T4

Channel saturation is well-documented but the precise shape of the CAC curve is rarely measured. Most companies see CAC rise as they scale a channel but attribute it to exogenous market changes rather than intrinsic saturation — this makes the underlying mechanism hard to separate empirically. The 'time-shifting portfolio' prescription is also contested: for early-stage companies with limited resources, running multiple channels simultaneously is operationally impossible, and the advice to hedge across channels can fragment effort below minimum viable concentration.

For any demand-generation channel (paid search, outbound SDR, content/SEO, events, partnerships), the channel has a finite addressable audience at a given intent level. As spend increases toward that ceiling, marginal returns fall because (a) the highest-intent prospects convert first, leaving lower-quality leads, (b) audience overlap increases as frequency rises, and (c) competitors respond by bidding up the same inventory. This produces a convex CAC curve: CAC(spend) is initially flat, then rises convexly. The optimum for any single channel is therefore sub-saturation — the point where marginal CAC equals target CAC. Because channels saturate at different rates and times, the portfolio-level optimum requires shifting spend toward less-saturated channels as the current channel approaches its ceiling. This is why GTM strategies must be periodically rebuilt: a channel that was below-saturation two years ago may be at ceiling today. The half-life of a GTM motion is approximately the time for the primary channel's CAC to double from its initial level.

• Facebook/Meta advertising: average CPM for B2B targeting rose ~60% from 2019 to 2022 as advertiser density increased, with auction-based pricing directly capturing saturation
• Outbound email: median reply rates fell from ~8% (2015) to ~2% (2023) per Salesloft/Outreach benchmarks as inbox density increased — a direct saturation signal
• Content/SEO: top-quartile SaaS companies that led with content (HubSpot, Drift, Intercom) saw organic CAC rise 2-3x as their categories became more competitive, requiring channel diversification
• Kyle Poyar (OpenView) analysis of PLG companies: the first 0-$10M ARR often runs on a single channel; companies that fail to add channels at $10-30M ARR frequently stall there

• Network-effect channels (referral, community) can have increasing rather than diminishing returns at early stages, violating the convex CAC assumption for a subset of channel types
• The optimal time to shift channels is empirically hard to detect in real time — companies often identify saturation retrospectively after CAC has already risen materially
• Brand investment (T13) may reset the carrying capacity of demand-capture channels by expanding the addressable intent pool, complicating the single-channel saturation model

For each active channel, track trailing-3-month CAC trend: if rising quarter-on-quarter without a corresponding improvement in lead quality, you are approaching saturation. Maintain at least one 'experimental' channel running at low spend so you have an alternative portfolio shift ready when the primary channel peaks. Build a channel-sequence roadmap: for most B2B SaaS, the historical sequence is outbound -> content/inbound -> events -> partnerships -> PLG, each layer adding capacity as the prior layer saturates. Review the roadmap annually, not just when current channels fail.