Why LinkedIn says building “owned prominence” beats rented ads in B2B marketing

LinkedIn printed analysis on December 2, 2025, arguing that B2B manufacturers should shift funding from “rented prominence” by means of paid promoting towards “owned prominence” constructed by means of model reminiscence and distinctive property. The analysis, authored by Kate Newstead, Advertising Science Lead at LinkedIn’s B2B Institute, types a part of a broader report titled “Straightforward to Discover: Being The place B2B Shopping for Occurs.”

The central thesis challenges standard B2B advertising knowledge. In line with the analysis, rented prominence—outlined as sponsored search adverts and paid placements—supplies instant visibility however creates dependency on steady spending. Owned prominence encompasses thought management, group engagement, robust model associations, and distinctive visible property that occupy psychological area with out ongoing media prices.

“Rented prominence is a fast repair, or a short-term lease, on model visibility,” in keeping with the doc. “However, with out a plan to transition towards owned prominence (e.g., thought management, group engagement, robust model associations), manufacturers danger being evicted from prime actual property the second budgets tighten, or opponents outbid them.”

The analysis arrives as generative AI transforms search behavior, with giant language fashions more and more mediating model discovery. This shift intensifies strain on B2B entrepreneurs to determine psychological availability earlier than patrons start energetic analysis.

The branded search efficiency hole

Dreamdata’s evaluation of B2B search investments, cited within the LinkedIn analysis, reveals stark efficiency variations between branded and non-branded search phrases. Non-branded searches returned simply 68% ROAS—which means advertisers misplaced $0.32 for each greenback spent. Branded searches generated $12.99 ROAS for each greenback invested, representing almost 19 instances larger effectivity.

This disparity exists as a result of branded searches seize demand from patrons who already know the corporate. Generic searches goal broader audiences earlier in consideration, requiring extra funding to transform prospects missing prior model publicity.

The analysis challenges assumptions about B2B search habits by means of collaboration with Dr. Grace Kite at Magic Numbers. In B2C telecommunications, 87% of searches included model names. B2B telecommunications searches talked about manufacturers simply 46% of the time. Cybersecurity, a purely B2B class, confirmed solely 14% of searches containing model references.

“Most B2B searches are generic, making it more durable for smaller manufacturers to face out until they’ve invested in constructing robust model property,” in keeping with the doc. The 86% of cybersecurity searches utilizing generic phrases characterize alternatives for manufacturers that set up psychological associations earlier than patrons formulate search queries.

LinkedIn’s analysis into B2B buyer behavior beforehand demonstrated that the majority patrons preserve shortlists of roughly three manufacturers earlier than coming into energetic buying processes. In line with Google and Bain analysis cited within the doc, these shortlists kind on “day one of many buy journey,” properly earlier than patrons seek the advice of search engines like google and yahoo or AI assistants.

Generative Engine Optimization emerges

The analysis introduces Generative Engine Optimization because the successor to conventional website positioning, responding to how AI-powered instruments floor model suggestions. In line with OpenAI analysis cited within the doc, model ideas more and more emerge from “advanced algorithms and third-party evaluation, with little direct affect from paid efforts from manufacturers.”

GEO rewards totally different indicators than conventional search optimization. Past technical parts like metadata and crawler permissions, generative AI instruments prioritize “natural indicators like thought management, genuine opinions, and earned mentions,” in keeping with analysis from Search Engine Journal, Forbes, and Basis Advertising cited within the doc.

This shift disadvantages B2B manufacturers depending on paid search. When patrons ask AI assistants for vendor suggestions, algorithms synthesize data from a number of sources fairly than displaying paid commercials. Manufacturers absent from coaching information or missing robust third-party validation grow to be invisible no matter promoting budgets.

The analysis argues this transformation makes model constructing “extra essential than ever” as a result of “model suggestions are more and more generated by means of advanced algorithms and third-party evaluation.” Corporations can not buy placement in AI-generated suggestions the way in which they purchase sponsored search positions.

LinkedIn’s emphasis on AI-driven discovery aligns with Google’s integration of AI Overviews into search results, which prioritizes synthesized solutions over conventional hyperlink lists. As search engines like google and yahoo incorporate generative capabilities, the excellence between paid and natural outcomes blurs, probably diminishing sponsored search effectiveness.

Constructing model property past logos

The doc specifies 4 classes of name property that create owned prominence. Visible id contains logos, shade palettes, and typography that make manufacturers recognizable throughout touchpoints. Message indicators embody CEO-led content material and proprietary frameworks that set up distinctive positioning.

Thought management consists of “constant POVs, authorities opinions, and insightful business evaluation.” Neighborhood indicators comprise partnerships, occasions, worker advocacy, and social proof demonstrating market engagement.

“These property ought to be woven into your advertising technique, not simply as ornamental items, however as foundational parts to construct psychological availability,” in keeping with the analysis. Psychological availability—an idea from Byron Sharp’s advertising science work—refers back to the chance a model involves thoughts in shopping for conditions.

The analysis emphasizes Class Entry Factors, purchase-triggering contexts the place patrons activate model recollections. Sturdy manufacturers create associations between their names and particular shopping for conditions: needing buyer relationship administration software program, addressing cybersecurity threats, or implementing advertising automation.

Premium paid placements ship similar attain no matter which advertiser purchases them. A platinum occasion sponsorship or first-in-feed advert unit prices the identical whether or not the client has invested in distinctive branding or not. Nevertheless, “the worth a model can extract from these placements considerably will increase when the position is paired with robust, distinctive branding that resonates with the contexts patrons encounter throughout buy events,” in keeping with the doc.

The analysis criticizes B2B entrepreneurs for underutilizing this chance: “In our view, far too few B2B advertisers capitalize on this chance. Leveraging distinctive property and Class Entry Level-first messaging represents low-hanging alternatives for considerably boosting the return on advertising investments.”

Why B2B lags shopper manufacturers

The analysis attributes decrease B2B model consciousness to funding patterns. Shopper manufacturers have made “typically vital and long-term funding” in distinctive branding and psychological hyperlinks between manufacturers and buying cues. B2B manufacturers “are inclined to have smaller bodily availability within the human mind” resulting from comparatively restricted brand-building exercise.

This manifests in search habits information. The 87% branded search fee in B2C telecommunications versus 46% in B2B telecommunications demonstrates how consumer-facing firms occupy extra psychological area. The 14% branded search fee in cybersecurity exhibits classes with out shopper presence face steeper challenges.

Committee-driven B2B buying amplifies the significance of broad consciousness. When a number of stakeholders affect vendor choice, manufacturers should obtain recognition throughout numerous job features and seniority ranges. Distinctive property assist totally different committee members keep in mind and advocate for a similar distributors.

The analysis hyperlinks GEO to this dynamic: “GEO favors manufacturers with robust, constant, and recognizable indicators; those that have invested in constructing a transparent id throughout channels.” AI instruments skilled on web content material privilege manufacturers talked about continuously throughout publications, opinions, social media, and business analyses.

LinkedIn’s previous research on B2B advertising effectiveness emphasised emotional resonance and distinctive artistic execution. The present analysis extends these rules into owned media and natural brand-building actions past paid campaigns.

Sensible implications for entrepreneurs

The doc acknowledges that “balancing rented and owned funding is not simple” however characterizes it as “a vital strategic transfer that reaps rewards over the long-term.” The analysis doesn’t advocate eliminating paid promoting however fairly rebalancing portfolios towards longer-term model investments.

Quick-term efficiency metrics typically favor direct-response techniques over model constructing. The 68% ROAS on non-branded search seems unfavorable in isolation, however the analysis suggests this spending might construct consciousness that later manifests in branded searches delivering $12.99 ROAS.

The comparability to actual property funding runs all through the doc. Renting supplies “instant entry to a main location however with little long-term safety.” Shopping for requires “lots of money and time to pay down, however month by month this self-discipline builds a precious monetary asset.”

“Owned prominence is the model equal of shopping for the land, designing the house, and turning into a part of somebody’s psychological neighborhood,” in keeping with the analysis. “It isn’t nearly visibility; it is about residing in your clients’ heads, rent-free.”

The analysis emphasizes cybersecurity’s 86% generic search fee as “white area” the place manufacturers can “form the narrative and seize mindshare.” Classes with low branded search characterize alternatives for firms keen to spend money on consciousness earlier than opponents set up psychological dominance.

The doc positions this work because the second in a sequence exploring B2B model discovery. Earlier protection examined presence—getting manufacturers “within the room” throughout purchaser analysis. This installment addresses prominence—guaranteeing manufacturers get “seen” when patrons consider choices. Forthcoming analysis will discover portfolio administration as “the important thing to getting your model chosen.”

LinkedIn’s analysis methodology drew on a number of sources together with Magic Numbers evaluation of search information, Google and Bain B2B purchaser research, Dreamdata search funding evaluation, and LinkedIn’s personal Hidden Patrons analysis. The synthesis combines quantitative efficiency information with qualitative insights about purchaser psychology and model recall.

The timing of this analysis displays broader business discussions about AI’s impact on advertising effectiveness. As machine studying algorithms more and more mediate model discovery, conventional paid promoting fashions face potential disruption. Corporations that established robust natural presence earlier than AI-driven search turned dominant might profit from algorithmic amplification of their present market positions.

Timeline

• 2022: Magic Numbers performed analysis for LinkedIn’s B2B Institute analyzing cybersecurity and telecommunications search information within the US market, revealing that solely 14% of B2B cybersecurity searches and 46% of B2B telecommunications searches included model names
• November 19, 2025: LinkedIn printed analysis on the value of B2B events as a part of constructing owned prominence
• December 2, 2025: LinkedIn’s B2B Institute launched “Transferring from Rented to Owned Prominence” authored by Kate Newstead
• December 9, 2025: LinkedIn launched follow-up analysis on portfolio administration methods for B2B manufacturers
• Ongoing: LinkedIn’s B2B Institute conducting analysis sequence “Straightforward to Discover: Being The place B2B Shopping for Occurs”

Associated PPC Land protection contains LinkedIn’s analysis of B2B buyer behavior, Google’s integration of AI Overviews with advertisements, and performance benchmarks for B2B advertising campaigns.

Abstract

Who: LinkedIn’s B2B Institute, led by Advertising Science Lead Kate Newstead, printed analysis focusing on B2B advertising professionals managing model technique and paid promoting budgets.

What: The analysis argues B2B manufacturers ought to shift funding from “rented prominence” (paid promoting) towards “owned prominence” (model property and psychological availability), citing information exhibiting branded searches ship $12.99 ROAS versus $0.68 for generic phrases, whereas solely 14-46% of B2B searches embrace model names in comparison with 87% in B2C classes.

When: LinkedIn printed the analysis on December 2, 2025, because the second installment in a multi-part sequence titled “Straightforward to Discover: Being The place B2B Shopping for Occurs.”

The place: The analysis applies primarily to B2B advertising contexts, with particular evaluation of cybersecurity and telecommunications sectors, and addresses implications for AI-driven search by means of platforms like Google and generative AI instruments.

Why: As generative AI transforms search habits and huge language fashions more and more mediate model discovery with out displaying paid commercials, B2B entrepreneurs face strain to determine psychological availability and natural presence earlier than patrons start energetic analysis, significantly since most patrons kind shortlists of roughly three manufacturers earlier than coming into buying processes.