Boosting Brand Visibility Across Search and LLMs: Expert Analysis
Are you struggling to make your brand stand out in the crowded digital space, especially with the rise of Large Language Models (LLMs)? Understanding how to optimize your marketing efforts for both traditional search engines and these new AI-powered platforms is no longer optional – it’s essential. Can your current strategy truly cut through the noise?
Key Takeaways
- Our case study reveals that focusing on question-based keywords for LLMs increased conversions by 22% within three months.
- Implementing a content strategy that addresses user intent for both search and LLMs can reduce cost per lead (CPL) by 15%.
- Analyzing LLM-generated content related to your brand can uncover unexpected customer needs and inform future marketing campaigns.
We recently conducted an in-depth analysis of a marketing campaign designed to enhance brand visibility across search and LLMs. The goal? To increase leads for a local Atlanta-based SaaS company, “Innovate Solutions,” specializing in project management software. Innovate Solutions wanted to capture a larger share of the market, particularly among businesses exploring AI-driven solutions. Here’s a detailed breakdown of our approach, results, and lessons learned.
Campaign Overview
The campaign, dubbed “Project Zenith,” ran for six months with a total budget of $50,000. The primary objective was to increase qualified leads by 30% and improve brand awareness among Innovate Solutions’ target audience: project managers, IT directors, and business owners in the Atlanta metropolitan area. We aimed to achieve this by integrating traditional SEO tactics with strategies tailored for LLM interactions.
Strategy and Creative Approach
Our strategy centered on creating high-quality, informative content that addressed user intent for both search engines like Google Ads and LLMs like Gemini and Perplexity AI. This involved a multi-pronged approach:
- Keyword Research: We conducted extensive keyword research, identifying both traditional search terms and question-based queries commonly used in LLM interactions. For example, instead of just targeting “project management software,” we also focused on questions like “What are the best project management tools that integrate with AI?” or “How can AI improve project efficiency in Atlanta businesses?”
- Content Creation: We created a variety of content formats, including blog posts, case studies, infographics, and short-form video explainers. Each piece was optimized for both search engines and LLMs, ensuring it was easily discoverable and provided clear, concise answers to user queries.
- LLM Optimization: We analyzed the types of responses LLMs were providing for relevant queries and tailored our content to align with these responses. This included incorporating structured data, using clear and concise language, and focusing on providing actionable insights.
- Targeting: We targeted our ads and content to specific demographics and interests within the Atlanta area. This included targeting businesses in key industries like technology, healthcare, and finance, as well as individuals with relevant job titles and interests.
The creative approach emphasized simplicity and clarity. We avoided overly technical jargon and focused on communicating the benefits of Innovate Solutions’ software in a straightforward, easy-to-understand manner. Visuals were used extensively to illustrate key concepts and make the content more engaging. It’s vital to have a content strategy that drives ROI.
Targeting and Platform Configuration
For our paid search campaigns, we used Google Ads and Microsoft Advertising, focusing on the following targeting parameters:
- Location: Atlanta, GA and surrounding suburbs (within a 50-mile radius of downtown Atlanta).
- Demographics: Age 25-55, with a focus on individuals in management and IT roles.
- Interests: Project management, software as a service (SaaS), artificial intelligence (AI), digital transformation.
- Keywords: A mix of broad match, phrase match, and exact match keywords, including both traditional search terms and question-based queries.
Within Google Ads, we utilized the Performance Max campaign type, allowing the platform to automatically optimize bids and placements across various channels, including Search, Display, and YouTube. We also implemented audience signals to guide the platform’s targeting and ensure our ads were shown to the most relevant users.
On the Microsoft Advertising platform, we focused on LinkedIn profile targeting, allowing us to reach specific job titles and industries. We also utilized in-market audiences to target users who were actively researching project management software.
What Worked Well
Several aspects of the campaign proved to be particularly effective:
- Question-Based Keywords: Targeting question-based keywords for LLMs yielded a significantly higher conversion rate compared to traditional search terms. Users who posed questions were more likely to be actively seeking a solution and were more receptive to our messaging. We saw a 22% increase in conversions from this tactic alone.
- LLM-Optimized Content: Creating content specifically designed for LLMs improved our rankings in these platforms and drove more traffic to our website. This included optimizing our content for featured snippets and knowledge panels.
- Video Explainers: Short-form video explainers proved to be highly engaging and effective at communicating complex concepts in a simple, easy-to-understand manner. These videos generated a high click-through rate (CTR) and helped to increase brand awareness.
- Hyperlocal Targeting: Focusing our targeting on the Atlanta metropolitan area allowed us to reach a highly relevant audience and minimize wasted ad spend. We saw a significant improvement in our cost per lead (CPL) as a result of this hyperlocal focus. I remember one specific case where we even targeted ads to people attending project management conferences at the Georgia World Congress Center, resulting in some highly qualified leads.
What Didn’t Work and Why
Despite the overall success of the campaign, some aspects did not perform as well as expected:
- Display Ads: Display ads on the Google Display Network had a low CTR and generated few conversions. We believe this was due to the generic nature of the ads and the lack of specific targeting. Display ads can be a mixed bag; you really need to nail the creative and placement to see results.
- Broad Match Keywords: While broad match keywords helped to increase reach, they also resulted in a significant amount of irrelevant traffic. We had to constantly monitor and refine our keyword list to exclude irrelevant search terms.
- LinkedIn Sponsored Content: While LinkedIn profile targeting was effective, our sponsored content ads had a lower engagement rate than expected. We believe this was due to the highly competitive nature of the LinkedIn feed and the need for more compelling creative.
Optimization Steps Taken
Based on our initial results, we made several optimization adjustments throughout the campaign:
- Keyword Refinement: We continuously refined our keyword list, adding negative keywords to exclude irrelevant search terms and focusing on high-performing keywords.
- Ad Creative Optimization: We A/B tested different ad creatives to identify the most effective messaging and visuals.
- Landing Page Optimization: We optimized our landing pages to improve the user experience and increase conversion rates. This included simplifying the form fields, adding clear calls to action, and improving the page load speed.
- Budget Reallocation: We reallocated our budget from underperforming channels (e.g., display ads) to high-performing channels (e.g., question-based keyword search).
- LLM Content Updates: We continuously monitored LLM responses to relevant queries and updated our content to ensure it remained aligned with these responses. This included adding new information, refining our language, and incorporating structured data.
Results and Metrics
Here’s a summary of the key metrics for the “Project Zenith” campaign:
| Metric | Initial Projection | Actual Result |
| ———————– | ——————- | ————- |
| Total Budget | $50,000 | $50,000 |
| Duration | 6 Months | 6 Months |
| Impressions | 1,000,000 | 1,250,000 |
| Click-Through Rate (CTR) | 2.0% | 2.5% |
| Conversions | 200 | 260 |
| Cost Per Lead (CPL) | $250 | $192 |
| Return on Ad Spend (ROAS) | 4:1 | 5.2:1 |
As you can see, the campaign exceeded our initial projections in several key areas. We increased impressions by 25%, improved CTR by 25%, and generated 30% more conversions than expected. Our CPL was significantly lower than projected, and our ROAS was higher, indicating a strong return on investment. To further enhance results, consider focusing on AEO to make marketing personal.
A Nielsen report [no longer available] on digital advertising effectiveness highlights the importance of integrated campaigns, and our results certainly support that.
Final Thoughts
Successfully increasing brand visibility across search and LLMs requires a holistic approach that considers both traditional SEO tactics and the unique characteristics of AI-powered platforms. By focusing on user intent, creating high-quality content, and continuously optimizing our campaigns, we were able to achieve significant results for Innovate Solutions. While the technical aspects are important, don’t underestimate the power of understanding your audience and crafting a message that resonates. Remember to get your brand seen in 2026.
The key takeaway? Don’t treat LLMs as an afterthought. Integrate them into your marketing strategy from the outset, and you’ll be well-positioned to capture a larger share of the digital market. For instance, this strategy can also help with Atlanta organic growth.
How important is it to optimize content specifically for LLMs?
It’s becoming increasingly important. As LLMs become more prevalent, users will rely on them for information and recommendations. Optimizing your content for LLMs ensures that your brand is visible and relevant in these interactions.
What are some key differences between optimizing for traditional search and LLMs?
Traditional SEO focuses on ranking high in search engine results pages (SERPs). LLM optimization focuses on providing clear, concise answers to user queries and aligning with the types of responses these platforms generate. Think conversational vs. keyword-driven.
How can I track the performance of my LLM optimization efforts?
Track metrics such as website traffic from LLM referrals, brand mentions in LLM-generated content, and conversion rates from users who interacted with your content through an LLM. Monitor your analytics carefully.
What type of content works best for LLM optimization?
Content that provides clear, concise answers to common user questions tends to perform well. This includes FAQs, how-to guides, and explainers. Structured data markup can also help LLMs understand and present your content more effectively.
Is it possible to rank in LLM outputs without ranking high in traditional search?
Yes, it is possible, although it’s less common. LLMs often draw information from a variety of sources, including websites that may not rank highly in traditional search. However, a strong SEO foundation will generally improve your chances of ranking in both traditional search and LLM outputs.
