The concept of Smart Bidding has evolved due to the ever-changing technological environment and user behavior. Earlier advertisers were confined to a limited set of devices comprised mainly of PCs. However, with the advent of new technologies and the adoption of mobile devices, setting up an exhaustive digital campaign has become a complicated task.
Benefits of Smart Bidding: A Smart and Self-Learning Search Campaign
Data and Knowledge Engineering: The machine learning algorithms involved in Smart Bidding use volumes of data to make more accurate predictions and bid adjustments across your account. As a best practice, it is suggested to initially run a campaign on manual bidding and collect performance data which can be used later by the Smart Bidding algorithms to make precise optimizations.
Customizable Performance Control Settings: Smart Bidding offers unique customization features. For instance, a user can optimize search bids to the selected attribution model, including data-driven attribution. The user can also set device-specific performance targets for mobile, desktop, and tablet with Target CPA bidding.
Contextual Signals for Optimization: Contextual signals are identifiable attributes about a person or their context at the time of a particular auction. These include attributes like device and location, which are available as manual bid adjustments. Additional signals and signal combinations exclusive to Smart Bidding like operating system and browser can also make an impact.
Understanding Contextual Signals Better
AdWords can optimize bids based on the following parameters.
Query Intent (Informational or Commercial): AdWords can optimize bids based on the query intent, and not only at the keyword level. For example, an iPhone seller may optimize bids if a user searches for “what is the price of an iPhone X” compared to “most promising feature of an iPhone X.”
Interface Language: Bids can be optimized by a person’s language preference. If someone searches for “how to learn French” or “learn French” and the language setting is English, the bids will be adjusted accordingly for a French learning website.
Time of Day: AdWords can optimize bids based on someone’s local time of day and day of the week. For a restaurant, bids may be adjusted if someone searches at 8 p.m. on a Thursday, when people are more likely to make a reservation for the weekend, compared to 8 a.m. on a Monday.
Demographics: Bids can be optimized based on age and gender. For Display campaigns, bids can also be optimized for interests. For a toy retailer, bids may be adjusted if someone has been identified as a parent and is more likely to convert on a Display ad promoting a new line of educational toys.
NX Insights: Smart Campaigns at NetElixir
NetElixir has been applying Smart Bidding techniques for clients to successfully boost their campaign performance and generate positive results without any trade-off in extra ad spend.
These results have given us deeper insight into how machine learning in AdWords manages the overall budget. It might accelerate the ad spend up to 30% of the overall budget on some select high-performing days while compensating for that extra spend on a slow business day.
The following are some key observations on how we helped one of our clients in the B2B bulk gifting industry:
We incorporated Smart Bidding in a Shopping campaign for a duration of two months and witnessed positive escalations in key metrics like cost and revenue/cost. The overall revenue share from PLAs rose from 0.004% to 0.091%, which is a staggering 2,175% overall increase. That said, we also witnessed a 9% decline in CTR.
The above observations helped us understand that we cannot attribute the success of a bidding strategy to one particular metric, and we should always take a holistic approach.
We used the Maximize Conversions Smart Bidding strategy for one of our clients’ Dynamic Search Ads campaign and witnessed the following results:
With Maximize Conversions as our strategy, the primary goal was to increase the number of orders. We were able to achieve an enormous 240% increase in overall orders.
An increase in orders resulted in an overall increase in revenue by 140%. This particular campaign raised the cost by 482%, which meant that the client’s revenue/cost metric declined by 59%.
All considered, the overall goal of this strategy was achieved and we saw a large increase in the total number of orders.