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Microsoft calls deceased NBA player ‘useless’ in AI-written obituary

Saturday, September 16th, 2023

Microsoft has been criticised after publishing an AI-generated obituary for NBA star Brandon Hunter.

The former Boston Celtics and Orlando Magic player passed away suddenly this week, aged 42, after collapsing during a hot yoga class in Orlando, Fla.

Shortly after his passing, fans were shocked to see the father of three described as “useless” in an obituary published on MSN.

The headline read:

Why we care. MSN laid off two dozen editorial staff a few years ago with plans to replace the writers with generative AI, the Guardian reported. This case highlights the importance of not relying solely on AI for generating content due to factual inaccuracies and problematic errors, and the need to ensure that all work produced by AI is supervised by humans. Failure to do so could harm your brand’s reputation as well as negatively impacting your search rankings.

Incomprehensible. While the MSN headline was offensive, the rest of the article was incoherent. It read:

Reputational damage. Despite swiftly removing the article from the MSN website, Microsoft was criticized on social media for publishing the offensive content:

What Microsoft is saying. A Microsoft spokesperson told Search Engine Land:

However, the company is yet to officially apologize.

Dig deeper. Futurism broke the news in Microsoft Publishes Garbled AI Article Calling Tragically Deceased NBA Player “Useless”.

Other brands stumbles with AI. We’ve previously reported on a number of brands that have published articles with errors, all of which were lacking in E-E-A-T in different ways:

As a reminder, Google doesn’t care who – or what – writes your content, as long as that content is helpful and not created to manipulate search results.

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Courtesy of Search Engine Land: News & Info About SEO, PPC, SEM, Search Engines & Search Marketing

Amazon sellers can now use AI to write product titles, descriptions and listing details

Friday, September 15th, 2023

Amazon is rolling out enhanced AI capabilities to help advertisers create better product listings.

The new technology simplifies how sellers create product descriptions, titles, and listing details by automatically generating content based on brief product descriptions.

Previously, sellers were required to enter many pieces of information to create product listings, however, the process has now been streamlined into just one step.

Why we care. Creating product titles, bullet points and descriptions has historically been a time-consuming task for sellers that demanded substantial effort. AI adoption could help alleviate this workload, simplifying and speeding up the process of listing new products, while also potentially improving product listing content.

How it works. To get started, you need to provide a brief description of your product in a few words or sentences. Amazon will then create content for you – which you can then review.

If you wish, you can make further adjustments to the generated content, or you can submit it directly to the Amazon catalog as it is.

Reviews. Early feedback collected over the last few months shows that most sellers are using the content generated by the AI model for their listings without editing it at all.

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What has Amazon said? Robert Tekiela, vice president of Amazon Selection and Catalog Systems, said in a statement:

Deep dive. Read Amazon’s announcement in full for more information.

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Courtesy of Search Engine Land: News & Info About SEO, PPC, SEM, Search Engines & Search Marketing

Google September 2023 helpful content system update rolling out

Friday, September 15th, 2023

Google has begun to push out an update to its helpful content system, the last helpful content system update was the December 2022 helpful content update. The update started on September 14 and should take about two weeks to fully roll out.

What is new. Google said, “The September 2023 helpful content update is rolling out with an improved classifier. It will take about two weeks to complete. We’ll update our ranking release history page when the rollout is complete.”

Google added new details about helpful content, specifically:

In May, Google told us a helpful content system update would be coming this year. Google said this update would enable the helpful content system to “more deeply understands content created from a personal or expert point of view.” “We’re also improving how we rank results in Search overall, with a greater focus on content with unique expertise and experience,” Google also said a few months ago.

Google said this is not today’s update. Google wrote, “This work is still continuing and is not part of this particular update. We’ll share more about our work in this area in the future.”

What to do if you are hit. Google has provided a list of questions you can ask yourself about your content. Read through those questions as we posted over here, and in an unbiased manner, ask yourself if your content is in sync with this update.

Please note if this update has hit you, it can take several months to recover if you do everything right and make changes to your content over time.

More on the helpful content update. Google’s helpful content update specifically targets “content that seems to have been primarily created for ranking well in search engines rather than to help or inform people.”

This algorithm update aims to help searchers find “high-quality content,” Google told us. Google wants to reward better and more useful content that was written for humans and to help users.

Searchers get frustrated when they land on unhelpful webpages that rank well in search because they were written for the purpose of ranking in search engines. This is the type of content you might call “search engine-first content” or “SEO content.”

Google’s helpful content algorithm aims to downgrade those types of websites while promoting more helpful websites, designed for humans, above search engines.

Google said this is an “ongoing effort to reduce low-quality content and make it easier to find content that feels authentic and useful in search.”

Why we care. If you notice any ranking and visibility changes in Google search over the next two weeks or so, especially if those were big changes, you can likely attribute it to this update. Read Google’s advice, make the necessary changes, and hope for a recovery in the upcoming months.

We hope you all will see a positive trend with your ranking and visibility in Google Search from this update.

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Courtesy of Search Engine Land: News & Info About SEO, PPC, SEM, Search Engines & Search Marketing

TikTok quietly adds Wikipedia snippets to its search results

Friday, September 15th, 2023

TikTok now serves Wikipedia snippets in some of its search results.

This is the first time that the platform has offered its users results from the wider web as historically, it exclusively featured its own content in SERPs.

The Wikipedia snippets were first noticed in TikTok SERPs by The Verge, as shown here:

A spokesperson for the social media app confirmed that the new feature has been live for several months, however, a formal announcement was never made.

Why we care. While Google has previously stated that it sees TikTok as a search competitor, the social media app is clearly intensifying its efforts in the search arena.

A recent survey revealed the majority of Gen Z women are favoring TikTok over Google for their search needs. This shift in user preference raises questions about whether Google might find itself facing a more concerning competitor in the search space than previously anticipated.

How it works. Wikipedia snippets are served on some accounts for select SERPs for”

The snippets been spotted wedged between relevant videos as users have been scrolling down through in-app search results pages.

By clicking on the links that appear at the bottom of the snippet, users are taken to different sections of the Wikipedia entry.

Deep dive. Read TikTok’s Search and Discover guidelines for more information.

The post TikTok quietly adds Wikipedia snippets to its search results appeared first on Search Engine Land.

Courtesy of Search Engine Land: News & Info About SEO, PPC, SEM, Search Engines & Search Marketing

Amazon launches new search functions on mobile to rival Google

Friday, September 15th, 2023

Amazon is rolling out new features to improve its search capabilities on mobile.

In a bid to rival search engines like Google and Pinterest, the retail giant is launching new search and discovery tools, including:

Why we care. Although each update may seem inconsequential on its own, together, these new tools can influence how consumers search for products and redirect more searches to Amazon. Consequently, these changes could affect Google’s advertising revenue, as Amazon has been closing in on the dominant position held by Google and Meta in digital ad spending.

Multimodal search. This new tool, which is an improvement on Amazon’s existing visuals search engine, allows consumers to add text as well as images to search for matching products. For example, if you need a replacement part for an appliance, you can snap a photo of the part and include the appliance’s name, such as “Frigidaire.”

Expanded AR efforts. Amazon’s augmented reality tool, initially used for visualizing furniture and decor in your space, now extends to smaller items such as lamps and appliances such as toasters and coffee machines. With this AR feature, you can also rearrange items from one surface to another.

Find-on-Amazon. With this tool, you can search for products using a photo from anywhere. If you see something you like on social media, while browsing the web, reading emails, or chatting online, you can tap the “Share” button and send the image to the Amazon Shopping app. This allows the app to find visually similar products even if you don’t know their name or how to describe them.

More updates. Amazon announced that in addition to the changes mentioned above, it is also rolling out other smaller improvements, including:

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What has Amazon said? An Amazon spokesperson said in a statement:

Deep dive. Read Amazon’s Search and Shop announcement in full for more information.

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TW-BERT: End-to-end query term weighting and the future of Google Search

Thursday, September 14th, 2023

Search is hard, as Seth Godin wrote in 2005.

I mean, if we think SEO is hard (and it is) imagine if you were trying to build a search engine in a world where:

On top of that, you’re also dealing with pesky SEOs trying to game your algorithm gain insights into how best to optimize for your visitors.

That’s going to make it a lot harder.

Now imagine if the main technologies you need to lean on to advance came with their own limitations – and, perhaps worse, massive costs.

Well, if you’re one of the writers of the recently published paper, “End-to-End Query Term Weighting” you see this as an opportunity to shine.

What is end-to-end query term weighting?

End-to-end query term weighting refers to a method where the weight of each term in a query is determined as part of the overall model, without relying on manually programmed or traditional term weighting schemes or other independent models.

What does that look like?

Here we see an illustration of one of the key differentiators of the model outlined in the paper (Figure 1, specifically).

On the right side of the standard model (2) we see the same as we do with the proposed model (4), which is the corpus (full set of documents in the index), leading to the documents, leading to the terms. 

This illustrates the actual hierarchy into the system, but you can casually think of it in reverse, from the top down. We have terms. We look for documents with those terms. Those documents are in the corpus of all the documents we know about.

To the lower left (1) in the standard Information Retrieval (IR) architecture, you’ll notice that there is no BERT layer. The query used in their illustration (nike running shoes) enters the system, and the weights are computed independently of the model and passed to it.

In the illustration here, the weights are passing equally among the three words in the query. However, it does not have to be that way. It’s simply a default and good illustration. 

What is important to understand is that the weights are assigned from outside the model and entered it with the query. We’ll cover why this is important momentarily.

If we look at the term-weight version on the right side, you’ll see that the query “nike running shoes” enters BERT (Term Weighting BERT, or TW-BERT, to be specific) which is used to assign the weights that would be best applied to that query.

From there things follow a similar path for both, a scoring function is applied and documents are ranked. But there’s a key final step with the new model, that is really the point of it all, the ranking loss calculation.

This calculation, which I was referring to above, makes the weights being determined within the model so important. To understand this best, let’s take a quick aside to discuss loss functions, which is important to really understand what’s going on here.

What is a loss function?

In machine learning, a loss function is basically a calculation of how wrong a system is with said system trying to learn to get as close to a zero loss as possible.

Let’s take for example a model designed to determine house prices. If you entered in all the stats of your house and it came up with a value of $250,000, but your house sold for $260,000 the difference would be considered the loss (which is an absolute value).

Across a large number of examples, the model is taught to minimize the loss by assigning different weights to the parameters it is given until it gets the best result. A parameter, in this case, may include things like square feet, bedrooms, yard size, proximity to a school, etc.

Now, back to query term weighting

Looking back at the two examples above, what we need to focus on is the presence of a BERT model to provide the weighting to the terms down-funnel of the ranking loss calculation. 

To put it differently, in the traditional models, the weighting of the terms was done independent of the model itself and thus, could not respond to how the overall model performed. It could not learn how to improve in the weightings.

In the proposed system, this changes. The weighting is done from within the model itself and thus, as the model seeks to improve it’s performance and reduce the loss function, it has these extra dials to turn bringing term weighting into the equation. Literally.


TW-BERT isn’t designed to operate in terms of words, but rather ngrams.

The authors of the paper illustrate well why they use ngrams instead of words when they point out that in the query “nike running shoes” if you simply weight the words then a page with mentions of the words nike, running and shoes could rank well even if it’s discussing “nike running socks” and “skate shoes”.

Traditional IR methods use query statistics and document statistics, and may surface pages with this or similar issues. Past attempts to address this focused on co-occurrence and ordering.

In this model, the ngrams are weighted as words were in our previous example, so we end up with something like:

On the left we see how the query would be weighted as uni-grams (1-word ngrams) and on the right, bi-grams (2-word ngrams).

The system, because the weighting is built into it, can train on all the permutations to determine the best ngrams and also the appropriate weight for each, as opposed to relying only on statistics like frequency.

Zero shot

An important feature of this model is its performance in zero-short tasks. The authors tested in on:

They only had a small number of evaluation queries and used none for fine-tuning, making this a zero-shot test in that the model was not trained to rank documents on these domains specifically. The results were:

It outperformed in most tasks and performed best on shorter queries (1 to 10 words).

And it’s plug-and-play!

OK, that might be over-simplifying, but the authors write:

“Aligning TW-BERT with search engine scorers minimizes the changes needed to integrate it into existing production applications, whereas existing deep learning based search methods would require further infrastructure optimization and hardware requirements. The learned weights can be easily utilized by standard lexical retrievers and by other retrieval techniques such as query expansion.”

Because TW-BERT is designed to integrate into the current system, integration is far simpler and cheaper than other options.

What this all means for you

With machine learning models, it’s difficult to predict example what you as an SEO can do about it (apart from visible deployments like Bard or ChatGPT).

A permutation of this model will undoubtedly be deployed due to its improvements and ease of deployment (assuming the statements are accurate).

That said, this is a quality-of-life improvement at Google, that will improve rankings and zero-shot results with a low cost.

All we can really rely on is that if implemented, better results will more reliably surface. And that’s good news for SEO professionals.

The post TW-BERT: End-to-end query term weighting and the future of Google Search appeared first on Search Engine Land.

Courtesy of Search Engine Land: News & Info About SEO, PPC, SEM, Search Engines & Search Marketing

Why now is the right time to implement SMS marketing by Digital Marketing Depot

Thursday, September 14th, 2023

On average, Americans now check their phones 262 times a day and daily screen time averages over five hours per day. People are using their phones more frequently, for longer periods of time, and are shopping from their phones more than ever before.

With 54% of web traffic coming from mobile, adding text messaging (also known as SMS) to your ecommerce stack can help your team reach more customers faster—while maintaining a seamless customer experience.

This practical SMS marketing guide from Cordial provides best practices and essential tips to help you build an effective SMS marketing strategy that drives new revenue streams and loyalty.

Visit Digital Marketing Depot to download Strengthen Customer Loyalty with SMS Marketing.

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Actionable. Digital. Free. Get your SMX Next sneak peek here.

Thursday, September 14th, 2023

Finish 2023 strong and step into 2024 ready to stay ahead of Google algorithm updates, supercharge your funnel with qualified leads, and leverage generative AI to your advantage: Attend SMX Next, online November 14-15, to learn actionable, brand-safe search marketing tactics for free without leaving your desk.

Programmed by the Search Engine Land editors, this expert-led training program explores the latest, most critical search marketing topics, including…

… plus so much more. And you’re the first to hear about our just-announced PPC keynote featuring the one and only Fred Vallaeys!

Stay tuned for more keynote details! Your free pass packs the entire SMX experience:

No plane ticket, hotel booking, or expense reports required.

For nearly 20 years, more than 150,000 search marketers from around the world have attended SMX to learn game-changing tactics, connect with like-minded professionals, and further their careers.

Don’t miss your final chance to join us in 2023. Secure your free pass now!

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Overcoming the Google SGE challenge: Assessment and recovery strategies by Cynthia Ramsaran

Thursday, September 14th, 2023

Google Search Generative Experience (SGE) is looming over the search industry, but little is understood about its mechanisms and expected impact on our organic traffic.

Join this webinar to understand how to overcome the Google SGE challenge. The first step is assessing how Google SGE goes live and how it will impact your organic traffic. Next, identify how to recover from expected traffic drops. Register now to learn about solutions that will help your organization mitigate the risk of SGE.

Register and attend “Overcoming the Google SGE Challenge: Assessment and Recovery Strategies” presented by AgileSEO.

Click here to view more Search Engine Land webinars.

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Google Performance Max: Everything you need to know

Tuesday, September 12th, 2023

Even the most traditional PPC manager can’t deny it anymore: Performance Max can do amazing things. Of course, that requires you to approach it with a different mindset than Search and Shopping.

Let me give you an example.

Years ago, when working with retailers selling products from many different brands, you typically make a separate Shopping campaign for each brand. Try that with Performance Max, and you’ll force it into doing something it’s not built for. And performance certainly won’t be at max.

Consolidation is the name of the game with Performance Max. Performance will take off if you lean in on its machine learning and smart algorithms. But carry forward your habits from the more granular campaign types, and Performance Max’s algorithmic nature will punish you.

Here’s everything you need to know about Google’s Performance Max campaign so that you can keep those needles moving in the right direction.

What is Performance Max?

Performance Max in Google Ads is the culmination of everything that makes the world’s largest search engine special. Years of collecting data on people’s browsing and purchasing behavior has allowed Google to create a campaign that’s tailored to individual searches.

Rather than placing ads in specific inventory types – like search results or product listings – Performance Max allows advertisers to upload all types of assets and access all of Google’s ad placements from one campaign. That includes:

After being released to limited accounts during its alpha (2020) and beta (2021) stages, Performance Max rolled out to the wider Google Ads community in 2022 ahead of the peak shopping season.

Since then, Google has continued to support Performance Max by releasing new features, including brand exclusions and asset group-level reporting.

What makes Performance Max powerful?

Google intended Performance Max to be an all-in-one campaign type capable of serving the needs of most advertisers. Here are some of the defining features that make that possible.

Targeting capabilities

Keywords, audiences, and product feeds remain the backbone of campaign targeting. This is no different when it comes to Performance Max, but it’s how those three elements behave and work together that sets this campaign apart.

While it will quickly bypass any initial settings you give it in pursuit of the best conversions, Performance Max starts on better footing when you apply these from day one.

Audience signals

Use these to tell Performance Max what kind of users you want to show your ads to – but remember, it won’t be those exact people. 

For example, uploading your customer list as an audience signal doesn’t mean your ad will show to them (or even to others like them) but as a jumping-off point for its own targeting.


Performance Max will quickly begin targeting broad queries not directly related to your initial targeting intent (based on custom intent audiences, product data feed, and website URL). 

While the absence of negative keywords can be frustrating, it’s likely you’ll still capture opportunities you didn’t consider. Performance Max can also analyze custom intent audiences you build from keywords.

Product feed

As always, a strong data feed is critical to success with Shopping campaigns. 

Without an optimized product feed, Google won’t know which queries to show your products for. 

Throw in a robust feed, and you will capture opportunities you didn’t even consider because of how Performance Max branches off from your initial path.

Bid management

Performance Max uses Smart Bidding to set cost-per-click (CPC) bids, which effectively means that advertisers have two options when it comes to bid strategies:

For this to work optimally, your account needs a sizable amount of historical data that Google can use to determine what’s worked best in the past.

I typically recommend that newer accounts begin with Search or Standard Shopping to gather data, only switching over to Performance Max after maxing out impression share and building a steady stream of conversions.

Complex auctions and intent matching

Google has a massive store of data on how people behave online.

Smart Bidding analyzes over 70 million signals in near real-time (actually a tenth of a second), but we never get to see what those data points are. A certain amount of trust in the system is required for this to work, but do that, and you’ll get the results you want.

Consider 100 people searching for the same exact query. Not only will each person be in a different part of the buying journey, but their unique histories will influence factors like how quickly they might convert. The system will try to find those people most likely to convert during that search.

For ecommerce, fill those data feeds out with the right information – keywords in titles and descriptions, product categorization, and so on. This will allow you to appear in as many searches as possible, irrespective of whether somebody is “window shopping” or ready to buy.

New customer acquisition and brand exclusions

Performance Max has long since allowed advertisers to target net new revenue by bidding higher for new acquisitions, and it recently began rolling out brand exclusions to better control when your ads show for branded queries.

These features may not be as important for smaller advertisers, but larger brands looking to scale can now tell the system to focus on more valuable opportunities. When used together, these features can significantly alter the speed and profitability of a scaling process.

Thanks to asset group-level reporting rolling out to many accounts, we can use these for segmentation more effectively. When we see that certain product segments – brand, category, individual products – are not getting traction or not performing as well, we exclude them and:

Think of it as pruning your campaigns for what’s not getting traffic or converting well.

Dig deeper: How to think about brand exclusions for Performance Max

Dynamic Search

Google recently announced the ability to upgrade Dynamic Search campaigns into Performance Max. Remember, the capability has always existed, but you now have a one-click option.

But with Dynamic Search likely to be next on the chopping block and deprecated in the near future – remember, Local and Smart Shopping campaigns already rolled into Performance Max – now is the right time to start testing it through Performance Max.

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What sets Performance Max apart from other Google Ads campaigns?

Let’s look at a few characteristics that set Performance Max apart from its more placement-specific counterparts.

Inventory and ad spend

Bidding and budgeting can only be done at a campaign level, which is familiar enough.

Where it gets tricky is that Performance Max doesn’t show you exactly where it spent your money and this ties in closely with reporting capabilities.

But while you’re buying traffic on inventories that may not typically have the quality of Search and Shopping, Performance Max is still only targeting people likely to convert. Additionally, some industries have a very high cost per click, and Performance Max can really decrease overall costs by looking outside that bubble.

Another thing to remember is that Performance Max is front-loaded in terms of expenses. Be sure to factor in the cost of data gathering during the learning period of a new campaign.

If you have a new account, this will take longer than the usual three to six weeks. 

But as you build historical data and get better results, subsequent campaigns should exit the learning period faster and bring costs down, allowing you to free up your budget to bid more aggressively or capture more conversions.


Reports in Performance Max can be seen at the campaign and asset group levels, and you can find those right in the Reporting tab inside Google Ads.

But I’ve spoken to several people who don’t ever navigate to where you can build custom reports based on landing page, placements, location, time of day, or products in your data feed. You can also analyze what proportion of your ad spend is data-feed-driven and what is creative-driven.

We’re also big fans of the Insights tab, which Google has revamped (update still rolling out). You used to only be able to look back to 7 and 28 days, but now you can choose any time frame – and download keywords. There’s a lot of good data in there, so don’t neglect it!


You can use third-party scripts to determine where your ads are going. Personally, I tend to shy away from that.

The way I see it, either the campaign is performing or not. When it isn’t, there are levers you can pull to try something different.

With Performance Max, you can’t decide when or where your ad shows up – only nudge and guide the algorithm. You also lose the ability to see more granular keywords, instead getting access to keyword themes.

I think accepting this is fundamental to success with Performance Max.

But while you can’t see your ad placements, there is an account-level placement report with impression data. Unfortunately, this doesn’t give you a breakdown of cost and revenue.

Keep in mind that the goal of all of this is to move to a format similar to Advantage Plus in Facebook, which only surfaces data that you can act on.


Many people think Performance Max is a “set it and forget it” campaign. Not really.

You have control, but it’s very different from what we’ve become accustomed to with other campaigns.

You program the system to do what you used to do yourself so you can focus on the decisions machines can’t make. What that comes down to in Performance Max is:

Don’t think of it as taking one step back, but stepping back to see the big picture.


How active do you need to be with Performance Max? Remember: Your goal is to guide the machine, nudge it in the right direction, and ensure it doesn’t veer off course.

Part of that is learning how to tame those compulsive feelings that making changes is the only way to feel involved. Maybe it’s because your clients keep asking why you only made two changes last month.

But with Performance Max, sometimes that’s all you have to do.

Instead, your involvement skews in favor of monitoring and big-picture changes. You set things up, step back and allow the campaign to run. Keep an eye on things while working behind the scenes.

Focus on making sure any first-party data is clean and accurate, that you’re integrated with a CRM (for lead generation), and improving landing page content – things that impact profitability and efficiency.

Performance Max in action: Sample campaign structures

Setting up a Performance Max campaign can be tricky if you don’t know what you’re doing. Here are some examples of how I’ve built campaigns for different types of accounts.


In ecommerce, there are generally two types of advertisers:

Sells own brand

These accounts typically lead with paid social, spending as much as 70-80% of their total advertising budget on platforms like Facebook and TikTok. Google might even be an afterthought. 

These are the brands where Performance Max with creative assets tends to work particularly well for the same reasons the brand works on paid social.

Sells multiple brands

For retailers selling hundreds of different brands or thousands of products – we have clients whose catalogs have hundreds of thousands of SKUs – it’s really about showing up at the very bottom of the funnel, so these accounts lead with Google Ads.

We typically shy away from creative assets and focus more on the “Smart Shopping” approach, which makes audience signals and ad copy less significant. Instead, we focus almost entirely on getting the data feed in near-perfect shape.

Performance Max for ecommerce

Lead generation

For lead generation accounts, we typically begin with Search to build up conversion data and volume – two critical components of making Performance Max work.

Once that’s achieved, we move to Performance Max, splitting asset groups by offering and location. This allows the system to target the right people in the right places so that a New Jersey plumber doesn’t get leads from Glasgow.

If your service is offered virtually or globally, you could omit the location split and just go by offering alone.

What’s absolutely vital is that you include some type of spam filter (like a reCAPTCHA) or low-quality leads will plague you. 

Ideally, you should also be feeding offline conversions and conversion values back into Google so that it can identify future leads based on data from your complete sales cycle.

Performance Max for lead gen

Verdict: The pros and cons of Performance Max

I’m bullish on Performance Max, but it’s not a perfect campaign.

Here’s what I admire about it and a few things I wish Google would improve.

Pro: It lets you scale beyond intent

Let’s say you’re targeting a market with limited search volume, but you really want to test opportunities beyond that limit. 

Performance Max can use its data signals to find people who might not be searching for your bottom-funnel keywords but will become a potential customer based on interest.

Performance Max is a full-funnel campaign, so it will find people it thinks are likely to convert based on all those millions of data signals – and it will then pull them down the customer journey.

This is probably Performance Max’s biggest advantage.

Not having the ability to set bids at the asset group level is a major drawback, and I understand why many PPC folks are frustrated with the obfuscation of search term data.

That said – and this could be a mentality issue – does all the other stuff matter? Shouldn’t we be figuring out how to get the most out of this toolbox instead of how to hack it? 

The whole idea of bidding with a ROAS target is that you don’t need to look at negative keywords. If it’s not hitting your target, it shouldn’t get that traffic.

I get that people want to be able to check the system quickly, especially when smaller budgets are at play, but patience goes a long way in seeing Performance Max’s true capabilities.

Con: It can be expensive at the start

Like a rocket ship, Performance Max can take you to places you never imagined – at the cost of a slow and expensive takeoff.

Getting somewhere meaningful can take three to six weeks, and that period can be pricey on the front end. 

Google monitors behavior rather than optimizing for conversions, so you’re spending considerably more for far fewer conversions than usual.

It takes clear communication and honest expectation-setting to convince clients and bosses that this is necessary to adapt to the modern avatar of Google Ads.

Pro: It’s a great way to try new campaign types.

For brands that are not ready to go all in on something untested like YouTube, Performance Max is a good way to test how that new media works.

Google claims that performance is better when routed through Performance Max, which it typically is. Their official figure is an average gain of 18%, but your mileage may vary.

Con: It’s not as easy as Google says it is

Performance Max is really not as simple as it seems. And while there will always be a place for PPC managers, it also means that we have to put in the effort to stay on top of things.

To get Performance Max right requires nuance, patience, and persistence. Many marketers will test it and give up after a few weeks because it’s not moving in the right direction.

This is shortsighted but understandable.

????: How do you make peace with PPC automation?

????: When I focus on my clients, I get results.

I've put a lot of time and energy into making PMax work. Same is true for Dynamic Search, RSAs, broad match, and Smart Bidding.

I like sharing what we learn because I feel helpful.

— Menachem Ani (@MenachemAni) June 7, 2023

Pro: It refreshes your marketing priorities

Performance Max forces PPC managers to think more like marketers than strictly media buyers.

I love the ability to go beyond Search for people who are not equipped to manage Discovery, YouTube, Display, and those more niche networks. 

This makes it a great way to scale beyond your capabilities without needing a high level of expertise.

What happens is you’ll reach the audience that you have but who might not necessarily be on the network you’ve been advertising on. Google has made this process uncomplicated.

Con: Its recommendations are far from ideal

I’m always cautious of Google’s recommendations.

Too many people don’t realize what they’re signing up for. On the surface, they appear to be things that you wouldn’t think of. But they can have deeper effects, so use them with caution.

Insights is a good place to get ideas, especially as you don’t have to act on them right away and can instead weigh up the risk-to-reward ratio.

Like everything else in Performance Max, it is very much “eyes on, hands off”:

Pro: It’s a reminder that we’re still needed

People are worried that Google wants to cut out agencies and experts, but Performance Max only reinforces the fact that PPC managers aren’t going anywhere.

Our role has changed, and it will change further, but the average business owner cannot optimally run Performance Max from day one. And if there’s anything more difficult than running a Performance Max campaign, it’s fixing one riddled with mistakes.

So whether you’re building from the ground up or fixing what’s broken, you’ll always be around and needed.

Should you run a Performance Max campaign?

Performance Max is a great option to have. But it’s just that: an option. 

You don’t have to use it. In some cases, you probably shouldn’t.

Which accounts benefit from Performance Max

Which accounts are better off with other campaign types

Special case: Regulated industries

Disclaimer: This is informed speculation. 

Accounts advertising things like pharmaceuticals and medical services (think detoxification and rehabilitation) aren’t allowed to retarget users. Performance Max offers a way around that because you aren’t targeting specific people, but the system probably will anyway.

As long as the proper teams can approve your ad copy and creatives, it really shouldn’t pose any problems.

Best practices: How to set up, optimize, monitor, and report on Performance Max

Ready to create and run your first Performance Max campaign? Have an active one, but not sure how to study or optimize performance? These resources might help.

Pre-launch checklist

My team has had access to Performance Max campaigns since Google Ads released it in beta, so we’ve had years to refine our go-live process.

Follow along with this detailed walkthrough to maximize your performance with Performance Max with everything you need to know to set up for success.

Read more: How to set up Performance Max campaigns the right way

Optimization stage

While there aren’t many levers to directly optimize Performance Max campaigns, that doesn’t mean you can’t shape them. 

Instead, your job is to guide the system governing your campaigns. Here’s a detailed walkthrough of what you can (and should) do to drive better performance.

Read more: How to improve your performance in Performance Max

Monitoring stage

Extracting data and insights from Performance Max can be frustrating, but it’s getting better thanks to features like asset group reporting. Use these tips and tricks to guide your reporting and monitoring process.

Read more: How to maximize insights from Performance Max

Underrated tips and tricks

Ecommerce and lead-generation accounts must approach Performance Max very differently – but what does that mean exactly? 

These guides will show you how to avoid repeating some serious mistakes that advertisers have made with their Performance Max campaigns.

Read more: 

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