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Agentic AI will give DOOH a central place at the planning table

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By Laure Malergue

In this article, Laure Malergue of Displayce, explains how agentic AI can bring DOOH into planning earlier, make recommendations easier to defend and connect data, activation and learnings. She explores what makes a strong DOOH agent, why specialist data and workflows matter and how this approach could help the media secure a more influential role in media strategies from the very first planning conversation.

Walk along the Croisette during Cannes Lions, and advertising is everywhere in its most physical form: posters, digital screens, branded spaces and large outdoor moments. This year, another presence was just as visible: AI agents.

For the past two years, most of the AI conversation in advertising has focused on production. This year’s adtech announcements mark a shift from AI-assisted tools towards agentic systems able to make, coordinate and execute advertising decisions.

That shift raises a more important question for the industry: Will AI agents make media decisions better?

Media planning has always been a discipline of choices: Which audience matters most? Which context will make the message stronger? Which channel should enter the plan earlier? Which budget split is easiest to defend? These choices shape the campaign long before it goes live.

For digital out-of-home (DOOH), this could be a turning point.

DOOH is invited too late to the party

DOOH has many of the qualities brands are looking for today: real-world and brand safe visibility, public attention, contextual relevance with the ability to adapt to location, weather, time of day, audience flows and live events. Yet, it still lacks discoverability within the media mix.

Too often, it enters the media plan late, once the brief, strategy and main budget choices have already been shaped. DOOH is then considered at the execution stage, although its strongest value could have influenced the plan earlier.

The challenge is practical. DOOH requires strong knowledge of audience data, mobility patterns, local specificities, screen environments, formats, availability, pricing, context, timing and measurement. The value is clear, but turning these parameters into a confident recommendation takes time.

Programmatic DOOH has solved a large part of the activation challenge by automating the buying process. The next challenge sits earlier, when a media planner decides whether DOOH deserves a place at the table, how much budget it should receive and why one scenario is stronger than another.

Making DOOH easier to recommend

This is where agentic AI can change the role of DOOH in the media mix. The strongest agents will be judged by the quality of the decisions they support: can they explain why one scenario is stronger than another, help a planner defend DOOH in a wider media strategy and turn campaign results into learnings for the next brief?

This is the concept Displayce is bringing to the market with Agentic DOOH: a way to connect the brief, recommendation, activation and learning loop, so DOOH can influence media thinking before the plan is locked.

This conviction comes from more than a decade building programmatic DOOH technology. Our goal is now to make DOOH easier to recommend, with specialist intelligence available inside the environments where agencies and brands are already building media plans.

This is why Displayce’s agents are available via Model Context Protocol (MCP). The MCP allows AI applications such as ChatGPT or Claude to connect with external data sources and tools. For agencies building their own agentic workspaces, this means DOOH intelligence can be accessed where planners already work. For Displayce, MCP is a way to bring specialist DOOH expertise into the existing media ecosystem, with more openness and interoperability.

What makes a good agent for DOOH?

A generic AI model can understand language, but it does not understand media by itself. For DOOH, a good agent needs to be built on a strong data ecosystem, expert workflows and simulation algorithms. This is the foundation behind Displayce’s agents.

The data ecosystem gives the agent access to the signals that matter: audience data, mobility patterns, inventory context, screen environments, local context and historical campaign performance.

The expert workflow helps the agent understand how DOOH planning actually works: the objective, the constraints, context, timing and budget, and the level of explanation a planner needs to defend a recommendation.

The simulation algorithm allows the agent to compare scenarios, test assumptions and understand why a city, venue type, screen, audience group, daypart or context is relevant.

Without these foundations, an agent can create a recommendation that looks convincing but has limited media value. With them, it can support stronger, clearer and more transparent DOOH decisions.

Make DOOH impossible to ignore from the very first media conversation

By bringing DOOH expertise into planning workflows earlier, Agentic DOOH can change how the medium is considered by agencies, brands and media owners.

For agencies, this means less time assembling data and more time shaping the argument. For brands, it means clearer recommendations and greater confidence in DOOH investment. For media owners, it means making local knowledge and premium inventory visible while the plan is still being shaped.

Human judgment remains central. Planners still decide what is right for the brand, the role of agents is to give teams better scenarios, stronger explanations and more time to think.

Agentic DOOH should be measured by one question: Does it help the medium earn a stronger place in the media plan? If the answer is yes, AI agents will help bring DOOH further upstream in the media decision-making process, at the moment when budgets are shaped, strategies are built, and channel choices are made.

 

By Laure Malergue

Sourced from The Drum

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How ChatGPT ads are forcing brands to rethink GEO and paid strategy

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These tips can support your workflow, save time and make the AI assistant’s responses much better

Claude has become one of the AI tools I use most often, whether I’m brainstorming, planning something, vibe coding, researching a topic or simply trying to make sense of a complicated question. But using an AI chatbot every day doesn’t necessarily mean you’re using it well

In fact, some of the habits that feel like they should make Claude better can have the opposite effect.

That’s what caught my attention when I came across a list of 27 Claude tips from AI consultant Ruben Hassid, who says he’s spent more than 1,800 hours using Anthropic’s chatbot.

Some of his advice goes against the way many of us have been taught to use AI. Keep everything organized in Projects? Maybe not. Keep correcting Claude until it understands what you want? That could actually make things worse. Spend 10 minutes crafting the perfect prompt? There may be a better approach.

Not every tip will make sense for every Claude user, and some of Hassid’s recommendations are based on his own experience rather than hard-and-fast rules. But several are worth trying if you use Claude regularly.

Here are five Claude habits worth breaking — and what to try instead.

1. Stop correcting Claude over and over

We’ve all had this conversation with an AI chatbot. You ask Claude for something. It gets it wrong and then you go back and forth trying to get the response you’re actually looking for — all while wasting your tokens in the meantime.

Even when you explain the problem in even more detail or add another layer of clarification, before long, you’re six messages deep trying to rescue an answer that wasn’t particularly good to begin with.

Hassid recommends doing something much simpler: go back and edit the original prompt. This is a feature that a lot of users overlook but it’s one of the best ways to avoid correcting every wrong answer, which in turn, keeps adding to the conversation.

That’s because every correction you add becomes part of the conversation Claude is working from. Instead of giving the model one clear instruction, you can end up with a growing trail of bad outputs, corrections and exceptions.

Editing the original prompt gives Claude another shot with cleaner instructions.

For example, imagine you asked: Plan a three-day trip to Boston.

Claude gives you an itinerary packed with museums, historical sites and early mornings. But what you really wanted was a relaxed weekend centered around food and neighbourhoods.

You could spend several messages correcting the itinerary.

Or you could edit the original: Plan a relaxed three-day trip to Boston centered around great food and interesting neighbourhoods. Include no more than one museum, avoid early mornings and leave plenty of unplanned time.

Same request. Much better context.

Try it: If Claude completely misses the mark, resist the urge to argue with it. Edit your previous prompt and regenerate the answer instead.

2. Stop keeping every conversation alive forever

An individual typing on a laptop, focusing on the hands and keyboard in an indoor setting.

(Image credit: Pexels / Eren Li)

 

This one is incredibly easy to do. Once Claude understands what you’re working on, abandoning that conversation can feel wasteful. So you keep going…and going!

Eventually the chat contains previous questions, rejected ideas, unrelated tangents, corrections and instructions that stopped being relevant 30 messages ago.

Hassid recommends starting fresh more often, arguing that very long conversations can eventually make Claude less effective.

There isn’t a magic number of messages where Claude suddenly becomes worse, and Claude’s context window is designed to handle a significant amount of information. But context isn’t the same thing as useful context.

A model having access to something doesn’t necessarily mean you want that information influencing its next response.

Imagine using the same Claude conversation to plan a vacation for weeks. You’ve discussed five hotels, changed the dates twice, ruled out three destinations and completely changed your budget.

Claude may technically have all that information available, but you’re now asking it to distinguish between what you wanted two weeks ago and what you want today. Sometimes the clean slate is the advantage.

Try it: When a conversation starts feeling cluttered, ask Claude to summarize the important information and decisions you’ve made. Paste that summary into a fresh chat and continue from there.

3. Stop obsessing over the perfect prompt

The internet has spent the past few years convincing us that getting great AI results requires elaborate prompts. A few minutes on X or Instagram and you’ll be swamped with plenty of prompts.

But Hassid makes a compelling case for doing something considerably less polished: brain dumping.

Instead of spending several minutes turning an idea into the perfect prompt, simply tell Claude everything you’re thinking.

This works particularly well with voice input because we naturally provide more context when we’re talking. We mention what we’re trying to accomplish, what we’ve already tried, what we don’t like and the half-formed thoughts we might remove if we were carefully typing a prompt.

For example, instead of: Create a weekly meal plan for a family of four.

Try the prompt: I need dinners for the next five days. I don’t want anything that takes more than about 30 minutes, we’re trying to spend less on takeout, one person hates fish, I already have chicken and pasta in the house and Wednesday is going to be really busy, so that meal needs to be ridiculously easy. Help me figure this out.

The second prompt isn’t perfect, but it’s packed with useful information.

Try it: Open Claude and dictate your request as though you’re explaining the problem to a friend. Don’t organize it first. Let Claude organize it for you.

4. Stop telling Claude only what you want

Man looking confused whilst sitting in front of a laptop

(Image credit: The Motley Fool)

Quite often AI users will prompt an assistant with “Make this better.” “Give me something more interesting.” “Make this easier.” “Be more creative.”

And while they will probably give you answers, these instructions are incredibly subjective. Claude has to guess what “better” or “interesting” means to you.

Hassid recommends giving the model negative examples — showing Claude what you don’t want. Say you’re trying to come up with ideas for a 10-year-old’s birthday party.

Claude suggests a trampoline park, bowling, laser tag and an arcade.

Instead of responding: Give me more creative ideas.

Try the prompt: I don’t want trampoline parks, bowling, arcades, laser tag or other typical birthday-party venues. I’m looking for something the kids probably haven’t done at another birthday party this year.

Suddenly, “creative” has boundaries and it’s far more useful to Claude. The same technique works for recommendations, travel plans, recipes, gift ideas, schedules and almost anything else where personal taste matters.

Try it: When Claude gives you suggestions you dislike, tell it specifically what those options have in common and ask it to avoid that entire category.

5. Stop putting everything into Projects

Projects are one of Claude’s most useful features. They let you keep related chats, instructions and reference material together so you don’t have to repeatedly explain what you’re working on.

But that doesn’t mean every task belongs inside one. Hassid argues that fresh conversations can sometimes be better for creative work because accumulated context can steer Claude toward ideas and patterns you’ve already explored.

I’d treat this as a rule of thumb not something universal for Claude. Projects can be enormously useful when the model genuinely needs background information.

The question is whether that background is helping with the task you’re doing right now.

If you’re using Claude to help plan a major home renovation, for example, keeping your measurements, budget, preferences and previous decisions in one Project makes sense.

But if you suddenly want Claude to give you completely unexpected ideas for what to do with an empty room, you might get more variety by asking in a fresh chat without all those previous assumptions.

Otherwise, you risk asking Claude to surprise you while simultaneously surrounding it with everything you’ve already considered.

Try it: Use Projects when Claude needs context. Try a fresh chat when you want novelty. You can even give the same prompt to both and compare the results.

The takeaway

Sometimes the best thing you can give Claude is a clearer problem. So the next time Claude isn’t giving you what you want, don’t automatically add another paragraph of instructions. Try editing the prompt, start a new chat or tell it what you don’t want.

You may just find Claude understands you better when you give it less to untangle.

Feature image credit: Anthropic/Claude

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This Is The Easiest Way To Understand Your Audience On Social Media

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By Lyn Wildwood

Do you ever wish you had a clearer picture of your audience on social media so you could create better content for them? Or better yet, just ask them directly what they want to see?

Most people think of social media polls as a way to boost engagement. And they are. But that’s only part of the story.

Used properly, polls and surveys give you something far more valuable. Real insight into what your audience actually cares about.

In this post, you’ll learn how to use social media polls and surveys to understand your audience and create content they actually want.

Let’s get into it.

1. Understand why audience research is important

You might think it’s enough to create any and all content that even remotely covers topics that relate to your niche, but this couldn’t be further from the truth.

Audiences are a lot more complex than that. Your niche likely has several audiences within it. That’s why it’s important for you to tailor your content to your target audience.

This could be members of your niche who are at a certain skill level (beginner, intermediate, advanced or expert) or who are mostly interested in a specific subtopic (“electric guitar” as opposed to the more broad “guitar” niche).

If you’re not sure who your target audience is, a few polls or a survey can help you identify it.

Audience research allows you to you uncover anything you think might help you create better content, including:

  • Subtopics your audience is interested in
  • What they think about certain topics
  • Social media platforms they use
  • When they browse social media
  • Why they browse social media
  • Whether or not they’re satisfied with your content

2. Choose a tool

You can run polls natively on a lot of social media platforms:

  • Instagram – Add polls to stories. It’s under the Stickers menu.*
  • Facebook – Add polls to stories.
  • Twitter (X) – Create poll posts.
  • YouTube – Create poll posts for the Community tab.
  • Bluesky – Not a native feature, but you can create polls with third-party apps.
  • Threads – Add a poll to a post.
  • LinkedIn – Create a poll post.

*You can only add quizzes to reels. Although they allow you to ask your audience a question, they make you designate one option as the correct answer to that question. Polls are opinion based. Therefore, they’re not meant to have a correct answer.

If you want to ask your audience more than one question at a time or get feedback from your TikTok audience, you’re going to need to use a survey.

Here are a few survey tools you can use:

  • ConvertBox – Not technically a survey or poll maker, but it does have a poll-based opt-in form that allows your audience to segment themselves as they join your email list. This is a better option because you can easily capture leads when/if it makes sense to.
  • Google Forms – Free form tool your audience is likely familiar with.
  • Typeform – A simple survey and poll maker. It allows you to create surveys that ask one question per page as well as polls where every option is visible. Comes with templates and plenty of marketing features.
  • SurveyMonkey – Simple survey and poll maker with templates, marketing features and insightful analytics.
  • SurveyPlanet – Simple survey tool that’s also great for creating surveys that show one question at a time. Comes with templates.
  • Quiz and Survey Master – Survey plugin for WordPress.

If you go the survey maker route, you’ll need to promote your survey link.

Here are methods you can use to promote links on social media:

  • Promote it directly in the post body itself. This is not an option on TikTok and Instagram.
  • Add the link as your bio link. This removes your current bio link.
  • Add the link to your link-in-bio page, a simple web page you can add several links to.

Shorby is a suitable tool for the third option. It’s very easy to use.

shorby link card

It is, however, a paid tool.

Alternatively, you could use Viraly. It’s primarily a social media scheduler but it offers a free plan that includes access to their link-in-bio page tool.

Their link-in-bio page tool also happens to be one of the best on the market.

Get started with Viraly for free.

3. Create a poll

Polls are great if you only need to ask your audience one simple question.

A lot of social media polls only allow you to add four options, but you can add unlimited options if you use a dedicated survey or poll maker.

The most important aspect of a poll is the way it only allows your audience to choose one option.

By asking your audience a simple question, giving them up to four options to pick from and only allowing them to pick one of those options, you can really learn a lot about their preferences.

Polls posted as Instagram and Facebook stories expire after 24 hours. This is because Instagram and Facebook stories themselves expire after 24 hours.

Twitter (X) allows you to choose a duration of up to a week. This means your audience has up to a week for the poll to show up in their feeds so they can respond to it.

Try using polls for the following purposes on social media:

  • Opinion – Ask your audience’s opinion about a topic.
    • Example: What is the most overrated electric guitar brand?
  • Insight – Learn more about your audience in general.
    • Example: What is your favourite electric guitar brand?
  • Analytical – Learn more about your audience’s habits.
    • Example: How often do you practice?

4. Create a multiple-choice poll

If you think your audience might have more than one preference, create a multiple-choice poll instead.

Your audience can only select one option when you use native social media polls, so you’ll have to use a survey tool and only add one question to it.

It’s best to use plural language in your question so that your audience knows they can select more than one option. You can also put a short notice in parentheses, such as “(select all that apply).”

In your survey tool, make sure you choose the Checkboxes option, and mark the question as “required.”

Here’s an example in Google Forms:

google forms poll

Use multiple-choice polls for the same purpose as you would a regular poll, but only use them when you want your audience to be able to select more than one option.

Stick with single-choice polls if you want to force your audience to be more decisive. This will give you more accurate data as your audience is likely to be more selective with their answers if they’re only able to choose one.

Once your poll is complete, add it to your link-in-bio page on Instagram and TikTok or as your bio link on these platforms before you promote it.

5. Create a multiple-choice survey

Surveys are fantastic tools to use to conduct audience research. They allow you to gain more insight into your audience by asking them a series of questions.

Social media content is fleeting, so it’s best if your survey is as well. Try to ask no more than five questions to increase your odds of receiving more completed surveys.

The most important thing is to make sure each question belongs to the same theme. If I ask my audience what their favourite guitar brand is, I shouldn’t also ask which guitarists they think is overrated.

The best part about using surveys is the number of question types you’re able to add to your survey. Specifically, the text-based question types where your audience can enter a short or long answer.

This is a fantastic option to include in case you’re worried that you forgot to include something as an option.

Another useful aspect about surveys are the conditional logic features they unlock depending on which survey tool you use.

Conditional logic is a feature that allows you to set up triggers and actions for your survey, or “if this, then that” rules.

For example, if your primary question asks your audience, “what is your favourite guitar brand,” and one of your options is Ibanez, you could ask a follow-up question that only appears if your audience selects the Ibanez option, such as “which guitar models do you own from Ibanez?”

Some survey makers, such as Typeform, have ranking question types that allow your audience to rearrange options based on how they’d rank them.

Overall, surveys are an effective way to expand on a question with additional questions, which ultimately leads to more data for you.

6. Use the data you acquire to optimize your social media marketing strategy

There’s quite a bit you can learn by asking your audience simple questions on social media.

If you’re in the guitar niche, knowing which brands your audience prefers lets you know which brands to focus on for reviews, unboxing content, product demonstrations and tutorials.

If you ask your audience about other social media platforms they use, you’ll know which other platforms you should be creating content for.

Polls and surveys help you align your social media content and overall marketing strategy with what your audience wants to see.

A lot of platforms have analytics you can view. There are even dedicated social media analytics tools out there. Plus, you can get a pretty good idea of your audience’s preferences by conducting keyword research and product research.

But it’s one thing to guess what your audience prefers or wants to see. It’s another thing to have them tell you outright.

Make a list of every piece of data you feel would help you understand your audience a little better. Then, come up with questions and answers that would help you uncover that information.

Final thoughts

When you’re just getting started as a blogger or content creator, there is a lot of guesswork involved.

But once you have an audience, no matter the size, you can start gathering qualitative data.

This is the data that matters most.

It’ll help you take a strategy based on guesswork and turn it into a solid strategy based on nothing but facts and hard data.

By Lyn Wildwood

Sourced from bloggingwizard

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The Click Is No Longer The Strategy: How Brands Win In A Zero-Click World

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By Esade Business & Law School

For more than two decades, digital marketing was built around one objective: get the click. Search ads pushed users to landing pages. SEO turned visibility into traffic. Social posts pointed people toward blogs, forms, product pages and downloads. The click became the visible proof that attention had turned into intent. But that logic is breaking.

Consumers now discover, evaluate and remember brands without necessarily visiting their websites. Google is moving from links toward answers. Social platforms reward content that keeps users inside the feed. Artificial Intelligence (AI) interfaces are training people to expect synthesis, not ten tabs of research. The result is a new marketing reality: influence often happens before the click, outside the website and beyond traditional attribution. This is the rise of zero-click marketing.

Zero-click marketing is not about abandoning websites, SEO or performance marketing. It is about recognizing that the first meaningful exposure to a brand increasingly happens inside a search result, short video, comment thread, community conversation or AI-generated answer. In that environment, the most valuable marketing is not always the content that gets clicked. Sometimes, it is the content that gets remembered.

Search is becoming an answer engine

Google describes AI Overviews as AI-generated snapshots that provide key information about a topic or question, with links for users who want to explore further. From the user’s perspective, that can make search faster. From a marketer’s perspective, it changes the economics of visibility. A person may get the answer, form an opinion and move on without visiting the original source.

The behavioral evidence is important. Pew Research Center analyzed U.S. Google users in March 2025 and found that when an AI summary appeared, users clicked a traditional search result in only 8% of visits, compared with 15% when no AI summary appeared. Links inside the AI summary itself were clicked in about 1% of visits.

This does not mean Google and the AI have killed traffic. It does mean marketers should stop treating traffic as the only evidence of value. Reuters reported in July 2025 that independent publishers filed an EU antitrust complaint against Google’s AI Overviews, arguing that the feature diverts traffic and revenue. Google responded by explaining that AI Overviews create discovery opportunities and send billions of clicks to websites. The disagreement is revealing: zero-click behavior is now a commercial, regulatory and strategic issue.

For brands, the question is no longer only, “How do we rank?” It is also, “Are we part of the answer?” Companies have to optimize not only for clicks, but for authority signals: clear explanations, original research, expert authorship, structured content, credible citations, distinctive points of view and brand mentions across the web.

Zero-Click Marketing is not posting more content

The most common misunderstanding is that zero-click marketing means publishing more on social media. It does not.

Zero-click marketing is the discipline of creating value inside the environment where attention already exists. A weak version says, “Here is a teaser. Click to learn more.” A strong version says, “Here is the insight. You can use it now.”

A LinkedIn post that explains a framework can build authority without requiring a blog visit. A YouTube video that solves a technical problem can shape preference before a demo request. A TikTok that demonstrates a product benefit can create cultural relevance without sending users to a website. The old model was built around traffic capture. The new model is built around trust creation.

The best “product story” may not need a landing page

One of the strongest consumer examples is Stanley. In 2023, a TikTok user posted a video showing her burned-out car after a fire. Inside the car, her Stanley tumbler had apparently survived, still containing ice. The product proof was visual, immediate, and native to the platform. Stanley’s president then responded publicly and offered to replace her car, turning an organic customer story into a brand-defining moment.

The lesson is not simply “go viral.” That is too superficial. The real lesson is that the strongest product message did not come from an ad, a landing page, or a product specification sheet. It came from a customer story, seen inside a social platform, amplified by a fast executive response, and understood without a click.

Stanley won because the audience did not need to be redirected to understand the value proposition. Durability was demonstrated in the feed.

That is zero-click marketing at its best: product proof, social credibility, and brand response compressed into a single public moment.

In social, the brand itself must become content

Duolingo offers a different example. Its green owl mascot became a social media character, not just a logo. The brand’s TikTok presence, humor and cultural fluency turned language learning into entertainment. TikTok for Business documented a Duolingo campaign that generated more than 90 million video views and a 1.400% increase in new followers.

The point is not that every brand should behave like Duolingo. Most should not. The point is that Duolingo understood something many companies still resist: on social platforms, the brand itself must become content. The audience did not need to click to a landing page to understand Duolingo’s personality. The download may come later, but preference is often built much earlier.

The B2B implication: buyers learn before they convert

Zero-click marketing is not only for consumer brands. In many ways, it may be even more important in B2B.

Business buyers often research silently. They read posts, listen to podcasts, attend webinars, follow experts, ask peers and evaluate companies long before they fill out a form. Much of that influence is invisible to attribution software.

This is where executive thought leadership becomes commercially relevant. A strong LinkedIn post, industry report, podcast appearance or expert commentary can shape how a buyer understands a problem before the buyer has entered the sales funnel. For B2B brands, the website may still convert the buyer, but it may not be where the buyer first learns to trust you.

What leaders should measure now

The biggest objection to zero-click marketing is obvious: how do you measure it? The answer is not to abandon measurement. It is to measure influence more intelligently. Sessions, leads, cost per acquisition or conversion rate still matter. But they should be complemented by signals that capture demand creation before the click: brand search growth, direct traffic, share of search, social saves and shares, community mentions, podcast and video engagement, newsletter growth, sales call references, executive profile visibility and pipeline influenced by content exposure.

The key distinction is between attribution and influence. Attribution asks, “Which click caused the conversion?” Influence asks, “What made the buyer trust us before the conversion?” In a zero-click world, influence often happens first.

The future is not Clickless— it’s Click-Optional

Zero-click marketing does not mean the click is dead. High-intent customers will still visit websites, compare products, download reports, request demos, apply to programs and make purchases.

But the click is increasingly a later-stage behavior. By the time it happens, much of the buyer’s perception may already be formed.

The companies that win the next era of digital marketing will not be the ones that obsess only over traffic. They will be the ones that create value where attention already exists, build trust before capture and become memorable before the customer is ready to act.

The click still matters. It is just no longer the beginning of the relationship.

Feature image credit: Getty

By Esade Business & Law School

Find Esade Business & Law School on X.

Sourced from Forbes

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TikTok says AI-generated spam ‘crowds out original creators’ — so it’s teaching users how to spot AI

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TikTok is the latest platform to push back against AI slop

If you’re getting tired of AI slop on social media, you’re not alone. Even TikTok, which has spent the last couple of years rolling out AI creation tools, is now testing new ways to detect AI-generated spam and teaching users how to recognize AI content.

TikTok says it is testing improved detection systems to target accounts dedicated to posting AI-generated spam that “crowds out original creators”, and it is also creating a new guide that helps its users use AI tools responsibly. TikTok is launching a new in-app hub within the next few weeks where you can learn practical skills for spotting AI-generated content when you search for AI-related terms.

TikTok app in the iPhone App Store

(Image credit: Future)

Is it really a moral stance?

We spoke to Donatas Smailys — CEO of Billo, the largest UGC creator marketing platform in the US — about the new tool. His take is that TikTok is fighting AI content because it doesn’t perform, and that hurts TikTok’s ad business too.

“It would be naïve to read this as TikTok taking a moral stance. The platforms can see in their own data what audiences respond to, and they’re quietly rebuilding their rules around real people.”

It strikes me as slightly ironic that TikTok, which has spent the last couple of years pushing AI creation tools, is now simultaneously educating people to recognize AI content and testing systems to suppress AI spam.

If TikTok’s own data suggests AI-generated spam is harming engagement or advertising performance, then it may be the saving grace for the rest of us who are tired of AI slop ruining the experience of social media. Frankly, at this point I’ll take anything that reduces the amount of AI videos that get served to me, for whatever reason.

What this means for the future

The wider issue here is that if TikTok is beginning to treat low-quality AI spam as a platform problem, then it should raise some red flags for advertisers who heavily rely on synthetic influencers and AI creators. If low-quality AI spam was improving the platform, TikTok would have little incentive to invest in detecting and suppressing it.

TikTok actually has pretty stringent rules on AI content on its platform already. It’s quite common to see the label “Contains AI-generated content” on TikTok videos.

It seems that regulators are moving in the same direction. “New York now requires disclosure of synthetic performers in ads”, says Smailys “with penalties for those who don’t comply. And my guess is that more states will follow. But the loss of trust is an even bigger risk here. Once your audience feels tricked, no disclosure label wins them back.”

While the rise of AI slop seems unstoppable at the moment, I wonder whether we’ll eventually look back at 2026 as the year platforms realized that flooding people’s feeds with AI-generated content wasn’t sustainable and that what users really wanted all along was more real people.

Feature image credit: Shutterstock / Good Ideas

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Graham is the Senior Editor for AI at TechRadar. With over 25 years of experience in both online and print journalism, Graham has worked for various market-leading tech brands including Computeractive, PC Pro, iMore, MacFormat, Mac|Life, Maximum PC, and more. He specializes in reporting on everything to do with AI and has appeared on BBC TV shows like BBC One Breakfast and on Radio 4 commenting on the latest trends in tech. Graham has an honours degree in Computer Science and spends his spare time podcasting and blogging.

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The Economist shades AI in sharp new billboard ads

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Stripped-back visuals become a powerful storytelling tool.

The Economist has launched a powerful new billboard campaign challenging the rise of AI in media. Wonderfully simple in its execution, the back-to-basics campaign is a prime example of how stripped-back visuals can be a powerful storytelling tool.

Paired with ingenious copy, the striking billboard ads demonstrate the enduring value of thoughtful copywriting in the branding sphere. In a world of loud, social-led design, The Economist’s latest campaign is a refreshing respite from the noise of the branding sphere.

Cocogun's campaign for The Economist(Image credit: The Economist/Cocogun)

Made in collaboration with independent creative agency Cocogun, The Economist’s latest campaign features minimalist red billboards with snappy copy such as “Think outside the bot” and “actual intelligence”. Unmistakably on brand thanks to the stripped-back colour palette and signature serif font, the campaign radiates authority and confidence without feeling sanctimonious.

Cocogun's campaign for The Economist(Image credit: The Economist/Cocogun)

The OOH campaign will appear around the World Trade Centre, key New York City and Chicago subway stations, alongside UK placements in Leicester Square, Carnaby Street and Canary Wharf.

On the project, Cocogun creative partner, Ant Melder, says: “To follow in the wake of some of the greatest advertising the world has ever seen is no small task. I like to think/am utterly terrified by the idea that a certain Mr Abbott is somewhere in the ether looking down on everything we do with a judicious, firm yet encouraging eye. We’re beyond proud to have been entrusted with this, and look forward to continued collaboration.”

Cocogun's campaign for The Economist(Image credit: The Economist/Cocogun)

For more advertising inspiration, check out Polaroid’s refreshing anti-AI campaign or take a look at McDonald’s painfully relatable new billboard ads.

Feature image credit: The Economist/Cocogun

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Natalie Fear is Creative Bloq’s staff writer. With an eye for trending topics and a passion for internet culture, she brings you the latest in art and design news. Natalie also runs Creative Bloq’s 5 Questions series, spotlighting diverse talent across the creative industries. Outside of work, she loves all things literature and music (although she’s partial to a spot of TikTok brain rot).

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The Fastest Way To Get In Front Of A New Audience (No Ads Needed)

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By Lyn Wildwood

Want to grow your social media audience without posting more content?

Collaborating with other creators might be the fastest way to do it.

Most people avoid it because they think it’s awkward, complicated, or only for bigger accounts.

But here’s the truth:

A lot of creators are actively looking for people to collaborate with right now, especially within their niche or adjacent ones.

In this post, you’ll learn how to master social media collaborations and turn them into real audience growth.

Let’s get into it.

What is a social media collaboration?

A social media collaboration, also known as a collab, refers to content a social media creator makes with another creator.

It’s an engagement strategy creators have been using long before the internet was even invented. Back in the old days, TV shows, musical artists and even film franchises would collaborate with one another by appearing in each other’s projects.

In modern times, collaborations are used to combine social media audiences on one or more videos.

It can be a huge growth strategy for both creators but particularly for the collaborator with fewer subscribers.

What are the benefits of collaborating with other creators?

Like I said, engagement is the biggest benefit of collaborating with other creators, especially if the creator you collaborate with has a larger audience.

Most social media collaborations have at least two videos: one that’s posted on your account and another that’s posted on your collaborator’s account.

By appearing in one of their videos, your brand awareness skyrockets.

If they put your username in the caption so that it’s clickable, or use the collaboration feature available on a platform like Instagram, their audience will be able to click through to your profile very easily to follow you.

If their audience likes your personality enough, they may even watch and like a few of your videos.

Working with another creator is also an effective way to revamp a dead timeline.

Maybe your videos were popular at one point, but now you struggle to receive a few thousand likes and views. Working with the right creator might just be the thing your account needs.

Combining your content creation budget with another creator’s budget can also help the both of you film a higher-quality, more ambitious video.

Maybe there’s somewhere in the world you want to explore. Maybe you have a project you want to build.

You can easily cover these expenses by combining your marketing budget with another’s.

Social media collaborations are also abundant sources of inspiration. Some of your best ideas will come from the collaborative content you make.

Switching up filming processes and editing styles can also do a lot to reset your brain and keep you from using the same process over and over again with little to no improvement.

A collaboration may even open doors for you.

Maybe the creator you collaborate with is friends with quite a few other creators. Maybe they have important friends in the industry.

Finally, social media collaborations also help you put the “social” back in social media. Many social media creators work alone, and it can get pretty isolating as they spend all of their time filming and editing videos while they grow their followings.

All of these are considerations to make when you’re deciding whether you want to collaborate with another creator.

Examples of social media collaborations

KallMeKris and CelinaSpookyBoo

KallMeKris and CelinaSpookyBoo are two very popular TikTok creators.

KallMeKris has 50.6 million followers and 2.4 billion likes on the platform while CelinaSpookyBoo has 28.6 million followers and 1.2 billion likes.

The two are friends and are, therefore, able to collaborate with one another quite casually.

One of their most popular collaborations included a Try Not to Cringe challenge that earned 54.2 million views, 8.3 million likes, 55,000 comments, 929,900 favourites and 409,200 shares.

It was a simple yet effective collaboration.

Peter Hollens and Whitney Avalon

Peter Hollens is a YouTuber who creates acapella covers for popular songs and musicals.

He often collaborates with other YouTubers. In fact, his most popular video is a collab.

It’s a medley he created of Disney villain songs with fellow YouTuber Whitney Avalon, who’s known for creating the Princess Rap Battle series on YouTube.

Peter has 3.29 million subscribers on YouTube while Whitney has 2.04 million.

Their collaboration, published in June of 2017, has received over 43.7 million views on YouTube.

Alex and Jon and Kat

Alex and Jon are a married couple who make content together, and they often make content with friend and fellow TikTok creator Kat.

Alex and Jon have 2.6 million followers and 210 million likes while Kat has 10.4 million followers and 678.8 million likes.

One of their most popular collabs is a video in which Alex blames Jon’s hispanic “cousin” Kat for getting her a bit tipsy off tequila at Christmas.

This particular collab earned 4.6 million views, 653,900 likes, 1,770 comments, 8,435 favourites and 17,700 shares.

How to find other creators to collaborate with

Create a list of creators you want to collaborate with

This will be your master list.

You can add dream collabs to this list, but know that you should probably stick with creators who are closer to you in follower count.

You should probably stick to creators in your niche and creators in adjacent niches as well to ensure your audiences don’t clash.

Pick creators from every social media platform you have a presence on.

Then, organize your master list in a few different ways. First, separate everyone by niche. Then, arrange those niche groups by follower count.

Focus on creators who have fewer followers, the same followers or a little more followers than you. However, creators with less than 100,000 followers may not receive as many direct messages as you think, so don’t be afraid to reach out to them as well.

You should also consider each creator’s personality and how well you think you’d get along with them.

Choose a minimum of three creators to contact initially. Just be mindful that each creator you reach out to could potentially say yes.

Come up with unique ideas for each creator

Like I said, there’s a potential for each creator you contact to say yes to your collab request.

To avoid creating the same type of content with every creator you collab with (even though this is a valid social media strategy many creators use), come up with unique ideas to pitch to each creator.

The ideas should incorporate their content style. You should also come up with at least one idea for your account and one for theirs so you can each have the collab on your respective accounts.

Reach out to each creator

This is by far the scariest part of this whole process. So, let’s break down a simple outreach template:

“Hi [creator’s name],

I’m [insert the name you want the creator to address you as, usually your first name]. I run [account name], a [channel/page] that covers [your niche as well as topics that you cover].

I’m reaching out in hopes that you’d like to collab with me on a couple of videos. I noticed your [channel/page] covers [niche/topic], which is closely related to my own channels’ niche, so I think our audiences would get along pretty well.

I have a few content ideas we can get started with if you’re interested:

  • Idea 1
  • Idea 2
  • Idea 3

Let me know what you think!

Thanks,

[your name]”

It’s a simple template, but it does a few things:

  • It humanizes you by introducing yourself as the name your personal friends address you as.
  • It lets the creator know that you’ve done your research on their content.
  • It lets the creator know that you have an idea of what kind of content you two should get started with.

The ideas you propose to the creator should take the creator’s content into consideration. In other words, make sure your ideas align with the creator’s content.

As far as where you should reach out to them at, try DMing them on whatever social media platforms you both have a presence on.

You can also resort to email if they have a dedicated email address for business inquiries.

Planning content with your collaborators

Share ideas

Once you find a creator to collab with, brainstorm ideas with one another, or refine the ones you already came up with.

You can go to lunch if you live in the same area. Otherwise, you’ll need to FaceTime, Zoom, text or stick to DMs to brainstorm content ideas.

Keep it casual

Working with other people isn’t always easy.

Sometimes you have two very different working styles as well as completely different approaches to the way you create social media content.

If this is the case, try to keep the planning stage as casual as possible by keeping it in DMs and planning content that’s as simple as possible to create.

Get technical with a project management app

If you and your collaborator want to create more sophisticated videos, or more than two videos, consider moving things to a project management app.

Unfortunately, there are a lot to pick from including Trello, Google Docs, Notion, Monday, Asana, ClickUp and more.

They all work differently, but they all allow you to break your project down into individual tasks then assign those tasks to you or your collaborator.

Use a file sharing app

Consider sharing each other’s footage with one another by uploading it to a file sharing app, like Dropbox or Google Drive.

This will allow each collaborator to access all of the footage you two shot for your project so you can each work on editing videos separately but collaboratively.

Decide where content will get published

As you get to work on planning, recording and editing your content, determine where each post will get published.

Will you each post a tiktok? Will you share images to Instagram? Will you appear on each other’s podcasts posted to YouTube?

Work all of this out before you start publishing so you can each be prepared for each piece of content’s premiere.

Credit your collaborators

When you publish the video, do not forget to credit your collaborators.

Include your collaborator’s username in the caption at the very least.

Instagram has a dedicated feature for collaborations now which you should definitely take advantage of.

Shoot behind the scenes content

Keep the camera rolling even if you aren’t currently filming a shot for your planned content.

You should also take images regularly throughout the filming process of the collaboration.

This will give you plenty of behind the scenes footage to tease your audience with.

Stay in touch

Once every piece of content you planned gets published and the collab wraps up, ask the creator you worked with if they’d like to stay in touch.

As you see from some of the examples of above, some of the collaborations you do have the potential to spark lifelong friendships.

Plus, if you befriend your collaborators, you’ll always have another creator to collaborate with.

Alternatives to partnering with other creators

Join a digital community

If you’re having trouble partnering with a creator by reaching out to them yourself, consider finding a digital community to join.

Look for forums, Discord servers and Facebook groups in your niche that might have fellow creators you can converse with.

Stitch and duet other creators’ videos

You can also stitch another creator’s videos if you’d like to respond to something they said in their video.

This is a technique many TikTok creators use, including Hank Green who often uses the feature to answer science-related questions.

You can also use the duet feature to react to other creators’ videos.

Instagram has these features as well. They’re called remix and sequence.

Request a podcast interview

Podcasts are an integral part of social media. In fact, most podcasts post clips to YouTube, TikTok and Instagram.

If there are a few podcasts in your niche or related to your niche, consider asking them if they’d be willing to allow you to join an episode for an email.

Final thoughts

Teaming up with other content creators is one of the best ways to grow your audience (and theirs).

If you have existing relationships with other creators, those will usually be a good point to start.

Just remember that collaborations need to be a mutual win-win for both of you.

So stick to collabs with creators that have a similar sized audience at first and then work your way up as your audience grows.

By Lyn Wildwood

Lyn Wildwood is a member of the Blogging Wizard content team and a freelance writer for hire with over a decade of experience in the marketing space. She’s an expert when it comes to blogging and WordPress. She also has a strong background in testing social media software.

Sourced from bloggingwizard

 

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How To Build A Scalable Social Media AI Infrastructure

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By Tanmay Ratnaparkhe

Every few months, a new AI tool lands in a social media manager’s inbox with a promise to “10x your content output.”

In my role building generative AI software for brands, and from working with social teams at companies from lean startups to enterprise brands to improve their AI adoption, I have seen the same pattern repeat when teams adopt these tools.

First, they become excited about the product and start producing content. Then, they hit a wall when engagement plateaus because either the content feels off-brand or the results don’t follow from the increase in volume.

Almost always, these teams have the same structural problem: They are treating AI as a single tool dropped into their workflow rather than thinking about where in the workflow it actually needs to live.

To solve this, social media teams should look at the way they are implementing these tools holistically. Here are three layers to examine to understand what’s going wrong and how to fix it.

Layer 1: Intelligence

​​The first layer is about context.​​​

​Before a single word is generated, your AI stack needs to be doing the analytical work that used to take a human analyst half a day: What conversations is your audience already having? Which content formats are gaining traction on which platforms? What’s the competitive white space your brand can credibly own?

Skipping this step is where most teams go wrong. The most common pattern I’ve seen is teams coming back after a few weeks of heavy AI-assisted posting, frustrated that engagement had flatlined or dropped. They were producing more content than ever, but it wasn’t landing.​

Often, the content was technically fine but pointed in the wrong direction. Nobody had checked what their audience actually wanted to hear, which formats were gaining traction or what angles competitors had already exhausted.

This intelligence layer belongs to AI-powered social listening, trend detection and audience analysis tools. Think of this layer as the briefing room. These tools matter not because they make the AI smarter, but because they make the brief smarter.

Generative AI produces output based entirely on what you feed it. Without real audience signals, it defaults to the most generic version of your prompt. By feeding it live data—what your audience is engaging with this week, which formats are outperforming on which platforms, what your competitors haven’t touched yet— the quality of what comes out can change dramatically. With AI, context changes everything.

​In my experience, teams that skip the intelligence layer end up using generative AI to produce more content faster, but not necessarily better content. Volume without direction is just noise. The intelligence layer turns the question from “What should we post today?” to “What does our audience most need to hear right now, and where?”​​​

Layer 2: Creation

​​Once you have the intelligence, the creation layer is where most teams are already experimenting. According to SurveyMonkey research, the top two use cases for AI in marketing were optimizing and creating content.

But using AI for creation and using it effectively are two very different things.

The teams I’ve seen struggle most are the ones with no documented voice guidelines. They generate content that is technically fine but completely interchangeable. It could have belonged to any brand in their category, and nothing about the content is distinctly theirs. The volume went up but the differentiation went down, and that’s a problem no amount of posting frequency can fix.​

Generic prompts produce generic content. On the other hand, by investing time building what I call a “voice architecture” before they ever generate a single post, teams can make sure the content is unique to their brand.

This isn’t necessarily a technical setup, but a reference system fed into every prompt that includes tone guidelines, examples of best performing posts, audience personas and platform-specific formatting rules, allowing the AI model to be briefed consistently every time it’s used. ​

Layer 3: Optimization

​​The third layer is where most social teams leave significant performance on the table.

AI-assisted optimization means more than A/B testing two headline variations and calling it a day. Instead, it requires feeding performance data back into the intelligence and creation layers continuously and deliberately.

At the end of every 30-day cycle, identify your top performing posts, and not just by likes, but by saves, shares and click-throughs. What did they have in common? Was it the format, the hook, the topic, the posting window? Those answers go back into your voice architecture brief before the next round of content generation.

The single most important metric to understand if your stack is getting smarter: engagement rate trends upward over 60 to 90 days, and time spent editing AI output trends downward.​

The Underlying Point​

For social teams, implementing generative AI correctly means building intelligence and production infrastructure where each layer makes the others more effective.​

In practice, this shift happens in stages. Content production gets faster because the brief is sharper. Engagement trends upward consistently because the content is informed by real audience signals rather than guesswork. And the team’s time shifts: fewer hours producing and editing, more hours on strategy.

The internal sign that tells you’re succeeding is simple: Your team has stopped asking, “What should we post today?” because the intelligence layer is already answering that question.​​

Feature image credit: Getty

By Tanmay Ratnaparkhe

COUNCIL POST | Membership (fee-based)

Tanmay Ratnaparkhe, Co-Founder, Predis.ai, which uses AI to help brands scale ads, ad videos and social content without losing their voice. Read Tanmay Ratnaparkhe’s full executive profile here.

Find Tanmay Ratnaparkhe on LinkedIn. Visit Tanmay’s website.

Sourced from Forbes

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What Makes a Killer Meta Ad, According to Experts

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By Liz Brody

Do you run ads on Meta? Have the results been unpredictable lately? There’s a good reason for that.

Late last year, Meta added an update called Andromeda. It’s a major shift in how ads are delivered. In the past, Meta ads were all about targeting: You refined the audience you wanted to serve, and then hit them with ads. But in Meta’s new system, targeting is automated — and Meta is now watching closely for performance. If your ad doesn’t immediately resonate with people, it’ll get filtered out. As a result, brands need to produce a lot more creative. You’ll win by constantly testing new ideas and comparing them. And these ads must look and feel very different from each other — because if Meta thinks they’re too similar, it won’t test them individually.

What does that look like, and what can you learn from these tests? We put together this case study.

Nove8 makes consumer-facing apps, and relies heavily on digital advertising. “Ninety-five percent of our success is performance marketing,” says cofounder Natalia Shahmetova. It has helped grow the company to $35 million in annual revenue. “We’ve run thousands of tests with different creative, and thanks to Meta algorithms, we know whether the ad is good or not within the first hour of a campaign.”

Shahmetova shared with us the results of some of those tests from Nove8’s dog-training app Woofz and fashion app Stylio. Then we asked the performance marketing agency Pilothouse Digital (which was not involved in making the ads, and could look at them with fresh eyes) to weigh in on why the winners succeeded. By understanding what worked for Nove8, you can improve your ads too.

The first ad shared potty training tips. The second ad spoke more personally to dog owners. “Instead of focusing on the pet’s behaviors with complex guides, we focused on the owner’s emotions, reassuring them that the tough moments are normal and easily overcome,” says Nove8.

The result: The second ad drove a 400% increase in click-through rate (CTR).

WHY IT WORKED: Pilothouse says: The weaker ad makes puppy ownership feel like a lot of work, with overwhelming details (take the puppy out every two to three hours, add a play session, etc.). The winning ad immediately reframes the chaos as containable: “Potty train in 3 days.”

But the real breakthrough is the line: “Regretting bringing a puppy home?” That names the taboo emotion most pet brands refuse to touch. It recognizes that the deeper job to be done here is not really “teach my dog where to pee.” It is instead “help me stop feeling overwhelmed, guilty, and incompetent.” The first ad explains the product, but the second markets relief.

Consumers often search at the symptom layer but buy at the identity layer. In other words, while they type in potty training questions, they are really asking: Is this normal? Did I screw up my life? 

THE BIG LESSON: Stop answering only the problem customers are willing to ask out loud. The strongest performing creative names the private crisis beneath it.

The first ad promised information on “how to dress like a rich woman.” The second was a quiz, asking users what kind of rich woman they dress like. “Most potential customers don’t click through to learn what you offer, so instead of relying on a short call to action to hook them, we demonstrated the expertise Stylio offers directly in the ad,” explains Nove8.

The result: The second ad drove a 20% decrease in customer acquisition cost.

WHY IT WORKED: Pilothouse says: The better ad also succeeds because as soon as a user reads “Old-Money Classic” or “Modern Minimal,” she is sorting herself. Categorization creates powerful psychological buy-in and makes the brand feel like an interpreter of identity. The smartest move is language like a “50+ body,” “skim, not squeeze,” and “nice, but hiding my body”—which proves that the brand understands not just style, but also the user’s lived experience, while helping Meta classify who should receive the ad.

THE BIG LESSON: Stop asking people to click for value you could have demonstrated in-feed.

The first ad promised to stop puppies from biting. The second explained why dogs bite in the first place. “Instead of focusing on correcting behaviors, we focused on explaining the behaviors—because there are countless videos, websites, and products promising to stop negative behaviors, but few address the underlying cause,” says Nove8.

The result: The second ad drove a 34% decrease in customer acquisition cost (CAC).

WHY IT WORKED: Pilothouse says: In-feed, diagnosis beats instruction. Also, that first ad risks sounding like another hack. (Teach your dog not to bite in one day? Really?) On Meta and TikTok, it casts a broad, noisy net around urgency. The second ad’s instructional visual format feels measured, expert, and low-threat. It prequalifies the right user before the click and gives the platform cleaner data about who finds this relevant.

THE BIG LESSON: In modern performance creative, the winning ad often interprets the customer more accurately, rather than explain the product more aggressively.

The first ad shared a fact: You only need 10 pieces to create the perfect wardrobe. The second ad was specifically for moms. Why? “If you try to speak to all customers, most won’t feel spoken to at all.  So instead, we focused on a specific person,” says Nove8.

The result: CAC was down by 80%.

WHY IT WORKED: Pilothouse says: The underperforming ad sold a fashion framework, but the winning ad sold relief for a very specific kind of woman living a very specific kind of day. And when consumers feel uniquely seen, they’re much more interested.

On Meta, the first ad might have reached more people. But that’s expensive, because Stylio would be paying for all that reach. By defining a cleaner pool of high-intent customers, they’re reaching fewer people but converting more, and saving money.

THE BIG LESSON: It’s not that brands should blindly niche down. The specificity only becomes powerful when it captures a real tension in a human problem and makes the customer feel understood.

By Liz Brody

Liz Brody is a contributing editor at Entrepreneur magazine.

Sourced from Entrepreneur

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As Google sits back and watches, terrible ads are ruining Android’s free app ecosystem

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By Jerry Hildenbrand

The enshittification of the Play Store.

Remember the early days of Android? It felt like the Wild West in the best way possible. You could hop onto the Play Store, type in a random app or game you wanted — like a flashlight, a simple unit converter, or a quirky indie puzzle game — and download a completely free app that did exactly what it promised.

Sure, there might have been a tiny, unobtrusive banner ad at the bottom of the screen, but it was a fair trade. You got a great tool, the developer made a few pennies, and everyone went home happy. Fast forward to today, and that beautiful, open ecosystem is actively suffocating.

If you download a free app on Android right now, you probably aren’t getting something free and useful (or fun); you’re getting an obstacle course. The free app ecosystem has degenerated into an absolute minefield of user-hostile advertising. And while developers and the ad networks themselves implement these nightmare tactics, the ultimate blame lies squarely at Google’s feet, which seems perfectly content to sit back, count its billions, and watch the platform burn.

Do you think ads are ruining free Android apps?

487 votes
Yes, I can’t stand them.
90%
The ads are annoying, but not the end of the world.
9%
No, I think they’re fine.
0%

The anatomy of a modern mobile ad night-terror

Android app with a pop-up about watching video ads.

We aren’t talking about simple banner ads anymore. The monetization strategies allowed on Android today feel less like business and more like psychological warfare. Some developers and advertisers even try to skirt the rules and go a step further.

Our top deals of the day

If you’ve used a free app recently, you’ve definitely run into these “greatest hits” of spammy ads:

  • The un-X-able interstitial: You open something like a basic calculator app, and boom — a full-screen video ad for a mobile strategy game slaps you in the face. You look for the “X” to close it, but it’s deliberately hidden, microscopic, or delayed by a fake countdown timer. Accidentally tap anywhere else? Congratulations, you’ve just been redirected to a sketchy landing page.
  • The psychological trap (playable ads): These are interactive mini-games that present a completely fake gameplay scenario (usually a puzzle that involves pulling pins to save someone from lava). They are intentionally designed to look easy, so you tap the screen, only for the ad to register that tap as a click-through to the Play Store.
  • The notification hijack: Some apps have the absolute audacity to push spam straight to your Android notification shade when the app isn’t even open, buzzing your pocket just to tell you there’s a “special bonus” waiting for you in a game you haven’t played in three weeks.

It’s exhausting. It turns a quick, two-second digital task into a multi-step battle against dark UI patterns designed to trick you into doing things you didn’t intend.

The death of the casual indie dev

Screenshot from Unity about data collection in an app.

The tragic irony here is that these toxic ads aren’t even saving the independent developers they were supposed to support.

Because the mobile ad market is dominated by massive, predatory ad networks, the payout per impression for normal, non-intrusive banner ads has tanked. To make any real money, small-time developers are practically forced to use aggressive ad SDKs (Software Development Kits) from major ad brokers. These SDKs are essentially black boxes that inject these horrible, flashing, high-volume video ads into the software.

If a developer refuses to ruin their app with these practices, they can’t compete. They get buried by the algorithm. The result? Talented indie creators are leaving the ecosystem entirely, leaving behind a vacuum filled by low-effort, template-based “copycat” apps designed solely to harvest user data and force-feed ads.

Where is Google? (Spoiler — it’s counting the money)

Google logo on smartphone stock photo 2

This brings us to the core of the problem: Google is the landlord of this digital slum.

Google owns Android. Google dictates the Play Store policies. More importantly, Google owns Google Ads and AdMob, the massive infrastructure powering a huge chunk of this very inventory. It possesses all the data, all the engineering power, and all the financial leverage required to fix this overnight.

Instead, Google treats the issue with a massive, corporate shrug. “Fixing” it is a conflict of interest: Every single time an intrusive, annoying ad successfully tricks a user into clicking it, money changes hands. And because Google is a dominant player in the mobile advertising space, a slice of that ad spend inevitably finds its way into Google’s pockets.

The proof is in the pudding, and the pudding tastes like malware.

To give credit where it’s due, Google claims it’s fighting the good fight. It publishes press releases highlighting how its AI defenses blocked millions of policy-violating apps or banned thousands of bad developer accounts. Google has also recently rolled out stricter developer verification programs. This is all well and good, and on the surface seems like a move in the right direction.

But anyone with an Android phone knows the truth: the proof is in the pudding, and the pudding tastes like malware. Google’s automated filters are clearly failing to catch the sheer volume of borderline-fraudulent advertising slipping through the cracks. It feels like Google only takes aggressive action when an ad is explicitly caught deploying literal spyware, while completely ignoring the ads that “merely” ruin the entire user experience. The financial gain from these spammy ads doesn’t give much incentive for change, either.

The road ahead

Samsung Galaxy S26 with its screen on, showing the app drawer.

Android’s greatest strength has always been its openness and accessibility. It allowed anyone, anywhere, to pick up a budget device and have access to a world of free, innovative software.
But “free” shouldn’t mean “toxic.” By allowing the ad ecosystem to degenerate into its current state, Google is actively training users to distrust free apps entirely. If a platform becomes so frustrating to use that people are afraid to click on a standard utility app for fear of a full-screen, un-closable pop-up, that platform is fundamentally broken.

It’s time for the tech giant to stop sitting on its hands. Clean up the Play Store, ban predatory ad networks, and give us back the Android ecosystem we actually fell in love with.

Feature image credit: Edgar Cervantes / Android Authority

By Jerry Hildenbrand

Sourced from ANDROID AUTHORITY

 

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