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Maximize Conversions is relatively new to Google’s automated bidding toolkit. Unlike earlier features like eCPC and Target ROAS, Maximize Conversions is not an ROI-driven strategy. Instead, this automated bidding solution sets bids to ensure the maximum number of conversions for retailers’ paid search and display ads. Many retailers are unsure how this sometimes costly tactic will impact their bottom lines.
In this installment of Keeping Up With Google–a series that helps you stay up-to-date on the latest changes shaking up Google Ads–we define Maximize Conversions and uncover how this tool can affect your performance marketing strategy.
Google released Maximize Conversions in 2017.
What It Does:
Maximize Conversions sets bids in order to capture the largest number of conversions for the retailer’s budget, based on historical campaign performance and auction data. Maximize Conversions is not an ROI strategy which means Google may spend the full daily budget amount to capture as many conversions as possible.
Retailers can only set a Maximize Conversions goal for a single campaign, and that campaign cannot have a shared budget.
Before retailers can implement Maximize Conversions, they need to set up conversion tracking within their Google Ads account.
Maximize Conversions is available on Google’s Search and Display Networks. It is not available for Google Shopping.
What Does It Mean for Your Business:
Maximize conversions is a bidding tool designed for businesses who have campaign-level goals focused on a singular conversion or event taking place with no other factors to consider. Businesses that focus more on lead generation and track downloads of a whitepaper, for example, may use this style of bidding.
Businesses in the retail sector will likely shy away from a bidding model like this as not all conversions are created equal. Conversion rates, average order values, products with varying price points (or margins) in an order, repeat purchasers versus new customers are all elements that can impact the value of a conversion, depending on the retailer’s goals. These factors require a more advanced model like a ROAS based model that accounts for the variables mentioned above.
There may be instances where a retailer’s catalog can be segmented into groups of products that are rarely bought in conjunction with other products, all products are a similar price or margin, and have the same goal. But this would be very rare and would present other challenges like over-segmentation of the data from which marketers can optimize.
Another limitation is the lack of data marketers receive when they use Maximize Conversions. Like other Google automated bidding tools, Maximize Conversions does not allow marketers to set the bid or have insight into how bids are being set for campaigns. If campaigns underperform, retailers will not have access to important data that can help them reassess the strategy.
That data is particularly critical as retailers grow their business. For example, if a retailer uses Maximize Conversions but then wants to build out a more granular and robust strategy, it will have no historical bid or keyword data on which to base the new campaign. Essentially, the retailer will have to start from scratch.
For retailers who know they will eventually expand their Google paid search or display ad business, it may make sense to begin with a simple, manual campaign so that they can leverage that data in the future.