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What Is Programmatic Advertising? How Does It Work?

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What Is Programmatic Advertising? How Does It Work?

Programmatic advertising has been a buzzword in the marketing industry for quite some time. But what does programmatic actually do? And how does it differ from traditional display marketing?

Programmatic advertising is a perfect realm where precision meets automation, and where your ads reach their perfect audience – almost as if by magic.

Gone are the days of casting wide audience nets and hoping for the best returns. In a digitally dynamic world, programmatic stands out as a blend of efficiency and effectiveness.

Ready to learn more? Read on to learn everything you need to know to be successful and harness the power of programmatic advertising.

What Is Programmatic Advertising?

Programmatic advertising uses automated technology and algorithmic tools for media buying. The term programmatic relates to the process of how ads are bought and sold in the advertising space.

Programmatic advertising differs from more traditional media buying methods in its use of automation.

It analyzes many user signals to ensure that ads serve the right person, in the right place, at the right time.

Essentially, it automates the decision-making process of ad placement – without having to manually negotiate prices or placements like other platforms.

This means your ads aren’t just thrown out into the digital void of the internet, hoping your audience will notice.

Instead, they’re strategically positioned when and where they’ll make the most impact.

Think of programmatic as the umbrella in this category, where different types of programmatic buying are categorized beneath it.

Read more: 7 Power Benefits Of Using PPC Advertising

What’s The Difference Between Programmatic And Display Ads?

It’s easy to confuse display and programmatic ads, especially with the strides that Google has made in its automated and real-time bidding capabilities.

The largest difference between programmatic and display is:

  • Programmatic refers to how ads are bought.
  • Display refers to the format in which ads appear.

Display ads are typically colorful banners, videos, or other interactive media that catch your attention on websites and apps.

Programmatic advertising, on the other hand, is considered the “behind-the-scenes” expert. It’s the technology-driven process behind the ads that decides which display ads you see, based on a whole host of factors such as:

  • Interests.
  • Behaviors.
  • Demographics.
  • Time of day.
  • And more.

The second biggest difference between display and programmatic is the ability to buy ads across platforms.

Display ads are more commonly referred to when placing ads within one specific ad network, such as the Google Display Network. Programmatic advertising, on the other hand, takes display media to the next level.

Multiple platforms exist for programmatic, such as sell-side platforms (SSPs) and demand-side platforms (DSPs), allowing advertisers to buy ad inventory across an open network of platforms.

With both programmatic and display, advertisers typically have control over the following:

  • Audience.
  • Bidding strategy.
  • Budget.
  • Creative and assets.
  • Placements.

Read more: How To Develop Your PPC Strategy

Programmatic Advertising Platforms

Automated technology has made significant strides throughout the years.

In the early days, programmatic platforms offered basic automation and targeting capabilities using simple data points.

As the digital landscape grew, so did the complexity and capabilities of these platforms.

These days, programmatic platforms are mostly powered by advanced algorithms, artificial intelligence, and machine learning.

To go even further, there are many types of programmatic platforms available today.

The three main types of platforms are:

  • Sell-side platform. Also known as a “supply-side platform,” this platform allows publishers to sell their ad impressions to advertisers in real-time. This platform encompasses both DSPs and ad exchanges. They’re equipped with technology that allows publishers to set minimum prices for their inventory, choose which ads appear on their site, and block ads from certain advertisers – if needed.
  • Demand-side platform. This platform allows advertisers to purchase ad inventory across multiple platforms at once. This is where most advertisers fit into this landscape. DSPs enable advertisers to manage their ad inventory bidding and target specific audiences using sophisticated data sources.
  • Ad exchanges. This is how SSPs flow their ad inventory to DSPs. DSPs connect to an ad exchanger, where ad prices fluctuate based on the competitiveness of that inventory. Think of the ad exchange as the neutral ground where transactions between SSPs and DSPs occur.

Understanding the key differences between SSPs, DSPs, and ad exchanges is crucial for navigating the programmatic landscape.

To familiarize yourself with the different platform types, let’s take a look at some of the major players in each category.

Sell-Side Platforms

A comprehensive list of SSPs for publishers includes:

  • Google Ad Manager.
  • Amazon Publisher Services.
  • OpenX.
  • SpotX.
  • Sovrn.
  • TripleLift.
  • PubMatic.
  • Adform.
  • Xandr (Microsoft).
  • Index Exchange.
  • Magnite.
  • Media.net.
  • Sharethrough.
  • StackAdapt.

If you’re looking for a video SSP, some of the leading companies include:

  • SpotX.
  • Teads.
  • SpringServe.
  • Verizon Media.

While there are many more available to publishers, these are companies you may have heard of but might not have associated with programmatic technology.

Demand-Side Platforms

If you’re a media buyer, this list is for you.

Like SSPs, these company names may ring a bell and offer DSPs.

Some of the top DSPs include:

  • Display & Video 360 (Google).
  • The Trade Desk.
  • Amazon Advertising.
  • MediaMath.
  • Xandr.
  • LiveRamp.
  • Adobe Advertising Cloud.
  • StackAdapt.
  • PubMatic.
  • Quantcast.
  • AdRoll.
  • Simpli.fi.
  • RhythmOne.
  • Criteo.
  • DemandBase.

Some of the larger DSPs for Connected TV and video include:

  • Display & Video 360 (Google)
  • OneView (Roku).
  • MediaMath.

Again, there are many more DSPs available to advertisers. It’s important to choose a DSP with the features and inventory you are looking for.

Some DSPs offer self-serve advertising, while others offer both self-serve and full-managed service (likely to larger advertisers or agencies).

Ad Exchanges

Some of the more well-known ad exchanges available to publishers include:

  • Xandr (Microsoft).
  • Verizon Media.
  • OpenX.
  • PubMatic.
  • Google Ad Exchange.
  • Index Exchange.
  • Magnite.
  • Smaato.
  • AdRoll.
  • InMobi.
  • Amazon.

Remember: not all ad exchanges are equal.

It’s important for publishers to research options carefully and choose platforms that align with their goals.

Read more: The 8 Best PPC Ad Networks

How Much Does Programmatic Advertising Cost?

Simply put, programmatic advertising can cost as little or as much as your budget allows.

It’s a common misconception that small businesses can’t benefit from programmatic technologies – but we’re here to correct that.

Programmatic ads are typically bought on a cost-per-thousand-impressions (CPM) basis. This means advertisers pay a set amount for every 1,000 impressions their ad receives.

CPMs typically range between $0.50 and $2.00; however, premium inventory can be upwards of $50 and more.

These prices are based on factors such as:

  • Which DSP you chose.
  • Your target audience and specificity.
  • Ad inventory quality.
  • Ad format.
  • Bidding strategy.
  • The level of competitiveness and demand.

A good rule of thumb for programmatic ad cost: the more niche your audience, the higher CPM you will pay.

So, whether you’re a multi-million dollar advertiser or a small business just getting started, you can likely fit programmatic into your advertising budget.

What Are The Benefits Of Programmatic Advertising?

There are many benefits to incorporating programmatic advertising into your marketing strategy.

Some of the top benefits include:

  • Large-scale audience reach.
  • Efficient and low-cost awareness.
  • Real-time data and analysis.
  • Ability to utilize first-party data.
  • Opportunities for cross-device campaign strategies.

Large-Scale Audience Reach

Arguably the biggest benefit of programmatic advertising is the ability to grow and scale.

Programmatic is the best way to buy ad inventory to reach the masses due to the abundance of cross-platform inventory.

Advertisers can also quickly adjust their audience strategies to capitalize on what is or isn’t working, ensuring their ads are always optimized.

Not only is it easier to scale your audience, but you can do so much more efficiently thanks to more precise factors like weather or time of day, coupled with real-time bidding.

Efficient And Low-Cost Awareness

Related to the above benefit of scaling reach, programmatic is one of the most cost-effective types of advertising that exists today.

Earlier, we discussed average CPMs for programmatic averaging between $0.50-$2.00.

Even with a small budget, your marketing dollars can go a long way toward reaching your target audience and increasing awareness of your product or service.

You can then take that audience further by setting up retargeting campaigns to guide users down their purchase journey, increasing incremental purchases and leads.

Real-Time Data And Analysis

Because programmatic platforms rely on real-time bidding, advertisers reap the benefit of receiving near real-time data.

Why does this matter?

Real-time data allows for faster decisions and pivots. It also puts you in a proactive rather than reactive mode.

Bids and strategies can be adjusted in real time based on immediate performance or even market conditions, which maximizes the chances of their ads being seen at the right time.

Utilizing First-Party Data

Another benefit of programmatic advertising is the type of data segments available to advertisers.

For example, advertisers can upload owned first-party data in a secure way and target those people directly using real-time bidding signals.

This avenue opens the door to finding new customers similar to current ones.

Cross-Device Campaign Strategy

It’s important to note that programmatic advertising is typically seen as an awareness tactic.

Because of this, companies that look solely at last-click success often overlook the true potential of programmatic advertising.

So, how does programmatic fit into a cross-device campaign?

The key is to capture that initial awareness to users through programmatic ads.

That initial awareness touchpoint can be run across multiple channels and formats like:

  • Display.
  • Video.
  • Mobile.
  • Social media.
  • Out-of-home.

Likely, a user won’t purchase a product or service after the first interaction with a brand.

Once a user’s interest is peaked, you have the ability to remarket to them on other platforms based on their interaction or engagement with that initial ad.

Marrying that data together from the first interaction to the eventual purchase is key to determining the success of your programmatic strategy.

Types Of Programmatic Advertising

There are different types of programmatic advertising.

These should not be confused with the programmatic platforms themselves.

The types of programmatic advertising are simply how an advertiser purchases ad inventory.

The four most common types are:

  • Real-time bidding. This type of bidding is open to all advertisers and most common form, where ad auctions happen in real time. This is also known as the “open marketplace.” Because it’s an open marketplace, it is naturally a highly competitive and dynamic space.
  • Private marketplace. Also known as PMPs, this bidding happens when publishers have invite-only agreements with a limited number of advertisers. These websites typically offer premium pricing because of the coveted ad space. There’s usually limited scale compared to RTB since inventory is restricted to that particular marketplace.
  • Preferred deals. Also known as “Spot Buying” or “Non-Guaranteed Premium,” this is a lesser-known type of programmatic advertising. Advertisers choose ad spots before they go on the private or open market. If the advertiser chooses not to buy the inventory, it can then be offered in a PMP or via RTB.
  • Programmatic guaranteed. Similar to a preferred deal, but there is no auction bidding. The publisher and advertiser have a direct agreement on a fixed price for ad inventory. It guarantees the advertiser a certain amount of inventory and guarantees the publisher revenue for that inventory.

Read more: What’s The Best PPC Bidding Strategy?

Programmatic Advertising Examples

Programmatic ads come in all shapes and sizes.

The beauty of using programmatic ads is tailoring the content to your chosen target audience.

A few well-executed programmatic campaigns include:

Amanda Foundation

The Amanda Foundation is a non-profit animal hospital and shelter rescue in the Los Angeles area.

It created a campaign to help at-risk shelter animals find a home during their final days.

Specifically, it leveraged programmatic signals like location, demographics, and browsing behavior to tailor specific animal images to its audience.

If users were interested in large dogs, they would be served a banner ad with large dogs instead of smaller dogs.

As you can see, messages and images were tailored to the individual’s behavior and interests.

Image from Amanda Foundation, August 2022

Geico Insurance

You’ve most likely seen or heard some version of a Geico ad.

Have you ever thought about the different ads Geico targets for you, though?

Geico uses such ad formats as TV commercials, website banner ads, social media ads, and more to create a true cross-platform awareness campaign.

The brand carefully chooses its content based on the platform it serves on, the target audience and demographics, and more.

Its commercials are so popular, in fact, that Geico has dedicated a resource page on its website where users can view their favorite commercials.

Progressive Insurance

While we’re on the topic of insurance, it would be remiss not to talk about Progressive’s use of programmatic ad targeting.

If you’re considered a Millennial or Gen Xer, you probably know what I mean.

Progressive created a series of commercials around the portrayal of young homeowners becoming like their parents.

As a homeowner myself, I’ve caught these commercials in the wild on my smart TV and within streaming services like Hulu.

Even further, their advanced targeting capabilities have caught my attention as I’m watching home shows like HGTV’s “Fixer Upper.”

Like Geico, Progressive hosts a dedicated page on its website of the famous character, Dr. Rick, and his videos on how to “un-become your parents.”

Brilliant Earth

Brilliant Earth is a leader in the fine jewelry space, with both physical locations and a strong online presence.

They’ve done a great job targeting different messages based on who was viewing items on their site.

In the example below, I visited their website and browsed different products.

A while later, I was served a subtle ad with an accompanying subtle message of “Drop a Hint.”

The brand had identified that I had been browsing rings but understands, based on user signals, that I may not be the one purchasing this item.

Its messaging based on these advanced signals is a great example of sending the right message to the right user at the right time.

Brilliant Earth programmatic ad example.Screenshot taken by author, March 2024

Programmatic Can Ensure That Advertising Budget Is Spent Wisely

The basics and benefits of programmatic advertising can help guide your existing programmatic strategy, or if you’re just getting started, create a new strategy that incorporates programmatic.

The evolution of programmatic platforms, with their sophisticated algorithms and data-driven strategies, has empowered advertisers to deliver their messages to the right people, in the right context, and with precision that was once only dreamed of.

The precision of programmatic advertising, married with efficiency and scalability, ensures that advertising dollars are being spent wisely, maximizing return on investment and driving meaningful engagement.

Understanding the functionality and features of each platform will be a critical component of your programmatic success.

More resources: 


Featured Image: ArtemisDiana/Shutterstock

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Google Search Leak: Conflicting Signals, Unanswered Questions

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Google Search Leak: Conflicting Signals, Unanswered Questions

An apparent leak of Google Search API documentation has sparked intense debate within the SEO community, with some claiming it proves Google’s dishonesty and others urging caution in interpreting the information.

As the industry grapples with the allegations, a balanced examination of Google’s statements and the perspectives of SEO experts is crucial to understanding the whole picture.

Leaked Documents Vs. Google’s Public Statements

Over the years, Google has consistently maintained that specific ranking signals, such as click data and user engagement metrics, aren’t used directly in its search algorithms.

In public statements and interviews, Google representatives have emphasized the importance of relevance, quality, and user experience while denying the use of specific metrics like click-through rates or bounce rates as ranking-related factors.

However, the leaked API documentation appears to contradict these statements.

It contains references to features like “goodClicks,” “badClicks,” “lastLongestClicks,” impressions, and unicorn clicks, tied to systems called Navboost and Glue, which Google VP Pandu Nayak confirmed in DOJ testimony are parts of Google’s ranking systems.

The documentation also alleges that Google calculates several metrics using Chrome browser data on individual pages and entire domains, suggesting the full clickstream of Chrome users is being leveraged to influence search rankings.

This contradicts past Google statements that Chrome data isn’t used for organic searches.

The Leak’s Origins & Authenticity

Erfan Azimi, CEO of digital marketing agency EA Eagle Digital, alleges he obtained the documents and shared them with Rand Fishkin and Mike King.

Azimi claims to have spoken with ex-Google Search employees who confirmed the authenticity of the information but declined to go on record due to the situation’s sensitivity.

While the leak’s origins remain somewhat ambiguous, several ex-Googlers who reviewed the documents have stated they appear legitimate.

Fishkin states:

“A critical next step in the process was verifying the authenticity of the API Content Warehouse documents. So, I reached out to some ex-Googler friends, shared the leaked docs, and asked for their thoughts.”

Three ex-Googlers responded, with one stating, “It has all the hallmarks of an internal Google API.”

However, without direct confirmation from Google, the authenticity of the leaked information is still debatable. Google has not yet publicly commented on the leak.

It’s important to note that, according to Fishkin’s article, none of the ex-Googlers confirmed that the leaked data was from Google Search. Only that it appears to have originated from within Google.

Industry Perspectives & Analysis

Many in the SEO community have long suspected that Google’s public statements don’t tell the whole story. The leaked API documentation has only fueled these suspicions.

Fishkin and King argue that if the information is accurate, it could have significant implications for SEO strategies and website search optimization.

Key takeaways from their analysis include:

  • Navboost and the use of clicks, CTR, long vs. Short clicks, and user data from Chrome appear to be among Google’s most powerful ranking signals.
  • Google employs safelists for sensitive topics like COVID-19, elections, and travel to control what sites appear.
  • Google uses Quality Rater feedback and ratings in its ranking systems, not just as a training set.
  • Click data influences how Google weights links for ranking purposes.
  • Classic ranking factors like PageRank and anchor text are losing influence compared to more user-centric signals.
  • Building a brand and generating search demand is more critical than ever for SEO success.

However, just because something is mentioned in API documentation doesn’t mean it’s being used to rank search results.

Other industry experts urge caution when interpreting the leaked documents.

They point out that Google may use the information for testing purposes or apply it only to specific search verticals rather than use it as active ranking signals.

There are also open questions about how much weight these signals carry compared to other ranking factors. The leak doesn’t provide the full context or algorithm details.

Unanswered Questions & Future Implications

As the SEO community continues to analyze the leaked documents, many questions still need to be answered.

Without official confirmation from Google, the authenticity and context of the information are still a matter of debate.

Key open questions include:

  • How much of this documented data is actively used to rank search results?
  • What is the relative weighting and importance of these signals compared to other ranking factors?
  • How have Google’s systems and use of this data evolved?
  • Will Google change its public messaging and be more transparent about using behavioral data?

As the debate surrounding the leak continues, it’s wise to approach the information with a balanced, objective mindset.

Unquestioningly accepting the leak as gospel truth or completely dismissing it are both shortsighted reactions. The reality likely lies somewhere in between.

Potential Implications For SEO Strategies and Website Optimization

It would be highly inadvisable to act on information shared from this supposed ‘leak’ without confirming whether it’s an actual Google search document.

Further, even if the content originates from search, the information is a year old and could have changed. Any insights derived from the leaked documentation should not be considered actionable now.

With that in mind, while the full implications remain unknown, here’s what we can glean from the leaked information.

1. Emphasis On User Engagement Metrics

If click data and user engagement metrics are direct ranking factors, as the leaked documents suggest, it could place greater emphasis on optimizing for these metrics.

This means crafting compelling titles and meta descriptions to increase click-through rates, ensuring fast page loads and intuitive navigation to reduce bounces, and strategically linking to keep users engaged on your site.

Driving traffic through other channels like social media and email can also help generate positive engagement signals.

However, it’s important to note that optimizing for user engagement shouldn’t come at the expense of creating reader-focused content. Gaming engagement metrics are unlikely to be a sustainable, long-term strategy.

Google has consistently emphasized the importance of quality and relevance in its public statements, and based on the leaked information, this will likely remain a key focus. Engagement optimization should support and enhance quality content, not replace it.

2. Potential Changes To Link-Building Strategies

The leaked documents contain information about how Google treats different types of links and their impact on search rankings.

This includes details about the use of anchor text, the classification of links into different quality tiers based on traffic to the linking page, and the potential for links to be ignored or demoted based on various spam factors.

If this information is accurate, it could influence how SEO professionals approach link building and the types of links they prioritize.

Links that drive real click-throughs may carry more weight than links on rarely visited pages.

The fundamentals of good link building still apply—create link-worthy content, build genuine relationships, and seek natural, editorially placed links that drive qualified referral traffic.

The leaked information doesn’t change this core approach but offers some additional nuance to be aware of.

3. Increased Focus On Brand Building and Driving Search Demand

The leaked documents suggest that Google uses brand-related signals and offline popularity as ranking factors. This could include metrics like brand mentions, searches for the brand name, and overall brand authority.

As a result, SEO strategies may emphasize building brand awareness and authority through both online and offline channels.

Tactics could include:

  • Securing brand mentions and links from authoritative media sources.
  • Investing in traditional PR, advertising, and sponsorships to increase brand awareness.
  • Encouraging branded searches through other marketing channels.
  • Optimizing for higher search volumes for your brand vs. unbranded keywords.
  • Building engaged social media communities around your brand.
  • Establishing thought leadership through original research, data, and industry contributions.

The idea is to make your brand synonymous with your niche and build an audience that seeks you out directly. The more people search for and engage with your brand, the stronger those brand signals may become in Google’s systems.

4. Adaptation To Vertical-Specific Ranking Factors

Some leaked information suggests that Google may use different ranking factors or algorithms for specific search verticals, such as news, local search, travel, or e-commerce.

If this is the case, SEO strategies may need to adapt to each vertical’s unique ranking signals and user intents.

For example, local search optimization may focus more heavily on factors like Google My Business listings, local reviews, and location-specific content.

Travel SEO could emphasize collecting reviews, optimizing images, and directly providing booking/pricing information on your site.

News SEO requires focusing on timely, newsworthy content and optimized article structure.

While the core principles of search optimization still apply, understanding your particular vertical’s nuances, based on the leaked information and real-world testing, can give you a competitive advantage.

The leaks suggest a vertical-specific approach to SEO could give you an advantage.

Conclusion

The Google API documentation leak has created a vigorous discussion about Google’s ranking systems.

As the SEO community continues to analyze and debate the leaked information, it’s important to remember a few key things:

  1. The information isn’t fully verified and lacks context. Drawing definitive conclusions at this stage is premature.
  2. Google’s ranking algorithms are complex and constantly evolving. Even if entirely accurate, this leak only represents a snapshot in time.
  3. The fundamentals of good SEO – creating high-quality, relevant, user-centric content and promoting it effectively – still apply regardless of the specific ranking factors at play.
  4. Real-world testing and results should always precede theorizing based on incomplete information.

What To Do Next

As an SEO professional, the best course of action is to stay informed about the leak.

Because details about the document remain unknown, it’s not a good idea to consider any takeaways actionable.

Most importantly, remember that chasing algorithms is a losing battle.

The only winning strategy in SEO is to make your website the best result for your message and audience. That’s Google’s endgame, and that’s where your focus should be, regardless of what any particular leaked document suggests.



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Google’s AI Overviews Shake Up Ecommerce Search Visibility

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Google's AI Overviews Shake Up Ecommerce Search Visibility

An analysis of 25,000 ecommerce queries by Bartosz Góralewicz, founder of Onely, reveals the impact of Google’s AI overviews on search visibility for online retailers.

The study found that 16% of eCommerce queries now return an AI overview in search results, accounting for 13% of total search volume in this sector.

Notably, 80% of the sources listed in these AI overviews do not rank organically for the original query.

“Ranking #1-3 gives you only an 8% chance of being a source in AI overviews,” Góralewicz stated.

Shift Toward “Accelerated” Product Experiences

International SEO consultant Aleyda Solis analyzed the disconnect between traditional organic ranking and inclusion in AI overviews.

According to Solis, for product-related queries, Google is prioritizing an “accelerated” approach over summarizing currently ranking pages.

She commented Góralewicz’ findings, stating:

“… rather than providing high level summaries of what’s already ranked organically below, what Google does with e-commerce is “accelerate” the experience by already showcasing what the user would get next.”

Solis explains that for queries where Google previously ranked category pages, reviews, and buying guides, it’s now bypassing this level of results with AI overviews.

Assessing AI Overview Traffic Impact

To help retailers evaluate their exposure, Solis has shared a spreadsheet that analyzes the potential traffic impact of AI overviews.

As Góralewicz notes, this could be an initial rollout, speculating that “Google will expand AI overviews for high-cost queries when enabling ads” based on data showing they are currently excluded for high cost-per-click keywords.

An in-depth report across ecommerce and publishing is expected soon from Góralewicz and Onely, with additional insights into this search trend.

Why SEJ Cares

AI overviews represent a shift in how search visibility is achieved for ecommerce websites.

With most overviews currently pulling product data from non-ranking sources, the traditional connection between organic rankings and search traffic is being disrupted.

Retailers may need to adapt their SEO strategies for this new search environment.

How This Can Benefit You

While unsettling for established brands, AI overviews create new opportunities for retailers to gain visibility without competing for the most commercially valuable keywords.

Ecommerce sites can potentially circumvent traditional ranking barriers by optimizing product data and detail pages for Google’s “accelerated” product displays.

The detailed assessment framework provided by Solis enables merchants to audit their exposure and prioritize optimization needs accordingly.


FAQ

What are the key findings from the analysis of AI overviews & ecommerce queries?

Góralewicz’s analysis of 25,000 ecommerce queries found:

  • 16% of ecommerce queries now return an AI overview in the search results.
  • 80% of the sources listed in these AI overviews do not rank organically for the original query.
  • Ranking positions #1-3 only provides an 8% chance of being a source in AI overviews.

These insights reveal significant shifts in how ecommerce sites need to approach search visibility.

Why are AI overviews pulling product data from non-ranking sources, and what does this mean for retailers?

Google’s AI overviews prioritize “accelerated” experiences over summarizing currently ranked pages for product-related queries.

This shift focuses on showcasing directly what users seek instead of traditional organic results.

For retailers, this means:

  • A need to optimize product pages beyond traditional SEO practices, catering to the data requirements of AI overviews.
  • Opportunities to gain visibility without necessarily holding top organic rankings.
  • Potential to bypass traditional ranking barriers by focusing on enhanced product data integration.

Retailers must adapt quickly to remain competitive in this evolving search environment.

What practical steps can retailers take to evaluate and improve their search visibility in light of AI overview disruptions?

Retailers can take several practical steps to evaluate and improve their search visibility:

  • Utilize the spreadsheet provided by Aleyda Solis to assess the potential traffic impact of AI overviews.
  • Optimize product and detail pages to align with the data and presentation style preferred by AI overviews.
  • Continuously monitor changes and updates to AI overviews, adapting strategies based on new data and trends.

These steps can help retailers navigate the impact of AI overviews and maintain or improve their search visibility.


Featured Image: Marco Lazzarini/Shutterstock



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Google’s AI Overviews Go Viral, Draw Mainstream Media Scrutiny

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Google's AI Overviews Go Viral, Draw Mainstream Media Scrutiny

Google’s rollout of AI-generated overviews in US search results is taking a disastrous turn, with mainstream media outlets like The New York Times, BBC, and CNBC reporting on numerous inaccuracies and bizarre responses.

On social media, users are sharing endless examples of the feature’s nonsensical and sometimes dangerous output.

From recommending non-toxic glue on pizza to suggesting that eating rocks provides nutritional benefits, the blunders would be amusing if they weren’t so alarming.

Mainstream Media Coverage

As reported by The New York Times, Google’s AI overviews struggle with basic facts, claiming that Barack Obama was the first Muslim president of the United States and stating that Andrew Jackson graduated from college in 2005.

These errors undermine trust in Google’s search engine, which more than two billion people rely on for authoritative information worldwide.

Manual Removal & System Refinements

As reported by The Verge, Google is now scrambling to remove the bizarre AI-generated responses and improve its systems manually.

A Google spokesperson confirmed that the company is taking “swift action” to remove problematic responses and using the examples to refine its AI overview feature.

Google’s Rush To AI Integration

The flawed rollout of AI overviews isn’t an isolated incident for Google.

As CNBC notes in its report, Google made several missteps in a rush to integrate AI into its products.

In February, Google was forced to pause its Gemini chatbot after it generated inaccurate images of historical figures and refused to depict white people in most instances.

Before that, the company’s Bard chatbot faced ridicule for sharing incorrect information about outer space, leading to a $100 billion drop in Google’s market value.

Despite these setbacks, industry experts cited by The New York Times suggest that Google has little choice but to continue advancing AI integration to remain competitive.

However, the challenges of taming large language models, which ingest false information and satirical posts, are now more apparent.

The Debate Over AI In Search

The controversy surrounding AI overviews adds fuel to the debate over the risks and limitations of AI.

While the technology holds potential, these missteps remind everyone that more testing is needed before unleashing it on the public.

The BBC notes that Google’s rivals face similar backlash over their attempts to cram more AI tools into their consumer-facing products.

The UK’s data watchdog is investigating Microsoft after it announced a feature that would take continuous screenshots of users’ online activity.

At the same time, actress Scarlett Johansson criticized OpenAI for using a voice likened to her own without permission.

What This Means For Websites & SEO Professionals

Mainstream media coverage of Google’s erroneous AI overviews brings the issue of declining search quality to public attention.

As the company works to address inaccuracies, the incident serves as a cautionary tale for the entire industry.

Important takeaway: Prioritize responsible use of AI technology to ensure the benefits outweigh its risks.



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