This free, no obligation performance analysis will uncover:
    • Opportunities to earn more from your catalog
    • Ways to optimize performance across search, shopping, social, and discovery channels
    • Wasted ad spend and how to reduce it

Just Blow up Your Google Shopping Product Groupings, OK?

Still thinking about how to jump out in front of the competition in Google Shopping and other PLA channels? Let’s talk about that for a minute, because one suggestion we have for you … and don’t panic … is to blow up your current product groupings.

Wait — don’t panic! Humor us for a minute. People can’t buy what they don’t see (if you underbid) and you don’t realize an optimal ROAS if you overbid and overexpose.

But here’s the problem: Google requires you to put products into groups and assign those groups a bid. Most retailers and agencies, understandably, choose to group SKUs by brand (all Nike shoes in this group) or category (all baseball gloves in this group).

But this is an inherently flawed methodology. Assume for a moment that you have a high-performing Nike sneaker that costs $300, and another high-performing Nike sneaker priced at $50. Should those products be grouped together?

Your $50 Nike is performing — but is it performing 6x as well at the $300 Nike? That’s where it would need to be in order to justify grouping these two products together. And this method doesn’t take your unique return goals into account.

Let’s take a closer look at this:

A “typical” PLA product group looks like this: Products are grouped based on category/brand/style/price – determined by the company, and ‘similar’ products receive the same bid. However, it is very likely that the products in these groups – even though they share a ‘similar’ attribute– do not perform similarly.

However, there are products within your catalog that do perform similarly, and should be grouped together. The problem is that these products may not share product attributes. Rather, they share performance attributes. So your $300 Nike sneaker might be better placed with a Michael Kors watch if the performance attributes are similar.

We know, we know. Blowing up your PLA structure seems scary, overwhelming, etc. Fear not marketing friends, we’ve got some tips to help you get started:

1. Let it go.

Google doesn’t care about how your products are grouped; they simply require products to be put in groups in order for you to assign them a bid. In order to maximize your campaigns, you must let go of the idea that product groups should have a common attribute;  they don’t.  The only commonality that should matter is whether the products in a particular group perform similarly enough to warrant the same bid.

2. Break it out.

Test the “right bid, right product, right time” theory this way: Choose one top product in your catalog — something you know consistently performs well on both your site and in the Google Shopping channel. Let’s say it’s a North Face jacket. Chances are, you currently have it grouped with other jackets or other North Face products, which means it’s not getting the attention it deserves.

3. Take it a step further.

Analyze the products in a single brand (one that you currently manage in a single product group) and use performance data to break products out in three or four groups, putting like-performing products together. Then assign bids and use data to adjust those bids at least once a day. See the difference? Now imagine those results for your whole catalog.

4. Try this as an example.

Break the jacket out into it’s own product group; use the data you have to bid that product accurately. Revisit and adjust the bid consistently, and see the revenue from that product go up as the cost of sale decreases. While you’re at it, you might also break out one poor performer, and measure what you save by not bidding this item with the SKUs that are driving revenue.


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