A shopper encounters your brand in an AI-generated response, validates it in a private Slack channel, and lands on your site without leaving a single iota of attribution in your analytics. The reality of multi-channel attribution is that demonstrating ROI often feels like navigating a maze blindfolded when the touchpoints with the greatest impact aren’t showing up in reports.
This tension was the focus of the paper “Content Everywhere: Winning Attention in a Fragmented Marketing Ecosystem” at the MarTech Conference in November 2026. Speakers explored how to design discovery-driven topic architectures across decentralized channels and demonstrate business influence far beyond direct clicks.
Tamara Scott, chief content officer at overQualified LLC, moderated the conversation with Steve Bevilacqua, principal consultant at Cella by Randstad Digital; Nichole Kelly, CEO of True North Growth Labs; and Patrick Schofield. associate director of relevance engineering at iPullRank.
Start with the questions buyers ask
Kelly shared that high-converting content architectures start directly with the specific, nuanced questions that prospects ask AI engines during the evaluation stages, specifically competitive analysis and stage-specific decision criteria.
He emphasized creating “evidential marketing”: backing every key claim with original data, verified customer testimonials and authoritative quotes. This gives both the target buyer and the algorithm that recommends your solution concrete reasons to trust your expertise.
Schofield urged leaders to move beyond single URL optimization. AI retrieval surfaces video snippets, graphics, and community threads alongside long-form editorial pieces.
“Plan around topics rather than pages,” Schofield emphasized.
A single, unified topic can anchor authoritative guidance, a short explainer video, executive-ready graphics, and thoughtful participation in community discussions. This structure turns deployment into an upfront design resource rather than an afterthought.
Find out where the flu happens
Bevilacqua highlighted a major shift among business organizations toward niche peer communities where professionals share unvarnished recommendations. These conversations drive revenue decisions without exceeding the baseline data that marketing analytics platforms typically depend on.
His advice provides an immediate path forward: Make client self-reported qualitative attribution a permanent fixture on intake forms.
Pairing self-reported data with automated category checks reveals gaps your reporting suite isn’t catching. Query popular AI tools across top product categories to see which authorities, publishers, and competitors get citations.
Schofield tracks this metric directly as “citation share,” tracking which domains and platforms large language models cite for high-intent category queries. This takes the guesswork out of showing where authority actually lives rather than where we assume it is.
Kelly encouraged teams to evaluate engagement across the entire buyer journey rather than retreating into rigid first-touch or last-touch models. Scott defined the challenge as “giving credit where credit is due through marketing.”
This shared visibility strengthens alignment across teams. Kelly highlighted the importance of treating PR and brand communications as strategic partners: third-party editorial mentions and contributed articles serve as primary knowledge sources for AI engines, building lasting brand authority even when they don’t pass direct referral traffic.
Make each section useful on its own
Schofield outlined a practical design framework for content built to survive modular retrieval and summarization engines.
“Each section has to make sense when taken out of context on its own,” he said.
Here’s the operational model: limit each section to a central insight, create subtitles that reflect users’ explicit questions and indicate the main answer in the first two sentences. Naming your brand and platform explicitly ensures that the context remains intact wherever the extract is served.
This discipline also pays the dividends of reuse. A standalone response cleanly transforms into a targeted LinkedIn insight, an executive quote, or a modular knowledge base article.
Kelly suggested working directly with Sales Engineering and Customer Success to catalog the questions prospects ask in the final stages of negotiations, then craft modular responses of varying depth.
When structuring the production pipeline, the panel noted distinct ways to integrate automation. Kelly uses an AI engine trained on approved brand messaging and technical documentation to generate first drafts. Bevilacqua claims to start with original frameworks written by professionals and leverage artificial intelligence to accelerate derived assets, video clipping, and workflow routing.
Schofield highlighted that research benefits greatly from automation, particularly graph mapping of research entities and tracking citation visibility.
Choose your next investment with evidence
When allocating the budget for amplification, Kelly recommended supporting resources that already show organic momentum.
“If it’s already starting to show signs that people agree with it, then it’s a great candidate to allocate budget towards amplification,” he said.
Bevilacqua added that context matters: monitor sentiment alongside volume so you can invest in discussions that actively build brand value.
For teams ready to implement this, Schofield offered a clear first sprint: test the top 10 business assessment questions on leading AI platforms.
“Write down who gets named, who gets mentioned, and what gets said about you, then put together a plan to fill in the gaps.”
This is doable and provides a reliable, data-backed foundation for bridging the gap between content investments and actual pipeline impact.
