Interview -Podcast

Optimising for AI searchHow to master the shift from SEO to Answer Engine Optimisation (AEO)…Interviewed by Rodrigo Wielhouwer, Founder, Datafeed.

Topic: How AI is changing consumer search behaviour: with Nishith Srivastava

Consumer behaviour is undergoing a significant transformation, particularly in terms of how people discover products and services. Gartner forecasts a 25% decrease in traditional search engine volume by 2026, largely driven by the rise of AI chatbots. This shift in searches towards AI-powered platforms, demands a new approach to visibility and engagement from marketers.

To gain a deeper understanding of these changes, we asked Nishith Srivastava, VP, Europe - BORN (Digital, CX, Martech, Data and eCommerce Transformation) at Tech Mahindra, with over 25 years of experience in omnichannel customer experience, MarTech architecture, data-driven growth and marketing strategy across global markets, about the implications of this shift for marketers, he emphasised the critical need for adapting to new consumer interactions shaped by AI:

“Users no longer 'search' in the traditional sense, they 'ask.' And that pivot demands a new kind of strategy i.e. Answer Engine Optimisation (AEO). It’s not just about ranking anymore; it’s about responding. ”

In practical terms, Nishith suggests: “Marketers must shift from 'ranking' to 'resolving' because if you’re not optimising for answers, you’re invisible. AEO flips the SEO playbook. Instead of optimising for keywords, we must optimise for answers. You must rethink how content is structured, semantically tagged, and contextually served to voice assistants, generative AI models, and zero-click platforms. This means investing in structured data, schema markup, and a laser-sharp focus on entity-based content modelling.”

A critical step, Nishith advises, is to “own the question space.” This means thinking from the user's perspective rather than the marketers. Instead of assuming consumers will ask explicitly about a brand or its offerings, Nishith notes that “the majority of users have an information need, and that's the sweet spot.” Marketers should thus shift the narrative from brand-centric to user-centric, highlighting benefits and purposeful information tailored to the consumer's intent.

“Change your AEO narrative from ‘About your Brand’ to ‘Benefits and Purpose for the User.”

Additionally, Nishith stresses, “If your content isn’t built to answer, it’s built to be ignored.”

To effectively compete in this new landscape, marketers should regularly audit their content for clarity and relevance in question-and-answer formats. Tools like AlsoAsked or AnswerThePublic can be valuable to uncover and identify latent semantic queries relevant to industry-specific topics. Accordingly, structure FAQ’s and responses in concise, scannable formats (bullet points, tables, or step-by-step guides) to align with answer engines' preference for snippet-ready content.

To ensure comprehensive coverage, marketers should also map audience intent across all stages of the consumer journey, aligning content closely with conversational queries. Nishith recommends prioritising conversational phrases such as 'how', 'why' and 'when', rather than limiting oneself to just 'what'. By integrating FAQ schema, leveraging knowledge graph relationships and employing natural language generation (NLG), businesses can efficiently scale authoritative answers that AI tools trust and value.

Finally, Nishith emphasises the importance of adopting a conversational tone. He points out that voice search and AI assistants prioritise natural language and suggests claiming your knowledge graph real estate with structured data (Schema markup) to reinforce entity-based authority.

By proactively embracing these strategies, marketers can successfully navigate and thrive in the evolving landscape of AI-assisted consumer discovery.

To read more: https://www.datafeed.website/post/optimising-for-ai-search

This podcast introduces Answer Engine Optimization (AEO) as a critical digital strategy for the age of AI-driven search. It explains that unlike traditional SEO focusing on broad keyword ranking, AEO aims to position content to provide direct answers to user queries through platforms like Google SGE, Microsoft Copilot, and AI chatbots.

The podcast outlines key strategies for implementing AEO, including optimising content for voice search, using structured data markup, and creating comprehensive FAQ pages, emphasizing that this approach enhances online visibility, user engagement, and organic traffic by establishing brand authority in the evolving search landscape.

Topics Covered:

• Whats is Answer Engine Optimization?
• Why is AEO becoming increasingly important?
• How AEO differs from traditional SEO - Future of SEO is AEO
• Types of Answer Engines
• The Functioning of Answer Engines – How do you optimize for Answer Engines?
• Benefits of AEO for businesses

This podcast discusses Vibe Marketing, a modern approach that leverages AI tools and automation to significantly enhance marketing efficiency and effectiveness. It explains that vibe marketing allows a small team, or even a single marketer, to perform complex tasks like rapid ad testing, multi-channel campaign deployment, and data analysis, which traditionally required numerous specialists.

The podcast contrasts vibe marketing with traditional methods, highlighting its speed and emphasis on AI handling execution while humans focus on strategy and brand voice. Several examples of brands successfully using vibe marketing are provided, alongside actionable steps and specific AI tools to help businesses implement this approach. Ultimately, the source posits that vibe marketing is a crucial evolution in the industry, offering cost savings, increased output, and a stronger focus on building authentic brand connections.

Topics Covered:

• Vibe Marketing for Dummies
• Market Forecast
• Vibe Coding vs. Vibe Marketing
• AARRR Pirate Funnel
• Examples Of Vibe Marketing – Use Cases from Brands
• How Can Your Business Implement Vibe Marketing?
• Various AI Tools for Vibe Marketing Future of Vibe Marketing

AI agents are software tools that act autonomously to perform tasks, leveraging AI models, particularly large language models, to understand language and interact with systems. These agents can automate workflows, augment individual productivity, and even form complex, collaborative systems within organisations.

Recent advancements have enabled agents to move beyond knowledge retrieval to action-oriented capabilities, leading to their potential widespread adoption across various industries. The podcast covers different types of AI agents, their operational processes, and their relationship with LLMs, further exploring their potential to drive business growth by reimagining processes and modernising infrastructure.

Organisations face hurdles in adoption, including building trust, managing change, and ensuring data protection, while their tech architectures will likely evolve towards multiagent models. Ultimately, the implementation of AI agents requires strategic planning in technology, talent, and operating models to unlock their transformative potential.

Topics covered:

• What are AI Agents and how do they work?
• How can they impact business performance and growth, with real examples
• Hurdles faced in adopting AI Agents
• How organizations can implement AI Agents

• The Global Marketing Technology market, valued at $250 billion in 2024 is projected to experience substantial growth, with a compound annual rate of 12% anticipated through 2030. This growth is primarily driven by the increasing adoption of artificial intelligence (AI). (Statista)

• AI has the potential to automate up to 30% of marketing tasks by 2025. (McKinsey)

What vibe marketing adds is a framework to harness this automation not just for efficiency, but for exponential growth.Vibe marketing is a significant evolution in marketing, driven by artificial intelligence and accessible automation, promising faster campaign cycles and greater efficiency. This new approach empowers marketers to achieve exponential growth by automating repetitive tasks and enabling rapid, large-scale testing.

The podcast contrast traditional, siloed marketing teams with the agility offered by vibe marketing, where a single marketer can leverage AI tools to manage complex campaigns.

Real-world examples illustrate its application, and the text suggests that embracing vibe marketingoffers a crucial competitive advantage in the rapidly evolving digital landscape.

Topics covered:

• Vibe Marketing: AI Reshaping The $250 Billion Marketing Technology Industry
• Pillars of Vibe Marketing
• What is Vibe Coding and Vibe Marketing?Vibe Marketing vs. Digital Marketing
• How to implement Vibe Marketing - Step by Step -> AARRR Framework
• Benefits of Vibe Marketing
• Use Cases - real world examples of Coca-Cola, Heinz and Spotify
• Future - Where Vibe Marketing are heading?

Agentic AI, a form of artificial intelligence capable of autonomous action and decision-making, is poised to significantly reshape the healthcare industry. This podcast highlights how Agentic AI can enhance diagnostic accuracy, personalise treatment plans, and streamline administrative tasks, ultimately leading to improved patient outcomes and reduced costs.

Furthermore, it discusses the potential of agentic AI to accelerate drug discovery and improve access to healthcare, particularly in underserved areas. The podcast also addresses crucial challenges for successful implementation, such as data quality and the need for strategic integration, offering solutions like centralised governance and a focus on measurable value.

Agentic AI: Transforming B2B Ecosystems in Key Industries

This podcast explores the burgeoning field of agentic artificial intelligence (AgenticAI) and its transformative impact on business-to-business (B2B) ecosystems, particularly within pharmaceuticals, industrial manufacturing, chemicals, and oil & gas.

It highlights the projected substantial growth of this market and contrasts agentic AI with generative AI, emphasising its specialisation in vertical-specific applications using proprietary data.

It discusses various use cases across these industries, illustrating how agentic AI enhances efficiency, optimises workflows, and improves decision-making through technologies like AI, IoT, and digital twins, ultimately leading to more proactive and personalised B2B interactions.

By exploring real-world use cases, it demonstrates how agentic AI drives efficiency, innovation, and transformation in these sectors. The discussion highlights the strategic integration of intelligent systems to optimize B2B workflows and enhancedecision-making by providing the overall technology stack that is required to integrate Agentics AI in existing B2B ecosystem.

This podcast examines the challenges and strategies for deriving return on investment (ROI) from generative AI (GenAI) investments. It then highlights the significant economic potential of GenAI, citing projections of trillions of dollars inadded value, while also cautioning that enthusiasm currently outpaces understanding.

The podcast then delves deeper into specific challenges in measuring GenAI ROI, such as the lack of standardised metrics, the complexity of attributing impact, and the difficulty in quantifying intangible benefits. It advocates for a balancedapproach to key performance indicators (KPIs), incorporating both financial and non-financial metrics.

Furthermore, it provides a balanced approach to key performance indicators (KPIs), incorporating both financial and non-financial metrics. Furthermore, the podcast outlines a framework for setting up and measuring ROI, including defining objectives, establishing performance baselines, and continuously improving implementations; as well as the importance of addressing data complexity, ethical considerations and business environment changes.

The challenges are evident: a lack of standardization, complexities in attribution, and benefits that are often hard to quantify. However, a practical and iterative approach—guided by clear objectives, human oversight, and data-driveninsights—can unlock the full potential of generative AI.

Organizations that perceive ROI as an ongoing process, continuously refining their strategies and metrics, will be best positioned to transform AI investments into measurableimpacts.

The true value of generative AI goes beyond cost savings and efficiency gains—it lies in its ability to transform processes, stimulate innovation, and empower better decision-making. In this rapidly evolving landscape, those who succeed will bethose who redefine ROI, striking a balance between quantifiable financial outcomes and strategic, long-term contributions.