Digital markets for consumer goods and services are inherently inefficient because the vast majority of tech investment is on the sell-side of the market. Despite this, most digital marketers provide highly personalized customer interactions less than 50% of the time, and most digital advertisers still waste an enormous amount of ad dollars on buyers that are not and will never be in-market for their products or services.
For decades, the tech industry has been selling brands and publishers a myth that more data and more analytics can make them omniscient about buyer behavior. While that investment dramatically improved the effectiveness of marketing and advertising, it hasn’t lived up to its potential because consumers are not equal players in the ecosystem. To be optimally efficient both sides of a market must have an equivalent ability to participate.
The emergence of Edge AI that enables data and Generative AI (GenAI) agents to reside on smartphones will flip consumer market models from enabling brands to control engagement with millions of consumers, to enabling consumers to intuitively control engagement with every brand and ad network with a single super-agent, not a cacophony of apps.
This creates the potential for consumer goods and services markets to approach the efficiency of stock markets as buyers will be able to programmatically control purchase intentions, and monetization models for publisher and brands can be based on commissions instead of impressions. Like search, social, and mobile, consumer super agents will transform digital marketing, advertising, and commerce, but will likely be adopted even faster.
According to U.S. Federal Reserve data, it took the Internet roughly 20 years to support $500B in retail sales. It took mobile roughly 15 years after the launch of the iPhone. GenAI could do it in less than 10, as scale accelerates scale.
For consumer super agents to be the universal front end to commerce requires that consumers possess their own data and AI which the next generation of smartphone chips and AI models are expected to support. Super agents can then be proactive market participants that identify products, assess offers, and automate purchases or ask permission to do so. Super agents can be trained with no more effort than managing a Spotify play list and will dramatically simplify consumer shopping. They can support replenishment and considered purchases, from household goods and groceries to fashion; they can make appointments, plan vacations, advise on auto, home, finance, education, and health care. They can curate offers as convergently or divergently as the user desires, consider substitutes or not based on consumer preference, and reveal users’ personal information only as needed (critical features missing from today’s platforms.)
To function, super agents require a rebalancing of consumer marketplaces in three major ways:
- Intuitive super agents: Consumers will want one GenAI super agent to manage all their purchasing, not a different agent for every brand, market, or product category. Super-agents will learn by watching organic consumer behavior and through conversation and function as next-gen super apps like WeChat and Alipay.
- Irrigating the customer data desert: Ironically, we’re still living in a retail world dominated by paper receipts. Technically there is no reason why consumers shouldn’t already have line-item visibility into all their household shopping regardless of how they pay. But retailers do not provide electronic receipts, nor do banks, payment processors, and credit card providers. Getting over the fear that giving consumers more data would result in less revenue is the greatest mindset shift needed for the market to evolve. Unlocking this data and feeding it though super agents would make markets for goods, services, and advertising far more efficient for both buyers and sellers. It will also inherently protect consumer data.
- Autonomous marketplace: Buyer and seller agents will need a global exchange that passes consumer bids to multiple platforms in which all sellers can respond regardless of their ecommerce presence (e.g. Amazon, Shopify, eBay, Etsy, etc.)
That brings us to two questions:
- Who will be the “Spotify” of super agents?
- Who will be the “NASDAQ” of AI marketplaces?
The “Spotify” of Super Agents
Spotify use cases are like those of household shopping — we tend to listen to our favorite songs over and over, we tend to like slight variations on song lists, and occasionally we want something special or completely different or a throwback from the past. Songs can be quickly liked and unliked, categories are easy to manage, and recommendations are presented in intuitive ways. It’s all a matter of taste as expressed by organic consumption and discovery behavior. Retail and advertising content is very similar. Consumers tend to repurchase their favorite products, sometimes need something new, or want to discover something completely different no matter how niche.
Super agents can communicate all this to ad networks, e.g. if a “no substitutes” tag is on a product, there’s no reason for a brand to pay to advertise to that buyer. If someone buys a car or truck it may be years before they are back in-market for those products, in the meantime all ads on any medium are a waste for both brands and buyers. GenAI will function as a chief of staff for the lifetime of a consumer across brands, channels, and life stages.
All the usual suspects will vie for dominance in this new era of super agents: Platforms such as Alipay, Amazon, Apple, Baidu, Google, Meta, Microsoft, TenCent, TikTok, WeChat, eCommerce players such as Shopify, customer experience companies such as Adobe and Salesforce. Payments companies such as Mastercard, Visa, and PayPal. AI players like OpenAI. Digital consultancies such as Accenture, Deloitte, Publicis/Sapient, etc. Or any combination thereof.
- The winners will wholly embrace the idea that the most important partners to share data with are customers. It is a bold proposition, but as the tech industry has proven again and again, fortune favors the bold.
Buyer Benefits
- Inherent privacy and consent: Super agents do not have to reveal why consumers are in the market for any specific item. The data that brands use for targeting such as demographics, click trails, social posts, lookalikes, transaction histories, weather, etc. are all weaker signals than intent. Personal information can be revealed progressively as needed to enhance offers and complete transactions.
- Better experience: Super agents provide automated access to the best deals on preferred products, services, and substitutes based on price, availability, delivery, convenience, etc. They will also obviate the need for third party cookies, stalker ads, and irrelevant marketing.
- Value-added insights: Examples might include analysis of savings potential across product categories, nutritional analysis from grocery purchases, ESG stats for the brands they patronize.
Seller Benefits
- Improved customer experience: Enabling consumers to tell brands when they are in market takes the guesswork out of marketing and brands don’t need to encroach on the private lives of buyers thereby reducing risks of privacy violations and poor customer experiences.
- Less tech expense: Brands don’t need massive customer data stores. They don’t need to send millions of emails or waste compute on trillions of personalization decisions when they know exactly who’s in and out of market every millisecond of the day.
- Lower go to market costs: Intent-based marketplaces will monetize based on transactions rather than impressions making the market much more transparent and measurable, resulting in lower customer acquisition costs, fraud, cart abandonment, and reliance on third party influencers.
The “NASDAQ” of AI Marketplaces
NASDAQ’s great innovation was to digitize, accelerate, and scale accessibility for stock transactions. It connects buyers and sellers and gives them an equivalent ability to control the terms of their market participation. At the transaction level consumer markets are not significantly different, but they are far more complex logistically. Super agents can advise consumers on the time, cost, and convenience of various delivery options, pick up at store, or how many stores they might have to visit to get desired products at the best deals.
The big advantages of a NASDAQ-like open platform include:
- Reduced costs for both buyers and sellers.
- Equal participation for sellers of all kinds from global brands to mom-and-pop shops from any platform.
A global AI-powered exchange offers many opportunities for tech companies to find their place in a new infrastructure from agent development, marketplace hosting, offer management, connectivity, security, governance, payments, logistics, and more.
Impact on Marketing and Advertising
Each new digital platform – the Internet, mobile, social, etc. – required new go-to-market practices. However, each of those innovations supported traditional ad models for a human audience. That will not go away, there is massive ad and influencer activity around stocks. But digital ad spend may undergo a major shift as brands and publishers get access to programmatic intent signals from super agents and overweight on paying commissions for transactions rather than fees for impressions.
Brands will have to find creative ways to extend incentive programs to encourage loyalty, advocacy, and lifetime value. Publishers will have to expedite intent pass-through to ad networks. Digital ad networks will have to be extended to traditional mass media. Those that move early at scale will have sustainable advantages. Brands and publishers that respond with the greatest immediacy and relevancy will have advantages. But they will have to make major changes to their go to market mindsets and practices and invest in new capabilities for supporting consumer data residency, dynamic real-time offers, frictionless logistics, and holistic support.
In other words, they’ll need an composable, intelligent infrastructure from intent signal to support call, from back office to front office, from supply chain to door drop. The payoff will be measured in $100Bs of revenue and trillions of dollars of market capitalization.
