By Helena Clark

Google are changing the way we manage Product Listing Ad (Google Shopping) campaigns with a new AdWords campaign type & new features. Find out what we think about them.

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Google announced the release of shopping campaigns back in October. These have been quietly rolled out globally this week. A few of our lucky accounts were accepted onto the initial beta so I'm going to run through my love-hate relationship with them so far. There are a lot of cool features for easier management and also competitor insight which isn't available with the current PLAs. However, there are some basic optimisation features you lose. Read on to find out more.

Why do we love PLAs so much?

PLAs are the bread and butter for so many e-commerce accounts. A picture tells a thousand words and so we tend to see ROI on this ad type outperform our search campaigns because users know exactly what they are clicking through to. Product listing ads saw a year on year growth of 200% in September and there are now over 1 billion products advertised globally.

However, some of the current features in PLAs have made management and set up a little more difficult. Currently we can add product targets for product ID, product type, brand, condition, adwords labels and adwords groupings.

Current problems with the standard set up of this:

  1. Overlap – if 2 of your targets contain the same product in their target it is generally the case that the higher bid wins. If you create a brand ad group and a few product ID ad groups you have to be very organised to make sure the bids stay at the right level, so traffic flows where you want it to.
  2. Time consuming - it is a case of choosing a target you can see in the feed, hitting verify and crossing your fingers that it picks up some of the products in that target. If you want to create lots of targets this is a pretty time consuming process.
  3. Organisation – this requires labelling in feeds to be kept very clean or you could be missing out on some products in your desired targets. Feeds tend to be pretty huge so sometimes this is easier said than done.

So, what was our solution here? One of our super geeks built a tool so we could turn a whole merchant feed into product specific ad groups in the space of a few minutes. This meant we knew every product in a feed was being covered. We could see our best and worst performing products, we can see what searches are triggering individual products. This set up gives us a lot of control over what our product listing ads are doing.

When the new Google Shopping Campaigns were announced they said they would provide the following:

  • An easier way to manage PLAs
  • Competitor landscape data
  • Advanced reporting
  • Access to the live merchant feed

I was pretty intrigued as this offered everything and more than we had built with our PLA tool.

The Shopping Campaigns interface

These are the tabs you see in a Shopping Campaign:

Google shopping product tabs

Product Groups - Where you create your product groups and manage their bids.

This is the most important tab and I will go into more detail below. It is where you can build your campaign using the attributes in your feed and also see benchmark data.

Products - Access to an up to date feed. This is a great feature that allows us to see live data from within a merchant feed.

Settings – Campaign level – the new part here is the advanced shopping settings.

Set different campaigns with a high, medium or low priority. The bid doesn't play a role in the hierarchy any more. If two campaigns have overlapping targets the high priority campaigns will trump the low or medium priority.

Ads – One promotional text at campaign level.

First negative mark – Standard PLAs let us do this at ad group level. This is great for products on promotion. Now promotional lines have to apply to all products in your campaign. Also, only allowing one promotional text per campaign means there is no facility to test copy.

Keywords – Add campaign level negatives. There is currently no search query report here.
Second negative mark – some keywords work for some products and not others, so adding a blanket negative across all products in a campaign is another feature taken away from our old set up.

Dimensions – Your usual dimensions with an added shopping report. This is currently the only place to see search query reports and device performance. This is also only at campaign level and you can't see which product or targeting group triggered which search term.

3rd negative mark – search query data at product level has been invaluable to our optimisations of our product specific PLA campaigns. There is also not a simple way to exclude these search queries from the campaign.

The Product Groups tab

This is where to see your main metrics by product target. You can also see competitive landscape data. Shopping campaigns allow us to see the following metrics:

  • Benchmark CTR & CPC – compared to other competitors appearing on similar products
  • Impression Share – of all the auctions you were eligible for
  • Bid Simulator (coming soon) - See how much traffic you would receive on a product group by altering the bid

They also allow us to organise our inventory. Organisation is simple as the campaign is linked to your feed. When you create a campaign an 'all products' target is automatically created. From this point the + is the key to creating more granular bids for specific products & groups of products. You can create product groups on the following attributes.

feed attributes

For each of these attributes you can see how many products sit within each one and add them in. Each product group can be subdivided up to 7 times. The historical data is at product level so if you decide to further segment one target the data is backdated.

product targets

Also, notice there is no longer and AdWords label or grouping target but we now have a custom labels column. These custom labels are a bit more flexible and allow you to add labels specific to your products to create product targets and campaigns. Add labels for attributes such as high ROI products, seasonal products and products on sale. An interesting way we can use these is to have our standard campaign that covers all products with a low priority setting and our standard ad. If a group of products is on promotion and we want to push them we can create a high priority campaign with an individual ad for these products by using the custom labels.

Once you have added segmentation to a target you can set a bid for each segment (see below). The clever feature here is that an “everything else" target is then created. This is again another way that shopping campaigns avoid overlapping targets.

shopping campaigns bidding


The table below is a comparison of the different campaign types we can use currently for Product Listing Ads. The first two are traditional ways of running PLA campaigns, the third shows the new Google Shopping campaigns.

camapign comparison table

Overall I think Shopping Campaigns are really exciting. They are still very new so a few bits still need to be ironed out by the Google tech team which is why I don't see us utilising them fully until this is implemented. The biggest one here is losing the ability to have search query data and negative keywords at targeting group level. This makes up a large part of how we currently optimise and report on product listing ads so losing this functionality is quite a big downside.

The biggest and best addition is the competitive landscape data. This is going to offer us huge insight on how much further we can push our campaigns. Impression share will show us how many auctions we are missing out on. If our cost per click is low and clickthrough rate is high we know our feed and strategy is working really well. If clickthrough rate is low this could indicate needing to improve feed images or that our prices are higher than our competitors.

Having data as deep as ID level in the dimensions tab is very useful, allowing you to quickly see which products are working and which are not. Our current set up of standard PLA campaigns means we have to have an ID level target for every product to see data at this level. Not all campaigns need to be this granular so this could make overall optimisation much faster.

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