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Hightouch Named a Leader in the 2025 Gartner® Magic Quadrant™ for Customer Data Platforms

Jan 30, 2026

Hightouch Emerges as a Leader in Gartner’s 2025 Magic Quadrant for Customer Data Platforms

In a major milestone for Hightouch, the company has been named a Leader in the 2025 Gartner Magic Quadrant for Customer Data Platforms (CDPs). This recognition is particularly noteworthy as it marks Hightouch’s first-ever inclusion in this esteemed industry report, underscoring its growing influence and innovation in customer data management.

Innovating Customer Data Activation

Gartner’s evaluation of Hightouch focused primarily on two criteria: Completeness of Vision and Ability to Execute. Hightouch stands out by enabling organizations to activate customer data directly from their cloud data warehouses such as Snowflake and Databricks. This approach allows companies to deliver personalized, real-time customer experiences across marketing, sales, and engagement channels — notably without the need to duplicate or move data.

This warehouse-native method reflects a broader trend in the marketing technology sector, moving away from traditional data silos and towards composable architectures that prioritize flexibility and speed. Hightouch’s platform not only increases data freshness but also supports AI-driven marketing strategies, further empowering businesses to optimize multi-channel campaigns effectively.

Embracing the Future of Marketing Technology

According to Tejas Manohar, co-founder of Hightouch, the recognition highlights how composable and warehouse-native solutions are reshaping the CDP landscape. Companies leveraging these technologies can expect to see enhanced data uptime, better integration capabilities, and more agile customer engagement techniques. This transition points to a future where organizations can make smarter decisions based on timely, actionable insights from their customer data.

Key Insights

What does it mean for Hightouch to be named a Leader? Being named a Leader validates Hightouch’s vision and execution in transforming customer data platforms by leveraging cloud data warehouses.
How does Hightouch’s platform improve marketing efforts? By activating customer data without duplication, marketers gain access to the freshest data, enabling precise personalization and real-time campaign adjustments.
Why is composable architecture important in CDPs? Composable architecture allows businesses to build modular systems that are more flexible, scalable, and easier to integrate with emerging technologies like AI.

Conclusion

Hightouch’s inclusion as a Leader in Gartner’s 2025 Magic Quadrant underscores a significant shift in how enterprises approach customer data activation. With its innovative warehouse-native platform, Hightouch is well positioned to help businesses harness the full potential of their customer data to deliver timely, personalized experiences. As more companies adopt composable and AI-augmented marketing technologies, platforms like Hightouch are set to play a pivotal role in shaping the future of customer engagement.

Source: https://martechseries.com/predictive-ai/ai-platforms-machine-learning/hightouch-named-a-leader-in-the-2025-gartner-magic-quadrant-for-customer-data-platforms/

How to optimize for AI search: 12 proven LLM visibility tactics

Jan 30, 2026

William Gu

Marketing AI Team @ MKTGAGENT.AI

How to Optimize for AI Search: 12 Proven LLM Visibility Tactics

Introduction As artificial intelligence (AI) search technology advances, businesses and content creators face new challenges and opportunities to maintain visibility. Leveraging insights from leading SEO experts, this article explores 12 effective strategies to optimize content for AI-driven search environments, particularly focusing on large language models (LLMs). Readers will gain a clear understanding of how to adapt SEO techniques to this evolving landscape while ensuring their brand remains prominent.

Key Strategies for AI Search Optimization

Leverage Advertorials and Paid Syndication Paid content distribution and advertorials can amplify brand reach by placing your message in trusted publications and platforms. These tactics help generate valuable backlinks and improve content discovery within AI search results.
Tailor Content for Diverse Audiences Creating tailored content that appeals to different segments broadens your overall visibility. AI systems prioritize relevance and context, so understanding audience needs and addressing them explicitly boosts search performance.
Maintain Homepage Clarity Your homepage serves as a critical anchor for brand identity. Clear messaging and well-organized information help AI understand your core offerings and improve brand signal consistency.
Optimize Footers for Brand Signals Often overlooked, footers are useful for reinforcing brand information such as contact details, social links, and trademarks. Enhancing these elements supports stronger AI recognition of your brand.
Actively Shape Brand Narratives Managing your brand story across digital channels ensures coherent messaging. AI search engines increasingly factor brand reputation and narrative coherence into ranking algorithms.
Keep Content Fresh Regularly updating content signals vitality, an important ranking factor in AI-driven search. Freshness can be the edge over competitors whose content remains static.
Utilize Social Media Effectively Social media posts can have a quick impact on AI search visibility by driving traffic and generating engagement signals that AI systems may interpret positively.

Building on Solid SEO Foundations While AI-specific optimization tactics—often termed AI Experience Optimization (AEO)—bring benefits, they are most effective when grounded in robust traditional SEO principles. This includes keyword research, site structure, mobile optimization, and quality backlinks.

Key Insights

Why is freshness important for AI search ranking? Fresh content signals to AI algorithms that your website is active and relevant, helping boost its visibility.
How can tailored content improve LLM search performance? Tailored content aligns better with user intent, making it easier for AI to match the right queries with your pages.
What role does brand narrative play in AI search? A consistent and well-shared brand story enhances trust signals, contributing to higher search rankings.

Conclusion Optimizing for AI search requires a balanced approach that combines innovative AI-focused tactics with foundational SEO best practices. Businesses that stay adaptive by maintaining content freshness, refining brand signals, and engaging diverse audiences will position themselves for success in the evolving AI search landscape. Continued attention to these strategies will be critical as AI technologies advance and reshape the digital search environment.

Source: https://searchengineland.com/optimize-ai-search-llm-visibility-tactics-468106

Visual Fan-Out: Make Your Products and Destinations Discoverable in AI Mode

Jan 30, 2026

William Gu

Marketing AI Team @ MKTGAGENT.AI

Visual Fan-Out: Revolutionizing Discoverability in AI-Powered Search

Introduction

As search technology evolves, so does the way we interact with images online. A groundbreaking shift known as Visual Fan-Out is transforming how images are leveraged in search engines, especially within Google’s AI Mode. This innovation moves beyond simply finding images to exploring the rich details contained within them, unlocking new opportunities for eCommerce and travel industries to make products and destinations more discoverable.

Understanding Visual Fan-Out

Visual Fan-Out represents a paradigm change where an image is seen not as a single searchable entity but as a multi-dimensional scene. AI algorithms analyze various objects and attributes within an image, allowing users to search through images by their elements. For example, instead of searching for “beach photo,” the system can identify and branch into queries about the type of beach, the attire worn by people in the photo, or items visible in the scene.

This comprehensive approach allows for a richer, more nuanced understanding of visuals, enhancing user engagement and the overall search experience.

How Visual Fan-Out Works

The process involves several phases:

Decomposition: Breaking down the image into its fundamental visual components.
Branching: Simultaneously exploring multiple related queries stemming from different elements in the image.
Grounding: Linking these queries to real-world entities to provide context and relevance.
Synthesis: Combining data to create actionable outputs that improve content interaction.

Structured data plays a critical role by making product attributes machine-readable, which enhances the discoverability and optimization of online items.

Impact on eCommerce and Travel

For retailers and travel marketers, Visual Fan-Out offers a powerful way to showcase products and destinations. Detailed image analysis means customers can discover specific items within a scene or explore travel destinations through layered visual content. This increases the chances of conversion by matching user queries more closely with the actual visual content, while also improving search engine rankings through enriched data.

Key Insights

What makes Visual Fan-Out a significant advancement? It transforms image search from a single query response to a branching exploration of image elements, providing a deeper user experience.
How can businesses leverage this? By ensuring product and destination attributes are structured and machine-readable, businesses can optimize visibility in AI-driven searches.
What industries benefit most? eCommerce and travel industries stand to gain significantly by improving customer engagement and discoverability.
What is essential for successful implementation? Adoption of structured data standards to fully unlock Visual Fan-Out’s capabilities.

Conclusion

Visual Fan-Out is set to redefine how users interact with visual content online, turning images into dynamic gateways to information. Businesses that embrace this technology and optimize their images with structured data will enhance product and destination discoverability, offering richer experiences that align with modern AI search behaviors. As AI continues to evolve, Visual Fan-Out exemplifies the innovative edge that forward-thinking companies need to stay competitive in a visually-driven digital landscape.

Source: https://wordlift.io/blog/en/visual-fan-out-in-ai-mode/

When search performance improves but pipeline doesn’t

Jan 30, 2026

William Gu

Marketing AI Team @ MKTGAGENT.AI

When Search Performance Improves but the Pipeline Doesn’t: Bridging the Gap Between SEO and Sales

Introduction

Many organizations celebrate rising SEO metrics such as improved search rankings and increased web traffic. However, a common dilemma arises when these strong search performance indicators fail to translate into tangible business outcomes like an expanding sales pipeline or higher revenue. This disconnect signals a deeper issue that extends beyond the search team’s optimization efforts.

Understanding the Disconnect

While SEO teams may successfully boost visibility and attract visitors, the journey from a website visit to a qualified sales lead or customer is influenced by multiple factors. These factors often involve different teams or systems, creating gaps where potential conversions can stall or drop off.

Key Challenges Contributing to the Gap

Misalignment of Search Intent and Sales Expectations: Visitors’ search intentions may not always match the sales team’s target buyer profiles or offerings, leading to poor lead quality.
Conversion Friction on Websites: Even with good search traffic, complicated or unclear on-site user experiences can prevent visitors from completing desired actions like filling out forms.
Lead Qualification Gaps: Inconsistent or inadequate criteria for qualifying leads can result in promising prospects being overlooked or mishandled.
Sales Handoff Issues: The transition from marketing to sales requires smooth communication and processes; any breakdown here delays or derails follow-ups.
Measurement Blind Spots: Without integrated tracking and comprehensive analytics, it’s difficult to attribute business success accurately to search efforts or identify where prospects drop out.

Collaborative Solutions for Alignment

Effectively turning improved search performance into a growing pipeline demands strong collaboration across marketing, sales, and analytics teams. Clear definitions of success metrics that encompass revenue and sales growth are crucial. Implementing joint strategies ensures search intent aligns with buyer needs, onsite experiences optimize conversions, steps in lead qualification are agreed upon, and sales handoff protocols are established and monitored.

Key Insights

Why does strong SEO performance sometimes fail to translate into sales? Because factors beyond search—like lead qualification and sales coordination—play critical roles.
How can organizations reduce conversion friction? By simplifying user experience post-click and aligning content with the buyer journey.
What role does team collaboration play? It is essential to connect marketing and sales processes for seamless lead management and follow-up.
How important are accurate metrics? They enable clear understanding of where leads come from and why potential sales may be lost.

Conclusion

For organizations experiencing a disconnect between strong SEO results and a stagnant pipeline, the solution lies in integrating efforts across functions and refining the entire funnel—from search intent to customer acquisition. By fostering collaboration, clarifying success measures, and optimizing both lead qualification and sales engagement, businesses can ensure that improved search performance truly drives revenue growth.

Source: https://searchengineland.com/when-search-performance-improves-but-pipeline-doesnt-468073

Why agentic AI is different from traditional marketing automation

Jan 30, 2026

William Gu

Marketing AI Team @ MKTGAGENT.AI

Why Agentic AI is Transforming Marketing Beyond Traditional Automation

Marketing automation has long been a staple for businesses aiming to streamline their campaigns, but the emergence of agentic AI is redefining what automation can achieve. Unlike traditional marketing tools that strictly follow preset instructions, agentic AI empowers systems to independently conceive, execute, and enhance marketing strategies with minimal human intervention. This shift marks a significant evolution in how companies connect with their customers and manage campaign operations.

Understanding the Difference: Agentic AI vs. Traditional Marketing Automation

Traditional marketing automation relies heavily on predefined rules and manual input to carry out repetitive tasks such as email scheduling or ad placements. In contrast, agentic AI acts autonomously, utilizing real-time data to make decisions, dynamically adjusting campaigns on the fly, and optimizing outcomes based on continuous learning.

This autonomous capability means that agentic AI can take initiative: it formulates marketing strategies, manages multiple channels simultaneously, and refines lead nurturing processes to elevate customer engagement more effectively than ever before.

Key Capabilities of Agentic AI in Marketing

Personalized Customer Experiences: By analyzing complex behavior and interaction data, agentic AI crafts tailored messaging and offers that resonate personally with each customer, significantly boosting conversion rates.
Cross-Channel Campaign Management: It seamlessly integrates efforts across email, social media, search, and other platforms, ensuring consistent and harmonized outreach.
Automated Testing and Budget Allocation: Agentic AI continuously tests different campaign variables and optimizes budget use to maximize ROI without constant human oversight.

Real-World Applications and Impact

Businesses adopting agentic AI benefit from faster campaign adjustments to market trends and customer needs. This technology handles nuanced tasks such as personalized follow-ups and resource allocation, which traditionally required substantial manual effort.

However, human oversight remains critical for complex judgments and strategic decisions that require contextual awareness beyond current AI capabilities.

Key Insights

How does agentic AI improve marketing efficiency? It reduces manual workload by independently managing campaign execution and optimization, allowing marketers to focus on strategic creativity.
What makes agentic AI more adaptive? Real-time data integration enables it to respond instantly to market changes and consumer behavior shifts.
Can agentic AI fully replace human marketers? Currently, it complements rather than substitutes human expertise, especially in high-level decision-making.

Conclusion

Agentic AI is revolutionizing marketing automation by moving beyond repetitive rule-based systems to intelligent, proactive campaign management. Companies leveraging this technology can expect enhanced personalization, improved ROI, and more dynamic interactions with their audiences. As the technology matures, the role of human marketers will evolve toward strategic oversight, creativity, and governance, ensuring the best of both human insight and AI efficiency in marketing operations.

Source: https://martech.org/why-agentic-ai-is-different-from-traditional-marketing-automation/