Short reads for short attention spans

B2B buying cycles shorten via LinkedIn "Member-to-Member" interaction

The landscape of B2B procurement on social networks has undergone a fundamental structural shift, with interpersonal thought leadership officially outpacing corporate brand pages. According to platform distribution data, corporate page organic content now accounts for less than 5% of total feed visibility, as algorithms systematically prioritise individual professional knowledge-sharing over static corporate updates.

B2B buyers are responding directly to this shift, starting 92% of their purchasing journeys by engaging with thought-leadership content published by individual founders, executives, and subject matter experts rather than following a brand's logo. This transition has dramatically shortened traditional buying cycles. When a prospect interacts with a founder's authentic, human-led post, they enter the sales funnel with a pre-established level of trust that traditional advertising cannot replicate. Comparative data shows that brand messages reach 561% further and generate a click-through rate that is 2x higher when shared natively by a professional's personal profile compared to an identical update on a corporate brand page.

For marketers, this means moving away from heavily polished, monolithic company communications and instead establishing an internal employee advocacy network to humanise the brand's expertise.

Why it matters

• The Trust Premium: B2B decision-makers treat individual personal expertise as a primary vetting signal, viewing insights from working professionals as far more credible than corporate self-promotion.
• Algorithmic Disadvantage for Corporate Pages: LinkedIn's feed is heavily dominated by member-to-member interactions, meaning companies relying entirely on company pages are invisible to over 90% of their addressable audience.
• Accelerated Lead Conversion: Leads generated via personal networks and employee advocacy are 7x more likely to convert into closed business, heavily reducing administrative overhead and sales lag.

Further reading at Supergrow:

LinkedIn Employee Advocacy Guide

Google Ads sets September deadline to retire Dynamic Search Ads

Google has officially announced the deprecation of its legacy Dynamic Search Ads (DSA) campaigns, setting a firm September 2026 deadline to automatically migrate all eligible search accounts into its next-generation automated framework: AI Max for Search.

For more than a decade, DSA served as a reliable automated safety net by scanning static website text to dynamically generate headlines for long-tail search queries. However, as consumer search habits become increasingly conversational, Google is shifting its baseline infrastructure. AI Max for Search marks a major transition by combining landing page text, advertiser-provided creative assets, and real-time contextual intent signals simultaneously. According to Google, search campaigns that adopt the full AI Max feature suite achieve an average 7% increase in conversions at a similar efficiency rate compared to legacy keyword and text-matching systems.

For search marketing teams, this change moves optimisation away from technical keyword mining and towards guided automation, where campaign success is steered by feeding the AI strict brand safety guardrails and high-quality copywriting assets.

Why it matters

• The New Automation Baseline: Automated account features, including automatically created assets (ACA) and campaign-level broad match configurations, will be absorbed into the unified AI Max ecosystem by autumn.
• Strategic Input over Manual Maintenance: Marketers will shift focus from scanning search term reports for exact keyword exclusions to training the system with clean first-party conversion data and deep asset libraries.
• Early Testing Advantage: Google has rolled out one-click upgrade experiments prior to the mandatory September migration, allowing advertisers to test campaign stability and protect performance early.

Further reading at Search Engine Journal:

Google Is Replacing Dynamic Search Ads With AI Max

Meta deploys "Andromeda" algorithm to make creative the new targeting

Meta has fully transitioned its advertising delivery network to a next-generation machine learning infrastructure, codenamed Project Andromeda. This architectural upgrade effectively replaces traditional, manual audience targeting with fully automated, creative-led delivery across Facebook and Instagram.

Built on custom deep neural networks running on NVIDIA Grace Hopper Superchips, Andromeda represents a 10,000x increase in model complexity at the initial ad retrieval stage. Rather than relying on advertiser-defined demographics, interest stacks, or lookalike audiences to choose who sees an ad, Andromeda scans the creative asset itself. The transformer-based system utilises computer vision and semantic analysis to read visual formats, opening hooks, text captions, and thematic clusters in near real-time. It then automatically matches the ad to the users most likely to respond based on their implicit behavioural patterns.

This update completely flattens traditional campaign structures. Uploading subtle variations of the same image is now actively penalised through "entity clustering suppression," which treats near-identical visuals as a single asset. To scale spend under Andromeda, brands must shift from technical audience slicing to producing highly diverse, platform-native creative hooks.

Why it matters

• Targeting is Automated: Manual interest targeting has become a soft suggestion rather than a strict gate. The Andromeda algorithm will routinely override your manual audience settings if creative signals point to a better match.
• Consolidation Wins: Meta’s testing confirms that a single campaign structure packed with diverse creative assets generates 17% more conversions at a 16% lower cost than splitting budgets across multiple narrow ad sets.
• Semantic Diversity Over Volume: Advertisers cannot trick the system by changing a button colour; Andromeda requires genuinely distinct creative concepts. Performance data reveals that brands testing 20+ entirely unique creative hooks per month achieve a 65% higher ROAS than those launching fewer than ten.

Further reading at The AI Journal:

How Meta’s AI Overhaul is Forcing Advertisers to Evolve