Wise words from one of the most memorable (if fictitious) advertisers of our time.
Few industries are experiencing AI’s immediate impacts as much as advertising. AI is upending today’s media landscape, from the way people consume content to the methods merchants use to catch their attention.
The good news: Marketers are adaptable to change. Looking back over the last 100 years of advertising, marketers have time and time again had to adapt to changing consumer behavior. The ad spend pie in the US has expanded exponentially (digital marketing has grown 7x over the last decade) as ad dollars move to new formats. And as consumption mediums change, marketers find new inventory to meet consumer demand in increasingly targeted and personalized ways.
Even the largest incumbents need to adapt their marketing strategies. Our investment team has had firsthand experience on the digital marketing team at Google, which constantly tests new channels and strategies to boost their advertising efforts. This involves implementing new search and display ad formats, trialing programmatic retail advertising on Amazon and Walmart, shifting TV media spend from linear to Connected TV (CTV), including YouTube TV, and even running one of the first TikTok ads.
Below, we dive into the changing landscape across digital advertising and the changes coming to every channel from search to CTV, to understand both how consumers are changing buying habits in an AI-first world and how merchants are adapting their strategies to meet them there.
To write this article, we spoke with industry veterans across advertising and marketing. Thank you to Emily Allen and Michael Carney at Google, Saket Mehta at Block, Tom Triscari at Quo Vadis, Nate Yu at Butter, and Jon Zacharias at GR0.
The changing marketing landscape
Digital marketing is a $300B+ industry in the US today, making up three quarters of total advertising spend (the remaining is from declining channels like linear TV, radio, OOH, print).
Today, we’re beginning to see the almost endless use cases for AI in advertising and marketing. It’s transforming how marketers plan, execute, and measure their campaigns. Predictive AI continues to get better, improving targeting, bolstering analytics (both pre- and post-campaign), and optimizing budgets and distribution of spend across channels.
Walled gardens and ad platforms like Google, Meta, and TikTok have launched new AI products that are optimizing spend, although this only works within their own ecosystems. Marketers are left to find platform-independent tools to maximize spend across digital channels. This feels like a big opportunity for new entrants to own cross-platform spend for marketers. We believe generative AI will have profound impacts on media planning, which has been a highly manual process to date. AI will automate the planning phase with optimized spend allocation to free up marketers’ time to focus on ad creative.
AI creates an opportunity to democratize access to these capabilities across all channels.
With generative AI, we believe marketers will be able to scale content creation like never before across all mediums: copy, imagery, and video. This potentially includes the ability to supercharge personalization, creating more relevant ad experiences for each member of their target audience; rapidly optimize campaigns based on feedback, because there are shorter cycles between ideation and implementation; and do all of this for far less money and at far greater speed. Some agencies we spoke with believe this will be the key to the future of marketing agencies, allowing them to service a far greater number of clients while hiring far fewer people.
As consumer and enterprise adoption of AI moves from early adopters to the majority, marketers will need to stay ahead of the curve and meet prospective buyers where they are. Below, we address where advertising is having the greatest impact across the major spend categories.
Search
One of the first areas of advertising being upended is search, including both search engine optimization (SEO) and paid search engine marketing (SEM).
Google has long dominated the search category, with an estimated 90% market share. But with the spread of LLM-powered chat tools, that market share may be eroding faster than any of us previously thought. A recent survey conducted by Evercore revealed that already 8% of consumers are choosing ChatGPT over Google for their search engine. More remarkably, only 1% of that same group of respondents stated that preference earlier in the year, representing an 8x increase in less than half a year.
Consumers have begun to change their behavior from searching for options to searching for answers. For example, you might ask ChatGPT to give you a list of the best TV shows of this year, rather than clicking through multiple links of editorials and aggregators yourself. Gone could be the days of searching, clicking through blue links, and scrolling sites until you find what you’re looking for. (This will also upend the “open web” as many online publishers monetize via consumers clicking on blue links.)
Instead, we’re moving towards a world where we’ll make a query, and there our answer will be: the machine-consolidated result, nicely packaged. But while this is incredibly helpful for the consumer, it has already created challenges for advertisers who have previously monetized the journey of finding the answer.
SEO
Specialists have long since cracked the code on how search engines like Google and Bing work, using techniques like EAT (expertise, authoritativeness, trustworthiness) and optimizing for backlinks or engaging content that would appear high up in rankings for keywords.
We believe AI is ushering in two competing forces in the world of SEO. On one hand, co-pilots and LLMs make it easier and faster to write content. Companies like Copy.ai and Jasper have already captured market share with e-commerce marketers, creating scalable content in the company’s voice and style.
At the same time, in the near future much of this content might not actually be read by the end consumer. Rather, it might be read by LLMs answering queries, which could then surface insights to the consumer. This change could necessitate a completely new type of SEO, one that optimizes content not for the human consumer, but rather for LLMs.
GEO (generative engine optimization) and AEO (answer engine optimization) are beginning to emerge to help marketers get their companies to be the top answers in AI search results. Companies like Evertune and Daydream are developing new strategies for companies to improve their search results in ChatGPT and other AI search engines.
SEM
Changes may be equally profound for search engine marketing. The new dominant search engines in the world of generative AI—ChatGPT, Claude, Perplexity, and Gemini (Google’s AI chat)—are already clearing out space for ad inventory in their offerings.
Perplexity, for example, has launched “sponsored follow up questions,” where brands are able to pay to have their company results surfaced first. We believe there will inevitably be new search ad units created from these developing AI search ecosystems, providing an opportunity for advertisers to creatively influence these new mediums.
AI agent shoppers
We’re also excited to see how marketers transition from targeting human shoppers to targeting the AI agents that are increasingly shopping on our behalf.
We’re already seeing Gemini, Claude and ChatGPT move towards this behavior, with agents starting to control computer functions and make decisions for us. For example, Google just released an AI agent product that takes over a person’s web browser to purchase a product or book a flight. Companies like Payman and Stripe are building payment rails for agents to make purchases on our behalf, closing the loop of searching and buying.
We believe e-commerce marketers will need a different approach to meet the agentic buyers. What features will increase conversion rates for AI agent shoppers? Visual merchandising and on-site experiences likely won’t matter. Will Shopify allow for faster check out experiences or easily indexable online merchandising for AI agents? Could another website infrastructure leader emerge, focused exclusively on agent shoppers? Companies like Browserbase are already building infrastructure for this new world—and we imagine more will follow suit.
Tips & takeaways for marketers:
- Optimize content for LLMs, not just humans—SEO now requires AI-focused strategies.
- GEO and AEO are helping brands rank in AI search results.
- GenAI search engines are opening new doors for ad content.
- Marketers must adapt to appeal to AI shopping agents that make purchases on a buyer's behalf.
Social media & influencer marketing
We believe social media platforms like Google (YouTube), Meta (Facebook, Instagram), and Bytedance (TikTok, Douyin) have been and will continue to be the greatest beneficiaries of AI.
These ad platforms—which represent three of the five biggest sellers of advertising globally—are at the forefront of AI development for both their advertisers and users. They have already started replacing traditional search engines for Gen Z and Millennial audiences who are using social platforms for discovery. TikTok has long been a leader in the space with its proprietary AI recommendation engine, and Google and Meta have invested billions developing their own LLMs, Gemini and Llama, respectively.
These platforms understand that content proliferation drives more users to the apps, and LLMs are expanding content creation. For example, AI-powered dubbing features help creators bring in audiences from new corners of the world that might not otherwise be able to engage with a creator’s content. Meanwhile AI tooling allows creators to build digital avatars that can increase their content output exponentially.
Ad creative
Ad creative—which includes the visual and auditory elements of advertisements—was one of the first areas of social media advertising to be affected by AI. Companies like Adcreative.ai, Motion and Chord are providing tools for advertisers to both create and measure endless amounts of creative content for merchants.
Analytics and targeting are also paramount. Some marketers are leveraging techniques such as DCO (dynamic creative optimization) to build hyper-personalized marketing campaigns to target specific audiences based on profile, geography, and time of day. While proprietary AI marketing products from Google, Meta, and TikTok can be effective tools inside their respective walled gardens, there remains an opportunity for new entrants to own cross-channel capabilities for merchants.
Influencer marketing
Another area we expect to see outsized gains from AI is influencer and creator marketing (we use “influencer” and “creator” interchangeably here). As social channels become more saturated with AI-generated content, we expect the more authentic and trusted-source of influencer marketing to take a bigger piece of the pie.
In the US, brands are expected to spend $8B on creator marketing campaigns in 2024. This is creators’ largest share of their income, accounting for two-thirds of dollars they pull in (other areas include ad share from platforms, subscriptions, and tips).
We believe AI is already creating better and faster matching for creators and brands, using past creator performance, social listening, and advanced analytics to review millions of videos and make the matching process more efficient—but this is only the tip of the iceberg when it comes to creator marketing efficiency.
While the $8B influencer marketing TAM is large and growing fast (at 26% CAGR over the last five years), it is still a fraction of the overall digital marketing budget. Why is this still such a small piece of overall ad dollars, even though virtually every brand we speak with wants to substantially increase their influencer marketing spend? One possibility is because spend in the category has been artificially capped due to how campaigns are executed.
Compare spending on Meta ads vs. hiring creators to conduct an influencer campaign on Meta. With the former, a digital marketer may set a budget, determine an appropriate ROAS, and then scale spend up or down according to performance. If the spend is effective, the next day they could easily increase it 10x. They would be able to target audiences accurately and at scale.
While AI today has allowed better targeting of influencer audiences, there is no scalable ad unit for influencer marketing. In this scenario, a campaign may require weeks or months to execute, and involves finding the right creators, navigating manager and agent relationships, negotiating rates, ideating creative, redlining contracts, measuring results, etc. If a campaign is a smashing success, there is no one-click way to 10x scale the next day: the marketer would have to repeat the time-consuming process.
This process has historically placed an artificial cap on creator marketing—a restriction that we believe can be lifted with AI facilitating the execution of an influencer campaign to make it more like paid digital media spend. Companies like Agentio are already testing this hypothesis on select channels like YouTube.
Our hypothesis is that creator marketing will become a much larger piece of the overall digital marketing spend in the near future, as AI drastically improves the execution of the ad unit. The gauge of success will not only be increasing influencer marketing spend as a category, but also shifting paid media budgets into influencer budgets.
Tips & takeaways for marketers:
- Social platforms are one of the greatest beneficiaries of AI adoption, but marketers need solutions to effectively allocate spend across all platforms.
- Social media is already a go-to search tool for younger audiences, getting even stronger with proprietary LLMs assisting personalized search on these platforms.
- AI has the potential to scale influencer marketing, making it more like paid ads and moving internal marketing budgets accordingly.
Retail media
For many years, Meta and Google maintained a clear duopoly in the US ad space, representing over 50% of all ad spend through their platforms. Today, retail media is taking market share—and is in fact the fastest-growing digital advertising segment, per ad tracker eMarketer—largely led by Amazon’s dominance in the category.
Amazon’s ad revenue is expected to surpass $42B this year, representing 14% of all US ad spend. (M13 investor Whitney Hazard experienced this growth firsthand during her time at Google, when she worked on performance advertising on Amazon, optimizing that channel for programmatic ads just like they did with traditional search.) Additionally, Walmart is a distant second at ~$4B, but nonetheless growing quickly.
These two massive retailers have set a precedent for other commerce providers and marketplaces to maximize their users’ attention: Uber, Instacart, Doordash are all increasing their focus on advertising on their respective platforms. In addition, commerce and payments providers like PayPal and Block are building their own marketing platforms leveraging their first-party data and payments ecosystems.
This should come as no surprise as marketers try to find high-intent purchasers in the post-iOS 14 world. While we believe it’s harder to target specific buyers across social media platforms today, the ad units inside of retail media networks (RMN) tend to be more targeted. For example, if a consumer searches for baby pajamas in their Amazon search bar, brands with sponsored placements will show up at the top of the search results.
We believe AI will continue to impact retail media beyond the current use cases of personalization and improved recommendations. Arguably, Amazon has nearly perfected its recommendation engine, training ML models on its hundreds of millions of shoppers. It’s been reported that over one-third of its marketplace GMV comes from these recommendations.
Looking ahead, we believe generative AI will democratize access to RMN for smaller retailers as well. These retailers can already harness the power of LLMs to make better personalized recommendations. For example, M13 portfolio company Rebuy gives DTC brands powerful AI-driven personalization tools to help with customer conversion on site. M13 portfolio company Pietra has introduced new tooling for online merchants to use AI to source and contact independent retailers to sell their goods. Meanwhile companies like Topsort enable smaller retailers to build their own ad infrastructure. We believe AI will transform how consumers (or their agents) discover products while shopping on retailers’ websites.
Tips & takeaways for marketers
- Retail media is breaking the Meta-Google ad duopoly.
- AI is transforming retail media with better personalization, targeting, and recommendations.
- Even smaller retailers can leverage AI to make better, more personalized recommendations.
Connected TV
CTV is quickly stealing ad budgets away from the linear TV channel: While in 2019 linear’s market share of ad dollars was 30%, it’s projected to be less than half of that by 2026.
The shift is partly driven by CTV allowing advertisers to move from reach and awareness (historically the purposes of linear TV) towards audience targeting and performance measurement, similar goals of digital-first strategies.
We believe this trend is unlocking opportunities for advertisers to harness the storytelling power of TV, paired with new tools for targeting, measurement, and leveraging programmatic strategies.
For example, AI systems can analyze vast datasets in real time to make split-second optimizations that humans cannot. This can allow advertisers to refine their campaigns dynamically and reallocate budgets to better-performing placements on the fly.
For targeting, machine learning models can analyze viewing habits and demographics to pinpoint high-intent audiences that are likely to convert, refining segments in real time as behaviors shift. Generative AI takes personalization further by tailoring ad content to individual viewers, creating customized experiences that feel more engaging and less intrusive.
AI can also streamline creative production, enabling marketers to produce localized, personalized ad variations in seconds to connect more deeply with audiences. Generative AI tools assist with concept brainstorming, narrative development, storyboarding, and video production, enabling marketers to create compelling CTV ads in a fraction of the time. For example, HeyGen and Creatify are AI video generators and have functionality optimized for CTV. This enables production of ads that might incorporate changes like localized voiceovers, store-specific promotions, or personalized messaging, all crafted in seconds.
Finally, AI-driven analytics offer granular insights into campaign performance, from engagement to revenue attribution. These tools could create a feedback loop that improves every campaign. While it’s still early innings, we believe CTV can become an increasingly valuable channel for advertisers with larger budgets.
Tips & takeaways for marketers:
- Connected TV is poised to become a key channel for advertisers who have the budget for it.
- Generative AI can deliver hyper-personalized ads, as AI analytics shift and refine ads in real time.
The road ahead
AI is already having profound impacts on the entire advertising industry as well as the end consumers it reaches. Consumer behavior is changing, and ad platforms and marketers will need to adapt to keep up, just like they have always done.
We believe that new channels and platforms will gain traction while others fade; creating content will be easier but breaking through will be harder; and targeting and personalization will get even better. We also believe all of this is only just the beginning of AI’s impact on marketing.
This creates massive opportunities for everyone in the ecosystem:
- Disruptive technology startups have a once-in-a-generation opportunity to claim market share in the massive and evolving digital advertising landscape.
- Incumbent ad platforms have an advantage in large user bases and vast amounts of data—but they will need to innovate to make their channels effective and resonant in the changing landscape.
- Merchants will need to evolve to utilize new advertising capabilities to reach consumers on new platforms.
Google and Meta came out of Web 1.0 and 2.0 shifts, respectively. What will come out of the latest technology wave driven by AI?
Get in touch
We’re excited to continue to invest in companies disrupting advertising and marketing.
Are you building in this space? We want to talk! Reach out to brent@m13.co and whitney@m13.co.
Wise words from one of the most memorable (if fictitious) advertisers of our time.
Few industries are experiencing AI’s immediate impacts as much as advertising. AI is upending today’s media landscape, from the way people consume content to the methods merchants use to catch their attention.
The good news: Marketers are adaptable to change. Looking back over the last 100 years of advertising, marketers have time and time again had to adapt to changing consumer behavior. The ad spend pie in the US has expanded exponentially (digital marketing has grown 7x over the last decade) as ad dollars move to new formats. And as consumption mediums change, marketers find new inventory to meet consumer demand in increasingly targeted and personalized ways.
Even the largest incumbents need to adapt their marketing strategies. Our investment team has had firsthand experience on the digital marketing team at Google, which constantly tests new channels and strategies to boost their advertising efforts. This involves implementing new search and display ad formats, trialing programmatic retail advertising on Amazon and Walmart, shifting TV media spend from linear to Connected TV (CTV), including YouTube TV, and even running one of the first TikTok ads.
Below, we dive into the changing landscape across digital advertising and the changes coming to every channel from search to CTV, to understand both how consumers are changing buying habits in an AI-first world and how merchants are adapting their strategies to meet them there.
To write this article, we spoke with industry veterans across advertising and marketing. Thank you to Emily Allen and Michael Carney at Google, Saket Mehta at Block, Tom Triscari at Quo Vadis, Nate Yu at Butter, and Jon Zacharias at GR0.
The changing marketing landscape
Digital marketing is a $300B+ industry in the US today, making up three quarters of total advertising spend (the remaining is from declining channels like linear TV, radio, OOH, print).
Today, we’re beginning to see the almost endless use cases for AI in advertising and marketing. It’s transforming how marketers plan, execute, and measure their campaigns. Predictive AI continues to get better, improving targeting, bolstering analytics (both pre- and post-campaign), and optimizing budgets and distribution of spend across channels.
Walled gardens and ad platforms like Google, Meta, and TikTok have launched new AI products that are optimizing spend, although this only works within their own ecosystems. Marketers are left to find platform-independent tools to maximize spend across digital channels. This feels like a big opportunity for new entrants to own cross-platform spend for marketers. We believe generative AI will have profound impacts on media planning, which has been a highly manual process to date. AI will automate the planning phase with optimized spend allocation to free up marketers’ time to focus on ad creative.
AI creates an opportunity to democratize access to these capabilities across all channels.
With generative AI, we believe marketers will be able to scale content creation like never before across all mediums: copy, imagery, and video. This potentially includes the ability to supercharge personalization, creating more relevant ad experiences for each member of their target audience; rapidly optimize campaigns based on feedback, because there are shorter cycles between ideation and implementation; and do all of this for far less money and at far greater speed. Some agencies we spoke with believe this will be the key to the future of marketing agencies, allowing them to service a far greater number of clients while hiring far fewer people.
As consumer and enterprise adoption of AI moves from early adopters to the majority, marketers will need to stay ahead of the curve and meet prospective buyers where they are. Below, we address where advertising is having the greatest impact across the major spend categories.
Search
One of the first areas of advertising being upended is search, including both search engine optimization (SEO) and paid search engine marketing (SEM).
Google has long dominated the search category, with an estimated 90% market share. But with the spread of LLM-powered chat tools, that market share may be eroding faster than any of us previously thought. A recent survey conducted by Evercore revealed that already 8% of consumers are choosing ChatGPT over Google for their search engine. More remarkably, only 1% of that same group of respondents stated that preference earlier in the year, representing an 8x increase in less than half a year.
Consumers have begun to change their behavior from searching for options to searching for answers. For example, you might ask ChatGPT to give you a list of the best TV shows of this year, rather than clicking through multiple links of editorials and aggregators yourself. Gone could be the days of searching, clicking through blue links, and scrolling sites until you find what you’re looking for. (This will also upend the “open web” as many online publishers monetize via consumers clicking on blue links.)
Instead, we’re moving towards a world where we’ll make a query, and there our answer will be: the machine-consolidated result, nicely packaged. But while this is incredibly helpful for the consumer, it has already created challenges for advertisers who have previously monetized the journey of finding the answer.
SEO
Specialists have long since cracked the code on how search engines like Google and Bing work, using techniques like EAT (expertise, authoritativeness, trustworthiness) and optimizing for backlinks or engaging content that would appear high up in rankings for keywords.
We believe AI is ushering in two competing forces in the world of SEO. On one hand, co-pilots and LLMs make it easier and faster to write content. Companies like Copy.ai and Jasper have already captured market share with e-commerce marketers, creating scalable content in the company’s voice and style.
At the same time, in the near future much of this content might not actually be read by the end consumer. Rather, it might be read by LLMs answering queries, which could then surface insights to the consumer. This change could necessitate a completely new type of SEO, one that optimizes content not for the human consumer, but rather for LLMs.
GEO (generative engine optimization) and AEO (answer engine optimization) are beginning to emerge to help marketers get their companies to be the top answers in AI search results. Companies like Evertune and Daydream are developing new strategies for companies to improve their search results in ChatGPT and other AI search engines.
SEM
Changes may be equally profound for search engine marketing. The new dominant search engines in the world of generative AI—ChatGPT, Claude, Perplexity, and Gemini (Google’s AI chat)—are already clearing out space for ad inventory in their offerings.
Perplexity, for example, has launched “sponsored follow up questions,” where brands are able to pay to have their company results surfaced first. We believe there will inevitably be new search ad units created from these developing AI search ecosystems, providing an opportunity for advertisers to creatively influence these new mediums.
AI agent shoppers
We’re also excited to see how marketers transition from targeting human shoppers to targeting the AI agents that are increasingly shopping on our behalf.
We’re already seeing Gemini, Claude and ChatGPT move towards this behavior, with agents starting to control computer functions and make decisions for us. For example, Google just released an AI agent product that takes over a person’s web browser to purchase a product or book a flight. Companies like Payman and Stripe are building payment rails for agents to make purchases on our behalf, closing the loop of searching and buying.
We believe e-commerce marketers will need a different approach to meet the agentic buyers. What features will increase conversion rates for AI agent shoppers? Visual merchandising and on-site experiences likely won’t matter. Will Shopify allow for faster check out experiences or easily indexable online merchandising for AI agents? Could another website infrastructure leader emerge, focused exclusively on agent shoppers? Companies like Browserbase are already building infrastructure for this new world—and we imagine more will follow suit.
Tips & takeaways for marketers:
- Optimize content for LLMs, not just humans—SEO now requires AI-focused strategies.
- GEO and AEO are helping brands rank in AI search results.
- GenAI search engines are opening new doors for ad content.
- Marketers must adapt to appeal to AI shopping agents that make purchases on a buyer's behalf.
Social media & influencer marketing
We believe social media platforms like Google (YouTube), Meta (Facebook, Instagram), and Bytedance (TikTok, Douyin) have been and will continue to be the greatest beneficiaries of AI.
These ad platforms—which represent three of the five biggest sellers of advertising globally—are at the forefront of AI development for both their advertisers and users. They have already started replacing traditional search engines for Gen Z and Millennial audiences who are using social platforms for discovery. TikTok has long been a leader in the space with its proprietary AI recommendation engine, and Google and Meta have invested billions developing their own LLMs, Gemini and Llama, respectively.
These platforms understand that content proliferation drives more users to the apps, and LLMs are expanding content creation. For example, AI-powered dubbing features help creators bring in audiences from new corners of the world that might not otherwise be able to engage with a creator’s content. Meanwhile AI tooling allows creators to build digital avatars that can increase their content output exponentially.
Ad creative
Ad creative—which includes the visual and auditory elements of advertisements—was one of the first areas of social media advertising to be affected by AI. Companies like Adcreative.ai, Motion and Chord are providing tools for advertisers to both create and measure endless amounts of creative content for merchants.
Analytics and targeting are also paramount. Some marketers are leveraging techniques such as DCO (dynamic creative optimization) to build hyper-personalized marketing campaigns to target specific audiences based on profile, geography, and time of day. While proprietary AI marketing products from Google, Meta, and TikTok can be effective tools inside their respective walled gardens, there remains an opportunity for new entrants to own cross-channel capabilities for merchants.
Influencer marketing
Another area we expect to see outsized gains from AI is influencer and creator marketing (we use “influencer” and “creator” interchangeably here). As social channels become more saturated with AI-generated content, we expect the more authentic and trusted-source of influencer marketing to take a bigger piece of the pie.
In the US, brands are expected to spend $8B on creator marketing campaigns in 2024. This is creators’ largest share of their income, accounting for two-thirds of dollars they pull in (other areas include ad share from platforms, subscriptions, and tips).
We believe AI is already creating better and faster matching for creators and brands, using past creator performance, social listening, and advanced analytics to review millions of videos and make the matching process more efficient—but this is only the tip of the iceberg when it comes to creator marketing efficiency.
While the $8B influencer marketing TAM is large and growing fast (at 26% CAGR over the last five years), it is still a fraction of the overall digital marketing budget. Why is this still such a small piece of overall ad dollars, even though virtually every brand we speak with wants to substantially increase their influencer marketing spend? One possibility is because spend in the category has been artificially capped due to how campaigns are executed.
Compare spending on Meta ads vs. hiring creators to conduct an influencer campaign on Meta. With the former, a digital marketer may set a budget, determine an appropriate ROAS, and then scale spend up or down according to performance. If the spend is effective, the next day they could easily increase it 10x. They would be able to target audiences accurately and at scale.
While AI today has allowed better targeting of influencer audiences, there is no scalable ad unit for influencer marketing. In this scenario, a campaign may require weeks or months to execute, and involves finding the right creators, navigating manager and agent relationships, negotiating rates, ideating creative, redlining contracts, measuring results, etc. If a campaign is a smashing success, there is no one-click way to 10x scale the next day: the marketer would have to repeat the time-consuming process.
This process has historically placed an artificial cap on creator marketing—a restriction that we believe can be lifted with AI facilitating the execution of an influencer campaign to make it more like paid digital media spend. Companies like Agentio are already testing this hypothesis on select channels like YouTube.
Our hypothesis is that creator marketing will become a much larger piece of the overall digital marketing spend in the near future, as AI drastically improves the execution of the ad unit. The gauge of success will not only be increasing influencer marketing spend as a category, but also shifting paid media budgets into influencer budgets.
Tips & takeaways for marketers:
- Social platforms are one of the greatest beneficiaries of AI adoption, but marketers need solutions to effectively allocate spend across all platforms.
- Social media is already a go-to search tool for younger audiences, getting even stronger with proprietary LLMs assisting personalized search on these platforms.
- AI has the potential to scale influencer marketing, making it more like paid ads and moving internal marketing budgets accordingly.
Retail media
For many years, Meta and Google maintained a clear duopoly in the US ad space, representing over 50% of all ad spend through their platforms. Today, retail media is taking market share—and is in fact the fastest-growing digital advertising segment, per ad tracker eMarketer—largely led by Amazon’s dominance in the category.
Amazon’s ad revenue is expected to surpass $42B this year, representing 14% of all US ad spend. (M13 investor Whitney Hazard experienced this growth firsthand during her time at Google, when she worked on performance advertising on Amazon, optimizing that channel for programmatic ads just like they did with traditional search.) Additionally, Walmart is a distant second at ~$4B, but nonetheless growing quickly.
These two massive retailers have set a precedent for other commerce providers and marketplaces to maximize their users’ attention: Uber, Instacart, Doordash are all increasing their focus on advertising on their respective platforms. In addition, commerce and payments providers like PayPal and Block are building their own marketing platforms leveraging their first-party data and payments ecosystems.
This should come as no surprise as marketers try to find high-intent purchasers in the post-iOS 14 world. While we believe it’s harder to target specific buyers across social media platforms today, the ad units inside of retail media networks (RMN) tend to be more targeted. For example, if a consumer searches for baby pajamas in their Amazon search bar, brands with sponsored placements will show up at the top of the search results.
We believe AI will continue to impact retail media beyond the current use cases of personalization and improved recommendations. Arguably, Amazon has nearly perfected its recommendation engine, training ML models on its hundreds of millions of shoppers. It’s been reported that over one-third of its marketplace GMV comes from these recommendations.
Looking ahead, we believe generative AI will democratize access to RMN for smaller retailers as well. These retailers can already harness the power of LLMs to make better personalized recommendations. For example, M13 portfolio company Rebuy gives DTC brands powerful AI-driven personalization tools to help with customer conversion on site. M13 portfolio company Pietra has introduced new tooling for online merchants to use AI to source and contact independent retailers to sell their goods. Meanwhile companies like Topsort enable smaller retailers to build their own ad infrastructure. We believe AI will transform how consumers (or their agents) discover products while shopping on retailers’ websites.
Tips & takeaways for marketers
- Retail media is breaking the Meta-Google ad duopoly.
- AI is transforming retail media with better personalization, targeting, and recommendations.
- Even smaller retailers can leverage AI to make better, more personalized recommendations.
Connected TV
CTV is quickly stealing ad budgets away from the linear TV channel: While in 2019 linear’s market share of ad dollars was 30%, it’s projected to be less than half of that by 2026.
The shift is partly driven by CTV allowing advertisers to move from reach and awareness (historically the purposes of linear TV) towards audience targeting and performance measurement, similar goals of digital-first strategies.
We believe this trend is unlocking opportunities for advertisers to harness the storytelling power of TV, paired with new tools for targeting, measurement, and leveraging programmatic strategies.
For example, AI systems can analyze vast datasets in real time to make split-second optimizations that humans cannot. This can allow advertisers to refine their campaigns dynamically and reallocate budgets to better-performing placements on the fly.
For targeting, machine learning models can analyze viewing habits and demographics to pinpoint high-intent audiences that are likely to convert, refining segments in real time as behaviors shift. Generative AI takes personalization further by tailoring ad content to individual viewers, creating customized experiences that feel more engaging and less intrusive.
AI can also streamline creative production, enabling marketers to produce localized, personalized ad variations in seconds to connect more deeply with audiences. Generative AI tools assist with concept brainstorming, narrative development, storyboarding, and video production, enabling marketers to create compelling CTV ads in a fraction of the time. For example, HeyGen and Creatify are AI video generators and have functionality optimized for CTV. This enables production of ads that might incorporate changes like localized voiceovers, store-specific promotions, or personalized messaging, all crafted in seconds.
Finally, AI-driven analytics offer granular insights into campaign performance, from engagement to revenue attribution. These tools could create a feedback loop that improves every campaign. While it’s still early innings, we believe CTV can become an increasingly valuable channel for advertisers with larger budgets.
Tips & takeaways for marketers:
- Connected TV is poised to become a key channel for advertisers who have the budget for it.
- Generative AI can deliver hyper-personalized ads, as AI analytics shift and refine ads in real time.
The road ahead
AI is already having profound impacts on the entire advertising industry as well as the end consumers it reaches. Consumer behavior is changing, and ad platforms and marketers will need to adapt to keep up, just like they have always done.
We believe that new channels and platforms will gain traction while others fade; creating content will be easier but breaking through will be harder; and targeting and personalization will get even better. We also believe all of this is only just the beginning of AI’s impact on marketing.
This creates massive opportunities for everyone in the ecosystem:
- Disruptive technology startups have a once-in-a-generation opportunity to claim market share in the massive and evolving digital advertising landscape.
- Incumbent ad platforms have an advantage in large user bases and vast amounts of data—but they will need to innovate to make their channels effective and resonant in the changing landscape.
- Merchants will need to evolve to utilize new advertising capabilities to reach consumers on new platforms.
Google and Meta came out of Web 1.0 and 2.0 shifts, respectively. What will come out of the latest technology wave driven by AI?
Get in touch
We’re excited to continue to invest in companies disrupting advertising and marketing.
Are you building in this space? We want to talk! Reach out to brent@m13.co and whitney@m13.co.
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