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Smart bidding: The right user, right time, right bid: How smart bidding increases efficiency and saves time

Manual bidding is not able to keep up with the variety of ads formats, devices, and audiences that are available today. Google Ads’ Unified Bidding solution Smart Bidding uses machine-learning to optimize for a wide variety of bidding signals in real-time — reducing complexity and improving outcomes.

While digital marketers have many more options to reach consumers on more devices than ever, it can be difficult to stay efficient while managing all the additional variables and options that result. From setting the right bids to two users with very different intentions to understanding how mobile impacts ROI, to understanding how buyers‘ journeys change when mobile is part, there are still many ways for them to reach their customers.

It is easy to get lost in the details and lose sight of what our core job is: to think strategically, use these opportunities to drive growth within our organizations.

Google, like many others, has been considering this problem. It is possible to eliminate all the complexity, save time, and make it easier for consumers. It is possible, we believe.

It all starts with strategies

The majority of online advertising bids are for one of these two purposes:

  1. Search to increase brand awareness
  2. Search to find more information about conversions and revenues

Most people use strategies such as to reach these goals.

They have all been successful in their respective ways. None of these approaches alone can make the most of today’s technology. Particularly manual approaches are not able to compete with today’s programmatic and automated world.

Machine learning is the answer.

Automated in real-time

Machine learning is an automated and real-time method to optimize your bids in order to increase conversions. Machine learning simply makes data work for you. Machine learning can help you bid the best for any auction by allowing you to choose the metrics most important to your business, such as ROAS or target CPA.

Machine learning is able to manage many bidding signals. It starts with the device of the user and adds variables such as their language, time of day, available creatives, and many more. Machine learning allows you to create bids that are tailored to the context of each user. Machine learning can detect which people are more likely to convert on mobile devices between 4-8 pm and use bidding tools to increase your bids to get the best results.

Improve Conversion Rates

Machine learning could help you see how different queries for “shoes”, “red shoes”, and “shoes” can lead to very different conversion rates. If you get a conversion rate of 2x for “red shoes”, you might want to increase your bids for that term while lowering them for “shoes”. These bids can be improved over time thanks to machine learning tools.

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Machine learning can add value to many verticals, including banking and eCommerce. If you are in real estate, and leads matter most to you, machine learning can analyze user signals to suggest higher bidding on those user segments that have demonstrated a greater likelihood of becoming leads. This is the type of complexity that manual bidding simply cannot handle.

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Google’s Response

Google launched Smart Bidding, a unified machine-learning and bidding solution to address these issues. Smart Bidding combines machine learning and true auction-time bidding to bring more relevant ads to users.

Google Ads 1 Smart bidding makes complex issues simple for advertisers. It compiles and integrates all of the current data. Then it uses auction-time bid adjustments in order to achieve outcomes that are impossible to humanly. Smart Bidding provides transparent reporting and status updates so that you can constantly test Smart Bidding’s effectiveness and learn about the inner workings of your bid strategies.

Google Ads Smart Bidding also works with many third-party advertising platforms, such as Adobe and Kenshoo. Advertisers have the option to use an eCPC bid strategy to complement third-party bids. This is provided that the conversions in both systems are within a 10% range.

Case studies

Smart Bidding is now being used by leading companies in India across a variety of industries, including travel and retail.

OLX allows millions to buy and sell used goods each day from one another in their local communities all over the globe. OLX recently tested Google Ads Smart Bidding against third-party platforms and found that Smart Bidding generated 89% more sales compared to the other two. This was at a 32% lower price per conversion.

Goibibo, Asia‘s most popular travel booking engine, offers hotel and airfare bookings via its website and mobile app. The 25% increase of hotel transactions in their A/B testing vs. target CPA smart bidding, as well as a 22% lower conversion cost for non-brand hotel search campaigns, were the results.

ICICI Prudential AMC, India’s largest mutual fund company (as measured by assets under management), improved their ROI through Smart Bidding. They activated tCPA-based bidding campaigns by correctly identifying keywords and query volumes. This resulted in a 70% increase in SIP Transactions and a 27% decrease in the cost per transaction.

IndustryBuying.com is one of India’s top B2B retailers. They wanted to improve their efficiency without losing their ad ranking for high-demand terms. They decreased their CPAs by 49% and maintained or improved their average mobile and desktop position.

All available

Anyone can use Smart Bidding with a Google Ads account. Smart Bidding is available for any strategy at any stage in the buying funnel.

It creates efficiency, which is perhaps the most important aspect. Your team can focus on strategic thinking and stop worrying about details.

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