Date of Publication: 5 April 2023

How are AI-Engines Revolutionizing Paid Search Ad Campaigns?

AI-Engines are changing the game in paid search ad campaigns, making it more refined and precise. They can help marketers understand and analyze user behavior, preferences, and search history to create highly targeted ads that are more likely to convert. AI-powered automated bidding, ad optimization, audience segmentation, and dynamic ad creation are some of the ways AI-engines are revolutionizing paid search ad campaigns. There are several AI-powered ad platforms available, such as Skai, MarinOne, Adobe Advertising Cloud, Acquisio,  and Quarizmi, which can optimize poorly performing search ads and help you get the most out of your ad spend.

In this blog post we will explore how AIEngines are revolutionizing the way you can launch, manage and optimize your paid search ad campaigns


Anirban Guha

Anirban Guha

Digital Marketing Expert | Media Strategist | Entrepreneur

Table of Contents

How are AI-Engines Revolutionizing Paid Search Ad Campaigns? - AgsDigitalTales - Kolkata Digital Marketing

Advanced Audience Targeting – in Paid Search Ad Campaigns:

AI-Engines will revolutionize paid search ad campaigns to the extent of understanding and analysing, user’s behavior, preferences, and search history to create a comprehensive profile. The near future marketers will be able to use this data to create highly targeted ads that are more likely to convert.

Here are some ways:

Predictive Analytics:

AI engines can use predictive analytics to analyse vast amounts of data and identify patterns in user behavior. This will allow marketers to understand their target audience better and anticipate their needs and preferences.

Real-time Insights:

AI engines with more advanced capabilities will provide accurate real-time insights into audience behavior and preferences. The marketers are able to adjust their targeting strategies in real-time and ensure that their Paid Search Ads are always remain relevant.


Advanced AI engines would evolve to more accurately analyse user data to create detailed user profiles for developing highly personalized ad contents that are tailored to the individual needs and preferences of each user.

You can improve your search engine results by understanding how PPC and SEO work together. Frequent search engine visibility helps, but irrelevant keywords can be detrimental. Pay-per-click and organic search can boost business growth and revenue with the right strategy and planning. We’ll explore how businesses can gain a competitive edge through both paid and organic search in this blog post. This article explores how best to synergize the two key element – paid and organic search…>>CLICK TO READ MORE

AI-Engines revolutionizing Paid Search Ad Campaigns through Automated Bidding

As more businesses have access to required technologies, automated machine learning is becoming a more and more common alternative for deciding what price to bid on paid search ad campaigns. A bid that is too low will prevent you from connecting with leads, while a bid that is too high will reduce your return on investment. In addition to being the same as what everybody else is using, Google’s automated bidding lacks the data it requires to maximize your ROI. Knowing consumer trends, purchasing patterns, seasonality, demographics, customer lifetime value, and other information is also necessary to accomplish that goal.


Features of a successful Automated Bidding Model for Paid Search Ad Campaigns:

  • Use statistical inference based on prior bids to calculate each ad’s price elasticity.
  • Consider the actual value anticipated from each individual ad click based on prior clicks
  • Iterate based on fresh information
  • Instead of making the mistaken assumption that past performance would always be a reliable indicator of future performance, quickly respond to changes in the bidding environment or the effectiveness of visits.


Things to keep in mind while using AI-powered Automated Bidding Strategy:

  • Models will draw incorrect conclusions if they are unaware of what is happening on your website. For instance, your model might start placing lower bids on those keywords if you test a fresh landing page and it lowers your ROI. The model can still be stuck bidding low on the keywords even after switching to a better landing page because there isn’t enough fresh information to raise the bids.
  • Models that too rely on statistical significance run the risk of testing a lost approach for an excessive amount of time, while models that don’t take statistical significance into account may miss out on good possibilities while supporting flukes.
  • Check your model for feedback loops. For instance, you wouldn’t want your model to make a higher bid on an advertisement with a high conversion rate if the sole factor contributing to the high conversion rate is the high bids. Conflicts of this sorts should be avoided.


Steps for Automated Bidding Paid Search Ad Campaigns:

  • Define your goals and KPIs: Before implementing any automated bidding strategy, it’s essential to identify your goals and key performance indicators (KPIs) for your search ad campaign. These could be different for each campaign, but common KPIs include cost-per-click (CPC), cost-per-conversion (CPA), return on ad spend (ROAS), and impression share.
  • Collect data: To train your machine learning algorithms, you need to collect historical performance data for your campaign. You can get this data from your ad platform, such as Google Ads, Bing Ads, or Facebook Ads.
  • Choose a bidding strategy: There are several automated bidding strategies you can choose from, including:
    • Target CPA (Cost-Per-Acquisition): This strategy sets bids to help get as many conversions as possible at the target CPA you set.
    • Target ROAS (Return on Ad Spend): This strategy sets bids to help get as much revenue as possible at the target ROAS you set.
    • Enhanced CPC (Cost-Per-Click): This strategy automatically adjusts your manual bids to help you get more conversions.
    • Maximise Clicks: This strategy automatically sets bids to help you get the most clicks within your budget.
    • Maximise Conversions: This strategy automatically sets bids to help you get the most conversions within your budget.
  • Choose an AI tool: There are several AI tools you can use to implement automated bidding. Platforms like MarineOne, Skai and Adobe Advertising Cloud provide AI-powered Ad platforms.
  • Monitor and optimize: Once you implement an AI-powered bidding strategy, it’s essential to monitor its performance regularly and make adjustments as needed. This includes analyzing your data, reviewing your KPIs, and testing different bidding strategies to find what works best for your campaign.

AI-powered Ad Platforms can help you optimize poorly performing Paid Search Ad Campaigns

AI-powered ad platforms can help with poorly performing search ads in a few different ways:

Ad Optimization:

The AI-Engines in ad platforms analyse data like click-through rates, conversion rates, and other factors to improve underperforming search advertising. The technology can automatically alter the ad’s location, keywords, or targeting criteria based on this information to improve the performance.

Audience Segmentation:

AI-powered ad platforms can segment audiences based on behavior and other data points to identify which audience segments are underperforming. This allows marketers to make adjustments to their targeting strategies to better reach those audiences.

Ad Testing:

By using machine learning algorithms to evaluate many iterations of poorly performing search advertisements, AI-Engines in leading ad platforms have revolutionized search ads. This enables marketers to pinpoint the parts of the advertisement that aren’t working well and make changes to raise their effectiveness.

Dynamic Ad Creation:

AI-Engines in leading ad platforms can create personalized ads in real-time, based on the user’s search query and other data points. This ensures that the ad is highly relevant to the user, increasing the likelihood of a click and conversion.


AI-powered ad platforms can help with poorly performing paid search ad campaigns by optimizing the ad, segmenting audiences, testing different versions of the ad, and even pause the ads helping advertisers get more relevant impression share, clicks and conversion.

AI-powered Platforms for optimizing Paid Search Ad Campaigns

Skai’s™ Budget Navigator

Combined with Google Smart Bidding, customers can benefit from Google and automated budget allocation from Skai™ to truly maximize efficient return on ad spend (ROAS) across a search marketer’s entire portfolio. As per the company sources, when they are used in combination the CPC on average gets reduced by 10% while Target ROAS increase by 18% resulting in 17% more revenue from the ad budget.

MarinOne Budget Optimizer

 It continuously monitors your campaign spending and automatically adjusts allocation to keep you on target. So that you never worry about over or under-spending again. The platform enables you to map any number of campaigns from multiple Google and Bing accounts to a strategy with a shared spending goal. It provides flexibility regardless of your account structure or program complexity.

Adobe Advertising Cloud

To provide you with more accurate campaign projections across all of your important indicators, Adobe has developed advanced bidding models. It automates and customizes bids using artificial intelligence so you can improve your campaigns without expending unnecessary time and effort. Enter your campaign’s target, and all of your bid units will be automatically optimized for the most key conversion events.


It provides end-to-end features and functionality built for easier campaign management. It offers SEM software and tools for paid search ad campaigns. With Aquisio you can scale up your search engine marketing efficiently, using one platform to launch, manage and report across Google and Bing campaigns.


One of the few AI platforms with a clear focus on Google Ads. It helps to automate your Paid Search Campaigns. It promises a 20% increase in Leads in 10 days and 10-15% increase in sales within a week. Instead of focusing on bidding against your competition or squeezing your current campaigns, it boosts your results through Long-Tail keywords.


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About the Author - Anirban Guha


Anirban Guha is an MBA graduate from Amity University, Noida. Starting his career with The Times of India Group, he has spent over 16 years in advertising and has been the founder-director of an award-winning digital marketing agency, Tejom Digital for over 6 years. He has worked with some of the top brands in India and beyond. He is an expert in creative design and digital marketing. He is passionate about helping businesses reach their goals. Beside his professional life, Anirban is an avid reader, a movie buff, a passionate gardener, an art enthusiast, and a foodie.