42DM Reveals LinkedIn Activity Outperforms Website Traffic in AI Infrastructure Market

TENAFLY, N.J., Sep 16, 2026 /CourierPR/ -- 42DM, a B2B tech marketing agency specializing in go-to-market strategy for AI and SaaS companies, has released a comprehensive benchmark study that reveals LinkedIn activity is a stronger predictor of revenue than website traffic.

The study, which analyzed more than 40 signals across 11 dimensions, including LinkedIn distribution, organic and AI search visibility, trust infrastructure, paid channels, and founder brand, found that trust infrastructure outperforms raw traffic volume. According to Vasylenko, "In a market as dynamic as AI infrastructure, you can actually watch companies rise or stall based on their GTM choices. That makes AI infrastructure a much cleaner lens for understanding which activities predict revenue and which ones just feel like progress."

The research highlights that the channel with the strongest controllable correlation to revenue is one often treated as secondary by most teams. The findings also show that early data on AI search visibility already demonstrates a measurable signal, despite referral volumes still being modest. On paid channels, the study surfaces meaningful differences between display, social, and search, with results that may prompt some teams to reconsider their paid budget allocation.

Vasylenko emphasized, "The patterns are consistent enough that we feel confident saying: the companies growing fastest in this space are building specific things, in a specific order. The research shows what those things are." The study analyzed data from 100 leading AI infrastructure companies, selected to represent top performers within the niche. Data was collected across LinkedIn, Similarweb, Ahrefs, G2, GitHub, analyst databases, and proprietary AI visibility tools. All correlations are reported as Spearman rank coefficients.

The full report is available at 42DM, which includes an interactive company explorer, GTM signal breakdowns, correlations segmented by GTM motion and company maturity, and a personalized audit checklist. Teams looking to benchmark their own GTM motion against the dataset can book a free review at 42DM.

The research was conducted to understand the cause-and-effect relationships in the AI infrastructure market, which is developing at a pace that makes GTM cause-and-effect visible far faster than in mature categories. Vasylenko explained, "AI infrastructure was selected because top performers in the niche compete for similar buyers and face similar GTM challenges without directly competing with each other. That structure allows clean comparisons across GTM approaches."

The study provides valuable insights for companies building their GTM motion today, offering a clearer understanding of which activities predict revenue and which ones are merely progress. By focusing on trust infrastructure and optimizing LinkedIn activity, companies can enhance their chances of success in the rapidly evolving AI infrastructure market.