Piling On Using Bid Adjustments With Google Shopping

Layering Bids

In my recently released book, Make Each Click Count Using Google Shopping, I dive into detail on the most effective ways to optimize product bids based on historical data.

Within the book, I have dedicated different chapters to optimizing bids based on each of the following: optimizing based on mobile device; based on customer location; based on when your customers shop and based on defined audiences.

With all these options, a well-optimized campaign will rarely adjust bids exclusively at the product level or even at the campaign or ad group level.

Not to say that it is unimportant to adjust bids at the product level, in fact, adjusting bids at the product level is one of my fundamental strategies for effectively optimizing Shopping campaigns.

You can read about the complete strategy in this article – Effectively Optimize Google Shopping Based on Your Past History, Nothing More.

This article revels not only how to adjust bids on the product level, but how to create and implementing my proprietary Google Profitability. Through this report advertisers can naturally increase bids for items selling at above average profitability levels and decrease bids for items not selling at profitable levels.

However, as good as the results are for optimizing solely at the product level based on history, many times it is necessary (especially with accounts with large product offerings) to make sweeping bid adjustments based on either the device, location, ad schedule (time of day/day of week) or audience.

In fact, many times a well optimized account will be utilizing multiple bid adjustments within various campaigns.

What Happens When You Are Changing Bids Using Multiple Adjustments?

When you are using bid adjustments at multiple levels, your bids can quickly become drastically larger or smaller than the product bid you have initially set at either the product level, ad group level or campaign level.

This article examines what might happen when advertisers make multiple bid adjustments to understand why and how it will affect final bids.

Note, these are examples based on fictional numbers and are not meant to be replicated within your own account.

For this example, to make it easy, let us assume all our product bids are set at $1.

Now, let us assume that we reviewed our devices and have determined that traffic comes through mobile devices has a conversion rate of 1% while traffic coming from desktop devices has a conversion rate of 5% (not entirely uncommon).

Given that data, it would be wise to do a bid adjustment such as decreased bids by 40% on mobile devices (-40%) and increasing bids on desktop devices by 15% (+15%).

If you are interested in how this is done, here is an article that discusses your mobile bidding strategy – Mobile Equality – It Almost Is Never Fair, Nor Should It Be So.

Next, let us assume that we after reviewing our account’s User Location Report and there are several states as an example California, Texas and New York that have very high conversion rates and profitability levels while there a few states such as Alaska and Hawaii that have very poor conversion rates.

In this case, it would be wise to increase the bids based on location of California, Texas and New York say 25% and decrease bids in Hawaii and Alaska say -25%.

If you are interested in the full location bidding strategy, here is the article – Increase Your Conversions By Knowing Your Customer’s Location

Next, for my private clients, I am also constantly reviewing the time of day and day of week that conversions are more profitable through the use of Ad Schedules.

In our ongoing example, we will assume that there are higher conversion rates during the week/during the workday (9-5) than they are during the weekends, evenings or early mornings.

In that case, it may be prudent to increase your bids Monday through Friday during working hours (say increase 25%) and decrease bids during evening hours or weekends (say decrease 25%).

Again, I have an article dedicated on exactly how to setup ad schedules and optimized on the data discovered that you can review here – Increase Your Conversions By Knowing When Your Customers Shop

Finally, as you may well be aware, users who have previously purchased from your website or those that have previously visited your website are generally much more likely to purchase.

With that fact in mind, it is typically an effective strategy to create audiences to target these groups and adjust bids to ensure higher ad rank when either previous purchasers or previous visitors are searching for a product you offer.

For private clients, I typically will setup a couple of difference audiences that include Past Customers and increase bids 100% (because it is typically well worth that increase) and Past Browsers and increase those bids by 33%.

There are more audiences you can create, but for this example, we will stick with those two. If interested in details on how to create audiences, you can read more details here – Using Audiences to Increase Conversions

Now We Do The Math –

Based on the assumptions laid out above, it is time to practice some quick math to determine our product bids for different scenarios.

First, we will calculate how much the product bid would be for a user doing a desktop search, during the workday, located in California and oh yeah, they have also purchased from us in the past.

Here is the math as I figure it.

$1 (original bid) x 115% (device bid adjustment = $1.15
$1.15 x 125% (location bid adjustment) = $1.44
$1.44 x 125% (ad schedule bid adjustment) = $1.80
$1.80 x 200% (audience bid adjustment) = $3.60
The final bid adjustment, one would expect would be around $3.60!

See how it adds up!

Alternatively, here is the other extreme:

The product bid for a user doing a search using a mobile device during the evening in Hawaii who has never purchased or visited from our website in the past.

$1 (original bid) x 60% (device bid adjustment = $0.60
$0.60 x 75% (location bid adjustment) = $0.45
$0.45 x 75% (ad schedule bid adjustment) = $0.34
$0.34 x 1 (no audience bid adjustment) = $0.34
The final bid adjustment, one would expect would be around $0.34!

As the great marketer, Frank Kern, often says: ‘Math is not an exact science’. He makes that statement to be funny, but for us it is kind of true.

Since Google does not reveal the order of how they calculate layering bid adjustments, actual bids can fluctuate slightly depending on what order priority is given.

However, what is important to know is that if you are making adjustments based on sound historical data, your bids should be well optimized based on different scenarios. However, it is important to realize why your bids could be substantially higher or lower that your original bid!

How Do You Even Know If Bids Are Highly Inflated?

One of the most effective ways to increase profitability in a Shopping campaign is by regularly reviewing your Search Terms Report. When reviewing your search terms for unwanted terms it is also important to review the Average Cost Per Click.

This is were some puzzlement may come into play.

Back to our example where we are bidding $1 for all products, it may be discovered within the Search Terms Report items with Average Cost Per Click over $3 or under $0.35.

This would typically happen where there are only a handful of clicks (1 to 3), but yet these highly inflated or deflated bids may be common if you are using multiple bid adjustments at different levels.

Final Word

The price you are paying Google per click can be important in terms of budget (especially tight budgets); however, with ecommerce companies there are much more important metrics to measure when it comes to calculating profitability.

Key metrics such as ROAS (return on ad spend) and ROI (return on investment) are going to be far better indicators of the overall health of your online marketing opposed to your average cost per click.

Afterall, for most savvy advertisers only profitability can determine your ad budgets and how much it is prudent to spend per click, per campaign and per account.

In order to maximize your profitability, adjusting bids based on historical data at the product level or at the device, location, time or by audience are effective ways to ensure you are increasing your position within Google for customers more likely to purchase.

Just know that if you are changing bids at multiple levels that it may continue to pile on to your final product bid based on the criteria of the final users Google search.

Remember to stay safe and stay healthy!

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Happy Marketing!
Andy Splichal


Andy Splichal is the founder of True Online Presence, author of the Make Each Click Count book series, host of the Make Each Click Count podcast, founder of The Academy of Internet Marketing and certified online marketing strategist with twenty plus years of experience helping companies increase their online presence and profitable revenues. To find more information on Andy Splichal, visit www.trueonlinepresence.com or read The Full Story on his blog, blog.trueonlinepresence.com.