crealytics' PPC Blog

The place to be for paid search and Google Shopping

Get the product price right for Google Shopping

New Crealytics feature: Price Advisor

Google Shopping takes product price transparency to a new level. Unsurprisingly, people tend to click on the cheaper product when the same product is sold by multiple retailers. This human tendency, means that Google’s learning algorithms will often surface the cheapest products first even if they don’t have the highest bid.

The result, is that if you sell the same brands or products as someone else, where your product price falls in relation to your competitors, heavily influences your traffic and conversion volumes. Product price becomes, next to the bid, the most important factor to attract shoppers on Google Shopping.

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Which product variant is a shopper more likely to click?

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Benchmark your Google Shopping Remarketing Performance with this simple script

Remarketing Lists for Search Ads (RLSA) and Customer Match have been proven to drive incremental revenues of 18% or more.

At Crealytics, we’ve seen many accounts and we developed a few rule-of-thumb benchmarks that give us an idea of how much potential we can unleash by fine-tuning the Remarketing strategy – be it via RLSA or Customer Match.

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A printable cheat sheet to essential RLSA and Customer Match audiences

Remarketing Lists for Search Ads (RLSA) and Customer Match have proven to drive incremental revenues of +18% and more, all while keeping ROAS stable.

One important key to making Audience Remarketing for Google Shopping work is to know which essential audience lists you should define and use.

At Crealytics, we’ve analyzed and optimized many Google Shopping accounts. As a result, we’ve developed a checklist that contains the most important RLSA and Customer Match audiences we typically create and optimize.

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How to make most of Audience Remarketing using RLSA and Customer Match on Google Shopping

The customer journey has become more and more complex. People tend to navigate between Google and a retailer’s website multiple times before they convert. According to our analysis, 46% of Shopping ad conversions have three or more clicks through to the retailer’s website from Google Shopping. Which makes it essential that you keep your brand front and center in the customer’s mind each time they search.

The good news is, Performance Marketers can act on this customer journey using Remarketing List for Search Ads (RLSA) and Customer Match. These tools make it possible to bid differently on shoppers who have interacted with your website and are searching for something relevant on Google again.

Crealytics A/B tests on the incrementality of Audience Remarketing have shown that bidding higher on people deeper in the conversion funnel drives incremental revenues of around 18% or more.

Done right, you’re not just making the sales you would have made anyway with a higher price bid, you’re actually increasing the number of sales generated by targeting highly relevant shoppers.

Take Audience Remarketing to the next level

Google Shopping is ideal for running Audience Remarketing at scale. This two-minute video provides you with an overview of how we bottled up the combined experience of our PPC experts at Crealytics into an automated solution that lets you leverage the full potential of Remarketing.

Crealytics customers have been able to benefit from the Audience Remarketing optimization since April 2016. If you have any questions, thoughts, comments or just want to chat about RLSA, feel free to reach out to your Crealytics account manager to discover more.

Not a Crealytics customer yet? To learn more about how our Smart Shopping Automation tool can help you get the most from your campaigns, get in touch with us on and we’ll be more than happy to tell you all about it!

How are your RLSAs doing right now?

To make it easy to evaluate the current state of your Audience Remarketing Google Shopping campaigns, we’ve put together these resources designed to help you check this task off your list.

More on RLSAs

For more on how to make the most of your audience lists, check out these other great resources.

How to adjust Google Shopping bids based on product performance

There are many scenarios in which Google Shopping campaign managers would love to have a special Bid Management strategy that allows them to influence product ad impression levels for certain products, brands or categories.

For example, you may want to give an added push to products that have a surplus inventory or pull back on products that are delivering low ROAS results.

At the moment, you can do this manually at the campaign level, but that will apply the change across all products in that campaign. You can also do it at the product level, but that would be an awful lot of manual work. Neither are ideal solutions.

So we’ve developed a Camato feature that gives you the power to customize bids down to a granular level. Introducing…Custom Bid Strategies.

Feature goal: Execute custom Bid Management strategies that take performance aspects into account

When would you use a Custom Bid Strategy?

There are typically two scenarios where you would want to increase your product bid:

  1. For temporary promotions which are usually tied to business goals defined outside of PPC departments.
  2. To clear stock levels or to promote new collections/brands.

In both of these, typical performance KPIs like Cost of Sale (COS), are often allowed to perform below average. They may even be combined with additional metrics such as yield, to account for the effective value of incremental sales.

Related: Guide to bid management in Google Shopping

In addition, PPC marketers can also exploit meta-knowledge. For example, if you sell certain products with competitive advantages, like low prices or fast delivery, you’ll want to bid slightly higher than average to get them in front of more people and make more efficient sales. Eventually, based on the tracking data, the Camato Bid Management system will identify these products and bid up on them by default. But, with your expert knowledge and Custom Bid Strategies, you can get a jump start on this process by bidding proactively instead of reactively.

Similar scenarios hold true when bidding lower. Low stock levels and competitive disadvantages (like high prices) are certainly reasons to pull back bid aggressiveness.

Why you shouldn’t rely on regular bid modifiers

You recognize the need to bid up (or down) on certain types of products, but how should you go about it? Usually, it’s done by either adding a few cents to the bid or adding a fixed-percentage bid modifier on top of the existing bid.

In this example, we want to increase ad impressions for products A, B and C. We’ll start by adding a +10% bid modifier on top.

Table 1: Bid modifiers push everything up

Product Cost Revenue ROAS Old Bid New Bid
A 100 1000 10 0.5 0.55
B 100 500 5 0.5 0.55
C 100 100 1 0.5 0.55

Of course, adding 10% across the board, means that product C – although performing poorly – gets a higher bid as well as products A and B.

The problem with this approach is that it does not take the relative performance of each product into account. In a perfect world, we would push A stronger than B, and B stronger than C. Even if the old bids weren’t the same to start with, using this bid modifier method is like using a hammer. There is only one bid direction, and that direction is up. Regardless of performance.

How Custom Bid Strategies solve the problem

Instead of adjusting the bid directly, what if we could tie bid adjustments to another metric? One that typically influences the bid calculation decisively – e.g. revenue. If revenue isn’t your main KPI, you can use another metric, like margin or customer lifetime value.

A simplified version of this theory would look like this, if our target ROAS was 5 and we didn’t do any additional bid modifications.

Table 2: Simplified new bid calculation without additional pushes

Product Cost Revenue ROAS Old Bid New Bid
A 100 1000 10 0.5 Above target: bid up (e.g. 0.55)
B 100 500 5 0.5 On target: leave bid as is
C 100 100 1 0.5 Below target: bid down (e.g. 0.4)

If you still want to more heavily push A, B and C, you can pretend these products performed better than they really did. You simply calculate an adjusted Revenue and, derived from that, an adjusted ROAS.

In this example, we’re pretending that these products performed 20% better than they really did:

Table 3: Adjusted new bid calculation with additional pushes

Product Cost Adjusted Revenue Adjusted ROAS Old Bid New Bid
A 100 1200 12 0.5 Even more above target: bid up a little stronger
(e.g. 0.6)
B 100 600 6 0.5 Slightly above target, bid up a little (e.g. 0.52)
C 100 120 1.2 0.5 Below target, Bid down, but not as strongly as
without adjustment (e.g. 0.44)

The big difference is that now, we’re taking A, B and C’s performance figures into account more forcibly. We bid up A more than B, and we still bid down C, although not as strongly as in Table 2.

Please note that the examples we’ve given are basic. There are other factors to consider, such as when you should stop bidding up due to the S-Curve dynamics in Google Shopping, or the fact that there are many long tail products, for which revenue or ROAS need to be estimated.

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The result

Adjusting the bid calculation influencers, instead of the bid itself, allows you to take past performance into account. You can do this manually – or you can use Camato’s new Custom Bid Strategy feature and advanced Bid Management techniques to remove the extra setup and monitoring work that bid customization would otherwise create.

What you gain from the extra customization is the ability to be hyper-targeted in your bidding, even though it’s done automatically. This saves you money and increases overall account performance.

Our ultimate goal when we created Camato was to give more control of Shopping campaigns to the people who need it most – Digital Marketers. And, we wanted to do it in a way that would take different performance levels into account and didn’t require a ton of extra work.

After creating Campaign Segmentation, allowing marketers to bid more for high-value search queries, and Bid Management, allowing them to optimize bid amounts for different KPIs, Custom Bid Strategies was the next logical step.


How to make Device Modifiers work for you

Earlier this year, Google rolled out a new feature to let advertisers set different bid strategies for different devices (desktop, mobile, tablet). These device modifiers are one of the most important performance levers, but all too often they’re neglected by the campaign manager.

There are a number of different strategies for dealing with this new found device freedom, and we’d like to share the one that’s worked for us and our clients. Although we primarily look at Google Shopping, you can also apply most of the ideas to Search campaigns too.

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Are your Local Inventory Ads working against your Shopping campaigns

How to set up a Google Local Inventory Ads campaigns the smart way

 56% of all in-store sales in the US are influenced by digital media

– Deloitte study (2016)

Online shopping is certainly growing in popularity, but don’t count out in-store shopping just yet. Nothing beats the instant gratification of picking up your new product IRL.

So, how do you effectively market to these shoppers who might research your product online, but buy in store? Enter: Google Local Inventory Ads (LIAs).

Since their beta launch in 2014, Google Local Inventory Ads have gained a lot of popularity with omnichannel retailers. We regularly see our customers spending as much as 23% of their Shopping budget on LIAs.

Local Inventory Ads are designed to allow us digital marketers to help sell products in brick-and-mortar stores. After all, a sale is a sale. And, if you’re a retailer who sells both online and in-store, this may sound like the perfect fit.

In this article, we’ll share our best practices for configuring Local Inventory Ads and demonstrate how they can co-exist peacefully with your online campaigns.

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Google Shopping is Conquering the Earlier Stages of the Customer Journey

Google have announced the beta of Showcase Ads in the US, UK and Australia. The new Google Shopping ad types, Local Inventory Ads and Showcase Ads mark the beginning of how Google Shopping will be supporting the earlier stages of the customer journey, for example when users are searching by broad terms. Instead of just showing a selection of multiple products over many retailers, the user is led to a Google-hosted area, in which more products of the same retailer, together with ratings and reviews collected across retailers, are shown. Thus, Google starts to let users explore and discover a retailer’s product offering outside of their own website.

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