The real pattern in all these headlines: everyone is optimizing in isolation
Scan those headlines and you see the same story on repeat:
- “Adapt your entire funnel with AI”
- “Social-first ranking strategies”
- “Answer Engine Optimization”
- “100 most expensive keywords for Google Ads”
- “What’s working with short-form video right now”
- “When customers create more customers: superfans”
Every article is about a slice of the system:
search, short-form, communities, AI tools, title tags, cannibalization, conversion tweaks.
The pattern that actually matters: operators are drowning in channel-level optimization while the system that turns attention into revenue is barely defined.
Funnels, as most teams run them, are now a liability. They’re static, channel-centric, and blind to how people actually move: search, social, DMs, communities, creators, AI answers, and back again.
Meanwhile:
- Google search ad clicks are at a five-year high while keyword costs keep climbing.
- AI is rewriting how people discover and evaluate (AEO, AI overviews, ChatGPT testing ads).
- Social is fragmenting (Threads, Bluesky, Reddit SEO, TikTok Shop) and attribution is getting worse, not better.
The operators who win the next few years won’t be the ones with the best channel playbook.
They’ll be the ones who treat marketing as a demand system and run it like a portfolio, not a collection of disconnected tactics.
From “funnel” to “demand system”
The classic funnel is simple: awareness → consideration → conversion → retention.
Useful for slides, useless for decisions.
It hides the two things that now matter most:
- Where demand is actually created (often off-platform, in communities, creators, and conversations).
- Where demand is harvested (search, marketplaces, answer engines, retargeting, email, sales).
A demand system is a more honest map of how your money turns into revenue:
- Demand creation – making more people care and remember you.
- Demand capture – catching people already in-market.
- Demand expansion – turning customers into more revenue and more customers.
- Demand feedback – using data and signals to reallocate budget and fix friction.
Every channel, tactic, and AI tool you’re reading about belongs in one of those four.
If it doesn’t, it’s probably noise.
Step 1: Draw the system you actually run (not the one in the deck)
Before you touch AI, SEO, or social “best practices,” do this with your team on one page:
Map demand creation
List everything that makes someone who isn’t shopping yet become aware and interested:
- Paid social prospecting
- Short-form content (TikTok, Reels, Shorts)
- Creator and influencer programs
- Brand search terms that are not triggered by bottom-funnel queries
- PR, podcasts, events, communities, newsletters
For each, write down:
- Main metric (e.g., reach among ICP, branded search lift, direct traffic lift, view-through revenue).
- Typical payback window (e.g., 60-180 days).
- Annual budget share.
Map demand capture
This is where most performance marketers live:
- Non-brand search and shopping ads
- Retargeting and remarketing
- Marketplaces (Amazon, retail media, TikTok Shop)
- Affiliate and comparison sites
- Answer engines and AI surfaces (AEO, AI overviews, ChatGPT ads when they mature)
For each, document:
- True CAC / ROAS after incrementality adjustments.
- Share of total revenue influenced.
- How much of its volume is brand vs non-brand.
Map demand expansion
This is where “superfans,” communities, and CRM headlines live:
- Email and lifecycle flows
- Loyalty and referral programs
- Communities (Discord, Slack, Facebook Groups, Reddit)
- Customer content and advocacy (UGC, case studies, reviews)
- Sales expansion plays (upsell, cross-sell, renewals)
For each, track:
- Repeat revenue share (and margin).
- Referral / word-of-mouth contribution (even if estimated).
- Churn and expansion rates by cohort.
Map demand feedback
This is the part almost no one draws, but it’s where your edge lives:
- Attribution, MMM, incrementality testing
- Search term reports, Reddit threads, support tickets, sales call transcripts
- SEO audits, cannibalization reports, title tag tests
- Conversion rate experiments and UX research
Ask:
- What data actually changes budget decisions each month?
- What data just decorates dashboards?
Once this is on one page, patterns jump out:
- You’re overspending on demand capture because demand creation is underfunded.
- Your “SEO strategy” is just harvesting brand and a few head terms.
- Your community and CRM work hard, but no budget is allocated to feed them with new customers.
- Your AI initiatives are tools bolted onto a broken system, not a new operating model.
Step 2: Stop optimizing channels, start fixing system constraints
Most media plans are built like this:
- What worked last quarter?
- What’s trending in the industry?
- What did the platforms pitch us?
A demand system approach flips that.
You ask: Where is the constraint?
Constraint 1: Not enough new, qualified demand
Symptoms:
- Non-brand CPCs and CPAs keep rising.
- Retargeting pools are shrinking or flat.
- Brand search volume is stagnant despite more spend.
Moves:
- Shift a fixed percentage of budget into mid- and upper-funnel programs with clear audience definitions and time-bound tests.
- Use AI to scale message variation, not just volume. Test hooks, angles, and creative territories that feed organic search and social.
- Instrument brand demand: track branded search, direct traffic, and category search share as primary KPIs for creation.
Constraint 2: You create demand, but you don’t capture it efficiently
Symptoms:
- High awareness and engagement, low revenue efficiency.
- Search term reports full of queries you should own but don’t.
- AI and answer surfaces showing competitors when people ask about your problem space.
Moves:
- Run a ruthless search and AEO audit: fix cannibalization, own core problem and solution terms, and build content that answer engines actually use.
- Use AI for scale tasks: title tag rewrites, description variants, FAQ generation, but validate with human judgment and incrementality testing.
- Rebuild your landing experiences around intent clusters, not campaigns. If 8,000 title tags got rewritten somewhere, it’s because the system was built around Google, not around how buyers think.
Constraint 3: You capture demand, but you don’t expand it
Symptoms:
- High CAC, flat LTV.
- Referral and word-of-mouth are anecdotes, not measured channels.
- CRM is a broadcast tool, not a growth engine.
Moves:
- Design explicit “superfan” paths: from first purchase to contribution (reviews, UGC, referrals, community roles).
- Use AI to personalize timing and content in lifecycle, not to auto-generate generic copy that erodes trust.
- Give community and advocacy programs real budget and targets (e.g., % of new customers from referrals, review coverage on key surfaces).
Step 3: Put AI where it compounds, not where it decorates
Almost every headline now has “AI” in it.
Most implementations amount to:
- Faster content production.
- More ad variants.
- Chatbots and “assistants.”
The risk, as a Copyhackers headline put it, is a “trust problem”: outsourcing your message to generic tools in a tight market.
The opportunity is to use AI to tighten the demand system, not just pump out more assets.
Where AI makes sense in a demand system
-
Signal mining
Use AI to summarize:- Search term reports by theme and intent.
- Reddit, reviews, and community threads into objection and desire lists.
- Sales calls into battlecards and messaging tests.
This feeds both demand creation (better angles) and capture (better keywords, better pages).
-
Portfolio simulation
Use AI with your historical data to simulate:- What happens if you move 10% of spend from capture to creation for two quarters?
- What happens if you cut non-incremental branded search and reinvest into content or community?
You still need human judgment, but you get faster scenario planning.
-
Operational scale
Let AI:- Generate first drafts of variants (ads, emails, titles) against strict brand and compliance rules.
- Score and cluster creative and copy performance to find what actually moves revenue, not just CTR.
The test: if you turned off the AI tomorrow, would your system break, or just your content calendar?
If it’s the latter, you’re underusing it.
Step 4: Run your media like a portfolio, not a religion
In the headlines, you can feel the tension:
- Search clicks at a five-year high, but also “most expensive keywords in 2026.”
- Short-form video “what’s working now” sitting next to “we should all be building people-first communities.”
- AI everywhere, plus articles warning about over-reliance and trust erosion.
The answer isn’t to pick a side.
It’s to treat each part of the demand system as an asset class with:
- Risk (volatility, platform dependence, regulatory exposure).
- Return (incremental revenue, margin, brand equity).
- Time horizon (weeks vs quarters vs years).
A simple operating cadence for CMOs and performance leaders
Monthly:
- Review performance by demand stage, not just by channel.
- Identify the current system constraint and move 5-10% of budget to address it.
- Kill one thing that creates noise but no measurable system impact.
Quarterly:
- Run at least one incrementality test on your biggest “sacred cow” channel.
- Rebalance the portfolio across creation, capture, and expansion based on updated CAC, LTV, and payback.
- Audit AI usage: where is it compounding learning and speed, and where is it just making more average stuff?
Annually:
- Redraw the demand system map based on how your buyers actually behave now (including AI search, new social platforms, and new retail surfaces).
- Reset targets and incentives to match the system, not just last year’s channel mix.
The headlines will keep coming: new platforms, new AI tools, new SEO acronyms, new ad formats.
The operators who outperform won’t chase them one by one.
They’ll ask, every time: Where does this sit in our demand system, and does it fix a real constraint?