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AI advertising is repeating the ad blocking wars’ mistakes

Maybe money does not explain everything, but it explains a lot. Goldman Sachs estimates the AI build-out will require roughly $7.6 trillion in capital over the next five years across compute, data centers and power. It’s unlikely that subscriptions alone will cover the bill, which is why ads are coming to AI.

OpenAI started rolling out ads in some ChatGPT tiers this year and forecasts $2.5 billion in ad revenue in 2026 and $100 billion by 2030. At an ad tech event this summer, OpenAI’s chief revenue officer Denise Dresser dropped the hedging and said the company is “clearly in the advertising business now.”

Perplexity, on the other hand, shut down its ad business entirely over user trust. Similar products, same opportunity, opposite conclusions.

This conflict is not new and the open web fought this battle 15 years ago, when ad blocking became mainstream.

Now, the AI industry is on track to repeat every mistake of the so-called ad blocking wars, unless it studies them instead.

Lesson one: users revolt faster than big platforms think

When ad formats became more intrusive – because again, money! – the industry assumed users would just accept a bad experience. Instead, users fought back and installed software to get rid of aggressive online ads. In what technology commentator Doc Searls called “the biggest boycott in world history”, ad blocking went from being a niche tool to a mainstream product.

And we see the same dynamic playing out again. Within weeks of sponsored ads appearing in ChatGPT, purpose-built extensions popped up to specifically block ads there. Existing ad blocking tools made sure to block those ads as well. It took hours and days, not weeks or months, for users to act.

The predictable response is, of course, to sue ad blockers. For some publishers, the idea that users take agency over their own screens was not acceptable, so they took ad blocker developers to court. Almost all of the legal attempts failed. With one case still pending at the German courts, China is the only country in the world that bans ad blockers.

Another tactic is technology to fight ad blockers. Platforms tried different circumvention methods to deliver ads to users with ad blockers installed. This prompted their developers to update their techniques to prevent websites from bypassing. Every technical escalation met a counter-escalation and the sum of a lot of engineering efforts on both sides is that, today, over a billion people still block ads.

AI platforms hold one card their predecessors didn’t, though: integrating advertising directly into the generated answers, instead of showing labelled ads. Researchers from the University of Michigan tried exactly this and the results should worry everyone involved: users largely don’t expect advertising inside a generated answer and frequently fail to notice it.

At the same time, 63% of consumers say ads decrease their trust in AI outputs, according to Ipsos. The format that works best technically is the one users are least equipped to detect, and least willing to trust. Which brings us to the most important lesson.

Lesson three: trust is the actual product

Search results pages survived the ad blocking wars because users had ten blue links to compare with the sponsored content and two decades of learning what’s paid and what’s organic. AI assistants, on the other hand, offer one authoritative answer, with no other content or adjacent organic results to check against.

As soon as users suspect that answers might be influenced by a sponsor, these doubts are attached to all answers and trust erodes.

Cory Doctorow coined the term “enshittification”, which the American Dialect Society crowned as its Word of the Year in 2023. Platforms start out by doing good to their users and then degrade their experience to make advertisers happy.

And compared to tracking-based advertising in the open web, AI assistants know so much more about you that they can sell to advertisers: your health worries, your finances, your political view, your job struggles and everything else these tools picked up from you, stitched into one persistent memory of who you are.

It’s the most revealing personal record people have ever handed to software, combined with the drive from digital advertising to always collect more data and more data for targeting. The table is set for the next wave of enshittification.

Lesson four: the ad blocking wars ended in a treaty, not a victory

There was no final winner and not one technical solution that settled ad blocking in the open web. There was a rough settlement: standards for ad formats many users tolerate, transparency about what is paid for, meaningful user control.

Not everyone loves that settlement and we still see platforms trying to circumvent ad blockers and vice versa. But the open web still has a functioning ad economy and users still have, mostly, a functioning veto.

Getting there took more than a decade and the lessons are written down. Which road to take is now a genuine choice and it sits with the AI companies themselves.

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Leads communications for Adblock Plus and AdBlock at eyeo.

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61% of marketers declare that Artificial Intelligence (AI) is the most critical element of their data strategy.

Marketing is a fast-paced discipline. If you want to succeed in it, you must stay at the bleeding edge of new breakthroughs.

By 2020, 85% of customer relations will be automated. You, therefore, need to position your brand to stay competitive.

AI is probably the biggest technology push of our time revolutionizing every aspect of marketing. To get the most out of automated customer service, marketers are turning to AI advertising for strategies that can deliver higher value.

Here are some ways in which you can incorporate AI into your marketing to keep up with the times.

1. Chatbots

A Chatbot is an AI software that is capable of simulating a conversation (chat) with a user in natural language.

Brands have taken to using chatbots to interact with their clients on messaging apps like WhatsApp, Slack, and Facebook Messenger.

Through these bots, brands can answer queries customers frequently ask in a speedy fashion.

Since they retain a customer’s data after the interaction, they can build on that information to deliver more personalized experience during the next interaction.

That reinforced learning pattern only makes the experience better for the customer.

2. User Experience (UX)

When you have a website, the user experience will significantly influence whether the customer will return to it or not.

You can use AI to collect information on customers and understand their likes, intent, and desire. Data points to gather here include location, the devices they use to visit the website, demographics among others.

As the user keeps browsing the site, you get to gain more insights about them and deliver appropriate offers and content that resonates with their needs.

AI marketing that helps shape your user experience for the better has the potential to increase your conversion rate.

3. Search Engines

People today take it for granted that they can search for anything on Google and find a relevant result.

Such a scenario is the result of decades of research and analysis on how to create and deliver a more intuitive search experience for customers.

After Google deployed RankBrain, its machine-learning based algorithm, many businesses saw the value of such an application.

Nowadays consumer companies like Amazon take advantage of artificial intelligence marketing tactics that can help them deliver relevant results to you.

Innovations like natural language processing and semantic search determine the relationships between products.

When you run a search, they help recommend similar items and auto-correct mistakes so that you can find the right products.

4. Predictive Analysis

Predictive analysis is the use of data, machine learning techniques, and statistical algorithms to draw conclusions on future actions based on the data.

Using predictive analysis you can determine the probability of a prospect becoming a client.

Thus, depending on the conclusion your draw you can determine how much resources you will dedicate to converting the prospect.

Another area predictive analysis is useful in is pricing. Using this tool, you can more accurately determine which price point will deliver more sales for you.

That information can then contribute towards your value proposition marketing.

5. Email Marketing

Email marketing is a crucial part of any brand’s marketing mix as it is one of the few digital assets they fully control.

But with the rise in sources of data from 10 in 2017 to 15 in 2019, marketers may struggle to personalize these emails.

AI can help you unify the piles of information on a subscriber and learn how to reach more effectively.

For example, it can help you determine how many times to send the email per user and what time of the day is best to send it.

6. Digital Marketing

Pay-per-click (PPC) advertising is a cornerstone for any digital campaign. Typically, PPC ad campaigns are usually managed by an in-house team or a large agency.

AI can help you discover new channels your competition may be unaware of.

Machine learning techniques can help you optimize the layout, bids, targeting, and copy for your campaign.

You will be able to realize a higher return on advertising per campaign by using AI in marketing online.

7. Social Listening

Every brand needs to have a presence on social media to extend its customer service to where its customers are.

Consequently, it is essential that brands have their finger on the pulse of what users are saying about them.

Natural language processing innovation has made it possible for brands to hear what users and the public at large like or dislike about them.

Therefore, they can get ahead of any potential issues before they blow up.

You can also use AI in social listening to identify potential purchasers and nudge them towards a sale.

8. Audience Targeting

Customers today have come to expect a certain level of personalization, and as a marketer, you can’t fail on this expectation.

To help you create more accurately personalized campaigns, you will need to segment your customers as finely as possible.

AI can draw on the data you have on your customers and identify a common variable that can help shape your communication with a specific audience.

For example, if your data shows you that a significant number of your customers are into destiny power leveling, you can set up banner ads to effectively reach them.

9. Voice-Based Services

In the past few years, voice-based services have gained quite some traction.

Voice assistants such as Alexa, Siri, and Cortana have made it infinitely easier for consumers to search and place an order by speaking at their devices.

Natural language processing technology helps improve speech recognition so that customers can successfully issue commands.

AI can help you deploy voice-based services to provide your customers with an avenue for easier sales and interaction.

Beef up Your AI Advertising Strategies or Get Left Behind

Artificial Intelligence is making a big impact on marketing. High automation levels in what once used to be human job roles call for precise AI advertising strategies by brands.

Are you concerned with the impact technology will have on your business? Thumb through our content to learn more about how you can use innovative breakthroughs to power your business forward.

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