Happy Sunday, Everyone!
I hope you’re all doing well, staying warm, and enjoying the weekend. This week’s issue marks number 100 – a milestone I was unsure this little newsletter would reach when I pressed “send” way back in 2023. Since that first send, the newsletter has grown from just 152 subscribers (for Issue #1) to 6,164 (and counting). Along the way, this has sparked more conversations than I thought possible, led to awesome opportunities with dozens of incredible brands, and - most importantly - helped a lot of readers, brands and businesses. That last one is why I started this, and it genuinely makes me happy every time I hear that something in one of these issues provided just a little bit of value, insight or inspiration.
To be candid, I have no idea how many newsletters ever make it to 100 issues. I’m sure it isn’t a high percentage, and I’m incredibly grateful to all of you for sticking with me, reading (or just not deleting) each issue, and sharing it with your friends & colleagues.
With that out of the way, let’s get to this week’s topic (and it’s one that’s been heavily requested over the past few months): the “hidden” or “advanced” features in Google Ads – and how to use them to your advantage.
I know that there’s significant debate around the future of search (check this issue out if you’re curious what I wrote way back when – and it aged pretty well). I know plenty of people and brands think that Google’s dominance is in greater jeopardy than at any point in the past 25 years. I know that the unfortunate combination of Google’s hyper-monetization of search has left more than a few marketers desperate for alternatives. And while all of that is true, so is this: search remains the gold standard for demand capture. Google is relied on by billions of people every single day. Until that changes, brands will continue to invest in paid search.
That leaves a single question: what separates the brands that win from those that merely spend on paid search? What sets remarkable ad accounts apart from the mediocre? And, how can you improve the performance of your ad account?
I’m not going to lie to you: ad accounts follow a pareto principle. 80% of the success of your ad account comes from stuff not in your ad account – the strength of your brand, the quality of your product, the caliber of your customer service, the weight of your reputation, the attractiveness of your offers, etc. An ad account is an accelerant. If the underlying business is strong, a well-designed, properly-maintained ad account will help it grow far greater than what would otherwise be possible; if the business is bad, the ad account is simply going to hasten its demise. Marketing & advertising can’t save a bad business or a garbage product over any reasonable period of time. The fundamentals (product, brand, offer, service, support, etc.) tend to win out over the long term. Assuming you and your competition have those fundamentals in place, the winner is decided by the remaining 20%.
That’s what this issue is all about.
Hidden Feature #1: Portfolio Bid Strategies
Portfolio bidding strategies have been around for nearly a decade - but less than 5% of the accounts I’ve reviewed use them. At their core, Portfolios simply create a single “variant” of a standard bidding strategy (Max Conversions, Max Conversion Value, tROAS, tCPA, tIS, Max Clicks) that can be shared across multiple campaigns. In and of itself, that might not be super useful – but where it shines is the aggregation of conversion data that comes along with it.
Google Ads optimizes on four levels:
- Primary Conversion Action(s)
- Campaign
- Portfolio
- Account
That means that if you're using a single conversion action (i.e. purchase, form fill) for multiple, disparate audiences (i.e. different service offerings, different buyer types, different customer types), you're reducing the homogeneity of the underlying conversion signal. That can impede learning. ML works best when the underlying signal is as "pure" as possible.
The same thing is true if you have multiple, materially-different primary conversions added to the same campaign (i.e. a purchase vs. a click-to-call). Smart bidding + machine learning are like water: they find the path of least resistance. If your primary conversion actions admit of wildly different intents and/or difficulty levels (from the above example, it’s far easier to get someone to click on a “call” button vs. actually complete a purchase), the platform will inevitably move to giving you the easiest-to-attain action.
The reason many brands do this is because they’re trying to balance volume with specificity – they know they need ~30 conversions per month in order to exit learning (it’s closer to 15 now, but your mileage may vary), but they don’t receive 30 (or 15) of those super-high-value actions each month. The solution? Add another conversion that does get the volume, and voila!
Unfortunately, the reality doesn’t quite match the theory. Google over-indexes toward the easiest-to-get conversion, the brand ends up getting less of what they really want, and everyone is frustrated.
Enter portfolio strategies. With these, the conversion signal is aggregated from all campaigns added to the portfolio. This is particularly helpful if you have several campaigns with less-than-ideal conversion volume, either as a result of underlying search volume and/or geographic limiters. So, if you have 5 campaigns, each of which gets 5-7 conversions per month, a shared portfolio strategy would be able to optimize off the 25-35 total conversions. For brands with limited budgets, or with niche audiences, using portfolio strategies can be a game-changer – it aggregates conversion volume while providing a few other benefits:
- Max Bids - One of my favorite features of portfolio strategies is the maximum bids (also known as free insurance). Anyone who has managed a Google Ads campaign can tell you a horror story (or 10) about a blowup CPC that completely tanked a daily budget. Put simply: max bids prevent that by allowing you (the advertiser) set a maximum CPC. The best way (IMO) to set those is to find the highest conversion rate among expensive, high-volume terms in your account, then multiply that conversion rate by the value of your conversion, then multiply that by 1.15 or 1.20. For example, if the highest conversion rate (over a good-sized sample) is 22%, and the value of a conversion is $100, you might set your max CPC at $100*0.22*1.15 = $25.30.
This effectively limits your downside risk, and does so with minimal impact to your total upside. The simple fact is that - for your brand - any click that costs more than $25.30 (on a conversion value of $100) has a staggeringly low probability of being profitable. Could it be? Sure. But the odds aren’t in your favor. Digital advertising is about placing smart bets, and, for the hypothetical brand above, paying north of $25 for a click isn’t one.
- Min Bids - Most PPCers would think these work like the inverse of a max bid (i.e. if smart bidding wants to bid less than this, it places the minimum bid instead), but they don’t. A minimum bid is the “floor” for the auctions you want to enter. So, if your minimum bid is $10, the system will only bid for those clicks that have a projected cost of (at least) the minimum. There are some wonderful uses for this – if you know (for instance) that low-cost traffic tends to be garbage or that see that Google is flooding your STR with absolutely bonkers matches, a minimum bid is a wonderful way to avoid spending on suboptimal traffic.
The same is true in hyper-competitive spaces, where you are confident quality CPCs are at or above a certain level – a minimum bid ensures that your budget is going toward the creme-de-la-creme of the available impressions. This will result in your account missing out on some (potential) long-tail or weird queries, but will also avoid your daily budget being killed by 1,000 cuts.
A practical example of this might be a competitive space where high-quality CPCs are consistently north of $20 AND where Google likes to be liberal with matches - say, [emergency plumber near me]. This is a staggeringly valuable query for any local plumber, and those shops want their budget to ONLY be used for the identical-match queries. If a PPCer in this space - after reviewing the historical data in the account and doing the keyword research - finds that those queries have an average CPC of $28.50, and queries under $20 tend to be quite bad, s/he could use the “minimum bid” set at $20 to avoid the weird/bad matches and focus the full budget on the valuable terms.
It’s a niche tool, but an incredibly valuable one.
Hidden Feature #2: Ad Customizers
Ad customizers are one of the least-used, and possibly one of the most valuable features in the entire Google Ads platform. Used properly, they can increase the relevance and scale of your account without adding structural complexity or fragmenting your conversion signal.
The problem is that they’re so under-used that even the best PPC management tools out there barely support them. Before we get into it, I’m not talking about the standard Ad Customizers (Countdown, Location Insertion, KW Insertion). Those are nifty, and they certainly have their uses, but they’re not game-changers.
Ad Customizer Attributes are game-changers. You’ll find them hidden within the “Business Data” section of Google Ads…and once you start using them, you’ll never go back.
At their core, Ad Customizer Attributes are placeholders that enable you to insert whatever information you want into your ads. They can be anything, from prices or discounts to locations, star ratings, number of locations, award counts, product attributes, number of models in stock, number of reviews – the possibilities are endless:
Reviews: if your brand is constantly getting reviews, you can dynamically pull the current number of reviews and average rating from your site (or whatever 3P tool you have), and ensure that every live ad uses the correct value. No more having to find-all / replace “1,256 5* reviews” with “1,311 5* reviews” every week. No more hoping that you have the right average rating on every ad. Ad customizers can automatically source the information and insert it into every ad.
Awards: No one likes to update the number of awards you’ve won or the most current recognition you’ve received. Make it a customizer, insert it, and never have to worry about it again.
Product-Level Customizations: if your brand sells a bunch of different products, you can customize each ad to the specific product - including the current price, star rating, number in stock, color/size/style, etc. Put yourself in the shoes of your potential customer - if you searched “Blue Nike Shox Near Me”, would you be more inclined to click on an ad that said: “7 Pairs of Blue Shox In Stock / $159.99 on Sale Now / Steve’s Sporting Goods” or “Shop Our Nike Shoes / Men & Women / Winter Sale Now - Feb 10”?
The first one, right?
Well, Ad Customers make that happen.
As a general rule, any piece of information you find yourself repeating across multiple ads – whether it’s a brand, a value prop, a differentiator, a statistic (like starting at $X or YYY Clients Served or ZZ Locations) - should be a customizer. The same is true for the brands in your catalog, the types of products you sell, your service lines, etc.
Strategically, Ad Customizers are the magic link that enables ML-friendly account structures and hyper-relevant, personalized ads to co-exist at scale. Most PPCers have accomplished this via SKAGs + EM + loads of negative KWs – but all of that adds complexity and introduces more potential error. With ad customizers, you can consolidate more of your ad groups, confident that the customizer will adjust the ad copy with the appropriate content. And the best part? If/when you need to change a customizer value, you only have to change it in one place (and you don’t have to wait for 100 or 1,000 new ads to be approved).
Hidden Feature #3: DSAs with Page Feeds + Negative Lists
I, like many advertisers, have been simultaneously frustrated by DSAs going rogue over the years and enchanted by their potential. If you’re unfamiliar, Dynamic Search Ads (DSAs) allow Google to crawl your site and generate ad headlines and direct users to any landing page on your site. For anyone managing a large site, this can seem like a godsend (no need to map KWs to hundreds or thousands of pages), right up until you notice Google going a bit crazy on the pages pulled in.
The solution to this is to pair DSAs with Page Feeds.
Page Feeds are a simple CSV of a subset of your site pages that Google can use to power the DSAs – so instead of the full site being eligible, only a select few pages are available to Google. You can further refine the structure by assigning each page one (or more - up to 20) custom labels. These can group the pages by service type, product type, brand, price point, promotion, theme (or whatever else you like) – and in so doing, allow you to control bids for each group or sub-group of pages.
The final component of this strategy is robust negative KW lists, which prevent your DSA from cannibalizing your existing, high-performing search campaigns. The trick to making this work is to include BOTH your other campaign negative keywords (i.e. the stuff you’ve found doesn’t work or isn’t relevant) AND the search campaign positive keywords (i.e. the stuff you don’t want to cannibalize). The benefit of using lists (vs. simple keywords) is that lists are dynamic - so as you add more negatives to the list, all campaigns using that list will automatically update.
Finally, you can use ad customizers in the description of your DSA (since that is a fixed value); you can’t pull it in for a headline (which is dynamically set) – giving you the opportunity to create hyper-relevant, targeted ads for just about anything.
Hidden Feature #4: Negative Keyword Match Types
I have a saying when it comes to ad platforms: The Devil is in the Defaults. There is no place that is more true than when it comes to negative keyword match types. Most people assume (wrongly) that match types function the same way for both negative and positive keywords – and that assumption leads them to approach negative keywords in a way that limits their efficacy.
Negative [Exact Match]:
This is the default setting for all negative keywords in Google Ads - and it’s also the least restrictive. If you have a negative exact match keyword, your ad will not show ONLY IF the search is an exact match to your negative keyword with no extra words. Thus, if you placed the following negative keyword into your campaign: [men’s sneakers], your ad won’t show if someone searches “men’s sneakers”, but will serve for:
- Men’s blue sneakers
- Men’s basketball sneakers
- Sneakers for men
- Men’s sneakers size 13
- Buy men’s sneakers online
- Men’s basketball hightops
- Mens Sneekers (misspelling)
Negative “Phrase Match”:
Negative Phrase Match is a step up from Exact Match, in that your ad will not serve if the search contains the exact negative keyword phrase, in the same order, even if there are additional words before or after. Continuing with the above search for “men’s sneakers”, this means that the ad would NOT appear for “Men’s sneakers size 13” or “buy men’s sneakers online” (since men’s sneakers is the exact phrase, in the exact order), but would still serve for:
- Men’s blue sneakers
- Men’s basketball sneakers
- Sneakers for men
- Men’s basketball hightops
- Mens Sneekers (misspelling)
Negative Broad Match:
We’ve finally arrived at the point where Broad Match is (usually) good - negative broad match will prevent your ad from serving if the search contains all of your negative keyword terms, in any order. This means that the only terms from the above list that would still serve are “Men’s basketball hightops” and (potentially) “Men’s Sneekers” (the misspelling).
There’s a reason why Google defaults to exact-match negatives but broad match positives, and it isn’t because they want to help you; it’s because that combination gives the greatest illusion of control to the advertiser while providing Google with maximum optionality.
As a pro tip, if you find that you’re starting to rack up the negative KWs, run an n-gram analysis on your negatives, then add the most common 2-3-4 word n-grams as broad match negatives. That will eliminate hundreds of negatives from your list, allowing you to add more as they arise.
Hidden Feature #5: Rules + Scripts
Rules are absolutely wonderful, and staggeringly, massively underused,
At their core, Automated Rules (found in Google Ads Settings & Tools → All Bulk Actions → Rules) enable you to make changes (and alert you to those changes via email) to your account, campaigns, ad groups, budgets, bids, keywords, ads, etc. automatically, based on conditions you select.
One of the best (though, certainly not the only) use-cases for rules is to automate common, day-to-day tasks – particularly the manual, tedious, boredom-inducing ones.
Some examples of how we’ve used Automated Rules includes:
- Changing Ad Status – pausing low-performing ads based on CTR, CVR, ROAS, Conv. Value / Cost, etc.
- Pausing Low-Performing Keywords/Audiences/Placements – if there are keywords, audiences and/or placements that are spending a ton, but not returning results, you can automatically pause them + have an email sent detailing what was changed. This enables you to review those keywords, audiences and/or placements manually, while stopping the unproductive spend.
- Applying/Removing Labels Based on Performance – I LOVE labels in Google Ads – there’s no better way to document what’s going on, what’s worked and what hasn’t in Google Ads. You can use Rules to apply labels to Ads, Keywords, Campaigns, Ad Groups, etc. based on any condition – for example, if you want to label every KW that has more than 30 conversions and less than $3,000 in spend over a month as a “Top Performer”, you can do that. If you want to tag anything with $2,000 in spend over a month, but less than 15 conversions as “Lower Target” you can do that.
- Adjusting Bids/Targets Based On Labels – you can also use Labels to trigger other changes – for instance, if you want to decrease your tCPA for everything labeled “Lower Target”, that’s possible, too!
- Bid Scheduling – if you want to automatically increase/decrease your bids, CPA targets or ROAS targets based on the time of day, you can do that with Rules. You can also use rules to increase/decrease keyword bids based on search page location.
- Audience Bids – Just as you can adjust CPA targets, KW bids, etc. based on Audience performance – so a top-performing audience can be given a Higher tCPA or Lower ROAS in order to drive incremental revenue // gain priority in the campaign structure.
From a high-level, you can create Rules in Google Ads based on just about anything – including:
- Campaigns
- Ad Groups
- Keywords
- Display Keywords
- Topics
- Placements
- Demographics (Age, Gender, Income, Parental Status)
- Audience
- Ads (Creative)
- Asset Groups (PMAX)
For 90% of accounts, the standard Automated Rule interface in Google Ads will provide all the horsepower you need to take your campaign performance to new heights, all while saving you a ton of time. However, there are a few limitations in the Google Ads interface that are NOT present in the API (or in API-powered tools):
- Layer Multiple Rules into a Single Strategy – Google Ads provides an excellent “If/Then” rule setup – but sometimes, you need an “Else” or “Do X & Y” – neither of those are supported by default in Google Ads. However, there are API-based tools like Optmyzr that do support this, which can dramatically simplify your life (and avoid your having to build multiple rules).
- Pipe In External Data – By default, Google Ads rules work using data from Google Ads – so if the data isn’t in G Ads, it can’t be used for Rules. However, there are ways around this – either Scripts OR API-based tools.
- Remove Recent Changes – any bid or budget modification strategy runs the inherent risk of multiple changes before sufficient data is available to evaluate if the initial change was sufficient. Google Ads doesn’t provide a native way to exclude recently-changed items from strategies for a period of time.
- Blend Data From Multiple Ranges – All Google Ads rules use a single date range (absolute or relative) for the entire strategy. This is usually nice, but it prevents you from creating a rule that says (as an example): “Find all KWs that have a CPA that is 25% or more higher over the L7 than the rolling 60 day average.” – this would be a great thing to identify, but you can’t do it natively. Likewise, if you wanted to create weird lookback periods (for instance, L28 vs. Prior 28), that’s a bit trickier, too.
- Comparisons Across Hierarchical Structure – This sounds complex, but it really isn’t. Say you want to compare the CPA of a keyword to the CPA of the campaign in which it is located, or against a relative value (for instance, 25% higher than the campaign average). In Google Ads, you can’t do that by default. In the API (or using an API tool), it’s easy.
- Move / Exclude Keywords (+ Search Terms) Around Your Ad Account – I’ve written (and talked) above the importance of good Ad Account structure extensively; the challenge is always maintaining that structure as the account and the broader market evolve. I’m a huge fan of automating keyword locations (for instance, demoting a low-performing keyword to another ad group/campaign, or pausing it entirely, or adding it as a negative, or adding search terms as negatives). None of those things can be done natively, but all can be done using the API.
All of these things are available within the API, but you’ll either need some serious dev resources or an API-based tool like Optmyzr or Adalysis to do them.
Even with those limitations, Automated Rules are incredibly powerful. As automation increases, Rules become increasingly valuable as guardrails on auto-applied changes and an enabler, allowing you to focus your time and attention on the aspects of your (or your client’s) business that need it.
Hidden Feature #6: Custom Conversion Sets
This is a feature that I wish would get more attention, especially given how Google has tinkered (to be polite) with how conversion actions are added to campaigns. By default, Google Ads now groups conversions based on their “type” (leads, calls, other, etc.), and allows you to add all “primary” conversions of a given type to a campaign. The problem is that you may have several actions of the same type (for instance, a “Lead Form - Service A” and a “Lead Form - Service B”) that should not be added to the same campaign (after all, you wouldn’t want a campaign focused on Service A optimizing for both Service A and Service B leads).
The solution to this is the “Custom Conversions” at the bottom of the conversions page. From there, you can define sets of specific actions (like “Lead Form - Service A” and “Successful Chat - Service A” and “Calendly Schedule - Service A”), then add just those actions to the Campaign for Service A. That’s the beauty of Custom Conversion Sets: there’s no more having campaigns optimizing for actions that aren’t relevant to the campaign, no more mis-labeling conversions just so you can add them to a campaign.
It’s simple, but it does make a world of difference.
Hidden Feature #7: Variants + Experiments
Experiments have been a feature of Google Ads for over a decade, and they’re still woefully under-utilized (less than 5% of accounts I reviewed in 2024 had run more than 3 in the past 12 months). The simple fact is that if we marketers are going to claim to be “data-driven” or “data-informed”, we need to back those claims up with actions. Experiments and Variants are a fantastic place to start.
At their core, Experiments and Variants are pretty similar – both provide mechanisms for marketers to assess the impact of a defined set of changes on the performance of their account or campaign.
Experiments operate at the individual campaign level, allowing you to modify anything - from the keywords to the audience to the bidding strategy, targeting, creative, ad copy, placements, whatever - then compare the impact of those changes in the experimental campaign to the base campaign. Setting up experiments is intuitive and easy - most can be done in <15 minutes (and many in <5).
Variants, unlike Experiments, can operate at multiple levels of the account - from a single ad group to account-wide. That flexibility makes them a fantastic tool for testing different core messages, value propositions, benefits, CTAs and landing pages across your account (vs. a single campaign).
If you’re doing ad copy testing (and you should be doing ad copy testing), there’s nothing better than variants. I wrote an entire issue about that here.
Hidden Feature #8: Bid For High-Value Customers
This is a brand-new feature in Google Ads - and I genuinely wish more people were talking about it/using it. Most PPCers know that there is a “bid for new customers” option in Google Ads - it leverages your uploaded customer list (PSA: make sure you upload your customer list) to tell Google to either (a) not bid when your current customers search for your brand or (b) to bid more for new customers / less for your existing customers.
Google has recently expanded that base functionality into High Value customers specifically for PMAX – so you can either (a) filter your existing customer list based on value or (b) upload a separate, high LTV customer list – then tell Google to bid more aggressively for users who match the behavioral patterns or are otherwise predicted to be high LTV.
I’m a huge fan of anything that allows you to leverage your 0P/1P data to help Google (or Meta, or Microsoft) make better advertising decisions for your brand (or your client’s brand). This is just the latest variation on Google’s customer data theme, and it’s a good one.
Hidden Feature #9: Custom Segments + Combined Segments
The ninth and final hidden feature of Google Ads that I wished more people used are Custom Segments & Combined Segments. At their core, Custom + Combined Segments allow you to leverage your insights about your audience AND Google’s treasure trove of data to better reach your target audience across campaign types.
While Custom + Combined segments are somewhat comparable, there are some important differences between the two:
Custom Segments are created using the Audience Manager (Tools & Settings → Shared Library → Audience Manager). They can be built using three different types of data:
- Searches on Google Properties (Exact or Theme)* – there’s nothing better than being able to use your existing keyword + topical research to create audience signals, which is exactly what the “People who have searched for any of these terms on Google” option allows you to do. The “Interests and Purchase Intentions” option functions similarly to Affinity Audiences. When in doubt, go with search terms.
- Types of Websites Visited – If you’ve done your audience research (and have used tools like Sparktoro to identify user behavioral patterns), there’s no better use for that data in Google Ads than audience building. If you know that your audience overindexes on certain sites, then build an audience of people who use that kind of site and use it for your PMAX, Discovery, Demand Gen and/or Display Campaigns. Google supports the inclusion of specific URLs (not just the root domain) as part of this functionality – which can help narrow down the audience if the number of pages on a given URL is massive (i.e. the WSJ has 100,000+ pages; you might want to focus it on /investing if you’re looking for investors).
- Types of Apps Used – This does exactly what you’d expect: it creates an audience of people who have a specific app either installed or used on their device. For instance, you’re trying to reach younger investors, you could use it to target people who have the Robinhood, Schwab, Acorns, etc. apps; if you’re trying to reach ecommerce sellers, people who have Shopify on their phones is probably a good start; if you’re trying to reach higher-income single people, target people who have Raya or Luxy installed.
*Note: search terms will only be used as such on Google-owned properties (YouTube, YouTube Shorts + Discover); for 3rd party placements (Display Network), they will be treated like interests.
The one limitation with Custom Segments is that they can only be added to non-search, non-shopping campaigns (i.e. Discovery, YouTube, PMAX, Demand Gen)
If Custom Segments are powerful, Combined Segments are downright magical. At their core, Combined Segments allow you to layer Google’s Data with your business data to create segments that are the best of both worlds.
- Want to overlay a Custom Segment with your existing site visitors? No problem.
- Want to find the people who are in-market for Luxury Vehicles AND are in-market for 5* Hotels? That’s possible.
- Do you want to identify everyone who is in-Market for a Vacation Rental, but under the age of 35? Check.
- Do you want to target people who are interested in child care, under the age of 35 and a parent of a child under 5? Check.
- Do you want to overlay a Custom Segment (for instance, people searching for an accountant) with everyone who has visited your website over the last 90 days? Check.
In short, Combined Segments give you the ability to use “AND” “OR and “NOT” modifiers for *any* audience in Google Ads – making it easy to identify + target the overlap between two in-market segments, or between an in-market segment and a business data segment.
The best part of Combined Segments is that they can be used in Search Campaigns, along with other campaigns (Demand Gen, PMAX, Display, Video, Discovery, etc.).
As search is moving to look more and more like a DSP, the importance of audiences can’t be overstated or overlooked. I fully expect we’ll see Google start to push advertisers more aggressively into using audiences (either as an expansion on PMAX, or as a straight-up alternative to keywords in campaign creation) in the near future; in order to be prepared for that reality, start building your audiences, custom segments and combined segments now.
Bottom line: Google Ads is one of the most powerful and complex ad platforms available – which means that the little things - the negative keywords, the bidding strategies, the audiences, the customizers – are often the dividing lines between success and failure (or hitting your goals vs. missing). I hope some of these tips are helpful as you’re optimizing + evaluating your accounts.
Until next week,
Sam
PS. If you’re wondering if any of these things are in-place for your account, or just want a second set of eyes, I’m happy to take a look. Just reply to this email and we’ll sort the details.
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