Irina Smirnova

How to get cited by AI and generate leads from LLM recommendations One of the biggest questions marketers are asking today is: How do I get my business recommended by ChatGPT and other AI tools? Looking for practical answers, I spoke with Vincent, founder of BlogSEO https://lnkd.in/endhXJrc , who has successfully driven traffic from LLMs. Here are the key lessons: 1. Representation bias matters LLMs are affected by representation bias. Simply put, the more often your brand, products, or expertise appear across the web, the more likely AI is to reference you. Every high-quality article, mention, or resource strengthens your presence in the data AI systems rely on. Takeaway: Publish consistently. The more valuable content you create, the stronger your AI footprint becomes. 2. Write for AI search LLMs don't rely only on their training data — they also search the web for fresh information. A recent Princeton University study found that websites can increase their visibility in AI search by up to 37% by following a few principles: - Include original data and statistics. - Reference credible sources. - Demonstrate real expertise. Answer the exact questions your audience is asking. After testing these practices with 20+ companies across SaaS, e-commerce, and coaching, many went from zero ChatGPT leads to being consistently cited by AI tools. Takeaway: Create content that's factual, authoritative, and directly answers user intent. 3. Don't ignore Bing Webmaster Tools Many marketers dismiss Bing because of its relatively small market share. But ChatGPT's web search uses Bing's search index, as does Microsoft Copilot. If Bing can't properly crawl and index your website, AI is much less likely to discover and cite it. Bing also introduced an AI Performance dashboard in Webmaster Tools, where you can track AI citations, top-performing pages, and visibility trends. Takeaway: Make Bing indexing part of your SEO strategy and monitor your AI visibility. 4. Cover the entire customer journey The best-performing AI content isn't just educational or sales-focused — it covers every stage of the buying journey: - Awareness: guides, explainers, how-to articles. - Consideration: comparisons, reviews, alternatives. - Decision: case studies, implementation guides, customer success stories. When your content answers the right questions at every stage, AI has more opportunities to recommend it. Takeaway: Build a content library, not isolated blog posts. The companies winning AI search aren't relying on hacks. They're becoming the most useful, trustworthy source in their niche — and AI rewards them for it. What strategies have worked for you in getting cited by AI?

SEO is dead (season 17, episode 26) 😁 With Google's AI Overviews and ChatGPT, generic informational content is becoming a commodity. Spending thousands on manually writing "how-to" articles just to keep your blog active is getting harder to justify. To use or not to use AI for content? My take here is to automate the baseline and invest people in differentiation. Today's tool review: BlogSEO https://lnkd.in/endhXJrc It's an AI-powered content engine that discovers keywords, writes articles, adds internal links and schema markup, and publishes directly to your CMS. Here's what stood out after testing it: 💥 What I liked: • End-to-end automation - it integrates with Webflow, WordPress, Shopify, and Framer, so your content pipeline can run with almost no manual work. • SEO built in - articles include internal links, structured data, and AI-generated images out of the box. • Built-in backlink network - it helps create contextual backlinks between sites in similar niches to strengthen your SEO over time. 💥 What I missed: • The content still needs a human touch. It's good for scaling informational content, but not for thought leadership or strong brand voice. • Keyword selection isn't perfect. For technical B2B products, you'll still want to validate that it's targeting buyer intent, not just search volume. ❇️ The verdict: Good for: SaaS companies, e-commerce brands, affiliate sites, and lean marketing teams that want to scale SEO without scaling headcount. Skip if: you're enterprise companies with strict approval processes or brands built on original research, expert insights, and thought leadership. Overall, I'd recommend BlogSEO for companies that see SEO content as infrastructure — not as their competitive advantage. Have you tried AI-powered content automation? Share your thoughts (and tools 😉 ) in the comments! Follow for next week's #MarketingToolReview

Some insights on what's coming to LinkedIn 🤫 As a LinkedIn Certified Professional, I recently had a conversation with the LinkedIn team about upcoming product changes. Here are a couple of updates worth watching: ❇️ Collaborative posts - you could add up to 5 people or company pages as collaborators on a single post. No more tagging someone and silently praying for a repost. The post will appear across all collaborators' audiences, and you'll get shared performance metrics in one place. This could significantly expand reach for partnerships, sponsored content, customer stories, and event coverage since you're building distribution together from the start. ❇️ Suggested feeds- LinkedIn is moving from a single feed toward multiple interest-based feeds. The idea is to show users more content that matches their professional interests and what's happening right now, while reducing the amount of generic content competing for attention. For creators, this means relevance will likely become even more important. Niche expertise should have a better chance of reaching the right audience, while broad, one-size-fits-all content may become less visible. The main takeaway is that LinkedIn seems to be doubling down on depth over breadth. If you've been building a focused audience and creating content that genuinely helps people, these changes should work in your favor. Hope these post finds you well 😄 What feature would you like to see in LinkedIn's next product update?

The math on standard B2B outbound is fundamentally broken. CAC is climbing, response rates are near all-time lows, yet sales teams are still locked into 5-figure annual contracts just to export basic corporate email addresses. Data is a commodity - paying a premium subscription tax for a legacy database just to get standard contact info doesn't make sense anymore. The smarter play might be to buy your raw data utility cheap, and reinvest those massive savings into what actually moves the needle - better offers, creative copy, or direct dials. And our tool for review today is OutEngine: https://lnkd.in/e6qHFHyP If you're looking at adding volume-first data extraction tool to your stack, here is my honest feedback: 💥 What I liked: - Disruptive scale: the pricing structure is built for high-volume modern outbound. You can pull ~18,750 export credits for $97/month, or up to 187,500 credits for $497/month. Compared to traditional enterprise providers, your cost-per-lead drops to almost nothing. - Rollover feature: they cap unused monthly credits with a 20% rollover. It prevents the typical "use it or lose it" data trap that forces you to pull irrelevant lists at the end of the month just to get your money's worth. - Fast queries: the search engine is built for speed. If you need to map out macro-segments (e.g., pulling thousands of mid-market tech decision-makers) it parses the data instantly. 💥 What I missed: - Raw fuel: this is a massive, 86M+ contact database, meaning you are getting unrefined data. If you blindly blast these lists without running them through a strict, secondary verification layer, you will wreck your sending domain reputation. - Lacks native CRM integration ecosystem of the legacy giants. You aren't getting one-click syncing into Salesforce or HubSpot. ❇️ The verdict: Good for: - LeadGen agencies & high-volume startups consuming 10,000+ leads/ month who need raw B2B data at rock-bottom costs to scale their campaigns. - Decoupled tech stack operators who use separate, specialized tools for data, validation, and sending, and prioritize high profit margins over a single, polished UI. Skip if: you're enterprise ABM team that require native, 1-click CRM syncing and hyper-curated, low-volume account data. Check the link in the post to try OutEngine for your needs 😉 Like the post and follow me for the next Tuesday #MarketingToolReviews 😎

Tool Crash Test # 1 👏 Today we're reviewing a GTM tool for finding and verifying emails. Swipe through the carousel and check the first comment for the link👇