What is smart bidding?

Smart bidding is a subset of Google’s automated bid strategy that helps advertisers optimize their conversion rates. Using machine learning, Google considers contextual data and historical search behavior to predict the likelihood of a conversion. When it believes a conversion is more likely, it increases the client’s bid automatically.

Understanding smart bidding

Smart bidding is a machine learning feature in Google Ads that is used to automate the bidding process and optimize conversions.

Within smart bidding itself are five different strategies:

  1. Target ROAS – bids are optimized to achieve an advertiser’s target return on ad spend (ROAS). This strategy enables Google to predict future conversions and determine a CPA that maximizes ROAS and conversion rate.
  2. Target CPA – in this case, bids are optimized to control the amount the advertiser pays for each conversion. This is known as target cost-per-action (CPA) and seeks to avoid a scenario where the business pays for unprofitable clicks.
  3. Maximize conversions – bids are optimized to maximize conversions with respect to an advertiser’s budget. This is a good option for smaller accounts since it only requires five conversions per month.
  4. Target impression share – this strategy involves setting a bid to show an ad at the top of the page or first in the carousel as frequently as possible. This drives more volume to a site but does not guarantee that all traffic has purchase intent.
  5. Enhanced CPC – which seeks to increase conversions by optimizing the maximum CPC. This strategy is used in combination with manual bidding to increase conversions while retaining more control.

The four key benefits of smart bidding

According to Google, there are four key benefits of smart bidding:

  1. Diverse contextual signals – businesses can factor in a broad range of signals into their bid optimization. These are identifiable attributes about a person or their contexts such as device, physical location, language preference, time of day, and location intent, among others.
  2. Advanced machine learning – algorithms consider vast amounts of data to better predict how different bid prices impact conversions or indeed conversion value
  3. Flexible performance controls – smart bidding is a tailored solution that enables the business to set performance targets relevant to its objectives. Targets can be set based on the desired attribution model and can also be device-specific.
  4. Transparent reportingGoogle offers various reporting tools and features that allow the business to pinpoint any issues and troubleshoot rapidly. Simulators, for example, predict how ads may have performed if different targets or budgets were set. There is also an experimentation feature that clarifies how smart bidding performs when compared to the current bidding method.

Pros and cons of smart bidding

Smart bidding has the obvious advantage of reducing the time and hassle associated with manual bidding. It is more of a set-and-forget solution where an algorithm does the bidding work on the business’s behalf. Google’s access to vast amounts of information also makes smart bidding an ideal solution for small or new businesses that lack historical campaign data.

However, one drawback of the passive aspect of smart bidding is the relative absence of visibility and control over how data is used to optimize campaigns. Advertisers who attempt to craft a strategy that increases conversions may find this lack of access frustrating. Google’s extensive store of data can also be seen as a negative when one considers that larger audiences tend to be less targeted. This has the potential to dilute ROAS and decrease conversion rates.

Key takeaways:

  • Smart bidding is a machine learning feature in Google Ads that is used to automate the bidding process and optimize conversions.
  • Within smart bidding itself are five strategies: Target ROAS, Target CPA, Maximize conversions, Target impression share, and Enhanced CPC.
  • Smart bidding is a more passive approach to advertising that has access to vast amounts of user data. However, both these positives could also be interpreted as negatives in certain contexts or for certain businesses.

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