Google releases August 2026 spam update

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Google has released the August 2026 spam update and said this update will take a few days to roll out. This update applies globally and to all languages, Google added.

More details. Google posted about the update on its incident dashboard and wrote:

  • Released the August 2026 spam update, which applies globally and to all languages. The rollout may take a few days to complete.

You can learn more about Google spam updates in this Google help document.

Why we care. This is the third Google spam update announced in 2026, the last one was the June 2026 spam update. If your site was not impacted, then you are good to go – at least for now.

There will always be cases of sites not spamming Google that get hit by a spam update but hopefully that won’t be one of your sites.

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What 9 months of AI Overview data and 51,000+ tracked events reveal

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What 9 months of AI Overview data and 51,000+ tracked events reveal

Most brands still don’t have a clear picture of how much traffic AI Overviews are sending them. Google hasn’t given us a clean signal for AI Overview traffic in Search Console, making it difficult to know how much organic traffic is coming from AI Overviews, which content is driving it, and how accurately that traffic is being reported.

So we built our own tracking.

Since September 2025, I’ve been capturing AI Overview referral data for one of the brands I manage in the transportation industry. From September 2025 to June 2026, we recorded 51,200 tracked events across 1,661 cited snippets.

The data shows that AI Overview prominence in the SERP isn’t stable. It also reveals clear patterns in the types of content Google cites, how those citations change over time, and how much of that traffic gets misattributed in analytics.

Here’s what nine months of tracking revealed — and what it means for SEO reporting, content prioritization, and GEO.

The tracking setup — and why it works

The methodology is straightforward, but most teams haven’t implemented it.

When a user clicks on a cited snippet inside a Google AI Overview, Google sometimes appends a #:~:text= fragment to the destination URL. We created a custom dimension in GA4 that fires whenever a session lands with that fragment present.

It’s not a perfect signal, but it’s the most reliable one available without waiting for Google to expose this natively in Search Console. The fragment is already sitting in your GA4 data. You just need to surface it.

Once we had it captured, we grouped snippets into thematic categories and started analyzing patterns. A few things stood out immediately.

  • Concentration is high: The top-performing snippet alone drove 2,276 events. The average across all 1,661 snippets is 31. Like most things in SEO, a small number of pages are doing the bulk of the work.
  • Snippets have lifecycles: Some peak during a specific period and then fade — usually when query intent shifts seasonally or when the content becomes stale relative to what Google is now preferring to cite. Others emerge months after publication and keep climbing. This makes freshness and specificity more important than you’d initially assume.
  • Content prioritization gets sharper: The most useful output of having this data is that it makes decisions more grounded. When you map snippet volume and growth trajectory against your current content investment, the gaps become visible.

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Certain topic types got cited

In our case:

  • Transfer time content and pricing content are already being cited frequently with clear upward momentum. The play there is to refresh and expand the existing content.
  • Destination guides are underperforming relative to what the data suggests they could be driving.
  • Structured transport comparison tables, formatted as actual HTML tables, are punching well above their weight in terms of citation frequency — which tells you something about how AI Overviews are selecting content to surface.

The broader pattern is consistent with what most people working in GEO are finding: AI Overview citations favor content that is specific, structured, and directly answers a well-defined question. Times, prices, named routes, comparison formats. Not vague editorial.

22.4% of AI Overview traffic is being misattributed to Direct

This was the most striking finding.

When we started plotting the dataset on a GA4 exploration report, we noticed that a meaningful portion of traffic arriving via AI Overviews was being attributed to the Direct channel rather than Organic Search.

We know AI Overviews only exist within Google Search. Traffic from there should be attributed to organic. So we built misattribution tracking into our AI Overview dashboard and started measuring it on a monthly and weekly basis.

Across the full dataset — more than 50,000 AI Overview events over nine months — the average misattribution rate was 22.4%.

That’s 11,468 AI Overview events attributed to Direct instead of Organic. The range varied by month:

  • Worst month: May 2026 – 29.3% of AI Overview sessions were misattributed to Direct.
  • Best month: April 2026 – 16.8% were misattributed.

The implications for SEO reporting are significant. Depending on your total organic traffic volume and how much AI Overview referral traffic you’re generating, you could be materially underreporting organic performance without realizing it.

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AI Overviews are driving 7.53% of organic sessions — but it’s volatile

Using the same first-party dataset, we built a percentage metric to track what share of our total organic sessions came from AI Overviews each period.

From September 2025 to June 2026, 7.53% of organic sessions came from AI Overviews.

But the distribution is not flat:

  • At its peak in February-March 2026, it reached 16-17% — meaning nearly one in six organic visitors arrived via an AI Overview.
  • More recently (as of writing), it has trended down to around 2-4%.

That volatility is notable. It suggests AI Overview prominence in the SERP is not stable — it fluctuates based on query type, Google’s confidence in available content, and possibly broader algorithmic changes. Brands treating AI Overview traffic as a fixed percentage of organic are likely miscalibrating their models.

The caveats you should know

Two important limitations with this approach:

The #:~:text= identifier isn’t exclusive to AI Overviews

The same fragment is used by Featured Snippets and People Also Ask results. So some portion of what we’re capturing may bleed from those formats. 

We did run the exercise in Ahrefs to check our Featured Snippet exposure, and at the time of checking, we were included in fewer than 30 — largely because we don’t target terms that typically trigger Featured Snippets. 

In practice, we believe AI Overviews are the dominant driver given the volume and the period of data collection, but it’s not a perfectly clean signal.

The metric compares events to sessions

Our custom dimension in GA4 is event-scoped, not session-scoped. The AI Overview share percentage therefore compares events against sessions, which isn’t an ideal comparison. 

It’s better than nothing — and it’s directionally accurate — but worth knowing if you replicate this.

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What this means practically

If you’re not tracking this yet, start. The setup isn’t complex, and the signal — imperfect as it is — is the best first-party data you’ll get until Google decides to surface this natively.

A few things to take away from nine months of data:

  • Structured, specific content wins. Times, prices, routes, named comparisons. Not editorial padding.
  • Freshness matters more than you think. Snippets have lifecycles. Stale content loses citation share.
  • Your organic traffic is likely underreported. If ~22% of AI Overview events are going to Direct, your channel reporting has a systematic gap.
  • The share is volatile. Don’t treat a peak month as a new baseline.

The #:~:text= fragment is sitting there in your GA4 data right now. You just need to surface it.

Special thanks to Simant Sah for helping collate the data and put together the report where the screenshots come from.

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Microsoft Advertising publishes Conversions API documentation

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Microsoft is giving advertisers a new server-side option for sending conversion data directly to its advertising platform, reducing their dependence on browser-based tracking.

What’s happening. Microsoft Advertising has published new documentation for its Conversions API (CAPI), a server-side measurement solution currently in beta.

CAPI lets advertisers send conversion and customer interaction data directly from their own systems to Microsoft Advertising through a single connection.

The details. Microsoft says the Conversions API can support multiple measurement scenarios, including online and offline events.

The potential benefits include:

  • Improving conversion measurement accuracy.
  • Increasing attribution coverage.
  • Sending both online and offline conversion events.
  • Reducing reliance on browser-only tracking methods.
  • Supporting multiple measurement use cases through one server-side integration.

How it works. Microsoft recommends using CAPI alongside Universal Event Tracking (UET) rather than treating it as a replacement.

UET continues to capture activity in the browser, while CAPI provides a server-to-server connection for sending event data directly to Microsoft Advertising.

Using the two together can give advertisers more complete measurement coverage when browser signals are unavailable or limited.

Why we care. CAPI gives Microsoft advertisers another way to preserve conversion signals and connect online advertising with actions that happen outside the browser, including offline events. For advertisers already investing in server-side measurement across other ad platforms, Microsoft’s solution could also make it easier to build a more consistent measurement strategy across channels.

Yes, but. CAPI remains in beta and isn’t available to every Microsoft Advertising account yet.

Advertisers will also need the technical resources to establish and maintain a server-side integration, making implementation more involved than simply installing a browser tag.

The big picture. Microsoft is following the broader advertising industry’s shift toward combining browser and server-side signals rather than relying exclusively on tracking pixels.

The new documentation shows that server-side measurement is moving from an advanced implementation option toward a standard part of advertisers’ measurement stacks.

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Google updates Branded Searches conversion measurement

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Google is giving advertisers clearer rules for measuring whether YouTube and Demand Gen ads prompt people to search for their brands — while making several notable changes from the metric’s original rollout.

What’s happening. Google has updated its documentation for Branded Searches, a conversion type that measures when someone searches for an advertiser’s brand on Google or YouTube after seeing an ad.

The conversion type itself isn’t new. Google introduced Branded Searches in 2025 as an always-on alternative to running Search Lift experiments.

What’s changed is how Google now defines its availability, attribution and reporting.

The details: Google’s updated guidance introduces or clarifies several important points:

  • 7-day default window: Branded Searches now uses a seven-day default conversion window, compared with the 30-day view-through window described when the feature originally launched. Advertisers can adjust the window between one and 30 days.
  • YouTube and Demand Gen: Google’s current documentation lists YouTube and Demand Gen as eligible campaign types. Performance Max, which was included when Branded Searches was announced in 2025, is no longer listed.
  • Consideration goal: Google now formally categorizes Branded Searches under the Consideration goal.
  • Reporting, not bidding: Branded Searches is treated as a primary conversion action but isn’t available as a bidding optimization goal. The data appears in Results and All Conversions rather than the standard Conversions column.
  • Brand mapping still matters: Advertisers don’t need to set up a Search Lift experiment, but Google says brand mapping must be configured for measurement to work.

Google’s documentation says Branded Searches can be viewed at the campaign, ad group and asset levels, as well as through Report Editor.

Why we care. Branded search behavior can provide advertisers with a useful signal between an ad impression and a traditional conversion.

Someone may see a YouTube ad, remember the company and search for the brand days later without clicking the original ad. Branded Searches is designed to make that influence more visible inside Google Ads.

That can help advertisers assess whether upper-funnel campaigns are generating genuine brand interest instead of evaluating them solely on clicks and direct conversions.

The bottom line. This isn’t a new conversion type or a new seven-day attribution window. The noteworthy update is that Google’s current Branded Searches documentation lists YouTube and Demand Gen — but no longer Performance Max.

First spotted. This update was spotted by Hana Kobzova, founder of PPC News Feed.

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Google Search Console now connects social content to search demand

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Google Search Console now connects social content to search demand

For the entirety of Google Search Console’s life, it has spoken one simple language: your website. Pages, queries, clicks, impressions, all tied to a domain you own and verify.

On July 7, that changed. Google shipped Platform properties, a new property type that lets you verify a social or video account and get the same first-party search performance data GSC has always given website owners. Think clicks, impressions, CTR, average position, and the actual queries behind them — just pointed at your social presence instead.

Worth noting up front: This covers Search, Discover, and News. So a TikTok clip or a YouTube Short can now be tracked across all three surfaces the same way you’d track a blog post.

The mechanics of the launch — which platforms are supported, how verification works, and how this differs from Google’s separate Search profiles feature — are already well covered.

However, one detail deserves repeating because it’s time-sensitive: there’s no historical backfill. Data collection starts the moment you verify. That means every week you spend deciding whether this is useful is a week of query data you can’t get back.

Let’s take a look at what this means for brands and SEOs, some examples of what it looks like in practice, and what it means for marketing going forward.

What GSC Platform properties actually changes for brands

The obvious win is a single first-party lens that gives brands access to both owned and earned content, instead of having to stitch together GA4 and native platform dashboards with a hefty dollop of guesswork.

But Google’s own guidance points at something more specific than better reporting. It points at a workflow. Three parts of it are worth knowing about:

  • Query groups: The Insights report clusters the search terms driving traffic into top, trending-up, and trending-down groups. That’s a real input for planning captions, hashtags and next topics. Ultimately, you’re working from demand that already exists rather than guessing at it.
  • The 24-hour filter: If a post starts picking up search traffic within a day of going live, you can catch it while it’s still live and act by cross-promoting to another platform or timing a follow-up.
  • Format comparisons: Using URL-based comparison filters, you can put Shorts against long-form, or Reels against static posts, and get an actual answer to “should we be putting more into short-form?”

These same three mechanics also change how you should work with creators. None of those three workflow parts are limited to owned content decisions, despite the signals coming from owned data.

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How GSC Platform properties can reshape creator partnerships

Smart brands could already be considering running them through a creator program to answer the questions brands have historically had to take on faith.

Query groups show you which conversations you already have traction in, but that also means, by omission, they tell you which conversations you don’t have a presence in. These insights become the foundations of an honest brief for creator activity.

Rather than simply picking creators based on reach and hoping the relevance follows, you can point to specific query territory you’re absent from and brief against it — developing your presence within new conversations. Alternatively, you could double down within a conversation by partnering with creators who can champion your brand, further developing your presence and preference.

This thinking reframes creator spend as buying coverage of conversations you don’t own yet or want to show up more within, rather than taking a risk on buying an audience you hope overlaps with yours.

Format comparisons can also feed straight into the brief itself. For example, if your own data shows Shorts consistently earning search visibility while long-form doesn’t for your category, that’s a concrete production instruction for a creator rather than a stylistic preference.

And the 24-hour filter gives campaign measurement a dimension it didn’t have before. During a live campaign, you can see whether creator content is earning genuine search visibility or just in-app impressions. This could provide a better read on whether the work is generating durable discovery or a spike that vanishes with feed changes.

There’s a neat symmetry here, too. This data lets creators show that their content genuinely ranks for specific searches, rather than simply racking up views. Platform properties give both sides of the negotiation the same evidence base and metrics.

Creator conversations that once centered on follower counts can now focus on which queries each party actually shows up for. That’s a far stronger basis for partnerships and can strengthen search marketing across the social-search landscape.

Dig deeper: Why creator-led content marketing is the new standard in search

An example of how GSC Platform properties could work in the wild

Picture a hypothetical running shoe brand called Tiger Feet. They connect their Instagram and YouTube properties to the GSC Platform properties, and a few weeks later, the Performance report shows something nobody expected: A Reel about lacing techniques for wide feet is pulling steady clicks from Google for variations of “how to lace running shoes wide feet,” while the website has no page targeting that query.

That’s three decisions in one data point:

  • There’s proven demand: You’re seeing real-world results for a topic nobody on the Tiger Feet content team had previously flagged, and you know it’s real because people are searching it and landing on your content.
  • You’re capturing it in the wrong format for conversion. A Reel earns the click but sells nothing. A product-linked guide on your site, with the video embedded, could.
  • You now know what to write and roughly how to angle it. Because Platform properties give you the exact query language, rather than a keyword tool’s approximation of it, you have a road map to where to focus your content next.

Run the same logic in reverse, and it’s just as useful: If a social post is already ranking well for a query, that’s a case for not commissioning a page that could end up competing with it. 

That’s the shift. Social content stops being measured purely on engagement and starts being measured on demand, which is a completely different question and a much more commercially useful one.

Platform properties give you first-party data, not competitive visibility

Platform properties only work on accounts you can verify, which means you get your own data and nothing else. No competitor view. No share of voice. No category benchmark.

Every other discipline in search has some form of competitive visibility. You can see who’s outranking you organically, estimate what competitors are bidding on, audit their backlinks, and track their positions.

Here, you get a perfectly clear view of your own performance and no visibility elsewhere — so this data should be combined with SERP analysis and manual research rather than relying on it in isolation.

What are the practical consequences of this limitation? It means:

  • You can’t tell good from great. If an article pulls 400 clicks from Google in a month, is that strong for your category or embarrassing? There’s no external reference point, so you’re benchmarking against your own history and nothing more.
  • You’ll spot demand, not competition: Query groups will tell you people are searching a topic and finding you. They won’t tell you that three competitors are already better positioned for it, or that the space is wide open. That still needs conventional keyword and SERP research alongside it.
  • Absence of data isn’t absence of opportunity: A query showing nothing in your reports might mean no demand, or it might mean healthy demand that’s all going to someone else. The report can’t distinguish between the two, and it’s an easy mistake to make.

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What Platform properties change for SEOs

The useful framing here isn’t that it’s a new report for SEOs to get lost within. The way to approach this development is as if it’s a new content inventory that behaves like your existing one.

That’s because Platform properties speak the vocabulary SEOs already work in, which means social content can easily fold into existing workflows instead of sitting in a silo owned by another team — further affording brands the opportunity to break down silos at a time when discovery of brands relies on collaboration across organic media strategies.

What can you do as an SEO with Platform properties? Turns out, a lot:

  • Gap and overlap analysis: You can check whether a query is already being answered by the brand’s own social content (or ask creator partners to share insights on their answers on your behalf) before commissioning a page for it. You can also spot cases where a page and an article are quietly competing and determine whether or not this is a good or bad thing.
  • Test captions and titles like meta titles: You can annotate the date that you rewrote a TikTok caption or YouTube title and then compare performance on either side of it. Same discipline you’d apply to standard optimizations.
  • Apply structural thinking off-site: Comparing things like playlist performance or formats within a platform allows you to think about grouping and cannibalization for content that doesn’t even live on your domain at all.

There are two caveats worth bringing up with clients before this lands in a report. 

  • Reporting carries the usual Search Console delays, so this isn’t a real-time dashboard despite the 24-hour view. 
  • Coverage will vary by platform and content type while the rollout matures, so early numbers need to be treated as directional rather than definitive.

Social strategy has traditionally sat with the social team and been judged on engagement. Platform properties give SEOs a legitimate reason to be in that conversation. The content is now visible in the same tool, in the same terms they already report in and understand, and that they can develop effective strategies around.

Dig deeper: How to optimize influencer content for search everywhere

What GSC Platform properties change for search marketing, generally

If you step back and look at this new rollout, it confirms something Google has been building toward for years: The results page stopped being a list of blue links a long time ago.

Google’s own documentation shows exactly where this content appears — short-video carousels, “latest posts” carousels, and “what people are saying” SERP features — all within Search and Discover results.

Platform properties are Google handing marketers an instrument for a part of the SERP that was already there and simply going unmeasured. This points to three things worth thinking about:

  • The search universe is expanding, and the SEO/social divide keeps dissolving: When both are measured in the same tool with the same metrics, it gets harder to defend treating them as separate disciplines with separate owners and separate budgets.
  • Feed-based discovery is becoming as strategically important as query-based search: In terms of the role search plays in a brand’s discovery, that shift has been visible for a while, and this is the first proper measurement tool for it.
  • Google is now building on the assumption that search behavior is cross-platform: Google isn’t just tolerating the fact that people search for things they saw on TikTok anymore. Instead, it’s actively shipping insights that acknowledge that it’s happening.

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What you can do this week to take advantage of Platform properties

You should connect every active social account now. Don’t wait for a question that needs answering. With no backfill, any account you haven’t connected to is a question you won’t be able to answer later. Take advantage.

If you’re an SEO, rather than a social manager, get yourself into that reporting. Query groups and format comparisons are exactly the kind of data that should be shaping a content calendar. For most brands, that decision-making is happening without SEO as part of the conversation — the best brands will ensure that that changes.

I’ll admit that this isn’t a dramatic feature, on the face of it, although I, for one, am extremely excited about the potential this affords “search everywhere” strategy considerations. The new platform properties are Google quietly conceding that “search performance” was never really about the website. It was always about wherever people go looking for answers.

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300 French newspapers file complaint over Google AI Overviews

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Google dam

Nearly 300 French newspapers filed a complaint today with France’s competition authority. They accuse Google of violating a compensation agreement by launching AI-generated search summaries without publishers’ consent.

What’s happening. APIG, the Alliance de la Presse d’Information Générale, filed the complaint after Google launched AI Overviews (the AI-generated summaries that typically appear above traditional organic search results) in France in late July, France 24 with AFP reported.

Why it’s happening. The publishers say the feature further reduces traffic to their websites. Instead of sending users to original news articles, Google answers their questions directly in Search.

What they’re saying. APIG says Google introduced AI Overviews without publishers’ approval. The group argues this breached commitments Google made under a 2022 agreement on compensation for news content.

  • Google says AI Overviews help people ask more complex questions, discover new content, and give publishers tools to manage how their content appears.
  • “The editors are not seeking to halt innovation. They are asking for this value to be shared, and for compensation of the use of their content,” said APIG President Marc Feuillee.

How we got here. The complaint revives a dispute that has already led to regulatory action.

  • In 2024, France’s competition authority fined Google €250 million for failing to comply with parts of the 2022 agreement.
  • Separately, the European Union opened an investigation in December into whether Google used publishers’ content to train, and provide AI services without appropriate compensation.

Why we care. Publishers argue that AI-generated search answers reduce referral traffic while citing their own reporting. The latest complaint adds to growing regulatory scrutiny over whether AI-powered search can use publisher content without violating licensing agreements or competition rules.

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Google tests advertiser list above mobile Search ads

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Google is testing a new mobile Search ad layout that surfaces the advertisers in a sponsored results block before displaying the ads themselves, potentially giving users more context before they click.

If rolled out more broadly, the change could influence how users scan and interact with paid search results.

What’s happening. The experiment places a list of advertisers—including each advertiser’s favicon and domain name—at the top of a group of sponsored results on mobile Search.

Instead of seeing the first ad immediately below the “Sponsored results” label, users first see the participating advertisers, followed by the individual ads.

Google has not commented on the experiment, and it remains unclear whether the feature will expand beyond a limited test.

Why we care. Highlighting advertisers before the ads themselves could increase brand visibility and help users identify the companies featured in the sponsored results block before reading individual ad copy.

For advertisers with strong brand recognition, the format may improve trust and encourage clicks. Less familiar brands, however, may need to work harder to stand out.

First spotted. This update was spotted by Digital Marketer Sachin Patel, who shared his discovery on X.

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Google adds Campaign Data Import Validation Report

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Google has introduced a Campaign Data Import Validation Report, giving advertisers a new way to check the quality of imported campaign data before it impacts reporting.

The report is designed to help identify missing or incomplete data from non-Google advertising platforms.

What’s happening. The new validation report reviews both non-Google campaign data and previously imported campaign data, highlighting campaigns that may be missing key performance metrics.

Specifically, it helps advertisers identify imports that lack essential reporting fields such as cost, clicks and impressions, making it easier to spot gaps before relying on the data for analysis.

Why we care. Missing or incomplete data can lead to inaccurate reporting, making it harder to compare channels or evaluate marketing performance. The new validation report provides an additional layer of quality control, helping you ensure imported data is complete and reliable.

Bottom line. Google’s new Campaign Data Import Validation Report helps advertisers identify missing campaign metrics and improve the accuracy of imported marketing data.

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12 things Reddit needs to make its ad platform more competitive

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12 things Reddit needs to make its ad platform more competitive

Channels outside of Google and Meta have struggled to get recent headlines in the paid advertising world. But my agency’s performance marketing team has seen one under-the-radar channel — Reddit — introduce a ton of new features and ad types in 2026, making it more viable for our clients.

Between new ad types and AI-powered functions, powerful integrations for shopping, video ad enhancements from late in 2025, and Reddit’s AEO and SEO clout making marketers more aware of the need to engage on the platform, we’ve got more clients active on, or curious about, Reddit than I’ve ever seen.

That said, Reddit’s ad platform — though much further along than it was a couple of years ago — still needs more features and improvements to existing ones to draw a bigger share of advertising budgets.

My Reddit targeting and audience wishlist

A huge part of Reddit’s influence comes from the extremely candid and opinionated content its users provide — and users are enabled to be exactly that, in large part, because accounts use usernames rather than real names.

Redditors can be as anonymous as they want, and I don’t wish to change that. Instead, I’d like Reddit to offer the following.

1. Expand reach without sacrificing privacy

Better identity targeting for anonymous or logged-out users in a privacy-safe way would expand our targetable reach, which is a big deal given Reddit’s niche status compared to Google and Meta.

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2. Bring B2B intent to Reddit

B2B and firmographic targeting that includes: 

  • Job title, function, and seniority.
  • Industry and company size.
  • Named-company and account-list targeting.
  • Tech usage and/or professional-interest segments.
  • Decision-maker and buying-committee audiences.

Reddit offers communities, interests, keywords, customer lists, and lookalikes. Adding privacy-safe firmographic data would make the platform more competitive with LinkedIn while preserving Reddit’s differentiated behavioral signals.

3. Make purchase intent easier to target

Reddit should turn its strongest advantage — people actively researching and discussing decisions — into understandable, scalable “in-market” and journey-stage audiences, including:

  • Recently researched a category.
  • Asked a question about a product or problem.
  • Engaged with comparison or recommendation threads.
  • Evaluated alternatives.
  • Repeated recent engagement.

4. Make existing audience signals more reliable

As for what we can do on Reddit with the reach we have, I’d like to request stronger retargeting depth, lookalike audiences, CRM integrations, and cross-subreddit behavioral signals. Reddit introduced all those targeting options, but they’re still patchy and unreliable, further eroding scale and performance.

5. Give advertisers more control over who they reach

Reddit advertisers need greater confidence that their strategies are hitting the right people. Adding exclusions would help ensure we can eliminate some irrelevant eyeballs, so I’d like to ask for:

  • Negative keyword and community exclusions.
  • Current-customer and existing-lead suppression.
  • Clear control over AND versus OR targeting logic.

6. Make audience planning more predictable

Last in the audience and targeting category, advertisers need better audience planning and forecasting. Before spending budget, they need to see:

  • Realistic audience sizes (Reddit currently has ranges that can seem wildly unrealistic).
  • Demographic and device composition.
  • Top associated communities and topics.
  • Estimated CPM, conversion volume, and audience saturation based on budget.

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My Reddit measurement and attribution wishlist

With the releases of Brand Lift, Conversion Lift, and CAPI, Reddit measurement took a huge step forward in 2023. 

Today, Reddit’s role in the user research and consideration phase is increasingly important as AI search minimizes clicks and pushes performance marketers to focus further up the funnel. 

That means Reddit’s value is increasingly measured through analyses like MMM and MTA rather than through a persistent reliance on last-click attribution.

All of that is to say that it’s easier to measure Reddit ads’ impact than it was a few years ago. Yet, indicative of a platform that’s still more of a challenger than a powerhouse, it’s falling short on some basics. 

There’s one specific (and persistent) gap that should be table stakes for a serious ad platform: more third-party integrations for dynamic UTM tracking. Beyond that, I’d love to see Reddit introduce the following.

7. Prove incremental value without leaving the platform

Reddit is generally considered a test channel, so self-serve incrementality testing — which larger competitors offer — would help demonstrate the incremental value it drives. Specifically, I’d like to see Reddit provide:

  • Conversion-lift studies.
  • Randomized audience holdouts.
  • Geo experiments.
  • Self-serve brand-lift studies.
  • Incremental reach and frequency measurement.

In aggregate, these tests would help Reddit advertisers defend upper- and mid-funnel investment when last-click reporting underrepresents its influence.

8. Connect ad delivery to revenue outcomes

Reddit has Pixel, CAPI, and omnichannel attribution capabilities. The larger opportunity is to make it easier to pull in offline data from CRMs and other sources, so advertisers can lean into down-funnel and revenue-based optimization.

Native HubSpot, Salesforce, and other CRM integrations would be particularly valuable. Advertisers need to tell Reddit which leads became valuable customers, then allow its delivery system to find more people with similar signals.

My Reddit ad formats and creatives wishlist

More than on most platforms, it’s critical to make sure your ads appear as native as possible to their context. Redditors turn up their noses at anything inauthentic.

In 2024, Reddit made some updates to Conversation ads that gave advertisers a useful option in a native setting, but there are many more native formats they could introduce. I’ll list some of my recommendations below.

9. Give advertisers more ways to fit into the conversation

Polls, product carousels, and Q&A ad units designed to fit within the Reddit environment would all be good formats for advertisers to test.

10. Bring short-form video up to speed

Another area of opportunity for Reddit is more competitive short-form video. Yes, they do have short-form video, but introducing vertical formats and optimizing for autoplay would make that format a lot more viable for advertisers (this is kind of in the “table stakes” category).

11. Put ads where high-intent Reddit research happens

Reddit Answers was integrated into the broader Reddit search experience in May 2026. Reddit Answers ads in high-intent searches and recommendation questions, with clear sponsorship labeling and strict relevance requirements, would give advertisers another way to reach users close to the purchase decision.

12. Let advertisers learn from past campaigns

The last big item on my creative list is an ad library that expands to show historical ads, much like Meta’s, where you can see both paused and active ads. That kind of archival reference would be super helpful to have on the back end.

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Reddit could earn more of the ad budget

If it’s not obvious, Reddit has taken some significant strides forward over the last few years, to the point where it can be surprising when it hasn’t checked some of the more basic boxes.

These requests shouldn’t be considered pipe dreams, either. The above list was compiled from situations where my team and I have butted up against limits when running real Reddit campaigns.

Given the way AI search engines have eaten into clicks and made awareness more of a paid media play, and given Google’s heavy-handed move away from control and toward mass automation, we’re very willing to divert budget to Reddit if we can make a solid business case for it. 

Reddit’s unique community and research signals would be powerful if the platform figured out how to turn them into targetable audiences using ad formats that enable real conversations throughout the buying journey.

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DMCA as a weapon: How to fight fraudulent takedown claims

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DMCA as a weapon: How to fight fraudulent takedown claims

Introduced in 1998, the Digital Millennium Copyright Act (DMCA) was designed to solve a specific problem: protecting creators from digital piracy while granting online platforms a “safe harbor” from liability. 

Under Section 512, search engines and host providers avoid expensive lawsuits as long as they act swiftly to remove content when a copyright holder flags an infringement.

That “act swiftly” requirement creates an unintended vulnerability. Because major platforms rely on automated processing to handle millions of removal requests every month, bad actors can trigger automatic deindexing without human review.

What was designed as a shield for intellectual property is now a weapon for corporate censorship, reputation management, and competitive sabotage.

A real-world example of DMCA abuse

In March, a clear demonstration of DMCA abuse played out in full public view. Investigative reporters at Press Gazette published a story examining how a digital media firm, Clickout Media, allegedly acquired established news domains to deploy AI-generated gambling content, a tactic known in SEO circles as site reputation abuse. 

Shortly after, Search Engine Land published a follow-up report detailing the findings.

Within 48 hours, both articles vanished from Google search results worldwide.

The weaponization cycle

An entity identifying itself as “US Webspam” filed a copyright complaint alleging that Search Engine Land had copied its material word-for-word, including proprietary images.

The claim was fraudulent:

  • Zero image match: The Search Engine Land article contained no images whatsoever.
  • No direct outreach: The filing claimed “multiple good-faith efforts” had been made to resolve the dispute, yet no communication was ever sent to the editorial team.
  • Fabricated source: The complainant pointed to irrelevant third-party domains as the “original source” of the reporting.

Despite these clear discrepancies, Google’s automated systems processed the request and deindexed the article.

It took public pushback from search industry analysts, widespread media attention, and a formal counter-notice before Google reinstated both Search Engine Land and Press Gazette in the search index several days later.

If an established publication with high domain authority can have its coverage muted overnight, individual creators, niche blogs, and small businesses face an even tougher challenge.

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The mechanics of bad-faith DMCA takedowns

Understanding why weaponized takedowns succeed requires looking at the incentives of online platforms.

Under U.S. copyright law, platforms like Google, Cloudflare, and major web hosts remain protected from copyright liability only if they act “expeditiously to remove, or disable access to” material claimed to be infringing.

Because taking down a page carries virtually zero legal risk for the platform, while ignoring a notice risks a lawsuit, platforms prioritize speed over verification.

Key structural flaw: Section 512 places the burden of proof on the accused rather than the claimant. The platform shoots first and asks questions later.

Malicious actors exploit this asymmetry using three primary techniques:

  • Scraper-and-backdate schemes: A bad actor scrapes your original article, pastes it onto a disposable site, alters the metadata or timestamp to make it appear published earlier, and files a DMCA claim alleging you stole their work.
  • Fabricated entities: Attackers submit takedown claims under fake organization names, such as “US Webspam,” or impersonate third-party blogs to hide their true identity.
  • Reputation suppression: Individuals or brands facing negative press file dubious claims against investigative pieces, product reviews, or customer complaints to suppress damaging search results during high-impact windows.

5 steps to take when your content is unfairly DMCA’d

Discovering that your URL has been de-indexed or pulled down by your host can be alarming. Following a structured procedure helps ensure your content is restored efficiently.

1. Identify and inspect the notice

When Google removes a URL due to a DMCA claim, you’ll receive a notification in Google Search Console under Security & Manual Actions, along with an email detailing the notice.

Locate the exact complaint in the Lumen Database (lumendatabase.org), a public repository that archives legal requests to remove web content. Examine the filing carefully:

  • Who is listed as the copyright owner?
  • What specific URL do they claim is the original source?
  • What specific text or media is alleged to be copied?

2. Gather incontrovertible proof of prior ownership

Before filing your response, assemble evidence establishing that your content predates the claimant’s alleged original version:

  • CMS timestamp logs: Export full publish logs from WordPress, Ghost, or your custom database showing creation dates and edit histories.
  • Wayback Machine archives: Pull historical snapshots from the Internet Archive showing your page live before the claimant’s alleged publication date.
  • RSS feed records: Retrieve original RSS distribution records, which index publication times down to the second.
  • Git commit history: If your site uses static site generators or version control, export commit hashes showing when the file was created.

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3. File a formal DMCA counter-notice

To force the platform to restore your content, you must file a formal DMCA counter-notification. Under statutory guidelines, a counter-notice must include:

  • Identification of the material that was removed and its original location.
  • A statement under penalty of perjury that you have a good-faith belief the material was removed as a result of mistake or misidentification.
  • Your full name, physical address, phone number, and email address.
  • Consent to the jurisdiction of the federal district court for your judicial district (or the district where your host is located if outside the U.S.).
  • Your physical or electronic signature.

4. Understand the statutory waiting period

Once the platform receives your valid counter-notice, the law requires it to forward it to the original claimant. The claimant then has 10 to 14 business days to submit proof that they’ve filed a formal lawsuit seeking a court order to restrain you from publishing the content.

If the claimant fails to produce evidence of a court filing within that 10- to 14-day window, the platform is legally obligated to restore your content to its index or server.

5. Escalate publicly and pursue Section 512(f) remedies

In high-stakes situations, such as time-sensitive reporting or ecommerce launch campaigns, waiting two full weeks can cause serious financial damage.

If your case involves an obvious fraudulent claim (such as alleging image theft on an all-text page), publicize the details on social platforms like X and LinkedIn while tagging the official search representative handles. Search engine teams do occasionally fast-track obvious manual reviews when blatant system gaming is exposed publicly.

Section 512(f) of the DMCA explicitly holds that any person who knowingly materially misrepresents that material is infringing shall be liable for damages, including costs and attorneys’ fees incurred by the alleged infringer.

While litigation takes time, sending a formal litigation hold letter to a bad actor who used a real legal identity can prompt a swift withdrawal of their claim.

Proactive steps to safeguard your intellectual property

While you can’t stop an anonymous actor from filing a fraudulent notice, proactive site hygiene makes resolving disputes far simpler:

  • Auto-archive upon publication: Set up an automated webhook or API connection to archive new articles to the Internet Archive immediately upon publishing.
  • Maintain clear byline and copyright notices: Ensure every article includes schema structured data (NewsArticle or Article schema) complete with datePublished, dateModified, and author metadata.
  • Monitor Search Console alerts: Ensure Google Search Console notification emails route to a primary inbox that gets checked daily. Missing a notice delays your counter-filing window.
  • Keep original source files: Store raw video files, unedited photography, audio recordings, and rough draft revisions safely off-site to demonstrate your creation process.

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Defending your content against fraudulent takedowns

The Search Engine Land incident highlights a structural issue in modern web governance: automated copyright tools built to shield giant platforms can easily be turned against legitimate creators.

Until policy revisions require stronger identity verification or impose stiffer penalties for false claims, bad actors will continue to misuse takedown requests to silence competitors and critics. By understanding your rights, documenting your publishing pipeline, and acting quickly with formal counter-notifications, you can defend your work and restore your digital presence.

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