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Domo Launches Domo MMM, an AI-Powered Marketing Measurement Service Built for Real Budget Accountability

William Gu
William Gu
Marketing AI Team @ MKTGAGENT.AI

Unlocking Real Budget Accountability with Domo MMM: The Next Frontier in AI-Powered Marketing Measurement

In today’s data-driven marketing landscape, understanding the true impact of marketing investments is critical. Domo, a leader in business intelligence solutions, has launched Domo MMM, a groundbreaking AI-powered marketing measurement service designed to bring real budget accountability to organizations. Developed in partnership with Stella Growth Intelligence, this new tool promises to transform how marketing teams analyze and optimize their spending.

What is Domo MMM?

Domo MMM is an advanced marketing measurement platform that leverages cutting-edge AI techniques such as Bayesian modeling and causal analysis. Unlike traditional measurement approaches that provide static reports, Domo MMM offers continuous, actionable insights. This means marketers can ask real-time questions about their campaigns and receive AI-generated, evidence-based answers that inform smarter decisions.

How Does It Work?

The service integrates securely with existing data environments, ensuring fast access to marketing performance data without compromising governance or security. By analyzing diverse datasets continuously, Domo MMM identifies underperforming marketing spend and highlights opportunities for optimization. This continuous feedback loop helps organizations allocate budgets more effectively and improve their overall marketing ROI.

Key Features and Benefits

  • Real-Time Insights: Unlike static monthly or quarterly reports, marketers receive continuous updates on campaign effectiveness.
  • AI-Driven Analysis: Utilizes Bayesian statistics and causal inference to uncover deeper insights.
  • Secure Integration: Connects safely to existing data systems with strong control over data governance.
  • Budget Optimization: Pinpoints ineffective spend and guides better resource allocation.

Key Insights

  • Why is continuous insight important in marketing measurement? Continuous insights allow marketing teams to react promptly and adjust campaigns dynamically rather than waiting for post-campaign analysis.
  • What role does AI play in enhancing marketing measurement? AI processes complex data and generates evidence-based insights that are beyond manual analytics, enabling more accurate effectiveness evaluations.
  • How does Domo MMM safeguard data privacy and governance? By integrating securely with existing data environments, Domo MMM respects organizational security protocols while enabling rapid analysis.

Conclusion

Domo MMM represents a significant advancement in marketing measurement technology. By providing AI-powered, real-time insights and maintaining strict data security, it empowers marketing professionals to make faster, smarter decisions and justify budgets with confidence. As marketing landscapes become increasingly complex, tools like Domo MMM are essential for organizations aiming to optimize spend and maximize returns efficiently.

Source: https://martechseries.com/sales-marketing/domo-launches-domo-mmm-an-ai-powered-marketing-measurement-service-built-for-real-budget-accountability/

DXC Launches London Customer Experience Center to Help Unlock AI Value

William Gu
William Gu
Marketing AI Team @ MKTGAGENT.AI

DXC Technology Launches London Customer Experience Center to Advance AI at Scale

DXC Technology has taken a significant step to accelerate enterprise adoption of artificial intelligence (AI) with the opening of its new Customer Experience Center (CEC) in London. This center is designed to facilitate close collaboration between DXC’s experts and clients, helping transition AI initiatives from experimental trials into full-scale business solutions.

Bridging the AI Gap from Experimentation to Enterprise

The London CEC leverages the knowledge and skills of over 6,000 DXC professionals working across the UK and Ireland in diverse sectors such as healthcare, government, and insurance. It offers a collaborative environment where multidisciplinary teams and customers can co-create tailored AI solutions that address their specific technology challenges. By fostering this hands-on co-development approach, DXC aims to accelerate the journey from proof-of-concept projects to scalable implementations that deliver real business value.

Expanding AI Expertise to Empower Organizations

As part of this initiative, DXC plans to recruit 150 new AI specialists to support its clients in operationalizing AI technologies and driving digital transformation. These experts will help organizations integrate AI into their processes and systems in ways that are sustainable and aligned with business goals. The CEC will serve as a proactive innovation hub where complex problems can be tackled collaboratively, and AI adoption can be strategically accelerated.

Key Insights

  • Why is the new Customer Experience Center important? It creates a dedicated space for collaboration, enabling organizations to move beyond pilot AI projects to industrial-scale solutions.

  • How does DXC’s expertise benefit customers? The center taps into a vast talent pool with deep sector knowledge, ensuring AI implementations are both technically sound and industry-relevant.

  • What opportunities does this open for businesses? Companies gain access to tailored AI solutions and specialist support to help them modernize operations and stay competitive.

Conclusion

DXC’s London Customer Experience Center represents a strategic investment in enabling enterprises to unlock the full potential of AI. By combining extensive domain expertise with a collaborative innovation environment, the center is poised to help organizations overcome technology complexities and accelerate digital transformation journey. The recruitment of specialized AI talent further strengthens DXC’s commitment to driving practical, scalable AI solutions that deliver measurable outcomes across key sectors like healthcare, government, and insurance.

Source: https://martechseries.com/predictive-ai/ai-platforms-machine-learning/dxc-launches-london-customer-experience-center-to-help-unlock-ai-value/

EZY.ai Makes AI Search Simple with a New Easy-to-Use, Affordable AEO Solution

William Gu
William Gu
Marketing AI Team @ MKTGAGENT.AI

Simplifying AI Search: Introducing EZY.ai’s Affordable AEO Platform for Small Businesses

The landscape of digital search is rapidly evolving with the growing influence of AI-driven search engines and chatbots. Recognizing this change, EZY.ai has launched a new platform dedicated to Answer Engine Optimization (AEO), designed to help businesses improve their visibility on AI-powered platforms such as ChatGPT and Google’s Gemini. This easy-to-use and cost-effective solution is particularly tailored to meet the needs of small businesses seeking to thrive in this new digital environment.

What is Answer Engine Optimization (AEO)?

AEO refers to optimizing digital content so that it ranks favorably in AI-generated answers on chatbots and AI search engines. Unlike traditional SEO, which focuses on search engine rankings, AEO targets how AI systems present concise, relevant answers to users’ queries. As AI chatbots increasingly influence purchasing decisions, enhancing AEO is becoming critical for brands aiming to capture new customer attention.

EZY.ai’s User-Friendly Platform

EZY.ai’s platform stands out due to its simplicity and affordability. It requires no technical skills or expensive SEO services, making it accessible for small business owners who may lack dedicated digital marketing teams. The platform automates several optimization tasks including:

  • Generating AI-friendly content
  • Creating structured data schemas to enhance AI comprehension
  • Monitoring brand presence and performance within AI responses

These features empower businesses to strengthen their visibility in AI-powered search results efficiently and at a nominal fee.

Early Success and Impact

Initial users of the EZY.ai platform have reported significant increases in website traffic and conversion rates. This success highlights how important it is for businesses to adapt current marketing strategies to include AI-centric optimization techniques. EZY.ai positions itself as an essential tool for companies that want to ensure their brand is found where modern consumers are searching.

Key Insights

  • Why is AEO important now? With AI chatbots becoming primary information sources, optimizing for AI-driven answers helps businesses gain a competitive edge.
  • How does EZY.ai simplify AEO? By automating complex tasks like content creation and schema generation, it removes technical barriers for small businesses.
  • What results can businesses expect? Enhanced AI search visibility can translate into increased traffic and improved sales conversions.

Conclusion

EZY.ai’s new AEO platform represents a pivotal shift towards embracing AI’s role in digital marketing. Its approach lowers entry barriers for small businesses, enabling them to stay competitive in an AI-dominated search landscape. As AI technologies continue to develop, tools like EZY.ai will likely become indispensable for brands eager to capture the attention of modern consumers in intelligent search environments.

Source: https://martechseries.com/predictive-ai/ai-platforms-machine-learning/ezy-ai-makes-ai-search-simple-with-a-new-easy-to-use-affordable-aeo-solution/

Genesys Launches LAM-Powered Agentic Virtual Agent

William Gu
William Gu
Marketing AI Team @ MKTGAGENT.AI

Genesys Unveils Next-Generation Agentic Virtual Agent Powered by Large Action Models (LAMs)

In a significant advancement for customer experience technology, Genesys has introduced its latest agentic virtual agent driven by cutting-edge Large Action Models (LAMs). Designed to redefine how businesses handle customer interactions, this autonomous virtual agent aims to deliver comprehensive resolutions by managing complex workflows across various enterprise platforms seamlessly.

Revolutionizing Customer Service with Autonomous Execution

Traditionally, virtual agents have utilized large language models to interpret and respond to customer requests. However, these systems often lack the ability to perform deterministic, end-to-end actions autonomously. Genesys’s new solution, integrated with Scaled Cognition’s APT-1 LAM, overcomes these limitations. By harnessing LAMs, the virtual agent can execute precise actions within enterprise environments, significantly enhancing self-service capabilities and reducing dependency on human intervention.

Early Adoption and Anticipated Rollout

Several major organizations are already piloting this innovative virtual agent, testing its efficiency and reliability in real-world scenarios. Genesys plans a broader rollout of the technology in early 2026, anticipating considerable improvements in operational efficiency. Early data indicate notable enhancements in key performance metrics such as resolution times and first-contact resolution rates, underlining the potential impact on customer support quality.

Key Insights

  • What differentiates Genesys’s agentic virtual agent from previous AI solutions? This agent uses Large Action Models that enable it to autonomously perform complex, end-to-end workflows, unlike traditional models that primarily generate responses.

  • How will this technology impact customer service operations? By automating deterministic actions and enhancing self-service, businesses can expect faster resolution times and increased customer satisfaction.

  • What are the next steps for Genesys in this initiative? Following pilot programs, Genesys aims to scale deployment in early 2026 to broaden access across industries.

Conclusion

Genesys’s launch of the LAM-powered agentic virtual agent signifies a transformative leap in customer experience management. This technology not only promises to streamline complex customer interactions but also offers scalable automation that improves operational efficiency and customer support outcomes. As enterprises continue to pilot and prepare for full deployment, the agentic virtual agent stands poised to redefine how businesses engage and serve their customers in the coming years.

Source: https://www.cmswire.com/contact-center/genesys-launches-lam-powered-agentic-virtual-agent/?utm_source=cmswire.com&utm_medium=web&utm_campaign=cm&utm_content=all-articles-rss

How to make automation work for lead gen PPC

William Gu
William Gu
Marketing AI Team @ MKTGAGENT.AI

How to Make Automation Work for Lead Gen PPC: Strategies for B2B Marketers

Introduction

In the world of B2B advertising, automation presents unique challenges. Unlike e-commerce, where automation tools thrive on quick conversions and clear cart values, B2B lead generation involves longer customer journeys, fewer conversions, and more complex data signals. However, with the right strategies, B2B marketers can still leverage automation to maximize lead generation and optimize their PPC campaigns.

Understanding the Challenges of Automation in B2B PPC

Automation tools are generally designed for e-commerce environments where purchase cycles are short, and transaction values are easily quantified. In contrast, B2B customers often take months to make decisions, resulting in prolonged journeys with lower conversion volumes. Additionally, the absence of clear cart or transaction values complicates automated bidding and optimization processes.

Enhancing Automation Through CRM Integration

A key method to overcome these challenges is integrating Customer Relationship Management (CRM) systems with advertising platforms like Google Ads and Microsoft Ads. This connection allows marketers to use offline conversion data, providing precise signals that guide automation algorithms more effectively. By syncing CRM and PPC data, marketers gain deeper insights into lead quality and campaign performance.

Leveraging Advanced PPC Strategies

Successful automation for lead gen PPC relies on specific tactics:

  • Offline Conversions: Tracking leads that convert offline to give systems real-world validation.
  • Micro Conversions: Using smaller engagement milestones (such as form fills or content downloads) to track user intent.
  • Campaign-Specific Optimizations: Tailoring strategies per campaign to sharpen focus and results.
  • Portfolio Bidding: Accelerating data accumulation by pooling campaigns for more effective bidding algorithms.

Employing AI for Better Results

Artificial Intelligence tools are invaluable in B2B PPC automation. They can automate repetitive tasks, offer rapid competitor analysis, and continuously refine audience targeting. AI’s ability to handle complex data sets and adjust strategies dynamically helps marketers respond quickly to market changes and improve lead quality.

Key Insights

  • Why is automation more challenging in B2B PPC? Long sales cycles and lack of clear transaction values make traditional automation less effective.
  • How does CRM integration help? It provides offline conversion data that feeds accurate signals to automated bidding algorithms.
  • What role do micro conversions play? They help detect user intent early, allowing for better campaign adjustments.
  • How can AI improve lead generation? By automating routine work and enhancing audience targeting with data-driven insights.

Conclusion

While automation tools were not originally designed for B2B lead generation, integrating CRM data, focusing on micro-conversions, and leveraging AI and portfolio bidding can significantly enhance campaign performance. With thoughtful strategy and technology integration, B2B marketers can harness automation to generate quality leads and optimize their PPC efforts effectively.

Source: https://searchengineland.com/automation-b2b-lead-gen-ppc-smx-next-465710