Maximise Your Sales Through Google Ads With an Automated Bidding Strategy

Are Automated Bidding Strategies Worth Using?

 


Automated bidding strategies have been around for a while within the Google Ads platform, enabling advertisers to offload their bid management to Google’s automated system.

The use of these strategies, are however, still a contentious issue within the pay-per-click marketing community.

Do campaigns generally get better results with manual bids? Or do the machines outperform their human counterparts in this department? Or is it a mixture of both?

The answer can vary between account managers, and depend heavily on the type of campaign and objectives.

There are a range of different automated bidding strategies on offer to help advertisers meet their marketing objectives:

The Automated Bidding Strategies to Choose From

Bid Strategy How it Works When to Use It
Enhanced CPC Half-way between manual and automated bidding - the Google Ads algorithm will increase your current bids when it's estimated a conversion is more likely to occur. Enhanced CPC can be effective for campaigns which do not yet have adequate conversion data to use one of the fully automated strategies; and in instances where the account manager does not want to give up full control of the bid management.
Maximise Conversions Google will optimise bids with the aim of generating the highest volume of conversions possible within the campaign's daily budget. All conversions will be valued equally by the algorithm, irrespective of their value to the business. This strategy is ideal for use in campaigns that have one conversion action being tracked, or multiple actions that have the same business value.
Target CPA Bids will be optimised in order to maximise the volume of conversions generated at the average CPA (cost-per-acquisition) price chosen by the advertiser. Some conversions may be generated at a cheaper or more costly price, but the system will aim to achieve the average. The bid strategy is ideal when achieving a CPA target is critical to the success and profitability of a campaign, and spending the full budget is a secondary objective. The algorithm will always priortise reaching the average CPA target over reaching the daily budget.
Target ROAS Bids will be optimised to achieve the advertiser's Target ROAS (return-on-ad-spend), adjusting bids for the different forms of targeting based on revenue that is expected to be generated. This bid strategy is ideal for ecommerce sites, and accounts that are tracking revenue data from conversions.
Maximise Clicks Google will optimise bids with the aim of generating the highest volume of clicks possible within the campaign's daily budget. It is useful to add a cap on the maximum bid, as the system will increase the max CPC as much ass possible to in order to reach the daily budget. All clicks will be valued the same by the system, irrespective of the targeting. For this reason this strategy is ideal for campaigns whose objective is to generate traffic, without any conversion goals; or in the early stages of a campaign, before any conversion data has been accumulated.
Target Impression Share Bids are optmised to allow ads to reach a certain position on the page (e.g. absolute top of page), a certain percentage of the time (e.g. 65% of available impressions). This bid strategy is useful when awareness and reach are the highest priority for a campaign. A cap on the max CPC can be added to prevent overly expensive clicks.
Target Search Page Location Advertisers can choose to target either the top of the first page, or the first page of the Google search results. Bids will then be adjusted to try to achieve this position. This bid strategy is often very useful for brand focused campaigns, in which gaining the maximum level of exposure is of paramount importance.

 

Can an Automated Bidding Strategy Help to Maximise The Volume of Sales Generated by Your Google Ads Campaign?

Google’s automated bidding strategies utilise the wealth of stored up campaign performance data, in addition to real-time user behaviour data, in order to help determine the optimal bid for each auction.

Therefore, the success of any automated bidding strategy will be contingent on the amount of data within your campaign, and also the level of user behaviour data that Google possesses on prospective customers within your target sector.

Some campaigns may benefit from the use of an automated bidding strategy and see an uplift in sales, while some campaigns may not.

Testing is Essential

The only way to really determine whether or not a particular bid strategy will be effective for a campaign, is by testing it.

In order to ensure the test is fair, and to confirm whether the given increase or decrease in performance is due to the change in bid strategy, both bid strategies need to run concurrently.

This testing can be carried out by duplicating the campaign and running both bid strategies side-by-side, or by using a campaign experiment.

Based on the results of the test, the better performing bid strategy can be identified and selected for ongoing use.

A Word of Caution

It’s important to be aware, when handing over control of bid management to an automated strategy, significant, and in some cases unintended changes can be made to bids. Average CPC’s can increase drastically, and beyond the level of profitability.

It is wise to always set a cap on the maximum bid where possible, and to keep a close eye on the performance, especially in the early stages.

It’s also important to realise that the process of optimisation carried out by the system can take days, or in some cases weeks, while the system tests different levels of bids to find the optimal setting. During this period, overall performance may see a dip before it improves.

Conclusion

There is a range of bidding strategies available to choose from, depending on the specific objectives of your campaign.

Automated bidding strategies can help to maximise the number of sales generated by your campaigns, and to achieve a variety of other marketing objectives; but the effectiveness of these strategies will depend heavily on the level of performance data within the account, and the level of user behaviour data possessed by Google.

In some cases, the machines will outperform their human counterparts, and in other cases, manual bidding will be the most effective option.Ultimately the only way to concretely confirm if a particular bidding strategy will be effective for meeting your campaign’s objectives, will be through testing.

Close observation of the performance is advised!

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philip July 23, 2019 0 Comments

How the Replacing of Google’s Average Position Could Affect You

Google’s Average Position is Going Away

 

We plan to sunset average position in September of this year.
– Google Ads

 
In place of the average position metric which will be going away, Google has added a number of new metrics which are meant to give advertisers a greater level of clarity when reviewing the performance of their ads.
 

What is Average Position?

 
Average position is represented as a number that indicates which order your ad appeared in relative to the ads of other advertisers. An average position of 1 for example would indicate that on average your ad appeared in the 1st position, the highest position on the results page relative to the other ads.

However sometimes the placement of ads in the search engine results can begin at the bottom of the page, below the organic results. An average position of 1 doesn’t necessarily mean your ad appeared at the top of the page, only above the other ads, and this is partly why Google have introduced the new metrics.

 

Why Is Average Position Being Replaced?

 
Google has constantly developed the way ads are presented within the search results, and on the display network, across a myriad of devices. The placements of ads is now more dynamic, and to help advertisers understand where exactly their had has appeared, a new set of metrics is needed.
 
absolute top
 

The New (Improved?) Position Metrics

 
To help offer advertisers more clarity on the position of their ads, Google has introduced the following new metrics:

  • Impr. (Absolute Top) % – is the proportion of impressions your ads have received while in the very first ad position, above the organic website listings.
  • Impr. (Top) % – is the proportion of impressions your ads have received anywhere above the organic website listings.
  • Search (Absolute Top) Impression Share – indicates the proportion your ad received of the total available impressions at the very first ad position, above the organic listings. For example, if there were 1000 impressions available, and your ad received 300, then your impression share of the Absolute Top would be 30%.
  • Search (Top) Impression Share – indicates the proportion your ad received of the total available impressions anywhere above the organic listings.
  • Search Lost Abs.Top IS (budget) – indicates the proportion of available impressions your ad missed out on in the ‘Absolute Top’ position, due to budget constraints.
  • Search Lost Abs.Top IS (rank) – indicates the proportion of available impressions your ad missed out on in the ‘Absolute Top’ position, due to a low ad rank.
  • Search Lost Top IS (budget) – indicates the proportion of available impressions your ad missed out on in the ‘Top’ position, due to budget constraints.
  • Search Lost Top IS (rank) – indicates the proportion of available impressions your ad missed out on in the ‘Top’ position, due to a low ad rank.

 

Position Metrics
 

 

What is the Advantage of These New Metrics?

 

Greater Clarity for Potentially Better Decisions

 
The new metrics provide more clarity on how often your ad has been placed at the actual top of the results page, above the organic listings, where it will be likely to get the greatest exposure and volume of clicks.

The additional metrics also provide clarity on how you can increase the proportion of impressions your ad will receive at the top of the page, whether this is by increasing your budget or improving your ad’s rank.
 

Dominating Branded Terms

 
The new metrics are especially useful for when targeting your own brand keywords. Instead of bidding to attain an average position of 1, you can now more clearly see how often your ad is appearing above the organic listings for your branded keywords.

 

Are there Any Drawbacks?

 

Clarity on Competition

 
Although the new metrics do add clarity regarding how often an ad appears above the organic search listings, without the Ad Position metric, it is difficult to know how your ad has been placed relative to your competitors. This is especially true in cases where the ad listings have appeared below the organic site listings.
 
With Google Ads, we are competing with other advertisers, not the organic listings. With this in mind, it makes sense to have an idea of how our ads are positioned in relation to our competitors.
 
Without the Ad Position metrics, we won’t be able to see if our ad is on average being placed in position 2 or 3, and to estimate the cost for improving our position.
 

Increased Costs

 
The change could potentially lead to an increase in competition, with higher bids in the auctions as advertises vie for the top/absolute top positions.
 

Adapting to The Change

 
Would it be nice to continue to have access to the Average Position metric? Yes. But with the changes we are seeing within the marketing landscape, Ad Position is becoming less and less important. Instead we are focusing more on audiences, context, and intent.

The new metrics can help to lend more insight into where on the page users are viewing and engaging with our ads, and should be embraced for what they can offer.

In anticipation of Ad Position being removed, any bid strategies for processes which make use of the Ad Position metric should be switched for those that incorporate the new metrics.

Additionally, it can be useful to view the new metrics in conjunction with the current Ad Position metric, to both see how the new metrics relate to the old, and to get accustomed to using the new metrics to optimise campaigns.

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philip April 18, 2019 0 Comments