3 Advanced Tips For Bid Adjustments In Google Enhanced Campaigns

Google’s introduction of Enhanced Campaigns is one of the most significant structural modifications to occur in the history of paid search. With the end of migration scheduled for July 22, marketers are scrambling to figure out “what works” on the new campaign format.

A key point of change in Enhanced Campaigns is the expanded use of bid adjustments — percentage modifiers to control relative bids between devices, geos, and other targets. Since efficiency varies by target, getting the adjustment factors correct is critical for achieving optimal performance.

Below are tips for marketers on how to calculate better bid adjustment values for Enhanced Campaigns. In my examples, I will only refer to mobile bid adjustments (MBA), but the same tips apply to geographic, day-parting, or any other type of bid adjustment available.

1. ROAS Calculation For Optimal Performance, RPC For Stability

Some sources recommend a revenue per click (RPC) based calculation of bid adjustment – setting the MBA to the ratio of RPC between devices – but this is not always ideal due to variation in Max CPC to Average CPC ratio (Bid-to-CPC ratio for short).

For instance, consider the case below where the mobile RPC is half that of desktop/tablet RPC, which gives an MBA of -50%. If the desktop/tablet bid is $1.00, the mobile bid will be at $0.50.

However, the competition on mobile is less than that on desktop/tablet, so the average CPC on desktop/tablet turns out to be $0.90, while the mobile CPC is only $0.30.







→ MBA: -50%

Bid (Max CPC)



Average CPC






ROAS = RPC / CPC, so we get an ROAS of $11.11 on desktop/tablet, and $16.67 on mobile. Since the Bid-to-CPC ratio is less on mobile, it ends up with a much higher ROAS compared to desktop/tablet when using RPC-based bid adjustment. This means that the MBA is likely not optimal: there is more room to increase mobile bids and volume.

An ROAS-based adjustment does not suffer from this issue, but it is not without its challenges. CPC can be influenced by a number of factors, such as competition and quality score, which means that the ROAS calculated at one point in time may not reflect long-term performance.





More stable

Does not account for Bid-to-CPC ratio


Closer to optimal

Sensitive to CPC fluctuations

While the RPC-based method is more stable, it will never achieve true optimization since it does not take into account Bid-to-CPC ratio. The ROAS-based method does, but due to its sensitivity to market fluctuations, more frequent adjustments will become necessary.

2. Use Weighted Ratios, Not Totals, To Calculate Bid Adjustments

One common pitfall for MBA calculation is to use the ad group or campaign level totals to determine the ROAS or RPC ratio between devices. This can cause the resulting MBAs to deviate quite a bit from the ideal.

Let us illustrate this with an example. Suppose there are two keywords, A and B, in an ad group. The desktop/tablet and mobile RPCs are equal on keyword A, whereas on keyword B, the desktop/tablet RPC is 10 times greater than mobile. However, keyword A is more scalable than keyword B, getting 10 times more clicks. What should the MBA for this ad group be?

Most of you probably came up with the answer: “close to (or a bit less than) 0%.” Since over 90% of clicks are on a keyword with no performance difference between devices, the MBA should also be set close to 0.

Now let us take a look at the example below.













Keyword A








Keyword B
















Despite over 90% of clicks happening on a keyword with no RPC difference between devices, there is a 45% calculated difference between the blended desktop/tablet and mobile RPC for the ad group. This is caused by the RPC for keyword B being higher than keyword A on desktop. The result is an MBA value that is obviously wrong.

One way to avoid this problem is to use click-weighted averages when calculating MBAs (Desktop refers to both Desktop and Tablet):


Or simply put, we first compute the RPC ratio for each keyword within the ad group and take the click-weighted sum later, instead of taking the sum first and then calculating the RPC ratio. Using this formula for the above scenario gives an MBA of -8%, a much better result.

For ROAS-based calculation, the same formula works using a cost-weighted average – just replace RPC with ROAS, and clicks with spend.

3. Set Min And Max Limits On Your Calculation Results

Setting thresholds is critical when performing MBA calculation. Whether using Excel or an automated bidding tool, there is some risk associated with letting a formula do all the work without putting in safeguards.

For example, a campaign that does not usually convert well on mobile may get a one-off large mobile order, temporarily spiking up the MBA. If this happens on a high-volume campaign, we may end up with a flood of non-converting mobile traffic that can wreak havoc on your account’s performance.

On the other hand, if the MBA falls to -100% even temporarily, there will no longer be any mobile traffic. This means that the ROAS/RPC on mobile will no longer be updated, potentially causing the MBA to permanently remain at -100% until reset manually.

Thus, it is important to constrain that range of bid adjustment factors within a reasonable range. But how do we figure out this range?

One method is to use percentile thresholds to limit the range that MBAs can take on. MBA values can often span across a wide range of values, but we can drop the top and bottom 5% by click volume or spend to narrow down this range.



Volume Percentile

Ad Group 1




Ad Group 2




Ad Group 3




Ad Group 4




← Upper Limit

Ad Group 5




Ad Group 6




Ad Group 7




Ad Group 8




Lower Limit

Ad Group 9




The raw MBA values in the example above vary from -90% to 80%, but by dropping the top and bottom 5%, this reduces to a much safer range of -70% to 0%. Any MBAs that exceed these thresholds can be adjusted to the upper and lower limits.

The benefit of this approach is that the possible downside impact on performance is very small if any, while risks are largely mitigated.

Key Takeaways

  1. ROAS-based calculation theoretically allows for improved performance over RPC, but requires more frequent adjustments.
  2. Use click/cost-weighted average of keyword-level ratios instead of aggregate ratios.
  3. Regardless of calculation method, always specify minimum and maximum values for bid adjustment factors.

The ideal bid adjustment varies depending on the relative volume on keywords within the campaign, which in turn is influenced by both bids and modifiers. This means that the ideal bid adjustment is never a static target: it is necessary to iterate and test in order to find the optimal combination of bids and modifiers.

The Enhanced Campaigns framework sets the stage for more levers to be added in the future, which means that bid adjustments will play an increasingly larger role in determining campaign performance.

If you have any questions on how to set Enhanced Campaign bid adjustments, feel free to leave a comment below, or reach out to me via Email/Twitter/LinkedIn.

Opinions expressed in the article are those of the guest author and not necessarily Marketing Land.

Related Topics: Analytics | Analytics & Marketing Column | Channel: Analytics | Google: Search | How To Guides | Search Marketing


About The Author: leads product marketing at Origami Logic, a cross-channel marketing intelligence solution for modern marketers. With a career of 8 years in marketing and analytics spanning various functions, Kohki's focus has always been on translating data into strategy, simplifying the complex, and bridging the gap between data and organizational silos.

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  • http://www.rimmkaufman.com/ George Michie

    Terrific post, Kohki! It is a shame it’s come out on a day many folks are out of the office. Thank you also for the link reference. Google’s “simplification” of the system is anything but simple to manage well.

  • Pat Grady

    Any stats worked into your formula for what % of your mobile conversions are untracked, or go to another device, and how they vary from desktop? :-)

  • Kohki Yamaguchi

    Thanks George! If Google keeps on adding on more and more layers of dimensionality, our fundamental approach on how to optimize paid search campaigns will have to change as well, for better or for worse.

  • Kohki Yamaguchi

    Hi Pat, great point. The % mobile conversions lost (with respect to desktop) varies by advertiser and tracking method, so the isn’t an easy way to approach this problem. There are some companies out there claiming to have a solution that uses behavioral pattern matching, but the only sure-fire method that exists right now is to individually map cookies to customer account data.

  • Rob Levin

    Kohki – this is Jedi level stuff, thanks!

  • Diarmuid O’Riordan

    Hey Kohki. This is a really great post. I am currently trying to set mobile bid adjustments based on Mobile ‘click to action’ (CTA) ratios. Target CPA X AG Mobile CTA = AG Mobile Target CPC, then: (Mobile Target CPC – Actual Ad-Group CPC)/Actual Ad-Group CPC = Multiplier. For this method, do you think I need to look at weighted ratios rather than ad-group (AG) totals?

  • Kohki Yamaguchi

    Hi Diarmuid – correct, it is still better to look at weighted ratios. What you put as CTA here is effectively conversion rate, which is the same as RPC expect using actions (units) instead of revenue (currency). So the same equation above applies, just replace all mentions of RPC by CTA.


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