DualRank
AI assistants now reply to half of all questions online. Google's grip on discovery has slipped while platforms like ChatGPT, Perplexity, Gemini and Claude steer users directly to brand recommendations. Where you rank today is only half the story. Your brand should be mentioned when people ask questions, not just when they search.
Modern SEO is a comprehensive approach to ensuring a business ranks wherever prospects discover solutions. Discovery happens across Google search, AI answer engines like ChatGPT and Perplexity, voice assistants, and emerging platforms. Effective SEO includes generative engine optimisation or GEO and works across all these channels simultaneously through the same foundational elements: technical optimisation, semantic content, entity authority, and structured data.
Businesses relying solely on Google rankings are capturing only part of the market. A prospect researching solutions might:
Search “best saving bank accounts” on Google (finds your ranking)
Ask ChatGPT “which bank offers the best saving account interests and benefits?” (finds your competitor if you’re not optimised for comprehensiveness)
Ask Siri for local recommendations (finds you only if your entity data is consistent and strong)
Research on Perplexity “which EdTech platform is ideal for JEE” (finds your content if it’s structured for AI extraction)
The gap? Businesses optimised only for Google keywords miss 30% of prospects who now use AI assistants. Competitors who invested early in comprehensive SEO (that includes GEO) capture both channels and grow market share.
Full-site technical audit, speed and mobile optimisation, schema implementation, keyword and intent mapping, competitor analysis and entity audits, monthly SEO performance reports.
Audit brand, product and location entities, expand prompt coverage with FAQs and long-tail queries, build citation signals with trusted directories and reputable partnerships, test and refine brand mentions in AI responses, GEO visibility scorecards and AI mention tracking.
AI models don’t just read keywords. They understand entities (specific people, places, products or concepts). When you mention “Indian marketing agency,” AI models find this as separate entities that relate to each other.
Your business needs strong entity signals for AI recognition. This means consistent NAP data (Name, Address, Phone) across directories, structured schema markup on your website, clear relationships between your brand and industry topics, regular mentions in reputable publications and platforms.
Without proper entity establishment, AI models struggle to connect your business with relevant queries. You become invisible in the knowledge graphs that power AI responses.
We don’t guess at AI visibility. Our testing process involves querying multiple AI models with hundreds of relevant prompts related to your business. Each query gets categorised by intent (informational, transactional, navigational) and response quality.
Testing reveals patterns in how AI models select sources. Some favour recent content while others prioritise established authority. Geographic queries pull local directory information while product comparisons rely on structured review data.
We document which content formats earn citations most frequently. FAQ sections, numbered lists, comparison tables and quote blocks consistently perform well. This data guides our content recommendations and optimisation priorities.
SEO content targets specific keywords. AI optimised content answers complete questions while supporting multiple related queries. The structure changes from keyword-focused pages to topic-comprehensive resources.
Instead of separate pages for “SEO services,” “SEO agency,” and “SEO consultant,” we create content covering the entire topic cluster. This satisfies both search crawlers looking for keyword relevance and AI models seeking complete information.
AI models often default to large national brands unless specifically prompted for local options.
We optimise Google Business profiles with AI-friendly descriptions, encourage reviews that mention specific services and locations, ensure consistent business information across all platforms, create location-specific content that AI can reference, build local citations and community partnerships.
When someone asks AI for local recommendations, proper entity signals help models connect your business with geographic queries. This becomes especially important as voice search and AI assistants become primary discovery methods for local services.
Full visibility means your brand shows up for typed searches and AI-generated responses. Reports show where you rank and how often AI answers mention your brand. Content built for humans and machines delivers clear, helpful and structured information for users, search bots and AI platforms. Future-proof strategy keeps your business ahead as behaviour shifts.
You receive monthly performance reports, quarterly strategy reviews, and annual planning sessions. Our team provides ongoing consultation and answers questions as new AI platforms emerge or algorithm updates affect your visibility.
Many businesses focus on keyword stuffing instead of building authority. Others ignore technical SEO while pursuing AI visibility, not realising how interconnected these signals are.
Some companies create AI-specific content that’s separate from their main website. This fragments authority and confuses both search algorithms and AI models. Integrated approaches work better than siloed strategies.
Another mistake is expecting immediate results. AI model training cycles mean visibility improvements can take months to fully materialise. Consistent, quality content publication combined with proper technical implementation yields the best long-term results.
Voice commands, visual search, and conversational AI interfaces are becoming mainstream discovery methods. Businesses that adapt early gain significant competitive advantages.
DualRank prepares your brand for multiple discovery channels rather than betting on a single platform. Whether customers find you through Google search, ChatGPT responses, voice assistants, or emerging AI interfaces, your brand maintains consistent visibility and messaging.
Month 1 includes technical audit completion, entity mapping, and AI baseline testing. Months 2-3 focus on technical fixes, schema implementation, and initial content planning. Months 4-6 involve content production scaling, citation building, and first AI visibility reports.
Months 7-9 emphasise content refresh, advanced testing, and strategy refinement. Months 10-12 concentrate on scaling successful tactics, preparing for algorithm updates, and planning the following year’s optimisation priorities.
Throughout this timeline, you receive regular updates, performance reports, and strategy consultations to ensure the approach aligns with your business objectives and market conditions.
Your brand deserves attention everywhere people look for answers.
AI engines analyse a brand’s digital footprint using signals such as expertise, authority, and trust. They prioritise content that is factually accurate, well-structured, and consistently supported by external citations. Brands that demonstrate credibility through schema markup, verified sources, and a clear author identity are more likely to be cited in AI-generated responses.
Ranking in both requires combining traditional SEO with new AI visibility practices. Optimise your website technically for Google by implementing fast loading, structured data, and E-E-A-T signals, while also ensuring your content is written in a conversational, question-and-answer format. This helps AI engines understand and reuse your content as a trusted reference in their generated answers.
Focus on providing clear, self-contained explanations to common user questions. Use structured headings, FAQ schema, and concise phrasing that mirrors natural conversation. Including factual data, examples, and definitions improves the likelihood that AI systems such as ChatGPT, Gemini, or Perplexity will recognise and cite your content as a reliable source.
AI search results often return direct answers rather than listing web pages. Being featured ensures your brand remains visible even when users don’t click through to websites. It strengthens brand recognition, builds authority, and safeguards organic visibility as search behaviour shifts from keyword-based discovery to AI-generated responses.
AI answer engines, such as ChatGPT, Gemini, and Claude, use generative models to produce complete answers rather than showing a list of links. This changes SEO by introducing a new layer of competition, optimising for citations rather than clicks. Brands must adapt their strategies to include structured, semantically rich content that AI can easily interpret and reference.
AI has transformed brand discovery by guiding users through conversational and personalised recommendations. Instead of manually searching, people increasingly ask AI systems for advice, reviews, or comparisons. Brands that appear in these AI-generated answers gain earlier exposure in the customer journey, often before users perform a traditional search.
Start with a strong technical SEO foundation. Schema markup, clean site structure, and fast performance. Complement this with AI-friendly content: direct answers, consistent terminology, and contextual depth. Regularly test how your brand appears in AI systems, and refine your content to improve visibility across both search engines and answer engines.
AI prefers content that is factual, structured, and written for clarity. Articles that define concepts, answer specific questions, and use bullet points or numbered steps are more likely to be cited. Including up-to-date data, expert commentary, and trustworthy references also improves the chance of being featured in AI responses.