Standby As Google Cannibalizes Itself (Whereas Additionally Devouring All Of Us)

In 2023, I wrote a couple of provocative “what if”: What if Google added an AI chatbot to Search, successfully cannibalizing itself?

Quick-forward to 2025, and it’s not hypothetical.

With AI Overviews (AIOs) and AI Mode, Google has not solely eaten into its personal search product, however it has additionally taken an enormous chunk out of publishers, too.

Cannibalization is often framed as a threat. However in the precise circumstances, it may be a development driver-or even a survival tactic.

In in the present day’s Memo, I’m revisiting product cannibalization via a contemporary AI-era lens, together with:

• What cannibalization actually is (and why it’s not at all times unhealthy).
• Iconic examples from Netflix, Apple, Amazon, Google, and Instagram.
• How Google’s AI shift meets the definition of self-cannibalization – and the place it doesn’t.
• The 4 large advertising and marketing implications in case your model cannibalizes itself within the AI-boom panorama (for premium subscribers).

Picture Credit score: Kevin Indig

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Today’s Memo is an updated version of my previous guide on product cannibalization.

Previously, I wrote about how adding an AI chatbot to Google Search would mean that Google would be cannibalizing itself – which only a few companies in history have successfully accomplished.

In this updated Memo, I’ll walk you through successful product cannibalization examples while we revisit how Google has cannibalized itself through a refreshed lens.

Because … Google has effectively cannibalized itself with the incorporation of AI Overviews (AIOs) and AI Mode, but they haven’t found a way to monetize them yet.

And publishers and brands are suffering as a result.

So who wins here? (Does anyone?) Only time will tell.

Product cannibalization is the replacement of a product with a new one from the same company, typically expressed in sales revenue.

Even though most definitions say that cannibalization occurs when revenue is flat while two products trade market share, there are a number of examples that show revenue can grow as a result of cannibalization.

Product cannibalization, or market cannibalization, is often seen as something bad – but it can be good or even necessary.

Let’s consider a few examples of product cannibalization you’re likely already familiar with:

• Hardware.
• Retail.
• SaaS/Tech.

Hardware companies, for example, need to bring out better and newer chips on a regular basis. The lifecycle of AI training chips is often less than a year because new architectures and higher processing capabilities quickly make the previous generation obsolete.

Right now, chips are the hottest commodity in tech – companies building and training AI models need them in massive quantities, and as soon as the next generation is released, the old one loses most of its value.

As a result, chipmakers are forced to cannibalize their own products, advancing designs to stay competitive not only with rival manufacturers but also with their own previous breakthroughs.

But there are stark differences between cannibalization in retail and tech.

Retail cannibalization is driven by seasonal changes or consumer trends, while tech product cannibalization is primarily a result of progress.

In fashion, for example, consumers prefer this year’s collection over last season’s. The new collections cannibalize old ones.

In tech, new technology leads companies to replace old products.

New PlayStation consoles, for example, significantly replace sales from older ones – especially since they’re backward compatible with games.

Another example? The growth of the headless content management system (CMS), which increasingly replaces the coupled CMS and pushes content management providers to offer new products and features.

Netflix made several product pivots in its history, but two stand out the most:

1. The switch from DVD rental to streaming, and
2. Subscription-only memberships to ad-supported revenue.

On November 3, 2022, Netflix launched an ad-supported plan for $6.99/month on top of its standard and premium plans. (It has since increased to $7.99/month. See image below.)

During the pandemic, Netflix’s subscriber numbers skyrocketed, but they came back to earth like Falcon 9 when Covid receded: Enter the “Basic with ads” subscription that promoted retention.

Image Credit: Kevin Indig

Another challenge for Netflix? Competitors. Lots of them – and with legacy media histories.

Initially, the strategy of creating original content and making the experience seamless across many countries resulted in strong growth.

But when competitors like HBO, Disney, and Paramount launched similar products with original content, growth slowed down.

When Netflix launched the ad-supported plan, only 0.1% of existing users made the switch, but 9% of new users chose it (see below).

A look at other streaming platforms suggests the share will increase over time. Here’s a quick look at percentages of subscribers on ad-supported plans across platforms:

• Hulu has 57%.
• Paramount+ – 44%.
• Peacock – 76%.
• HBO Max – 21%.

Image Credit: Kevin Indig

However, Netflix’s new plan is not technically considered product cannibalization but partial cannibalization based on price.

The product is the same, but through the new plan, it’s now accessible to a new customer segment that previously wouldn’t have considered Netflix.

Additionally, it prevents an existing customer segment from churning since the recession shuffles the spending behavior of customer segments.

We can conclude that the new ad-supported Netflix plan is not the same type of cannibalization as its streaming service.

In 2007, internet connections became strong enough to open the door to streaming. Netflix was not the first company to provide movie streaming, but the first one to be successful at it.

The company paved the way by incentivizing DVD rental customers to engage online, for example, with rental queues on Netflix’s website. But ultimately, the pivot was the result of technological progress.

Another product that saw the light of day for the first time in 2007?

The iPhone.

When it launched, the iPhone had all the features of the iPod and more, making it a case of full product cannibalization.

As a result, the share of revenue from the iPod significantly decreased once the iPhone launched (see image below).

Even though you could argue it’s a “regular case” of market cannibalization when looking at revenue streams from each product, it was a technological step-change instead of partial cannibalization based on pricing.

Image Credit: Kevin Indig

However, big steps in technology don’t always lead to a desired replacement of an old product.

Take the Amazon Kindle, for example.

Launched in 2007 – just like Netflix’s streaming product and the iPhone (something was up that year) – Amazon brought its new ebook reader, Kindle, to market.

It made such an impact that people predicted the death of paper books. (And librarians everywhere laughed while booksellers braced themselves.)

But over 10 years later, ebooks stabilized at 20% market share, while print books captured 80%.

The reason is that publishers got into pricing battles with Amazon and Apple, which also started to play an important role in the ebook market. (It’s a long story; but you can read about it here).

Amazon attempted to cannibalize its core business (books) with the Kindle (ebooks), but couldn’t make product pricing work, which resulted in ebooks often being more expensive than print editions. Yikes.

The technology changed, but consumers weren’t incentivized to use it.

Let’s look at two final examples here. These two companies acquired or copied competitors to control partial cannibalization:

• YouTube videos are technically better answers to many search queries than web results. Google saw this very early on and smartly acquired YouTube. Video results took some time to fill more space in the Google SERP, even though they technically cannibalize web results. But today, they’re often some of the most visually impactful results (and often the first results) that searchers see.
• Instagram saw the success of Snapchat stories and decided to copy the feature in order to mitigate competitor growth. Despite the cannibalization of regular Instagram posts, net engagement with Stories was greater. (And speaking of YouTube, you could argue that YouTube Shorts follow the same principle.)

With all this in mind, we can say there is full and partial cannibalization based on how many features a new product replaces.

Pricing changes, copied features, or acquisitions lead to partial cannibalization that doesn’t result in the same revenue growth as full cannibalization.

Full cannibalization requires two conditions to be true:

1. The new product must be built on a technological step change, and
2. Customers need to be incentivized to use it.

With this knowledge foundation in place, let’s examine the shifts in the Google Search product over the last 12-24 months.

Let’s apply these product cannibalization principles to the case of Google vs. ChatGPT & Co.

In the original content of this memo (published in 2023), I shared the following:

If Google were to add AI to Search in a similar way as Neeva & Co (see previous article about Early attempts at integrating AI in Search), the following conditions would be true:

1. AI Chatbots are a technological step-change.
2. Customers are incentivized to use AI Chatbots because they give quick and good answers to most questions.

However, not all conditions are true:

1. AI Chatbots don’t provide the full functionality of Google Search.
2. It’s not cheaper to integrate an AI Chatbot with Search.

I’ve been clear about my hypothesis for a while now. As I shared in my 2025 Halftime Report:

I personally believe that AI Mode won’t launch [fully in the SERP] earlier than Google has discovered the monetization mannequin. And I predict that searchers will see approach fewer adverts however significantly better ones and displayed at a greater time.

And I highlighted this in Is AI reducing into your conversions? additionally:

Google gained’t present AI Mode all over the place, as a result of adoption is generational (see the UX examine of AIOs for more information). I believe AI Mode will launch at a broader scale (like displaying up for extra queries general) when Google figures out monetization.

Plus, ChatGPT just isn’t but monetizing, so advertisers go to Google and Meta – for now. And that’s my speculation as to why Google Search is continuous to develop.

Bear in mind, to efficiently cannibalize your current product, you want clients to wish to use it. And in accordance with a latest report from Garrett Sussman over at iPullrank, over 50% of customers who tried Google’s AI Mode as soon as and didn’t return. [Source] (So it appears Google’s nonetheless determining the incentivising half.)

Even with the developments we’ve seen within the final six to 12 months with AI fashions – and the inclusion of dwell net search and product suggestions into AI chats – I’d argue that they’re helpful for information-driven or generative queries however lack the databases wanted to provide good solutions to services or products searches.

Let’s check out an instance:

In case you enter “finest plumber in Chicago” or “finest toaster” into ChatGPT, I’d argue you’d really get much less high quality outcomes – for now – than for those who enter the identical queries into Google. (Go strive it for your self and let me know what you discover. However right here’s a walk-through with Amanda Johnson hopping in as an instance this under.)

On the similar time, these product and repair queries are the queries that serps with an advert income enterprise mannequin can monetize finest.

It was mentioned that ChatGPT prices at the least $100,000 per day to run when it first crossed 1 million customers in December 2022. By 2023, it was costing about $700,000 a day. [Source]

Immediately, it’s more likely to be a big a number of of that.

Bear in mind, Google Search sees billions of search queries daily.

Even with Google’s superior infrastructure and expertise, AI chatbots are expensive.

And so they can (nonetheless) be sluggish – even with the developments they’ve made within the final 12 months. Present and basic Google Search methods (like Featured Snippets and Individuals Additionally Ask) may present a a lot sooner reply.

However, alas, right here we’re in 2025, and Google is cannibalizing its personal product by way of AIOs and AI Mode.

Proper now, in accordance with Similarweb information, utilization of the AI Mode tab on Google.com within the U.S. has barely dipped and now sits at simply over 1%. [Source, Source]

Google AIOs at the moment are seen by greater than 1.5 billion searchers each month, and so they sit entrance and heart. However engagement is falling. Customers are spending much less time on Google and clicking fewer pages. [Source]

However Google has to compete with not solely different serps that present an AI-chat-forward expertise, but additionally with ChatGPT & Co. themselves.

Under, I’ve listed out essential issues in your model for those who may make the most of product cannibalization as a technique.

You’ll wish to:

1. Reframe cannibalization as a strategic choice for the model relatively than a failure.
2. Use the total vs. partial cannibalization lens.
3. Check the 2 success circumstances.
4. Defend your core choices when you experiment.
5. Use aggressive cannibalization defensively.
6. Monitor, be taught, and regulate.

Within the subsequent part, for premium subscribers, I’ll stroll you thru what to be careful for for those who resolve to make use of product cannibalization as a development technique.

1. Reframe Cannibalization As A Strategic Choice

• Don’t default to seeing product cannibalization as a failure; assess if it may well shield market share or speed up development.
• Audit your product line and GTM technique to determine areas the place you would self-disrupt earlier than a competitor does.

2. Use The Full Vs. Partial Cannibalization Lens

• Full cannibalization works finest when there’s a tech leap and robust buyer incentives.
  • Instance: Apple iPhone changing iPod – all iPod options plus way more functionality led to the iPod’s speedy decline.
• Partial cannibalization by way of pricing, options, or acquisitions is much less dangerous however might not ship large development.
  • Instance: Netflix ad-supported plan – similar streaming product, however a lower-cost tier opened the door to new segments and diminished churn threat.
• Map present and future choices in opposition to these two classes to resolve your method.

3. Check The two Success Situations

A cannibalizing product is extra more likely to succeed when each are true:

• Tech Leap: Provides a meaningfully higher option to clear up the issue.
  • Instance: Netflix DVD → Streaming in 2007 leveraged sooner web speeds to alter the supply mannequin fully.
• Buyer Incentive: Decrease price, higher efficiency, extra comfort, or standing.
  • Instance: YouTube acquisition by Google made richer, extra visible solutions potential in Search, enhancing the person expertise.

If each apply → pursue full cannibalization.

If one applies → pursue partial cannibalization with managed scope.

4. Defend Your Core Whereas You Experiment

• Establish high-revenue segments and defend them from early disruption.
  • Instance: Google conserving AI Mode away from extremely monetizable queries like “finest bank card” till the advert mannequin is prepared.
• Check self-disruption in lower-stakes markets to validate demand earlier than scaling
  • Instance: Instagram Tales rolled out in a approach that boosted web engagement whereas defending the feed’s advert stock.

5. Use Aggressive Cannibalization Defensively

• When a rival launches a risk, select between:
  • Purchase: Google buying YouTube to regulate the rise of video as a search reply format.
  • Copy: Instagram adopting Tales from Snapchat to cease person migration and develop engagement.
  • Differentiate: Amazon Kindle – a tech leap that attempted to maneuver readers from print to digital, however with no worth benefit, adoption plateaued.

6. Monitor, Be taught, And Regulate

• Observe engagement, income combine, and adoption by phase.
  • Instance: Similarweb information on AI Mode – U.S. utilization holding simply over 1%, signaling limits to adoption velocity.
• Regulate rollout tempo primarily based on generational adoption patterns and competitor strikes.
  • Instance: Google AIO engagement drop – displaying that placement alone doesn’t assure sustained person curiosity.

A great instance is how to do that is Chegg.

The corporate has been obliterated by Google’s AI Overviews and even sued Google. Chegg’s worth was solutions to homework questions, however since virtually each pupil makes use of ChatGPT for that, their worth chain broke. How is the corporate reacting to this life-ending risk?

In my Q2 Market Deep Dive, I clarify that Chegg has discovered a lifeboat:

Chegg has launched a brand new instrument, Answer Scout, that enables college students to match solutions from ChatGPT & Co. with Chegg’s archive.

As an alternative of attempting to beat AI Chatbots, Chegg hits them the place it hurts: within the hallucinations.

LLMs could make stuff up, which is very painful in the case of studying and taking exams. Think about you spend hours internalizing the flawed information!

Answer Scout validates AI solutions with Chegg’s archive of human-sourced materials. It compares the reply from foundational fashions and highlights variations and consensus.

Featured Picture: Paulo Bobita/Search Engine Journal