But here’s what I’ve learned after years of evaluating these announcements—not every Google update deserves equal attention. Some are genuine game-changers, others are incremental improvements, and a few are just repackaged existing features with shinier interfaces.

Let me break down what’s actually worth your time and budget this holiday season.

The Lead Gen Updates That Could Actually Move the Needle

Enhanced Lead Form Ads

Lead Form ads have always felt like missed opportunities. You could collect information, sure, but the forms were static and treated every lead the same way. That’s changing.

The new qualifying questions and conditional responses mean you can now:

Pre-qualify leads in real-time instead of sorting through unqualified submissions later
Adapt the form experience based on how people answer your questions
Identify high-value prospects before they even hit your CRM

If you’re not already testing Lead Form ads, this is your reason to start. If you are using them, these features should be live-tested immediately. The potential impact on lead quality—not just quantity—could be significant.

Google Analytics Gets Serious About Lead Intelligence

The three new Analytics features address real problems most lead-gen marketers face:

Lead Acquisition Reports let you trace back to a lead’s first touchpoint with your brand. This isn’t just attribution theater—it’s actionable intel about which early-stage content and channels actually influence your best leads.

Lead Disqualification Reports surface why prospects didn’t convert. Most advertisers obsess over what works but ignore what doesn’t. Understanding drop-off patterns can be more valuable than celebrating wins.

Eight new audience templates for lead nurturing. Here’s the reality: most businesses are terrible at nurturing leads through the middle of the funnel. These templates give you segmentation starting points based on where leads are in their journey.

The combination of these three features creates a complete lead intelligence system. That’s rare from Google.

The Retail Updates: Practical vs. Promotional

Campaign Total Budgets

Managing budgets during promotional periods has always been painful. You want to maximize opportunity during peak times, but you also don’t want to blow your monthly budget in the first week of Black Friday.

Campaign Total Budgets solves this by letting you set spending limits across defined timeframes (3-90 days) while still allowing Google’s AI to optimize day-by-day within those constraints.

This is immediately actionable for any retailer planning holiday campaigns. Set your promotional period budgets now and let the system balance spending while maintaining optimization.

Demand Gen Gets Local: The Mid-Funnel Meets In-Store

If you’re not running Demand Gen campaigns, you should be. They’re exceptionally effective at reaching users in the consideration phase—that crucial middle-funnel space between awareness and purchase intent.

The local offers integration means these campaigns can now surface nearby store inventory and drive in-store visits alongside online conversions. For omnichannel retailers, this bridges a gap that’s existed for years.

The key requirement: your product feeds and location data need to be current and comprehensive. If they’re not, fix that before you try to leverage these features.

Merchant Center Insights: The Update That Deserves Immediate Attention

This is the most immediately valuable update for retailers. Google is using AI to surface actionable insights about your product catalog, including:

Popular product identification based on search and shopping trends
Competitive pricing analysis against similar products
Audience trend data showing who’s engaging with your products

The difference between data and insights is analysis. Google is finally providing the analysis layer that most retailers lack the resources to build themselves.

Every retailer should be reviewing these insights weekly as we move into holiday season. This isn’t just reporting—it’s competitive intelligence delivered automatically.

The GenAI Tools: Useful, But Don’t Lead With Them

Product Studio and Asset Studio represent Google’s commitment to generative AI for advertisers. You can now generate product backgrounds, create video content, and enhance imagery directly within Google’s ecosystem.

These tools are legitimately useful, but they’re creative enablers, not performance drivers. Use them to scale content creation and test creative variations, but don’t expect them to fundamentally change your results.

The real value comes from testing multiple creative approaches quickly and affordably, not from the AI generation itself.

What This Really Means for Your Holiday Strategy

Google’s pattern is consistent: they announce features that sound transformative but require strategic implementation to deliver actual value. Here’s how to approach these updates:

Lead Gen Advertisers: Prioritize the Lead Form enhancements and Analytics features. These address real conversion quality issues that impact revenue, not just volume.

Retail Advertisers: Focus on Merchant Center insights and Campaign Total Budgets first. Both solve immediate operational challenges during peak selling periods.

Everyone: The GenAI tools are nice-to-have, not must-have. Implement them after you’ve optimized the fundamentals.

The Real Intelligence Approach: Prove Before You Scale

At Brainlabs, we don’t chase every new feature Google releases. Instead, we test systematically and scale what actually moves business metrics.

That means treating these updates like any other optimization opportunity: hypothesis, test, measure, scale. The features that genuinely improve performance will prove themselves through real results, not just Google’s marketing materials.

The holiday season isn’t the time for experimental tactics—it’s when proven strategies need to perform flawlessly. Use these updates to enhance your existing approach, not rebuild it from scratch.

Your budget and timeline are limited. Choose the features that address your biggest current challenges, test them properly, and scale what works. Everything else can wait until January.

The post Google Just Dropped Ad Updates During Think Week—Here’s What Actually Matters for Your Performance appeared first on Brainlabs.

The way that people find information online is changing.

Strides forward in LLM capabilities over the last few years have transformed the types of questions that people can ask online. Rather than having to learn to “speak search engine” and enter truncated queries into a search bar, AI can provide effective responses to far more multi-faceted queries – whether those queries are grounded in natural language, or visual & multi-modal search.

This shows up in a variety of data points. Firstly, on Google search, we’re seeing consistent growth in more open-ended queries – for instance, queries containing “what”, “how” & “best”. These are subjective questions that require complex comparison skills, which search engines of old would have struggled to address. Compare this to the more closed, “command”-style queries, such as “buy” or “cheap”, which are trending either flat or in marginal decline.

We also know that the queries people are asking are growing in length. Whilst Google are seeing growth across query strings across all lengths, nowhere is that growth greater than in the longer-tail. This is happening even more in AI environments, with users of Google’s AI Mode asking queries that are on average 2-3x longer than those on regular Google search.

All of this change has drummed up a lot of interest in the search industry, and is leading clients to ask one question time and time again: How can we ensure our brand is present within AI responses to queries that are relevant to our brand?

Until now, the answer has mainly been confined to the realm of SEO practitioners, because paid advertising opportunities have been incredibly limited. When we look across the AI answer engines from a paid advertising perspective, it’s only Microsoft’s Copilot that today has an operational advertising unit. 

Perplexity has launched its “Follow Up Questions” format, but so far only in a very limited testing phase to some US brands.

Sam Altman, CEO of OpenAI, has historically taken a very anti-advertising stance to ChatGPT. Whilst his view may be softening, ads in ChatGPT are certainly still not on the immediate horizon.

And finally, in Google’s sphere, whilst we’ve known for some time now that Ads in AI Overviews have been in testing, the launch had always looked like being a fair way away. Google had been very tight-lipped around any potential timelines.
All that changed last week. At the beginning of August, Google revealed that Ads in AI Overviews could be landing in English-speaking markets in as soon as the next 5 months – ie, before the end of 2025.

It’s hard to overstate just how big a change this will represent for Google and for clients.

Why is this such a big deal?

The short answer is that this will open up the floodgates on a huge amount of previously un-monetised Google search inventory.

To understand why this is the case, and why this won’t just cannibalise existing advertising opportunities on Google, it’s helpful to build a segmentation of all of the different types of text-based queries that Google receives today.

A 2024 report by SparkToro revealed that only 15% of such queries demonstrate a clear commercial intent. A further 32% of queries are “navigational”; this encompasses brand searches, as well as more generally any queries where the user has a known destination in mind that they are looking to reach.

And then, finally, making up over half of all traffic on Google, are the “informational” queries. In these queries, users are asking a question that doesn’t – at least, on the face of it – demonstrate an obvious intent to purchase a product or service. Questions like the ones users are asking even more often within AI experiences, as discussed above.

With our segmentation in place, it’s then helpful to think about what the SERP looks like for each of the three query types. Whilst there are some exceptions, by and large it is the case that ads are bought against commercial & navigational queries, whereas AI Overviews are the most suitable response for Informational queries.

The crucial callout here is that there is very little overlap between these two result formats. When ads do arrive within AI Overviews, they will appear on queries which have largely been un-monetised – and so will genuinely present a net new, incremental opportunity for marketers to access their customers.

Of course, it would be a mistake & an exaggeration to propose that every single one of those informational queries is going to be monetised. However, in even our most conservative scenarios, we’d expect this to unlock a 20% expansion in ad inventory on Google search.

Why can Google put ads on these queries all of a sudden?

There is a crucial difference in how ads will work within AI Overviews compared to how they work today within “regular” search.

In a regular search context, by far and away the most important signal to determine whether an auction will be initiated is the search query itself. If one or more advertisers are deemed to have an ad that could be relevant for the query, then an auction will be triggered.

However, Ads in AIOs can also be triggered based on the content that is included within the gen AI response itself. Think of the AI Overview as a bridge: first of all, it will answer the query that the user asked of it, and then it will suggest “oh and by the way, if you did happen to be thinking of buying a product or service to help you out with your question, then here are some suppliers you could consider.”

It’s a simple enough idea, but it’s hard to overstate just how significant a conceptual leap this is.

What do marketers need to do about it?

Firstly, it’s worth being clear that there will be no “AI Overviews” campaign type appearing in your ad account any time soon. In keeping with their general direction of travel over the past few years, Google will be consolidating all advertising inventory in AIOs into existing campaign types.

However, that’s not to say that we can afford to stand still and have the +20% uplift land in our laps. These auctions are materially different from the ones we’ve played in before, and trying to access this new inventory with your existing search tactics will see you quickly run into some hurdles:

The good news though, is that everyone else is in the same boat. This opens up the potential for a huge first-mover advantage – but what do we need to do to capture it?

From the three challenges above, it’s not difficult to see the direction we need to move in for our Google Ads campaigns:

Targeting: Adopt intent-based targeting solutions that assess ad relevance based not just on the query, but on Google’s understanding of your business

Messaging: Lean into creative assets generated in real-time that allow you to show up in the most relevant possible way

Bidding: Provide bidding strategies with more flexibility to target never-before-seen queries

Specifically, the tactics that Brainlabs is recommending its clients to test & implement between now and the end of the year are:

Somewhat understandably, many advertisers have historically been wary about some of these features: in particular, when it comes to sharing control over assets & messaging with Google. And up until now, there hasn’t been a pressing performance need to overcome this reticence. But with Ads in AIOs just down the line, we’ll very soon reach a point where this hesitance will put the brakes on advertisers achieving the visibility and performance that they desire from AI environments.

As a practitioner, what’s most exciting about these tactics is that, with AI Max in particular, Google have learned from the feedback they received throughout the launch of PMax a few years prior. Almost right out of the gate, Google launched AI Max with an array of reporting and experimentation features that will provide clients with greater levels of transparency & influence over how the campaign is behaving and performing. A full breakdown of these features is for another post – but four particularly notable callouts would be:

1. Cookie-based A/B testing functionality for AI Max campaigns vs. regular Search campaigns;

2. An “AI Max expanded searches” row within Search Term Reports, to indicate what performance has been driven through AI Max’s targeting capabilities in addition to your existing keyword targeting;

3. Asset reports that allow for a comparison of performance between advertiser-uploaded and automatically-created assets;

4. Asset control functionalities, such as Asset Exclusions & Asset Removals. You can mentally liken these to negative keywords, but for assets rather than search terms.

Call to arms

Ads in AI Overviews will almost certainly represent the largest overnight expansion of search inventory that we have seen within the last decade.

The growth of mobile devices & Broad Match keywords are the two other events that had a comparable impact – but both instances required gradual adoption from users and advertisers, respectively. Contrast that to AI Overviews, which already reach 1.5 billion people globally. When Ads in AIOs & AI Mode do arrive, it’s hard to see Google opting for anything other than a wide-scale “turn on the tap” approach. The whitespace ahead for brands will be huge.

However, by committing to a sprint test & learn roadmap between now and the end of the year, marketers have a chance to tip the scales even further in their favour and to build distance between themselves and their competitors. The five-month countdown has begun.

The post Winning the New AI Paid Search Game: How to Capture 20% More Ad Inventory Before Your Competitors Do appeared first on Brainlabs.

Imagine you have set up a brand new restaurant ( congratulations! ) for which you have big ambitions. You’ve hired an amazing chef. You lead the chef into the kitchen on her first day. You’ve laid out all the ingredients for her, but you’ve separated them into three boxes. You tell her that you’d like her to design her dream menu, but with a catch: each item on the menu can only make use of the ingredients within one of the boxes – there can be no overlap between the boxes.

Clearly, these constraints are not a recipe for success. They’re going to leave your chef with one hand tied behind her back, and will prevent her from conjuring up the very best recipes.

Welcome to the world of optimisation problems

In setting up your new restaurant, you’ve unknowingly stepped into the world of optimisation problems.

An optimisation problem requires that we find an optimal solution, subject to a set of constraints. A constraint is a limitation on the solution of the problem, which can introduce with our next example. We also have what is called an objective function, which is the thing we want to achieve.

Imagine now that you have a factory that can make chairs or tables, and you are constrained by labour and machine time. You make $40 per chair, and $30 per table. A chair requires 2 hours of labour and 1 hour of machine time. A table requires 1 hour of labour and 3 hours of machine time. How do you maximise profit?

This is an optimisation problem – the objective function is maximising profit, and the constraints are the labour and machine time.

And as it turns out, in this case there is an optimal solution, which is 42 chairs and 16 tables, or $2,160 of profit per day. While this is a very simple example, for most real-world optimisation problems we rely on AI to find optimal solutions, as we can very quickly get into a place where we have hundreds of dimensions to consider.

An artificially segmented solution space will have lots of locally optimised solutions, but they won’t be able to get to the true globally optimal solution. This is what our hypothetical chef is dealing with.

You can see from this example that constraints are important. They allow us to find the optimal solution within the real world constraints. However, constraints that don’t match up with the real world will limit our ability to get to the true optimal solution. A solution within a constrained space may be called a ‘locally optimal solution’, as opposed to the true ‘globally optimal solution’. Where the constraints have been added artificially, we’ve limited our efficiency in solving the problem for no good reason.

Paid Search is a lesson in communication

Understanding optimisation problems, especially optimisation problems that are solved by AI, is critical for us as PPC practitioners. For instance, most have now accepted that smart bidding solutions achieve better results than manual bidding… but what techniques can we use to make smart bidding work even better for us?

In any paid search account, our objective function is to maximise the number of fires that take place of a particular conversion goal. There will also be one necessary constraint – either the budget we are willing to spend, or the efficiency target we are required to hit.

However, in many paid search accounts, practitioners end up introducing additional constraints that the bid strategies believe they have to work within. These constraints are often communicated by the way we structure our accounts. Sometimes, these constraints are genuinely important for the business; in other cases, they are artificial.

What is our job then, as PPC practitioners? We are communicators. The structures and goals we choose communicate to Google what optimisation problem we want them to solve. AI algorithms are very good at solving optimisation problems; but solving an optimisation problem is no good to you if the solution isn’t ultimately aligned to benefitting your business.

“ In the age of AI, our job as Paid Search practitioners is to communicate our clients’ business goals to algorithms via the structure, goals and budgets we choose .”

Staying in control?

This is all very well, you might say, but we are Paid Search practitioners, and we like to be in control of the activity we are running because we know our business best. We like segmented structures that allow us to have varied budgets, bid strategies and see segmented data across different parts of our business. We want to decide what ads we show when and monitor all of our keywords separately.

We get it.

There was a time a few years ago when Brainlabs shouted about the fact that a Single Keyword Ad Group structure was the best way to run Paid Search, because of the control it offered. And many clients and advertisers feel that giving up that granular structure for a consolidated structure also means giving up control.

But we would argue that we don’t actually have to give up control. In fact, by learning the language that Paid Search systems speak, we actually gain more influence over the auction than our competitors have.

A granular structure might make you feel like you are in control, but you are actually communicating to the algorithm that you have a constrained system, and stopping it from maximising your potential performance.

Brainlabs’ approach to search structures

So, how do we keep the right level of control over our activity, while giving our AI chef access to a fully stocked kitchen to get us the best possible results?

We need to communicate to bid strategies in ways they understand. Now that we know a little bit about optimisation problems, we know that there can only be two ways we can possibly influence the situation:

1. Setting good objective functions.
2. Setting constraints that actually matter – now you have consciously ditched the ones that don’t.
3. Directing investment via bid strategy targets, rather than campaign budgets

An example of this is altering your conversion goal to indicate differing value between products, rather than putting some products into their own campaign with their own budget.

You do make more money on boots vs sandals ( a real objective function communicated to the algorithm via your conversion goal ) but you do not need to only spend 20% of your budget on sandals ( an artificial non-real-world constraint that is limiting your optimisation problem ).

While we always tailor structures to our clients’ businesses, there are three fundamental principles that sit behind the structure methodology we choose, that we’ve seen work well time and time again:

Show me the data

Whilst these results give us a high degree of confidence, it is worth openly acknowledging that, within the topic of account structures, it’s difficult to find truly like-for-like data points; when launching a new campaign you tend not to be editing the campaign & ad group structure is isolation, but rather you’re likely to combine this with a broader spring clean of the campaign; potentially introducing new match types, new keywords, and refreshed ad copy.

So what underlying factors were driving these results? We’ve identified two specific ways in which our consolidated structural approach actively improved the optimisation decisions being made by Google’s AI.

Firstly, Google’s keyword-to-query matching algorithms can learn more efficiently when they have access to the whole solution landscape. This is evidenced by data we found from our own client base, which showed that advertisers using a more consolidated structure saw the number of search terms matching to broad match keywords increase at a faster rate from the day they were launched.

We have a proprietary structure that abides by these three rules we’ve set out, whilst still allowing us to be cognizant of clients’ business goals. We have tested this widely, and it’s led to an average efficiency improvement of 22%, when tested against more granular alternatives.

Not only that, but Google’s bidding algorithms make more accurate decisions when they are provided with greater volumes of data. This is illustrated by these anonymous charts from some of our biggest advertisers which show that bid strategies with more data going through them often have lower CPAs than bid strategies belonging to the same advertiser but with less data.

In conclusion

Campaign structures are a fundamental part of any Paid Search set up, but they can be elusive to test and understand. It’s expected that you will be skeptical of any change where it feels there is less freedom to pull levers.

However, as Brainlabs’ CEO Daniel Gilbert once said in 2019:

“The rise of automation doesn’t steal jobs, it just changes the game.”

While algorithms are doing the job of solving optimisation problems, your job has changed to communicating with them effectively. Our hope is that you understand a little bit more about how algorithms understand structures, and feel empowered to take on your role as an effective communicator of your business.

Lead author

Holly Chetwood

Senior Director, Paid Search

Contributors

James Freeman

Engineering Manager

Andy Goodwin

Head of Paid Search

Preview Not Working? Open PDF

The post Unlocking Smarter Paid Search: Why Structure Is Your Secret Weapon appeared first on Brainlabs.

With the introduction of OpenAI’s ChatGPT technology on Bing and Google’s AI chatbot, Bard, powered by their own LaMDA language model, there are many discussions surrounding the accuracy, reliability, and ethical implications of these AI experiences.

From a search advertising perspective, our report examines the possible implications of these developments and the potential opportunities they present for advertisers.

The Impact of Generative AI on Search Advertising
what you need to know

A new world of conversational search

Last week witnessed the biggest announcements in the world of search in the last decade. Dubbed the “Search Wars”, both Microsoft and Google announced new Generative AI experiences that they will soon be integrating into their search engines. The “new Bing experience” will see an iteration of OpenAI’s ChatGPT technology integrated alongside Bing’s web-crawling capabilities to offer a new chat functionality. On Google, search users will soon be able to interact with Bard, an AI chatbot powered by Google’s own conversational neural language model, LaMDA, which was created nearly three years ago.

These announcements have sparked huge amounts of debate, with discussions spanning the accuracy & reliability of the models, the ethical & environmental impact of Generative AI, and how these new tools could impact the entire monetization model of the web. For this article, we’re going to speculate primarily around what this could mean for search advertisers.

What are these releases designed for?

First of all, we need to ask how these product launches are intended to serve users on a day-to-day basis. AI promises to open up a whole new way of interacting with search engines that previously wouldn’t have been possible. In particular, Generative AI can offer specific responses to far more complex, multi-faceted queries than before. Users will no longer be required to “speak search engine” through short-tail, truncated queries and tricks like minus signs, quotes, and boolean operators.

Many have – very rightly – drawn comparisons to say that voice search offered a very similar opportunity, but never materialized as a change in user behaviour. However, what’s different this time is the underlying Generative AI technology is better suited to address a wide range of nuanced long-tail queries – even if there are undoubtedly issues with accuracy & reliability that need to be ironed out. In the short – and mid-term we expect Generative AI will be additive to the existing search experience, rather than a replacement for it.

As an aside, it’s worth bearing in mind the often-quoted stat that every day, 15% of Google queries have never been seen before. It’s plausible that this figure will rise as users become more familiar with both search engines’ new capabilities, and so there’s a genuine argument to be made that tools such as broad match will become even more crucial for paid search advertisers to continue to reach searchers as they explore these new types of interactions.

What can Bing help you search for today? What can Google help you search for today?

Will Microsoft steal share from Google?

The biggest question on a lot of people’s minds is whether AI will enable Bing to disrupt Google’s share of the search engine market. The coming months will show whether users make the switch, but it’s also interesting to examine this tug-of-war from the perspective of an advertiser trying to determine the value of investing more in placing ads on Bing. For any auction-bought media, there are 4 fundamental levers the media owner can pull to impact their revenues:

• Increase the number of users on the platform
• Increase the number of advertisers in the auction
• Increase the base cost of buying an ad placement
• Increase the (real or perceived) value-per-dollar-spent that is generated for advertisers

For now, Microsoft’s AI play is centred almost entirely around lever #1 – Microsoft is trying to draw users across from Google’s ecosystem, and into their own. Whilst both players will surely have an eye towards building ad placements directly into their AI responses, for the time being, conversational AI will be monetized indirectly. For instance, the new Bing experience will position the AI unit on the right-hand-side of the SERP, meaning users will still receive exposure to ads for relevant queries.

Working in Google’s favour is their established market share, with them being the default search engine for so many users (and devices). Getting users to make a conscious decision to move away from their device defaults is always going to be an uphill battle for Microsoft, even if their ChatGPT-based solution does turn out to be a higher-performing AI assistant than Bard.

Microsoft may find that when it comes to marketing the new Bing experience, their biggest challenge lies not in getting users to attempt using the platform for the first time, but getting them to come back the next time they feel inspired to search.

On the other hand, any shifts in user behaviour should deliver a short-term payback for Microsoft. Due to the automated nature of search media buying, and it being an easier channel to measure than many others, we should see ad revenue quickly follow the user base.

What next?

The recent announcements are only the beginning of what promises to be a series of developments in this space. Both Microsoft & Google are working fast to try and overcome the deficiencies and inaccuracies that have been pointed out in both of their models so far before releasing their Generative AI solutions more widely in the coming weeks and months.

However these developments pan out, it’s certainly a very exciting time to be in the search industry. Whether or not this materializes in a re-balancing of the market-share scales, an increase in competition will certainly lead to an acceleration of innovation within the industry. As the situation develops, stay close to your agency partner to remain in the loop with the latest conversations.

Are you ready to rumble?

Brainlabs in the news

In the wake of the dualling announcements from Google and Microsoft camps last week, some of our Brainlabs experts have hit the headlines with their POV.

Chief Product Officer North America, Jeremy Hull, spoke with Patrick Kulp about how marketers can adapt and put their best foot forward in this exciting new world, and how crucial it is to lean on your agency partners.

This is going to move really fast. And it’s going to change really fast. If you are concerned about how this topic will impact your marketing, you’re going to have to proactively lean into the news and coverage, you can’t wait to get an end-of-month recap or quarterly look-back or something like that. Which means you and your team either have to be plugged in or lean on your agency partners who are having these conversations.

Jeremy Hull
Chief Product Officer, NAMER

Read the full article »

Head of Paid Search UK, Andy Goodwin caught up with Lara O’Reilly at Business Insider about the potential impact on search advertising.

The moneymaker for search advertisers is short-tail, transactional terms. New ad units aside, the hype around OpenAI’s ChatGPT — which reached 100 million users last month — and a new, refreshed Bing could drive more use of Microsoft’s search engine. Advertisers usually follow the eyeballs. That’s where the opportunity for share moving around is.

Andy Goodwin
Head of Paid Search, UK

Read the full article »

VP of Paid Search, NAMER Alessandro Creso spoke to Marty Swant at Digiday about what the future of advertising on Bing might look like, and how the upheaval in search could also benefit others besides Bing.

The opportunity is there. When there is so much of a shift in the industry we have to take into account everyone else…It does give other engines a chance to catch up rather than just being underdogs.

Alessandro Creso
VP of Paid Search, NAMER

Read the full article »

Thanks to our Brainlabs expert contributors from across the globe

• Jeremy Hull
  Chief Product Officer, NAMER
• Andy Goodwin
  Head of Paid Search, UK
• Alessandro Creso
  VP of Paid Search, NAMER

Get in touch

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  APAC SVP
  gyn.ang@brainlabsdigital.com
• Leo Jennings
  UK SVP, GROWTH
  leo@brainlabsdigital.com
• Rachelle Risner
  VP, NEW BUSINESS
  rachelle.risner@brainlabsdigital.com

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The post The Impact of Generative AI on Search Advertising appeared first on Brainlabs.

The results reveal the strengths of PMax, demonstrating its ability to achieve superior CPA and ROAS outcomes compared to similar Google Ads campaigns. We also delve into the crucial inputs that contribute to success within the PMax environment, namely data, creative assets, and feeds.

We also provide valuable insights and recommendations for effectively harnessing PMax’s potential and navigating the ever-evolving landscape it presents.

Google Search in 2023: Is Performance Max a must?

Jan 2023

Andy Goodwin,
Head of Paid Search UK
at Brainlabs

Index

• Changes to Google as we know it 3
• What do the changes to Google Search mean for advertisers? 5
• So, is Performance Max any good? 6
• How do brands win at Performance Max? 8
• Our wishlist for Performance Max 13
• Final takeaways 15

Changes to Google as we know it

We’re on the cusp of a very exciting time in the search landscape – and for once, we’re not referring to automation, privacy or first-party data – but rather to an overarching facelift to Google Search as we know it.

For decades now, Google Search has relied on its familiar model of “ads at the top, and ten blue links”. Whilst SERP features have evolved over time with additions such as creator video content & infinite scroll, the overall way we interact with search has remained largely unchanged.

One glance at the announcements coming out of Search On 2022 will tell you we’re not far away from Google heading in a very different direction with their user-facing products, with the aim of making search more natural and intuitive.

• Ads at the top
• Ten blue links

Visual experiences were the predominant theme of Search On, and there are plenty of plans to bring that to life in the outputs we see – whether it’s using Maps to reconstruct a 3D visualisation of an area, or creating 360° spins of product results.

But the outputs are only part of the picture, and arguably more interesting are the advances in Google’s ability to process visual inputs, particularly when it comes to Multisearch. Combining text, image & voice inputs will allow users to search more intuitively, as well as to process queries that would be difficult to distill into a standalone text string in the search bar.

Many use cases were presented, and some of our stand-out favourites were:

• Information overlays onto realtime camera images, via “Live View” in Maps
• More seamless translation of languages embedded within images
• Combining image & text inputs to find products more tailored to your needs

Images courtesy of Google

What does this mean for advertisers?

Whilst we’re yet to see exactly how these changes play out, it doesn’t feel too bold a prediction to claim that Performance Max will be absolutely central as the buying-engine for brands to tap into these new user experiences.

Performance Max – often referred to as PMax – came onto the scene as a beta product at the tail-end of 2020, and has been rapidly picking up momentum ever since. Both its benefits & its shortcomings have been hotly debated over the last 2 years.

At the heart of its proposition, PMax strives to single-mindedly hit an advertiser’s performance objective, without constraining itself to any one media placement in Google’s ecosystem. However, this media-agnostic approach, along with the associated lack of visibility into what is actually driving campaign performance, has been a major talking point for the industry as it gets used to this new ad product.

Image courtesy of Google

So, is Performance Max any good?

To weigh in on the debate, we tasked ourselves with assessing whether PMax was actually delivering on the performance it promised.

As we’re often prone to do, we turned to our proprietary testing database, Hippocampus. Named after the memory centre of the brain, we use Hippocampus to assess the macro impact witnessed by our clients across a wide range of digital media tactics.

We aggregated test results from 18 Brainlabs clients in a range of sectors, and identified two topline findings:

1. Most importantly, PMax drove stronger CPA & ROAS than similar Google Ads campaigns. This supports the proposition that, by having the freedom to optimise across multiple touchpoints, the algorithm is able to drive outcomes more efficiently for advertisers.
2. What’s more, PMax is already making healthy contributions to overall conversion & revenue volumes. On average, our clients who used PMax netted out at spending 17% of their Google Ads budget through this campaign type. Note that this figure does vary considerably – for instance, many retailers invested in excess of the 17% average.

Median uplift metrics:
18% Conv.
-12% CPA +16% ROAS
30% Rev.

Data relates to the % of convs/revenue achieved by PMax vs. similar campaigns in Google Ads, and the % difference in CPA/ROAS vs. similar campaigns. Revenue & ROAS metrics are measured across the subset of clients that tested PMax & who also record conversion value within Google Ads.

“Google’s PMax proposition is centred around delivering results… and it’s fair to say that PMax achieves this pretty comprehensively”

Andy Goodwin, UK Head of Paid Search

How do brands win at PMax?

As well as figuring out if it could do what it said on the tin, a secondary aim of our testing was to identify exactly how brands could differentiate themselves in a World of PMax. With the nuts and bolts of media optimisation accounted for, what can agencies & advertisers do to drive further success through PMax?

We identified three main inputs that represent a substantial amount of the value that marketers can add to PMax campaigns. They represent quite a shift away from the more familiar skill-sets of Google Ads practitioners, so it’s important to start thinking today about how you can bring this to life for your brand.

1 Data 2 Creative 3 Feeds

Data

In this context, we’re referring to the data that we feed into Google to direct its optimisations. PMax offers less control over other aspects of your campaign, so there’s now greater emphasis on defining your objectives.

In practice, this is achieved through first-party data integrations, paired with value-based bidding. It’s no coincidence that on average we saw PMax deliver +2% better efficiencies when paired with value-based bidding.

In our eyes, thinking more strategically about the challenges our media is solving can only be a good thing. It encourages us to get closer to customers, and to really contemplate what drives value for the business.

We’ve seen that PMax will achieve what you ask it to, but have you told it to do the right thing?

Margin
First-time buyer Returns
Account creation

Client Database Brainlabs Offline Upload Tool Brainlabs Audience Sync Tool

High value customers
Repeat purchasers
Margin based bidding
Segmented audience messaging

Creative

When it comes to creative, the number one rule is don’t use the auto-generated assets. Whilst anyone who’s played around in a PMax campaign for 5 minutes could probably tell you this already, it’s interesting to note that Google themselves make point of stressing this; they acknowledge that whilst auto-generated creative is getting better, it does not compete with advertiser assets. If you’re going to test PMax, make the effort of building all the assets.

More generally, learning to optimise image & video creative for performance purposes will be a new challenge for a lot of specialists who’re most familiar with the trusted text ad format. Whilst creative insights in PMax aren’t hugely forthcoming right now (more on that later), we’re keeping our fingers crossed for greater creative testing capabilities being introduced into the PMax roadmap.

A B

Feeds

For eCommerce brands, feeds represent the 3rd key pillar for success. Shopping placements are crucial for many retailers, and the pivotal role feeds play in those auctions mean they’re an essential lever to test & optimise.

For non-retailers, feeds aren’t to be ignored either – they may not play much of a role today, but indications from Google suggest that feeds will come into use more broadly to help connect PMax with the more visually rich SERP experiences that are being developed. This will touch much more than just the retail vertical, so it’s worth keeping an eye on any developments in this space.

Exactly how this will looks for each sector remains to be seen – but it doesn’t take too much imagination to envisage, for example, how feeds would be incorporated to help promote the inventory of travel brands.

Feeds Determine:

1. How much we need to pay to win the auction
2. How competitive we are in the ad auction
3. Whether our ads are eligible to show
4. The information a user sees

Agency model

Bonus insight

And finally, whilst it didn’t make it into our top 3, it’s worth also giving some thought to the structure of the agency doing the media buying. It doesn’t sound like the most exciting topic, but it is important: the objective-focussed approach of PMax is at odds with the more traditional, channel-siloed agency models. Internal challenges such as “which department should run this campaign” can throw up blockers to effective activation on PMax.

Agencies with a less siloed structure have greater freedom when it comes to budget allocation, and so don’t face these same difficulties. For a number of years now we’ve designed our biddable teams around Client Partners, who are tasked with taking a client brief and translating it into a multi-channel plan, by tapping into the various channel specialists within their immediate team.

Client Partner Client Brief

Our wishlist for PMax

No article on PMax would be complete without acknowledging its limitations, and this one is no different. There are elephants in the room, and they need to be addressed.

We know that Google themselves would want feedback to improve on what is already an incredibly valuable product in the industry. It’s our belief that the vast majority of industry concerns stem from one of two places – and so, to make PMax work even harder for our clients, we’d hope to see Google’s product roadmap focus on two key areas..

1. Incrementality

Firstly, we can all agree that any performance media product should be all about growing the business in the short-term. This necessitates a focus on incremental conversions & revenue.

Whilst PMax places more emphasis on defining objectives, it feels like a bit of a miss that you can’t actually set a PMax campaign to the “correct” objective – ie one of incremental outcomes. This isn’t such an issue when media channels are kept in silo, because we can isolate the incremental contribution of each channel through tests, and subsequently refine our spend allocation.

However, when you can’t optimise for incremental outcomes, and everything is housed together under one roof, this leads to some of the very valid concerns that have cropped up – for instance, around the identical treatment of branded & generic queries.

And whilst Google are correct in pointing out that the DDA model used in PMax is weighted towards incrementality, that can only ever mean incrementality within Google’s ecosystem – which doesn’t capture the whole picture.

2. Reporting

Google engineers look away now, you’ve heard this one before – but item #2 on our wishlist is to have greater access to raw data breakdowns within PMax.

When raised in Google forums previously, there’s been a tendency to deflect towards the Insights page. The conversation tends to go something like this:

• We want more data!
• What do you need it for?
• We don’t know… but we know we’ll need it for something!

On the face of it, we’re not putting forward a very compelling case. But the point that’s being missed is that, when it comes to answering marketers’ most pressing, strategic challenges, it isn’t possible to pre-empt the questions we’ll have. The process of building a marketing strategy throws up questions that are bespoke to each individual brand. Google Ads’ raw data has historically been a fantastic source to answer some of these questions – but we’re doubtful this can ever be done through a “generic” suite of insights.

On the other hand, it’s not hard to see why Google are going down this route. Quite frankly, many practitioners haven’t kept pace with the changes in machine learning over the last few years, leading them to misinterpret data and make suboptimal decisions in their campaigns – understandably something that Google want to avoid. Our view is that whilst these more directional insights might provide a helping hand for the less skilled practitioners, they actually curtail the potential of those who are most fluent in automation & machine learning.

Final takeaways

To wrap up

Just over 2 years on since its beta launch, and Performance Max is already driving undeniably impressive results. For performance marketers, it’s become a topic can’t be ignored; results have to be our number 1 criteria for success.

If anything, the evolution of Google’s user-facing products will only lead to PMax becoming a more integral part of their Ads offering. We believe there’s still huge headroom for PMax to get better – and we’ll continue to agitate for the changes that we want to see. Whilst we can’t disclose the specifics in this report, the good news is that we are now starting to see some more exciting, additive features materialise in the PMax product roadmap.

For now, start to think about the capabilities you can build into your team to make the most of this format, across data, creative, feeds – and potentially even your media agency. It’s never too early to start testing.

The post Google Search in 2023: Is Performance Max a must? appeared first on Brainlabs.

Google Marketing Live is an incredibly exciting event, especially as it heads into its ninth year and returns to an in-person format. It’s an opportunity to connect with fellow marketers, a chance to provide feedback directly to Google’s product teams, and a look at Google’s vision for the future of data, advertising, and privacy.

Today Google shared several announcements that will make their advertising ecosystem more powerful and simpler to use. During the opening keynote of GML a diverse group of Google leaders showcased new advertising solutions and enhancements for current products to a crowd of several hundred in-person attendees and even more online viewers. These announcements unsurprisingly featured a wealth of new enhancements to Performance Max, Google’s fully-automated solution for marketers looking to take a performance-based approach across Google’s entire ecosystem of ad inventory. Google also debuted new measurement and testing features and highlighted their commitment to privacy-first solutions for advertisers.

Performance Max gets more conversion sources & transparency

Performance Max is a revolutionary goal-based campaign format that leverages automation to harness intent and serve ads across all Google properties and help advertisers find more converting customers. Last year Google announced that the Performance Max was going into an open beta test, and last November this campaign type became available to all advertisers – and along the way Google has regularly added more features that provide insights and integrate first-party data.

This year Google has announced five new features coming to Performance Max campaigns:

1. 1. Performance Max | Experimentation tools – The underlying question every savvy advertiser has about Performance Max is “Does it work better than my current campaigns?” Google’s Performance Max Experimentation Tool allows marketers to run A/B experiments to measure the performance uplift their account may get when using Performance Max as a complement to existing performance campaigns that are optimizing to the same conversion goal.

      This tool has been in beta for the past few months and will enter general availability later this year for campaigns without a product feed attached. In tandem, Google will also release a new A/B experiment tool specifically for advertisers to test Performance Max against Standard Shopping Campaigns.

   2. Performance Max | Explanations – When performance changes, we all want to know why. Explanations, already launched for some search and app campaign types, are coming to Performance Max. This diagnostic tool will help marketers understand Performance Max campaign performance changes in just a few clicks. This new feature will help save time in understanding what’s driving performance fluctuations over time, leaving more room for campaign optimization. Explanations will be rolled out this month and will be expanded over time.

   3. Performance Max | Recommendations & Optiscore – The trickiest challenge with any type of automation is figuring out when and how to lean in and impose changes on the system. To help answer this question for Performance Max campaigns, Google is adding two features that have long provided value for advertisers in other campaign types.

      The Recommendations page will surface recommendations to improve a Performance Max campaign based on performance history, campaign settings and Google search volume & trends. Optiscore will surface and quantify optimization and growth uplift potential for Performance Max campaigns. Optiscore will provide more clarity to common questions such as “What can I do to make Performance Max work better?”

   4. Performance Max | Search Ads 360 & Floodlight tags – The new SA360 has already allowed advertisers to create, manage and report on Performance Max campaigns. The next update will provide advertisers the ability to measure and optimize Performance Max campaigns using Floodlight tags for click-through conversions.

      It is necessary to migrate bidding to the new Search Ads 360 to optimize with the same goals, settings and targeting. This was the missing piece we have been waiting on here at Brainlabs in the last few months, to finally combine the power of automation from Performance Max and the advanced bidding solutions we leverage daily through SA360.

   5. Performance Max | Store Sales Reporting & Bidding – Performance Max has supported some Local goals since the very beginning. With this new feature, advertisers will now have the ability to optimize for Store Sales and not just Store Visits within Performance Max.

      Additionally, as soon as Q3, marketers will also be able to promote in stock in-store products, hours, and available offerings like curbside pickup, takeout, or drive through, all of which have massively grown in importance over the past few years of the global pandemic.

Simple, privacy-safe conversion measurement improvements

As changing privacy regulations continue to impact digital measurement it becomes pivotal to evolve measurement solutions to close the gaps. Regardless of the industry shifts, third-party cookie deprecation and regulations, advertisers can still access accurate measurement that enables optimization for improved performance over time. Google is launching several new privacy-safe measurement solutions for marketers:

1. 1. Enhanced Conversions | Web in SA360 – This new privacy-centric conversion tracking feature enables conversion tags to capture hashed user-provided customer data that advertisers collect on a conversion page (like email address) and then match it against the Google hashed web data, future proofing measurement by alleviating the reliance on third-party data. It is already available for Google Ads, and it will be rolled out as a closed beta globally on SA360.
   2. Enhanced Conversions | Leads – Any advertiser who is focused on lead-gen activities knows there’s a big difference between an initial lead and a qualified or converted lead. Released earlier this year, Google has now rolled out Enhanced Conversions that addresses the struggle of lead-focused marketers without a full CRM integration. Enhanced Conversions for Leads brings simplicity and accuracy to lead-gen measurement. It allows advertisers to import offline conversions directly into Google Ads for reporting and optimization. The added simplicity driven by this product is created by the removal of the need to store GCLID data in the marketer’s CRM. This feature is available globally.
   3. Data Driven Attribution Enhancements – Initially launched five years ago, Google Data-Driven Attribution (DDA) creates a unique attribution model that Google is now confident to categorize as the best model for the majority of advertisers that are seeking to measure and drive performance. DDA has now become the default model for new Google Ads conversion actions and Google Analytics 4 properties. Google will also start to automatically upgrade selected conversions to Data Driven Attribution when they believe this will lead to improved results. Advertisers will still have the option to opt-out of this automatic feature, which will be available globally.

      Additionally, any new account created will use Data Driven Attribution, which will be selectable from all web conversion actions in Google Ads and GA4, regardless of the volume. This is the real game changer, as previously a conversion action could only be switched to DDA after recording at least 300 conversions and then had to maintain a certain level of volume to remain eligible. This means that any existing lower-volume conversion actions will now become eligible for DDA for the first time, hence embracing a full DDA model transition.

Lift Measurement quantifies the impact of YouTube advertising on search behavior

Testing is the core principle Brainlabs was founded on, so we’re especially excited about Google’s new lift measurement tools. It’s built to answer a common question that comes on the heels of even the most successful YouTube advertising campaign–how did the video ads influence future search behavior?

Previously such tests took time and effort to create, run, and measure, usually using manually created geo-targeting and geo-exclusion test and control groups. With this new tool advertisers can quickly launch controlled experiments to measure the causal, incremental effects of video campaigns. The outputs will showcase the correlation between YouTube advertising and shifts in organic searches on both Google.com and YouTube.com as well as incremental conversions, enabling marketers to understand how campaigns are influencing user search behavior.

Savvy search marketers were already testing and quantifying these incremental contributions, but the Search Lift and Conversion Lift measurement tools makes it easier than ever to run these tests without taking time away from other analysis and optimization. 

Automation + Insights = Impact

Today Google announced several more innovative upcoming initiatives, such as Google Business Messages, Google Audiences for connected TVs (via Display & Video 360), and video ads on the Discovery feed and YouTube Shorts. However, the core theme of this year’s Google Marketing Live announcements is refinement – and that’s a great thing. Google have clearly been focused on identifying feature gaps, proactively solving for privacy challenges, and listening to user feedback. The 2022 GML announcements are centered around delivering more data and greater transparency to marketers – enabling all of us to pair the power of automation with the insights that accelerate the speed to optimization.

The post More Automation, More Insights: Google Marketing Live 2022 appeared first on Brainlabs.

If you haven’t started testing RSAs yet, don’t panic (but also–start testing RSAs. They work. Really well.). Google has generously given us ten months until this change goes live–plenty of time to deploy or refine your RSA strategy.

So let’s bid farewell to yet another Google ad format, and then take a look at the key things search marketers should keep in mind in order to create the most effective Responsive Search Ads.

A Look Back: The History of Expanded Text Ads

Launched in 2016, Expanded Text Ads provided approximately 50% more text than STAs (Standard Text Ads). Search marketers were able to utilize these additional character lengths to provide more details about their products to the searchers.

For historical context, STAs consisted of one 25-character headline and two 35-character description lines, whereas ETAs added a second headline and the expanded description line lengths to 80 characters. The second iteration of ETAs added a third description line and further increased the limit to 90 characters.

ETAs fully replaced STAs on January 31, 2017 (after a three month extension from original deadline of October 26, 2016).

Google has now announced that marketers will no longer be able to create or edit ETAs starting June 30th 2022. Based on similar past changes, we anticipate pre-existing ETAs will continue to serve for at least an additional year, although Google has not yet shared a definite date when they will be fully deprecated.

The new standard ad type: Responsive Search Ads

Responsive Search Ads debuted in 2018 and became the default ad format for text ads in February 2021. They enable advertisers to leverage Google’s automation and vast amounts of audience data to personalize messaging and rapidly test a massive amount of ad copy variations.

RSAs offer true query-time optimization by assembling the assets that are predicted to perform best for each individual user’s search based on contextual and intent signals. As an added bonus, RSAs can also show in more inventory across the Search Network and Partner sites, a clever incentive by Google to encourage advertisers to utilize this ad format. Google has found that overall, advertisers that switch from ETAs to RSAs (using the same assets) see 7% more conversions at a similar cost per conversion.

Instead of writing multiple discrete ads to test messaging, RSAs enable advertisers to submit up to 15 unique headlines and four description lines. Google then dynamically combines these assets to create tens of thousands of potential combinations. For brands who want or require more control over their messaging, Google offers the option to “pin” headlines and description lines in specific positions – for example, to ensure that a specific call to action always shows or to display legally required text (especially important for brands in regulated industries like finance and pharma).

One key benefit of RSAs is increasing the speed to optimization for search marketers. Advertisers save time by having Google do the testing. Prior to RSAs, an ad group may have had three to five ETAs running at a time with each testing a different message. Over time a winner will emerge, but determining that winner came at the expense of manual ad creation and the advertiser’s time. RSAs accelerate this process by enabling Google’s algorithm to do the testing rapidly and dynamically.

However, this functionality does come with a trade-off. For many search marketers, the frustration with RSAs has been the lack of transparency. As a whole, advertisers can see how each group of RSA assets performs – for example, in one test Brainlabs identified that an RSA produced 20 conversions at a cost per conversion that is half of its ETA counterpart. But Google does not yet provide insights into which assets and combinations are driving those conversions. Instead, Google only shows the number of impressions for each individual asset and combination. Even with all of the performance benefits that RSAs provide, some advertisers have continued to rely on ETAs to better see what messaging is working. We’re hopeful that over the next ten months Google will evolve and expand the reporting provided for RSAs to deliver more transparency that search marketers can utilize to derive insights based on specific combinations of ad assets.

How to Maximize Success with RSAs

If anything, the sunsetting of ETAs will simplify the ad creation process. By combining all available assets each RSA is able to generate upwards of 30,000 different combinations, so there’s no need to create multiple separate RSAs within the same ad group

Google’s recommended best practices for creating RSA assets is straightforward: Use the maximum number of available assets, make the assets distinct from one another, and include popular keywords in the headlines. The good news is that all of these factors can be evaluated via the Ad strength report in Google Ads. The better the ad strength, the better the projected performance.

Marketers should evaluate the importance of pinning ad assets. Pinning enables more control over the content of the displayed ads, but also reduces the number of permutations Google can deliver, so marketers that have historically pinned specific RSA elements should test whether removing these pins delivers incremental gains. Of course, as mentioned above brands in a restricted industry should continue to leverage pinned ad copy to ensure legal compliance.

One thing we have seen firsthand is that RSA performance dramatically improves when fueled with greater volumes of data through each ad group. A minimum of 3,000 impressions per week is the target amount recommended by Google’s Hagakure structure, and based on Brainlabs testing this does appear to hold true (and serves as the foundation of our own proprietary D’Artagnan structure). The removal of ETAs certainly puts more weight behind the argument to look at consolidating account structure, which also aligns well with other recent Google recommendations like making use of broad match keywords and leveraging smart bidding.

One big unknown off the back of this announcement is how Google will update their recommendations for overall creative best practices. Historically Google has recommended running at least 2 ETAs in each ad group alongside RSAs to allow the RSAs to learn from “static” ad formats. We’ll look forward to seeing how Google’s recommendations evolve in the near future as we test into our own updated Brainlabs best practices!

Unsurprising, but Still Actionable

This update didn’t come as a complete shock and will not disrupt current account performance – which is welcome news for retailers staring down a fast-approaching holiday season. Google has provided a long lead time before ETA creation is disabled, and RSAs are well established (have been around for well over two years).

Even if you haven’t yet deployed RSAs, the most important things to do next are:

• Review high-performing expanded text ads and identify top performers to inform RSA strategy
• If relevant, work with your/your client’s legal team to define which headlines need to be pinned down to meet compliance
• Test, test, test! The more ad variations you have, the more learnings you can gather.

As with any Google announcement, it is important to keep an open, curious mind. Know that this update should be an improvement directionally. Be curious about how it will impact performance and how you can test for optimal use cases – like pinning headlines for exact match keywords and testing different combinations for broad match.

Google is constantly evolving their product offerings, and these changes often bring new challenges. But in this case, we can confidently say that the best move is to lean into RSAs, which have proven to be an extremely effective ad format.

The post Goodbye Expanded Text Ads: Google Announces Full Transition to RSAs appeared first on Brainlabs.

What is a Responsive Search Ad?

The concept of Responsive Search Ads is one that makes many marketers a little uncomfortable, at least at first. However, once you start to understand the potential power that these types of ads can deliver, the idea becomes hard to ignore.

It works like this: rather than setting up static ads that combine the same headlines and descriptions each time, you offer Google a collection of headline and description options to test. Over time, Google Ads will automatically mix and match your headlines and descriptions in an effort to find winning combinations. In essence, you are giving up some of the control over your text ads and trusting the intelligence of the Google algorithms to settle on the right blend of headlines and descriptions to draw maximum clicks.

The Basics of Responsive Search Ads

There is plenty to learn about writing copy for responsive ads – more than we could cover in this single article. Let’s quickly touch on some of the basics to get you started.

• You are able to add as many as 15 headlines and 4 descriptions for a responsive ad. These will then be combined in various ways as the campaign goes along.
• It’s important to avoid redundancy when you write your copy. Since you don’t know how the headlines and descriptions will be combined, you don’t want them to say basically the same thing.
• Use the ability to write so much copy to touch on all the various strengths and selling points of your business.

Overcoming Skepticism

As a marketer, it is easy to become stuck in your ways. When you find something that works, you just want to ride that successful formula without venturing too far into the unknown. That tendency is understandable, but it can also cause you to fall behind the competition.

Initially, we were a little hesitant to embrace this new form of advertising ourselves. However, we set that aside and decided the only way to know if it worked was to try it out. And, getting our Responsive Search Ads up and running, we were pleasantly surprised by the outcome.

The key was how the optimization of our ads improved our AdRank, which in turn led to a greater number of impressions. In fact, we more than doubled our impressions when we used Responsive Search Ads, which is a powerful change, to say the least.

The Results that Matter

Of course, simply improving impressions doesn’t do much good if no one actually clicks on those ads. And, it was true that our click through rate fell – but only by 5%. We would encourage you not to dwell too much on clickthrough rate while considering responsive ads. Even giving up a bit of CTR will be well worth it when you consider how many more clicks you are getting as a whole.

Finally, we need to address the topic of conversion rate. At the end of the day, this is what we are all here for – to turn clicks into customers. Impressively, and perhaps a bit surprisingly, we found that our lead conversion rate went up by 5% while using responsive ads. So, we were getting more clicks, and those clicks were converting more often. Based on these results, we’d say that Responsive Search Ads are certainly worth a look in your own marketing efforts.

A Couple of Other Keys

Even with something as modern and high-tech as responsive ads, you still can’t just sit back and expect outstanding results. Plenty will be required on your end, and we have a couple of extra keys to highlight here that may help you optimize this kind of campaign.

• Continue to test. Persistent testing is one of the core fundamentals of any marketing endeavor, and you don’t want to give up on testing just because you use responsive ads. You can continue to test different copy for your headlines and descriptions to track not only how many clicks you can draw, but how copy changes impact conversion rate.
• Save top performers. As you monitor your responsive ad campaigns, you will see which ad combinations are performing better than the rest. Then, you can simply use those as standard ads, so the headline and description are always paired together in a way that has been proven to work.

The Way of the Future?

We would not be surprised to see Responsive Search Ads take over more and more of the Google ad platform in the years to come. So, if these kinds of ads are going to be the standard for PPC advertising moving forward, why not get started now? By learning the ropes as soon as possible and fine tuning your methods, you may be able to get a leg up on the competition. Good luck!

About the author

Ty Alyea is Director of Search Marketing Product at Service Direct, where he is responsible for creating and managing thousands of digital ad campaigns across hundreds of local service industries for 1,000+ clients across North America. He has a B.A. from UCLA as well as an M.A. and PhD from the University of Texas at Austin.

The post How to use Responsive Search Ads to improve your PPC ROI appeared first on Brainlabs.

The two synergy ideas covered in this post will be focused on the following subjects:

• PPC ad copy testing for SEO: we recommend taking learnings from your PPC ad copies and start testing your SEO metadata and on-page copy.
• A direct link between Quality Score and both PPC & SEO channels: we cover an experiment we conducted where we try to validate our hypothesis that QS has a direct impact on PPC but also SEO.

PPC ad copy testing for SEO 

Remember when I was talking about using PPC to test keywords for SEO? Here we go again! This is where it gets interesting: because Google Ads provides a platform where we can easily test different ad copy (dear SEOs, I feel your pain as we can’t do this so easily for our organic listings), it makes sense to use it with SEO in mind as well.

The obvious destination for our tests is SEO metadata (title tags, meta descriptions, headings), but also on-page copy. Has a certain ad worked well for a particular keyword? Great, let me think about using it for SEO purposes.

Explore new page titles with CTR in mind

I strongly recommend exploring new page titles for instances when you want to optimise title tags with CTR in mind, especially for head terms where the SERPs display sites with the same/very similar title tags. 

Trust me, this happens a lot (see the example below). Normally speaking, standard title tags often rely on individual high volume keywords, which make it hard to experiment with them as much as we would like to. Besides, character restrictions won’t allow us to make too many changes to our tags, which makes all SEOs quite lazy and prudent when it comes to optimising metadata.

We believe that testing is the way forward, rather than just assuming something will (or won’t) work. Thanks to SearchPilot, we have carried out several tests on page titles and collected several case studies.

Example: top 5 results for the query “Christmas gifts” 

As a consumer, what would you do if all page titles look the same? Wouldn’t you want to see a website standing out with a catchier and cooler title rather than the examples above?

Test new meta descriptions

Another instance when I use data from PPC ads is when I need to (re)write meta descriptions, for two main reasons:

• Most meta descriptions nowadays are very dull so anything that can save me time and proves to be working, I am all in. 
• They are more relatable to real ad copies and play a significant role from a CTR point of view.

Differently, from page titles, it is easier and safer to conduct tests on meta descriptions as they are not really a ranking factor anymore, so why not giving it a go?

What you need to decide next is which ad copies you are willing to use/take inspiration from: to be clearer, I will explain it with an example.

Imagine the following scenario:

Let’s assume I have a website samtshirts.com that sells personalised t-shirts. I have a total of 3 ads running in rotation for the key term ‘personalised t-shirts’ – meanwhile, my SEO visibility is pretty good and I manage to rank on page one for this highly commercial term. 

Now the question is: in case I want to test my ad copies in my metadata, which of the three ads do I pick for my SEO page?

• Option 1: I pick the strongest ad (with the highest CTR), and I will be in a situation where the messaging coming from my PPC and SEO is reasonably similar, if not the same. This will guarantee a consistent message and will reinforce my intent.
• Option 2: I pick the second strongest, and I will be in a situation where my messages coming from PPC and SEO are different and might be complementing each other/working together.

What should you do? Test the above and implement what works for you!

Test new copies on your transactional pages

I talked about this idea in detail in my guide to e-commerce category pages.

To sum up the core concept, e-commerce category pages are often the main destination of PPC ads. An underrated part of a transactional page is the character description which is usually placed at the top/bottom of the page: historically used for SEO purposes (extra text on the page), such copies are often neglected, as they tend to be reasonably badly written (keyword-stuffed) or moderately pointless in my opinion.

Why not avoid the hassle of coming up with a lousy description when you can use one that is actually useful? By retrieving data from your PPC Ads, you can choose copies with the best CTR and use them on the page. 

The benefit will be two-fold:

1. Your copy has been proven to be catchy/enticing rather than a boring one – instead of wasting precious time coming up with entire copies yourself, your PPC ads can quickly inform your content.
2. Most e-commerce pages tend to be reasonably thin: they have little text on-page, which increases the likelihood of duplication in the eyes of Google among similar transactional pages. By providing an efficient description, we are adding context to the page which impacts the SEO potential of the page & influences the overall landing page experience (we covered this concept in-depth in post number 1) when such a page is used in PPC ads.

How to get started

If you do not know where to get started and which pages to test first, follow this process:

1. Look at your Search Console for landing pages that don’t perform as well as they should: your key metric here is low CTR. 
2. Cross-reference your rankings with CTR industry standards (click here for my go-to page for this type of data) and determine which pages are underperforming from a CTR point of view. Bear in mind: in some instances, CTR is low due to ambiguity in the keyword, such as dual meaning to a term – these particular cases should be dealt with separately.
3. Start from the URLs which organically appear on page one of the SERP as they are the most valuable – export the list and start experimenting. 
4. In 2-3 weeks (at least try and reach a good amount of impressions on GSC, unique for every keyword/industry) review your changes and make a call on what is best to do next: leave the new metadata in place, revert back or keep experimenting.

Quick recap: why is this worth it?

• By taking advantage of PPC’s platforms and data availability, we can provide more effective SEO metadata and text descriptions on the e-commerce pages that can help us improve our CTR and hit the bottom line.
• This approach will save you time, effort and is based on real data collected from Google Ads.

QS and Page speed go hand in hand

In post one of our series, we touched on Landing Page Experience and the five main elements that constitute this key component of Quality Score. In this section, I want to focus on the aspects of Landing Page Experience that relate to page speed.

According to Google, these are the two main points about page speed:

• Decrease your landing page loading time: make sure your landing page loads quickly once someone clicks on your ad, whether on a computer or mobile device.
• Make your site fast: see how your site scores on mobile speed, and get quick fixes to improve it. 

All the above makes sense: you should have a fast site, so that when a user clicks on your ad, your page will load quickly and the overall user experience will benefit from it.

So if it is so obvious, why did we decide to spend time and resources to do an experiment on the direct link between page speed and quality score? 

These are my main reasons:

• We like to test any hypothesis to prove whether it is true
• The lack of research on the subject made us want to test this even more
• Most importantly: showing a direct correlation between page speed and quality score will stress the importance of page speed itself, as it can show clear benefits from an SEO & PPC point of view. When talking to your clients or your devs, you can now tell them “let’s make page speed a priority: it will improve my SEO performance (Google confirmed it is now a ranking factor), it will improve the overall quality score, which ultimately impacts the spending and efficiency of our accounts”.

Methodology

Before we dive into the results of our test, let’s talk about our methods. See the list below to understand our rational and limitations:

• We conducted our tests on our Google Ads account rather than using a client’s account for two main reasons: direct control on changes to the pages from a dev point of view & intention to prove the validity of our test before suggesting the use of client resources for it.
• Our quality score for our account when conducting the test was low (overall average between 2.5 and 3) due to a mix of factors which are not important to cover now.
• We conducted two tests in total, taking learnings from the first one, which we applied to the second one (which is the one we will talk about in this post).
• The timeframe of our final (and second) test was just under a month.
• In order to monitor the average value of quality score throughout the test, we used a script which populated a Google sheet for us.
• In order to monitor page speed throughout the test, we used a Pingdom subscription to monitor the page speed continuously, while also regularly checking page speed insights, Lighthouse, GT Metrix, Webpagetest (manual checks).
• We did not make any change to our Google Ads account or any other changes at all to the page of interest during the testing time frame since they might have altered our findings.

Limitations

Our tests were not perfect: let’s clarify it from the start – but we could also argue: how many studies & research we see online are perfect?

We did our best to examine the correlation between all variables involved, but obvious limitations applied:

• We used a small budget compared to what a big PPC spender/account might use
• We ran the test targeting one page mainly as the Google Ads campaigns were built to promote one particular page

In all fairness, having a small budget made it harder to prove the validity of our test due to the fact our keywords did not collect data as fast as big budgets would allow. With a more significant spend, we surely would have had an easier time & data-turnaround.

However, having a small budget has one positive: the lower the traffic, the less likely that CTR or ad relevance factors would change in the tested timeframe; therefore the Landing Page Experience portion of the QS should have been highlighted.

Ultimately, most of you might be thinking about this question right now:

Can I trust this test or are you guys talking BS?

My humble response to the above is to be short and sweet: this test aims to provide validity for more and bigger tests, so we see it as the start of the conversation rather than the final answer.

Page speed changes

To identify what changes to make on the page of interest, we decided to use both Lighthouse and Page speed insights reports, which are Google products: at the end of the day, quality score is a Google metric itself.

We based our suggestions on both reports and compiled a list of the three main changes to apply on the page at different times:

• Reduce render-blocking resources
• Minify CSS and JS
• Optimise images on the page

After talking to our devs here at Brainlabs, we agreed on making the changes above, following a precise time frame that we used to coordinate efforts.

Without going into a page speed rabbit hole (this post is not about that), let’s move onto the results we came across.

Results

Find the table with all the results below:

Result highlights:

• Avg Quality Score improved by almost 2% at the end of the test, but reached a peak of almost 5% improvement after the second change
• Page speed scores improved by 130% (Page speed insights) & 115% (Lighthouse) at the end of the test
• While all changes did have an impact on page speed scores, the first change did not have any effect on QS (render blocking resources)
• The second change to the page was the one that impacted QS the most (minification of CSS & JS)
• The third change to the page seemed to have lowered QS if compared to levels reached after the second change (image optimisation). The reasons behind this change could be attributed to other external factors related to our server or site that occurred while the test was run, so I would personally not focus too much on this finding.

Conclusion & Questions

The initial hypothesis was proven right: there is a direct correlation between page speed and quality score. It appears to be lower than what we initially expected, but due to the limitations of our test, we were happy with the results.

All changes recommended by Google seemed to have affected page speed scores, as expected, but not necessarily on quality score. There were instances when page speed scores went up, but the quality score stayed the same. Therefore, it seems that all changes aimed to improve page speed do not necessarily imply direct changes to levels of quality scores.

Some changes seemed to have impacted page speed and quality score the most: minifying CSS & JS was the driver of the largest change. Surprisingly, compressing images or adopting WebP formats (for another test we ran, which we did not cover in this post) did not seem to impact quality score. 

Most importantly, I was reminded that landing page experience is a significant factor of quality score, but does not account for the entirety of it. So any changes we implement with landing page experience in mind, actually impacts only a portion of the total quality score – so to move the needle in terms of quality score, we need a serious level of page speed improvements, as one simple change might not do the job. As for the exact measure of what the landing page experience accounts for, further testing should help us determine its weight. 

In case you had one of the following questions, we put together a list here:

Will you run another test on the subject to validate the results of this one?

We plan to keep running more of these tests to validate our hypothesis better – we are advocates of knowledge sharing at Brainlabs, so please get in touch if you decide to run a similar experiment.

What was the most surprising thing about the results, in your opinion?

The biggest surprise was the minimal changes to page speed scores and quality score provided by image improvements. More on this in question 4.

What change had the highest impact on quality score?

Our efforts to minify CSS & JS seemed to have had the highest impact compared to the other two changes.

What changes did you make to the images?

For our first test, we initially used the WebP format that Google has been advocating for a long time: surprisingly that did not seem to have had any direct impact on the speed of the page (very minimal to none changes detected).

For our second test, we just compressed the images, keeping the same format. Even this action did not provide as much improvement as we hoped for, which make us believe images do not seem the needle in terms of speed and quality score changes.

What changes did you make in terms of render blocking resources?

This involved auditing any javascript files that did not need to be executed immediately when loaded. These scripts would otherwise block the rendering of the page and loading of other resources. By adding an `async` attribute to these script tags, we can defer the execution of that script and allow the rendering of the page to continue immediately.

What changes did you make in terms of CSS and JS minification?

This involved auditing all the CSS and JS files and running them through a minifier to reduce file size. A minifier will retain the logic contained in the original file but remove any unnecessary characters.

Quick recap: why is this worth it?

• Showing a direct correlation between Page speed and QS will impact the way we see page speed as a whole: its direct impact on both SEO & PPC will help increase the priority and importance of page speed fixes.

Our series of SEO & PPC synergy ideas terminates here.

In case you have not done it yet, check part one and part two:

• Part 1: Finding Efficiencies
• Part 2: Landing Page Testing

Finally, we have put together a checklist that hopefully can help you promote synergies between the channels. All synergy ideas have been pasted in the Google Sheet file, together with additional info and recommendations.

The post PPC & SEO synergy part 3: ad copy testing & QS correlation with page speed appeared first on Brainlabs.

• Part 1: Finding Efficiencies
• Part 2: Landing Page Testing
• Part 3: Ad Copy Testing & QS Correlation with Page Speed 

Part 2 includes two more synergy ideas which will be focused on the following subjects:

• Landing page testing: we recommend testing the SEO landing page for instances where SEO & PPC landing pages differ, for the same keyword/s.
• Strategy when both organic & paid results appear at the same time: we re-create a series of scenarios and recommend what tests to implement in instances where your site appears for organic and paid results for the same keyword/s.

Before reading the post below, I recommend you check part one.

Landing page testing

As you might all know, while in PPC the advertiser can pick the landing page that will be shown for a specific keyword, in the SEO world this is not possible as the search engine does the decision making.

SEOs can obviously work towards the desired outcome, mapping and optimising landing pages for specific keyword groups, making sure a search engine is able to pick the page we want – but in reality, with larger sites (e-commerce in particular) with tons of pages, this process is not as easy and straightforward as we would like.

Another difference between PPC and SEO lies in the diversity of intent between the two results:

• Generally speaking, PPC ads tend to aim for conversion – so when the landing page is picked, this happens with a site conversion in mind.
• On the other hand, Google picks organic pages based on how well they think such pages could respond to a user query: this is an important difference we have to understand.

Have a look at the example below to picture this [note: this is a very simplified example for a brand query, picked for the purpose of this post – the landing page testing synergy is applicable to a multitude of queries, not just brand ones]

When looking at some of my clients’ account, I used to run into this discrepancy a lot, which is sort of normal considering the differences between the two channels.

PPC vs SEO results

Based on what was discussed above and the example provided, does this mean Google ‘likes’ the SEO page better than the PPC page for the queries such as “ticketmaster lion king”?

• For an organic result: yes, because for informative or more generic queries, Google assumes that users are still at the top of the marketing funnel, where they are probably still browsing results – the average user wants to check the price and description of the lion king musical on Ticketmaster.
• For a paid result: no, because the main objective of this activity is a conversion, which generates money to Ticketmaster and Google: win-win.

What would happen if PPC picked the SEO informative page for their ads instead of the transactional page? Would the Quality Score be impacted as a result?

My suggestion is the following:

For keywords whose Quality Score is low, it is worth testing the SEO landing page instead of the PPC one, when there is a discrepancy between the two.

And here is why:

• A lot of times, PPC ‘lazily’ picks the destination URL without thinking too much about landing page experience (remember part one?), which is a crucial contributor to the final score, which then impacts CPC.
• Other times, PPC picks the most transactional page to help their case: SEO pages are often too far from the conversion point, which is what PPC ultimately cares about.
• However, not all keywords might require a transactional page: it is important to consider the user intent and act accordingly. If we are willing to bid on some top-of-the-funnel keywords, landing page experience and user intent should be the priority.
• Testing whether landing page experience could be easily improved by switching to the SEO page is easy and is worth trying.

How to get started

To get started, these seven steps need to happen:

1. Pick keywords with a low QS (lower than 7 is a good start)
2. Find out if the landing pages between the SEO & PPC results are different
3. Analyse the type of keyword and intent behind it. This step is crucial: depending on the type of keyword and intent that Google associates for that particular keyword, the outcome of this test could be very different.
4. Check how different the SEO & PPC pages are: how far off a conversion is the SEO page? If the SEO page is far from the conversion point, then I would expect my conversion data to be noticeably impacted if I were to use it for my PPC ads.
5. Implement the SEO page in the PPC ad and keep monitoring the quality score for the keywords where the changes have been applied to.
6. Keep the SEO landing page where changes have been positive, revert back if not.
7. Start the process over and check your QS frequently.

Quick recap: why is this worth it?

• In some instances where the landing pages between SEO and PPC results differ, it is worth experimenting with SEO landing pages for PPC ads as this change can help you increase quality and lower your CPC.

Organic and Paid listing appearing at the same time: what to do?

I am sure you all had this conversation at some point in your SEO-SEM career: should we bid on this X set of keywords, for which we have already good organic visibility? Is there any point in having PPC ads if my SEO results are strong already?

Let me start with a clear statement: I do not have the answer and beware of the people who say that do! What I learnt in 5+ years of experience in digital marketing is that most of the time all you need to do to prove a point is to test things/assumptions: what works for one site might not work for another and so on.

I am going to re-create a series of scenarios and share my thoughts on the differences of approach that you could take when discussed what to do when organic and paid listings appear at the same time.

Scenario 1: Brand keywords, good organic positioning

Imagine the following situation:

• Keyword: brand type
• SEO situation: ranking in position 1

The key question here is the following:

Should I or should I not bid on my brand terms, using precious PPC spend if I am already ranking 1 organically?

Reasons to do bid on your brand terms:

• Brand defence: especially for highly competitive markets, you want to occupy as much search space as possible, so it makes sense. Also, for certain markets and situations your competitors (or retailers or partners) are allowed to use your brand terms in their ads, so in these situations, definitely do defend your name!
• Brand awareness: a lot of people I talk to in the industry want to see their brand bid on these terms from a credibility and brand awareness point of view. If you think that is important, then do so.

See an example where it is worth bidding on your brand keyword:

• For the query ‘halifax mortgage’ Halifax is appearing with a text ad and a couple of SEO results. It is worth noticing that there is competition for this term and that the destination URLs between the PPC ad and the first organic results are different.
• My opinion here: keep bidding on your term.

Reason to NOT bid on your brand terms:

• Save that cash: self-explanatory right? If there is no competition on that keyword and you think your SEO listing will absorb the traffic that a potential PPC ad would have attracted, then definitely consider a SEO-only approach.

Before going for it, I recommend building a testing framework that eliminates seasonality, takes into account all the other marketing channels you are running (they could skew the analysis otherwise) and then test if this is true. I have experienced tests where not bidding on brand terms makes absolute sense and the savings are quite substantial when applied to a large number of keywords: so why not explore the opportunity? It is worth reiterating that this would only work for brand terms where no other competitors are bidding on.

See an example where it might be worth NOT bidding on your brand keyword:

• For the query ‘halifax mortgage calculator’ Halifax is appearing with a text ad and a couple of SEO results. In this instance, there is no competition for this term and the destination URLs between the PPC ad and the first organic results are the same.
• My opinion here: consider an SEO-only approach.

Scenario 2: Non-brand, good organic position

Imagine the following situation:

• Keyword: non-product type, non-brand type
• SEO situation: ranking in position 1

There are a lot of considerations to keep in mind here, I will mention the most important ones in my opinion:

• Volatility: are organic rankings too volatile?
• Competition: Is the competition very tough for this keyword/cluster?

If you answer is yes to any of the above, then you clearly cannot rely on SEO to consistently be at the top of the SERP. Consider PPC to hold a position at the very top instead.

But the real key question is this:

How important is this keyword to your business?

If it is very important, you want to try and use both PPC and SEO at the same time: it will guarantee more space on the SERP (especially on mobile, where space is even more precious), therefore higher CTR. If it is not as important and you are confident that your organic result is better than the competition, then you may want to use that PPC spend on something else.

See an example below where a site occupying the organic position 1 decides not to bid on PPC: fantasticcleaners.com has no ads showing for the keyword ‘find cleaner’ despite being a high volume and high competition type of term.

Scenario 3: Product keyword, good organic position

Imagine this hypothetical situation:

• Keyword: product type, non-brand
• SEO situation: ranking in position 1
• Google Shopping Ads: appearing for that keyword

As most of you know, Shopping Ads tend to appear for product-related searches where the likelihood of intent for a user is a conversion. This scenario is similar to scenario 2 and will involve the same questions: answer them with Shopping Ads in mind instead of text ads.

See an example below where a site ranks at position 1 organically and has Shopping Ad showing:

notonthehighstreet.com is appearing both on Google Shopping for ‘birthday gifts for family’ and as the top SEO result.

Scenario 4: Informative keyword, featured snippets

Imagine this fourth scenario:

• Keyword: informative/generic keyword (non-product), non-brand
• SEO situation: ranking in the answer box (featured snippets)

As most of you might know, you do not have to rank first organically to be eligible in the answer box (read this post to know more), so it is a very appealing opportunity for a lot of sites with less established organic results. As featured snippets occupy such a large portion of the SERP, it is quite evident that the user’s attention will be dragged there – the key question here is the following:

Do you think it is worth appearing for generic/informative terms where chances of conversions might be low (very top of the funnel activity)?

If you are trying to generate traffic and interest in your brand, why not consider it? The price of these keywords might be very cheap and not a lot of companies are interested in bidding in that space, so, as a result, it might be an opportunity worth exploring.

See an example below where a site ranks in the answer box and there are PPC ads appearing for the query:

Despite the fact that getyourguide.co.uk appears in the featured snippet, Airbnb still decides to bid on that particular query.

Always audit your landing pages: a must step before testing

Another key consideration relates to the major differences between PPC and SEO landing pages (refer to the previous paragraph about Landing page testing to understand this point).

When considering whether to ‘switch off’ PPC, always think about how well the SEO page/s could pick up that traffic.

Follow these steps to have a better idea:

• If PPC and SEO use the same page for a particular keyword, then this applies:
  • we expect the user journey to remain the same in case the paid ads were removed, as the page between the two channels does not vary
  • by removing the PPC results (same landing page), we expect SEO to absorb most of the PPC traffic and conversions
• If PPC and SEO use a different page for a particular keyword, then do the following:
  • Analyse the type of keyword and intent behind it – top vs bottom of the funnel
  • Check how different the SEO & PPC pages are: how far off a conversion is the SEO page? How much information and content does the PPC page display?
  • If the SEO page is significantly different (more informative or further to a conversion) than the PPC page, our expectations should be adjusted accordingly: for example, it is likely the SEO page will absorb the PPC traffic but not conversions, as the path to conversion is not comparable. So, it is likely that switching off PPC in these instances will save money, but my overall number conversions will be impacted – hence, a slightly riskier approach that should be tested.

Make sure to account for the above considerations when conducting this type of testing.

Creating a table like this fictitious event example in Excel/Google Sheets can really help you:

Quick recap: why is this worth it?

• It is worth experimenting with your paid & organic listings for multiple reasons: from brand defence to awareness to saving you a lot of money (if applied on a large portfolio of keywords).
• Doing so will help you understand more about your market and your audience, with the ultimate goal of improving your PPC spend and take advantage of your SEO presence.

Part 2 of our SEO & PPC synergy series terminates here. 

Check out the other 2 posts:

• Part 1: Finding Efficiencies
• Part 3: Ad Copy Testing & QS Correlation with Page Speed 

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