Think of building a house. I’m sure there are several components which come to your mind immediately: walls, a roof or different rooms. The combination of these elements is what we call structure. The Oxford English Dictionary defines the term structure as “an arrangement and organization of interrelated elements in a material object or system, or the object or system so organized.”
- A Google Shopping campaign can have three dimensions
- Google Shopping queries have own characteristics
- How to use query sculpting for an advanced campaign structure
- It’s a lot of effort, but bid management should never be a guessing game
When we are talking about AdWords and Google Shopping, the structure describes the way how the whole account is built.
Let me describe it from the perspective of Shopping Ads: In AdWords, there are accounts. Inside these accounts, there are campaigns, ad groups and several Product Groups. Unlike Text Ads, Shopping Ads are eligible to show for any search query that matches your products. Thus, keywords are not part of that structure. If you need more information about the account structure, click here.
Long Story short: Each single Shopping Ad represents one single product of your product feed. You can’t trigger the impression of your ads with keywords because the items are matched to the search query by Google.
As with regular Text Ad campaigns you can also make use of negative keywords. But with Shopping campaigns you have some additional functionality that can assigned in combination with your campaign priorities. You can use them on campaign level to make sure the right ad from the right campaign is shown. They are an essential part of query sculpting. Keep this in mind for later.
Avoid Black Box Bidding
At the first glance, automatic query matching might sound great. If you use regular Text Ads, generating and analyzing keywords and then matching them to the most relevant ad is almost 80% of your work. The truth is that Google took away the steering wheel and made YOU a passenger. You don’t have many (actually almost none) control mechanisms and it’s time-consuming to bid on single products. Not cool!
In our award-winning talk at the HeroConf London 2016, Christian Scharmüller coined the term “Black Box Bidding” to describe this problem.
“Black Box Bidding” fits well, because you are not able to distinguish between individual products, devices and search queries. As an experienced PPC marketer, you know that there are differences, and there is a way to reclaim the driver’s seat. You can influence and control your campaigns and bids with the right campaign structure. But before you start hacking your account, we take a closer look at these three dimensions of a Google Shopping campaign.
The dimensions of a Google Shopping campaign
If you consider a new Google Shopping campaign structure and want to avoid black box bidding, you need to think about three essential dimensions of a Shopping campaign. These three dimensions are:
Why three dimensions? Because these are the parameters which let you control the major levers of a Shopping campaign and reclaim the driver’s seat!
1. Dimension: SKUs
The goal of an advanced account structure is to make your campaign as granular as possible to avoid misleading conclusions. A short example: You’re targeting products by product type, e.g. “running shoes”. If you look at the ROAS of a specific Product Group, you’ll see a quite solid 10, so there is nothing to worry about. But don’t fool yourself by this first impression. If you take a closer look deeper into this Product Group you may encounter this scenario:
Two of your products are performing well as expected, but one single product completely skews your statistics. Without this badly performing product, you would achieve an ROAS of 38. The reason is the average performance statistics. If you rely on averages, you can’t spot badly performing SKUs. You may use a setup like this to save time. Bidding on granular sub-divisions (or all products) is always a trade-off between workload and performance.
2. Dimension: Devices
The next dimension is quite easy to explain. For example, the conversion rate on mobile has turned out to be usually much lower than on Desktop, but this is not valid for every product. And keep in mind that device bid modifiers are only available on campaign and ad group level. This is another reason to make your campaign as granular as possible. To set bids for every SKU and device, you can add one SKU per ad group, or manage the bids with three campaigns to handle each device individually.
3. Dimension: Queries
Ok, you’ve already taken SKUs and devices into your considerations. The most complex dimension are Shopping queries. Almost all approaches for an advanced campaign structure are based on queries, it is worth to describing them in an own paragraph.
Understanding the characteristics of Shopping Queries
If you are already a bit familiar with Google Shopping you may have got a feeling what Shopping queries look like. Because we are all into PPC, we don’t trust our gut instincts. If you analyze the performance of Shopping queries, you need to check real data. Fortunately, we already have a lot of data which we can use to make a substantial analysis. What we found out is nothing new. Many PPC guys already found the same results. Therefore, you can consider these insights as valid conclusions.
An Example out of the wild
Before diving into the theory, I’ll show you a real-life example of different shopping queries. Below you see a regular Shopping Ad. You also see the different ways how it gets triggered by a searcher. For example, people are searching with a broad-match-like query “Men’s Running Shoes”.
You can also see that all of the statements we made before, apply in this example. The more detailed the search (“Nike Free 5.0”), the higher the chance of a conversion. Furthermore, have a look at the CPC which is quite low compared to the others. If we have a look at more generic queries, e.g. “Men’s Running Shoes”, you’ll see that the conversion rate is much lower.
After this short example, let’s start with the more theoretical stuff.
Characteristics of Shopping Queries in detail
As you can see in the image above, there are a lot of differences between the Shopping queries.
This analysis is important for understanding why Shopping queries are essential for any best practice Google Shopping account structure.
Why is it important to understand these characteristics? For every advanced account structure, you need to categorize search queries. An advanced account structure makes it possible to bid on a clustered search query level. But not every search query has the same performance. If you would not distinguish between the different queries, you won’t be able to profit from any advanced structure.
Advanced campaign structures: Query Sculpting
When we talk about advanced campaign structures, we need to discuss the term “query sculpting” too.
The definition of query sculpting is:
Addressing shopping queries with the right bids by using several campaigns, campaign priorities and negative keywords to increase the performance.
Hence, query sculpting includes a combination of methods (that you need) for setting up an advanced campaign structure.
I’ll show two approaches, both based on this concept.
Approach #1: Explicit query sculpting by Martin Roettgerding
In Google Shopping you also have the possibility to use negative keywords to manage your campaigns. Why? Because maybe you want to exclude queries that do not fit your assortment. If somebody is looking for “expensive jewelry” and you’re a retailer that sells low-budget products, it wouldn’t make sense to bid on this query. Now a little (well known) hack: you can also use negative keywords to structure your account in Google Shopping.
The idea of using negative keywords for campaign structuring is to transfer the AdWords concept of keyword matching to Google Shopping. For Text Ads there are five different matching options:
- Broad match
- Broad match modifier
- Phrase match
- Exact match
- Negative match
Martin Roettgerding came up with a great approach. Using three campaigns to structure a Google Shopping account with negative keywords:
- Product Campaign
- Brand Campaign
- Others Campaign
To filter queries into the right campaign, Martin uses negative keywords and the campaign priorities feature.
To make sure that the correct ad from the brand campaign shows up, you need to add a negative keyword with the brand name in the campaign with the highest priority. Further, you need to set the correct campaign priority (low, medium and high). Without the right campaign priorities, the wrong ad might show up.
A short addition to the slide above: Like Martin mentioned in the slide, you can use any internal structure for your campaign. But if you want to take different devices into consideration, you need to think about the internal structure too. You can only deal with different devices on campaign or ad group level. BTW: You can watch the full presentation of Martin here.
The benefits of this approach are:
- The performance of every query will are taken into considerations.
- This enables you to set bids according to the each query’s performance.
- Most query patterns are heterogeneous and can also change over time
- You need to research patterns.
- Potential valuable queries which do not follow the pattern will stay in the “SKU”-campaign.
The negative issue that you need to research for patterns is also the reason why this concept is called EXPLICIT query sculpting. You need to evaluate the queries manually based on your personal knowledge and the data you have.
But what if your assortment does not contain any well-known brands? Martin also mentioned this in his talk: Explicit Query sculpting may only work with several well-known brands and products.
Approach #2: Implicit query sculpting by Whoop! and Reinhard Einwagner
No question, Martin’s approach is great and he deserves all the positive reactions of the PPC community. However, you can go even further and include more dimensions than brand, non-brand and unique SKUs.
The approach of Reinhard Einwagner (our Head of Product Development) and the Whoop!-team does exactly this. It extends the explicit sculpting with the dimension of term scoring. The big difference to Martin’s approach is that we are not clustering the queries into brand or non-brand. Instead, we use a scoring system based on many factors. This also improves the explicit approach: it also works when you don’t have many brands in your account because you can add any criteria to build a more objective and meaningful score.
Criteria for the term scoring can be:
- color reference
- brand reference
- term length
- performance metrics
- term frequency–inverse document frequency weight(tf/idf)
- and much more…
To make it more tangible, a short metaphor for it. The traffic (queries) will be directed into the right lanes (campaigns) by the use of negative keywords.
The advantages of this approach are:
- The explicit query sculpting, the performance of every query will are taken into considerations.
- This enables you to set bids according to the performance of each query.
- You can use insights from your AdWords account, which means your decisions rely on real (and objective) data.
- A lot of effort if you do it manually.
- Hard to automate.
The requirements for successful query sculpting
Both approaches, the implicit and explicit Query Sculpting, are not easy to implement. You should ask yourself if it is worth it to spend time and resources to build a new account structure. According to our experience, the most important constraints are the conversions. If you want to start with explicit query sculpting, you need at least 200 conversions per month in one target country. For the even more advanced implicit query sculpting, 1000 conversions should be the absolute bottom line.
Also keep in mind that you need to check and update the negative keywords regularly. There will be changes in the performance of certain brands or products and you will spot new negative keywords and maybe discard older ones.
The Outcome: Is it worth it?
I just made a quick analysis of some accounts that use Martin’s query-level bidding to check the performance. Note: This was not a profound in-depth analysis (Thomas, our Head of Data Science, please forgive me 🙂 ), but I saw two sides of the same coin. Some had a good performance, some a bad one.
A general statement and recommendation for or against query sculpting cannot be made. It depends on your assortment and many other factors. But some of our customers had remarkable success with query sculpting. If you’re undecided, the best help is asking a Google Shopping expert who is already familiar with this kind of account structure.
Note: Of course you can use account structures that use query sculpting in combination with our bid management tool Whoop!. It works great with these kinds of account structures. Just set it up by yourself or ask our team for it, they support you with it in exchange for a service fee.
Conclusion: Bid Management is no guessing game
Finding the right bid is not a guessing game. You should always rely on hard facts aka historical data. But of course, there’s no historical data on new items. If your products are new (or have sparse performance data), it’s hard to “guess” the right bid. Our tool Whoop! solves this problem by looking for similar products, brands or categories (= products in the neighborhood) and calculates the best bids based on the historical date of these products. (By the way: convince yourself, just use our 30 days trial).
Query Sculpting is a great way to avoid black box bidding and use the insights of your account for a personalized and more efficient account structure. Think about it!