Marketing’s AI Triad: Large Customer Model, Digital Twins, Co-Marketer

Published July 12-19, 2024

1

Coming Change

Digital marketing to maximise customer LTV (lifetime value) typically has three primary components: zero- and first-party data, segments and cohorts, and campaigns driven by martech platforms. There are other elements also: push channels to send messages, analytics to help personalise recommendations, and in the case of eCommerce companies, product catalogs. But at the core, it is about data, segments, and multi-channel campaigns.

The new world of agentic AI will transform all the three: customer data will be subsumed in a marketing LLM (what I call a “Large Customer Model”), segments will be represented by Digital Twins, and journey orchestration and campaign management done by marketing teams will be coordinated by a Co-Marketer. This new AI-powered triad will make marketing more efficient, helping businesses in their Profipoly Quest by maximising LTV for every customer and reducing CAC (customer acquisition cost).

This will be driven primarily by Agentic AI’s ability to use data to hyper-personalise conversations and anticipate intent, and then use Channels 2.0 (powered by Email’s triad of AMPs, Epps, and Ads) to influence actions by creating hotlines to solve the attention recession problem. In doing so, marketers will finally be able to address the three big profit killers: poor data, funnel friction, and marketing waste. Customer retention and development will take precedence over constant new acquisition. This will help businesses create a flywheel of exponential forever profitable growth.

Martech’s AI triad of LCM, Digital Twins, and Co-Marketer will add a customised AI layer fine-tuned for every business to bring a new level of customer understanding and personalised experiences across all touchpoints. It will also bring to fruition the oft-discussed vision of madtech (combining martech and adtech). It will enable early adopters to challenge leaders, thus creating new winners. In other words, Martech’s AI triad (along with Email’s triad) will reset consumer-facing industries.

To bring this vision to life, CEOs will need leaders who can combine a deep understanding of marketing and AI with a passion for not just growth but profits. While CMOs are well-placed to lead this next wave, they will need to unlearn and learn. AI’s “co-intelligence” will open new vistas, enabling them to create a “department of one” for a “segment of one.” The soon-to-be trillion-dollar advertising industry will be disrupted and so will Big Tech. A new world awaits.

In this essay, I will bring together my recent writings with some new thinking to discuss how Martech’s AI triad will reshape the digital landscape. In a subsequent essay, I will discuss how email is about to be transformed from an engagement channel to a frictionless conversion platform. Together, AI-powered martech and email herald new opportunities for businesses and vendors (email, CPaaS, and martech sellers).

2

Recent Writings

From CEO Memo: How Agentic AI can Power the Profipoly Quest: “What does the AI-first avatar of your business look like? While AI-ML models and Gen AI will help with supply chain management, process optimisation, customer services, and basic predictions, how will your customer relationships in a world where Agentic AI can enable large customer models, mirror worlds, digital twins for every customers, a Co-Marketer, and generative journeys? Are you ready for this coming future – beyond chatbots which help with coding and creatives generation? Are you prepared for a fundamental transformation in your customer relationships? How can you create this future first?…While generative AI will continue to improve productivity of every employee, the real opportunity lies is in the next generation of AI: the world of Agentic AI for the customer interface.  This world will have five building blocks: Large Customer Models, Mirror World, Digital Twins, co-Marketer, and Generative Journeys. Taken together, they will enable the three objectives of hyper-personalisation, the digital twin interacting with the Co-Marketer to simplify the engagement process, and win-win journeys which are value-maximising for both the brand and the customer to enable faster conversions.

From Martech’s 10+1 Foundations in the AI Age:

1. Unistack: A unified technology stack that integrates various martech functionalities into a single platform for better data consistency and reduced complexity.
2. Unichannel: Seamless integration of multiple communication channels to ensure consistent and synchronized messaging across all platforms.
3. Large Customer Model: Advanced models built on extensive customer data to create dynamic, real-time evolving profiles for hyper-personalization.
4. Digital Twins: AI-powered replicas of individual customers predicting needs and behaviors for personalized interactions at scale.
5. Co-Marketer: An AI-powered marketing assistant that collaborates with human marketers to optimize segmentation, campaign planning, content creation, and customer journeys.
6. Mirror World: A virtual environment where AI agents can simulate and test various customer scenarios and strategies, allowing for refined approaches before real-world deployment.
7. Generative Journeys: Dynamic, adaptive customer journeys that leverage AI to create personalized, real-time engagement paths, ensuring smooth transitions through various stages of customer interaction.
8. Bundled Kaizen Services: Continuous improvement services integrated into martech offerings, combining human expertise with automated enhancements for evolving customer needs.
9. Profishare: A profit-sharing model where martech companies earn revenue based on the incremental profits generated for their clients, aligning interests and ensuring mutual success.
10. B2C Business/Platform: Owning and operating a B2C platform to demonstrate the efficacy of martech solutions, providing real-world performance evidence and building client trust.
11. Profits: The foundation of business sustainability, allowing martech companies to invest in innovation and withstand market fluctuations, ensuring long-term success and control.

3

Large Customer Models

This is what the new AI-first Martech stack look like:

The Large Customer Model is at the heart of this stack. In Large Customer Model: Foundation for AI-first Martech, I discuss the three layers comprising the LCM:

1. Generic Foundational Models: These include advanced AI models like ChatGPT, Claude, and Gemini, which provide the baseline capabilities for understanding and generating language, sentiment analysis, and more. These models serve as the backbone for further customisation and development.
2. Marketing (“Madtech”) Foundational Model: This layer is built using non-PII data aggregated across various businesses, industries and channels to enhance marketing strategies and insights. This is where the intelligence from martech and adtech (termed “madtech”) platforms can be unified to provide a comprehensive view of customer interactions across different touchpoints, improving targeting and personalisation. This allows for the development of industry-specific and channel-specific insights marketing tactics.
3. Enterprise Model: This layer incorporates PII data unique to the enterprise’s customer base, enabling deeper personalisation and precision in customer interactions. It helps tailor marketing efforts to individual customer needs and preferences, enhancing engagement and loyalty.

Data is at the heart of the LCM. There are multiple sources of data:

• Customer Data Platform (CDP): Demographic and transactional data residing within a “customer data warehouse” (as termed by Gartner).
• Marketing Automation Platforms: Behavioural data across the brand’s properties (websites, apps) and channels (opens, clicks).
• Adtech Platforms: Offsite data for segments (e.g., best customers, churned customers) aggregated via platforms like Google and Meta, including web content, search intelligence, and social media insights.
• Product Enrichment: Data enhancing catalog attributes and descriptions for better search and product discovery.

These become the 5 Cs of LCM data:

1. Customers: Detailed profiles and preferences
2. Channels: Data from all communication and interaction channels
3. Cohorts: Grouped customer segments based on behaviours and characteristics
4. Catalog: Product and service data with enriched attributes
5. Conversations: Interaction data, including customer service exchanges and social media engagements

The more the data, the better will be the messaging, communications, and targeting leveraging all the 3 AI variants: predictive (forecasting customer behaviour and trends), generative (creating personalized content and interactions), and agentic (enabling autonomous customer interaction agents that can make decisions and take actions).

By integrating these elements, the LCM provides a comprehensive framework for understanding and engaging customers, ensuring that marketing efforts are highly personalised, effective, and adaptive to changing customer needs and behaviours.

4

Digital Twins

The Large Customer Model allows for the creation of two types of digital twins: Segment Twins and Singular Twins.

Segment Twins are AI-powered models representing groups of customers who share similar behaviours, preferences, and demographic characteristics. By leveraging data from various sources such as customer data platforms (CDPs), marketing automation tools, and adtech platforms, Segment Twins analyse vast amounts of behavioural and interaction data. This includes interests, engagement patterns, and demographic details from platforms like Google, Meta, Instagram, and TikTok. These twins provide a comprehensive view of customer segments, enabling marketers to tailor strategies more effectively. By simulating these segments, brands can craft targeted and impactful marketing campaigns, ensuring higher relevance and engagement. More interestingly, marketers can converse with these twins to better understand the mindset. [See this post by Gautam Mehra.]

Singular Twins are AI-powered replicas of individual customers, capturing detailed insights into their preferences, behaviours, and interactions. These dynamic models continuously evolve, reflecting real-time customer journeys. By aggregating data from sources like CRM systems, purchase histories, browsing patterns, social media interactions, and demographic information, Singular Twins provide a comprehensive understanding of each customer. Operating within a simulated environment, or “mirror world,” Singular Twins interact with the brand’s Co-Marketer, an AI-powered assistant, to test various scenarios and identify optimal engagement strategies. This facilitates true 1:1 personalisation, allowing brands to deliver highly targeted and effective marketing campaigns by anticipating next actions. The integration of Singular Twins enables brands to anticipate customer needs, make tailored recommendations, and optimise customer journeys, ensuring every touchpoint is personalised.

The integration of AI-powered Segment Twins and Singular Twins will revolutionise marketing by providing unparalleled insights and personalisation. Segment Twins enable marketers to understand and target customer groups with precision, crafting campaigns that resonate deeply with specific demographics. Singular Twins, on the other hand, offer a granular view of individual customers, allowing for real-time, 1:1 personalised interactions. Together, these digital twins transform marketing from a broad, impersonal approach to a highly tailored strategy, driving engagement, customer satisfaction, and ultimately, higher conversion rates and loyalty. This shift not only enhances marketing efficiency but also fosters stronger, more meaningful customer relationships, positioning brands for sustained success in the AI era.

5

Co-Marketer

At the heart of the AI-powered transformation of marketing lies the concept of the Co-Marketer, an AI-driven assistant designed to enhance and optimise marketing efforts. As the third pillar of the new Martech AI Triad, alongside Large Customer Models (LCMs) and Digital Twins, the Co-Marketer promises to revolutionise the way marketing departments operate, bringing unprecedented efficiency, personalisation, and strategic insight.

A Co-Marketer is an advanced Agentic AI assistant that collaborates with human marketers to perform a range of tasks, from segmentation and campaign planning to content creation and journey optimization. Unlike traditional tools that merely assist with data analysis, the Co-Marketer acts as a dynamic partner, capable of reasoning, decision-making, and executing complex marketing strategies in real-time by creating sub-agents on demand for specific tasks.

Here is how the role Co-Marketer can transform Modern Marketing:

1. Data Aggregation and Analysis: The Co-Marketer starts by aggregating vast amounts of data from various sources, including CRM systems, purchase histories, browsing patterns, social media interactions, and demographic information. This comprehensive data collection forms the foundation for all subsequent actions.
2. Predictive Capabilities: Leveraging machine learning algorithms and LCMs, the Co-Marketer can predict customer behaviour, identify emerging trends, and forecast campaign performance. This predictive power enables marketers to proactively adjust strategies for maximum impact.
3. Content Creation and Personalisation: By understanding individual customer preferences and behaviours, the Co-Marketer assists in generating highly personalised content. This includes crafting messages, designing journeys, producing creative assets, and optimising content for different channels to ensure each customer receives a unique and relevant experience.
4. Campaign Planning and Execution: The Co-Marketer can autonomously plan and execute marketing campaigns. It identifies the most effective channels, allocates budgets, and continuously monitors campaign performance, making real-time adjustments to optimise results.
5. Real-Time Optimisation: With its ability to analyse data in real-time, the Co-Marketer provides ongoing optimization recommendations. Whether it’s tweaking a live campaign, adjusting messaging strategies, or reallocating resources, the AI ensures that marketing efforts are always aligned with the latest insights.
6. Collaborative Decision-Making: Acting as a true co-intelligence, the Co-Marketer engages in interactive dialogues with human marketers. It provides recommendations, explains its reasoning, and adapts based on feedback, fostering a collaborative environment that enhances overall decision-making processes.

For Chief Marketing Officers (CMOs), the Co-Marketer is an invaluable asset that transforms the marketing landscape. Here are some key benefits:

1. Enhanced Efficiency: By automating repetitive tasks and providing data-driven insights, the Co-Marketer frees up human marketers to focus on strategic and creative initiatives. This increased efficiency leads to higher productivity and better use of resources.
2. Improved Personalization: The Co-Marketer’s unparalleled ability to deliver hyper-personalised experiences ensures that customers receive relevant and engaging content, which enhances satisfaction and loyalty.
3. Strategic Insights: With its advanced analytics and predictive capabilities, the Co-Marketer offers CMOs deep insights into market trends, customer behaviours, and campaign performance. These insights enable more informed strategic decisions.
4. Scalable Solutions: The Co-Marketer’s AI-driven approach allows for scalable marketing solutions that can adapt to the needs of any business, from small startups to large enterprises.
5. Outcome-Based Optimisation: By continuously learning and optimising based on real-time data, the Co-Marketer ensures that marketing strategies are always aligned with business goals, leading to improved ROI and long-term success.

The Co-Marketer is the product martech companies will deliver in partnership with adtech vendors, with its efficacy driven by the strength of the underlying Large Customer Model. The Co-Marketer will subsume with it the AI-powered Digital Twins. From conversations with Segment Twins to personalised messaging for Singular Twins, the Co-Marketer is the future of marketing, promising a “Department of One” for a “Segment of One.”

The Co-Marketer represents a groundbreaking product that martech companies will develop in collaboration with adtech vendors, underpinned by the robust capabilities of the Large Customer Model. By integrating AI-powered Digital Twins, the Co-Marketer offers unparalleled personalisation and engagement. It enables marketers to have insightful conversations with Segment Twins and deliver tailored messaging to Singular Twins. As the embodiment of the future of marketing, the Co-Marketer transforms traditional approaches, creating a “Department of One” for a “Segment of One,” thereby bringing precision and efficiency to modern marketing.

6

Maya, the Modern Marketer – 1

Based on my writings, I asked ChatGPT and Claude to write about a day in the life of Maya, a modern marketer. Here is ChatGPT’s version.

Maya, the Chief Marketing Officer (CMO) of a leading eCommerce company, starts her day early, powered by the latest advancements in marketing technology. With a cup of coffee in hand, she opens her dashboard powered by the Martech AI Triad—Large Customer Model (LCM), Digital Twins, and Co-Marketer. This triad not only revolutionizes her marketing strategies but also makes her role more efficient and impactful.

6:00 AM – Reviewing Insights with the Large Customer Model

Maya begins her day by reviewing the latest insights from the Large Customer Model. This AI-driven model aggregates vast amounts of data, including CRM records, purchase histories, browsing patterns, and social media interactions. The LCM provides Maya with a comprehensive view of her customers, predicting trends and behaviors. Today, it highlights an emerging trend among young professionals showing increased interest in sustainable products.

7:00 AM – Segment Twins Analysis

Next, Maya delves into the Segment Twins. These AI-powered models represent groups of customers sharing similar behaviors and preferences. By simulating these segments, Maya can understand the collective mindset and preferences of each group. She examines a Segment Twin for young professionals interested in sustainability. The insights reveal that they value transparency in sourcing and prefer eco-friendly packaging.

8:00 AM – Strategy Session with the Co-Marketer

Maya then moves to a strategy session with the Co-Marketer, her AI-powered assistant. The Co-Marketer helps her plan campaigns, create content, and optimize customer journeys. Today, it suggests a multi-channel campaign focused on the new sustainable product line, tailored specifically for the segment identified earlier. It also recommends budget allocations across different channels to maximize engagement and ROI.

10:00 AM – Content Creation and Personalization

With the strategy in place, Maya collaborates with the Co-Marketer to create personalized content. Leveraging AI, the Co-Marketer generates creative assets and custom messages for each customer segment. For the sustainability-focused young professionals, it crafts messages emphasizing eco-friendly practices and transparent sourcing. The content is tailored for various platforms, including email, social media, and the company’s website.

12:00 PM – Lunch Break and Reflection

During lunch, Maya reflects on how the AI triad has transformed her role. The combination of LCM, Segment Twins, and Co-Marketer has streamlined her workflow, allowing her to focus on strategic initiatives rather than getting bogged down by data analysis and campaign management.

1:00 PM – Monitoring Campaigns in Real-Time

After lunch, Maya monitors the ongoing campaigns. The Co-Marketer continuously analyzes real-time data, providing optimization suggestions. It detects that the email open rates are lower than expected for a particular segment. Maya quickly adjusts the subject lines and content based on the Co-Marketer’s recommendations, ensuring higher engagement.

3:00 PM – Interacting with Singular Twins

Maya spends the afternoon interacting with Singular Twins—AI-powered replicas of individual customers. These twins offer deep insights into the preferences and behaviors of each customer. Maya identifies a few high-value customers showing signs of disengagement. She uses the Co-Marketer to send personalized offers and re-engagement messages, tailored to their unique interests and past behaviors.

5:00 PM – Preparing for Tomorrow

As the day winds down, Maya reviews the overall performance of her marketing efforts. The AI triad’s predictive capabilities and real-time adjustments have driven significant improvements in customer engagement and sales. She sets up a meeting for the next morning to discuss long-term strategies with her team, informed by the insights gained throughout the day.

6:00 PM – Closing the Day

Maya ends her day feeling accomplished. The AI-powered tools have not only enhanced her efficiency but also allowed her to deliver personalized experiences to her customers, driving loyalty and satisfaction. She looks forward to the continuous evolution of marketing technology, knowing that it will only make her role more exciting and impactful.

By leveraging the power of the Large Customer Model, Segment and Singular Twins, and the Co-Marketer, Maya exemplifies the modern marketer, seamlessly integrating AI into her daily workflow to drive success and innovation.

7

Maya, the Modern Marketer – 2

This is Claude’s story about a day in the life of Maya, a modern marketer.

Maya takes a sip of her coffee as she settles in at her desk, ready to start another day as CMO at TrendSetters, a fast-growing fashion retailer. She opens her laptop and is greeted by Claude, her trusted AI Co-Marketer.

“Good morning Maya!” Claude’s friendly voice chimes. “I’ve prepared the daily briefing for you. Shall we dive in?”

“Absolutely, let’s do it,” Maya replies. Claude begins walking through the key insights and recommendations for the day.

“I had some great conversations with our key Segment Twins overnight,” Claude explains. “It looks like our eco-conscious millennial segment is really resonating with the new sustainable denim line. I’m seeing high engagement and purchase intent in that group. I’d recommend boosting our spend there by 15%.”

Maya nods. “Great suggestion, let’s do that. What else?”

“I noticed Jessica Smith, one of our highest-value customers, was browsing the site last night,” Claude continues. “Based on her Singular Twin, I predict she’s likely to purchase one of the new summer dresses in the next 2 days. I’ve drafted a personalized email with tailored recommendations for her. Want me to send it?”

“Yes, go ahead,” Maya confirms. “I’m sure she’ll love your suggestions. You know our customers so well!”

As the briefing wraps up, an alert pops up on Maya’s screen. “Maya, I’m detecting an emerging trend – looks like ’90s retro fashion is starting to take off on social media. Shall I generate some creative concepts in that style for your review?”

“Oh wow, good catch!” Maya exclaims. “Yes, put together a few ideas and we can discuss this afternoon.”

Maya spends the rest of the morning in strategy meetings, confident that Claude is working behind the scenes to optimize their campaigns and generate valuable insights. Around lunchtime, she gets a ping from Claude.

“I’ve got those ’90s style creative mockups ready for you. Want to take a look? I’ve already tested them with our Segment Twins and they’re projecting a 10% lift in engagement.”

“They look amazing!” Maya replies as she scrolls through the images. “You’ve really nailed that retro vibe. Let’s launch these as soon as possible. Thanks Claude!”

As the day winds down, Maya checks the real-time campaign dashboards one last time. Everything is looking great – engagement is up, conversion rates are exceeding targets, and Claude’s intelligent optimizations are driving strong performance across the board.

Before logging off, Maya leaves a final note. “Fantastic work today Claude! Your insights and execution are invaluable. I don’t know what I’d do without you!”

“Thank you Maya!” Claude responds warmly. “I’m always here to help. See you bright and early tomorrow – I’ll have the coffee ready! Well, virtual coffee at least.”

Maya smiles as she closes her laptop. Working with an AI Co-Marketer like Claude has transformed her role as CMO – allowing her to focus on strategy while Claude perfectly orchestrates the details. She can’t imagine going back to the old way of doing marketing. The future is here, and it’s AI-powered.

8

AI Inputs

I asked ChatGPT, Claude, and Gemini to list the following:

• 3 marketing breakthroughs – what will be possible in the future that is not possible today
• 3 additional ways tomorrow’s AI can improve marketing
• 3 coming innovations in marketing that I have missed

ChatGPT

3 Marketing Breakthroughs

1. Hyper-Personalized Interactions: The integration of AI-powered Singular Twins enables hyper-personalized customer interactions at an unprecedented scale. This level of personalization ensures that every communication is tailored to the individual’s preferences and behaviors, significantly enhancing engagement and conversion rates.
2. Predictive Customer Engagement: With the advanced predictive capabilities of the Large Customer Model (LCM), marketers can anticipate customer needs and behaviors before they happen. This allows for proactive engagement strategies, ensuring that marketing efforts are always one step ahead of customer expectations.
3. Real-Time Campaign Optimization: The Co-Marketer’s ability to continuously analyze data in real-time and provide optimization suggestions ensures that marketing campaigns are always aligned with the latest insights. This real-time adjustment capability enhances the effectiveness and efficiency of marketing strategies, leading to better ROI.

3 Additional Ways Tomorrow’s AI Can Improve Marketing

1. Dynamic Content Creation: AI can autonomously create and personalize content based on individual customer data. This includes generating custom messages, designing creative assets, and producing tailored marketing materials for different channels, ensuring relevance and engagement.
2. Enhanced Customer Journey Mapping: By leveraging Digital Twins, AI can map out and optimize the entire customer journey, identifying pain points and opportunities for improvement. This holistic view ensures a seamless and engaging experience for customers across all touchpoints.
3. Advanced Sentiment Analysis: AI’s capability to perform deep sentiment analysis on social media interactions and customer feedback can provide valuable insights into customer opinions and emotions. This helps marketers tailor their strategies to address customer concerns and capitalize on positive sentiments.

3 Coming Innovations in Marketing

1. Voice-Activated Marketing: As voice assistants become more prevalent, AI will enable brands to engage with customers through voice-activated marketing strategies. This includes personalized recommendations and interactions via smart speakers and other voice-enabled devices.
2. AI-Driven Creative Testing: AI will allow for rapid testing and iteration of creative concepts. By automatically generating variations and analyzing performance, AI can help identify the most effective creative elements for different customer segments.
3. Blockchain Integration for Transparency: Integrating blockchain technology with AI-driven marketing efforts can enhance transparency and trust. Blockchain can provide verifiable data on customer interactions and ad placements, ensuring accountability and reducing fraud in digital marketing campaigns.

Claude

3 marketing breakthroughs that will be possible in the future

1. Hyper-personalization at scale: With Large Customer Models, Digital Twins, and Co-Marketers, businesses will be able to deliver truly 1:1 personalized experiences to every customer. The AI will deeply understand each individual’s preferences and behaviors, enabling personalized content, recommendations, and journeys that dynamically adapt in real-time.
2. Unified customer understanding: The Large Customer Model will aggregate data across all touchpoints to create a comprehensive, 360-degree view of each customer. This will break down data silos and enable holistic customer insights and seamless omnichannel experiences.
3. Collaborative human-AI marketing: The Co-Marketer AI will work alongside human marketers, augmenting their capabilities. It will handle data analysis, predictions, and campaign orchestration, freeing up marketers to focus on strategy, creativity, and building customer relationships. This human-AI collaboration will lead to better decisions and breakthrough marketing outcomes.

3 additional ways tomorrow’s AI can improve marketing

1. Proactive trend detection: AI could continuously monitor diverse data sources to identify emerging trends, customer sentiments, and market shifts. It would proactively alert marketers to arising opportunities or threats, enabling businesses to stay ahead of the curve and quickly capitalize on new trends.
2. Automated content generation: Advanced language models and generative AI could create highly persuasive, tailored marketing content at scale. This could include ad copy, email content, landing pages, product descriptions, social media posts, and more – all automatically generated and optimized for each individual customer.
3. Predictive campaign simulation: Before launching campaigns, AI could simulate and test them in a virtual “mirror world” environment. It would predict performance, identify potential issues, and suggest optimizations. This would allow marketers to refine campaigns and maximize impact before deploying them to real customers.

3 potential marketing innovations

1. Emotion-aware AI: Future AI models may be able to analyze user-generated content, such as social media posts or product reviews, to understand the emotions and sentiment behind the text. This emotional intelligence would allow for more empathetic, resonant marketing that deeply connects with customers’ emotional needs and desires.
2. Real-time marketing in the metaverse: As virtual and augmented reality technologies advance, AI-powered marketing could expand into immersive metaverse environments. AI agents could interact with users’ avatars in real-time, providing personalized recommendations, offers, and experiences seamlessly integrated into the virtual world.
3. Quantum computing-powered optimization: As quantum computing matures, it could be leveraged to solve complex marketing optimization problems. Quantum algorithms could rapidly identify the most effective campaign strategies, budget allocations, and targeting parameters from vast combinatorial solution spaces, leading to unprecedented marketing performance.

Gemini

3 Marketing Breakthroughs

1. Hyper-personalized customer journeys: AI-powered marketing tools will be able to create dynamic and adaptive customer journeys. This means that marketing messages and interactions will be tailored to each individual customer in real-time, based on their unique preferences and behaviors.

2. Agentic AI for customer interaction: In the future, AI will be able to handle customer interactions in an autonomous way. This means that AI-powered chatbots or virtual assistants will be able to have conversations with customers, answer their questions, and even resolve issues without human intervention.
3. Digital twins for customer insights: AI will be able to create digital representations of individual customers (Singular Twins) and customer segments (Segment Twins). These digital twins will be used to generate insights into customer behavior and preferences, which can then be used to improve marketing campaigns.

3 Ways Tomorrow’s AI Can Improve Marketing

1. Improved data analysis and insights: AI can analyze large amounts of data from various sources to identify trends and patterns that would be difficult for humans to see. This can help marketers to better understand their customers and target their campaigns more effectively.

2. Content creation and personalization: AI can be used to create personalized marketing content, such as emails, social media posts, and website copy. This content can be tailored to the individual customer’s interests and needs.
3. Real-time campaign optimization: AI can be used to monitor marketing campaigns in real-time and make adjustments as needed. This can help to ensure that campaigns are performing at their best and that they are reaching the right audience.

3 Coming Marketing Innovations

1. Privacy-preserving Marketing: With increasing consumer concerns about data privacy, there’s a growing trend towards privacy-preserving marketing techniques. This involves using anonymized or aggregated data to target customers and measure campaign effectiveness, without compromising individual user privacy. Techniques like contextual targeting and privacy-preserving machine learning are being developed to achieve this.
2. Shoppable Livestreaming: Livestreaming platforms are being leveraged by brands to directly connect with audiences and promote products in real-time. This approach allows for live product demonstrations, influencer marketing integration, and real-time audience interaction, all within a purchase-friendly environment.
3. AI-powered customer experience personalization: This goes beyond content creation. Imagine a website recommending products you’d love, a chatbot that perfectly understands your needs, and emails that adapt to your interests – all powered by AI that personalizes your entire journey with the brand.