irrelevant queries. To address this, remove colors from the product title or replace them with a more generic color name.
Low traffic volumes can also indicate a data issue. I’ve worked with several manufacturers whose products weren’t showing as consistently as many of their resellers. So what was the problem? After a bit of digging, I found that their product titles did not include their brand name. On one such account, we added the brand to the beginning of the titles and saw both traffic and revenue more than double within two days.
The more time I spend working with the data in the Google Shopping Dimensions tab, the more insights I discover to tie together data quality management, campaign structure, and bidding strategy. Do some exploring and let me know what you find!
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