The AI Commerce Playbook for DTC CMOs in 2025
A focused plan to reallocate budget, refactor teams, and win in AI shopping without breaking your current engine.
You're running a DTC brand. You have revenue targets that don't care about emerging channels. Your board wants growth this quarter, not experiments that might pay off in two years.
And now you're hearing about AI shopping, ChatGPT commerce, and agentic discovery. You know it matters, but you don't know how to prioritize it without breaking what's working.
Here's how to do both.
The core tension
Traditional channels still drive most revenue. Paid search, paid social, email, organic. You know how to scale them. You know what levers to pull for growth.
AI shopping is different. New playbook. No years of historical data. No proven ROAS benchmark. You don't know how much to allocate or who should own it.
But here's what you do know: discovery is shifting. Consumers are asking AI agents for recommendations. ChatGPT Shopping is live. Walmart just partnered with OpenAI. Perplexity has shopping features. The infrastructure is being built right now.
The risk isn't missing a trend. It's that in two years, when this channel drives 20% of category sales, you're playing catch up against competitors who've been iterating for 24 months.
So the question isn't whether to invest. It's how to invest without jeopardizing current performance.
Budget reallocation that works
Most CMOs don't have extra budget. You need to reallocate. Here's how without killing performance.
Take 5-10% of non-branded search and prospecting budget Not the spend driving efficient conversions. The marginal dollars hunting new customers at higher CACs. Redirect to AI shopping readiness.
This works because AI shopping is fundamentally a discovery and acquisition channel. You're not retargeting existing customers. You're showing up when new shoppers ask for recommendations.
In practice: reduce spend on broad keyword targets in Google that aren't converting efficiently. Pull back slightly on cold audience prospecting in Meta. Trim the edges to fund something with higher long-term leverage.
Reallocate content and brand budget If you're investing in SEO content, brand awareness, or influencer partnerships, some of that can shift to building source authority for AI shopping. Similar tactics. Earning credible mentions and building category authority. Just optimized for AI discovery instead of traditional search.
This isn't massive reallocation. Tens of thousands per quarter, not millions. Enough to fund the work that matters without destabilizing your core engine.
Team and ownership
The biggest mistake is treating AI shopping as a side project for the SEO team. It becomes one more thing on a long list and never gets focus.
You need someone who owns it as their primary responsibility. The ChatGPT Shopping Specialist. The person who wakes up thinking about product data, testing visibility, earning source authority, and coordinating with engineering on instant checkout.
This person reports into growth or ecommerce. Not buried three levels down. They need visibility and influence because the work crosses functions. Product data lives in merchandising. Source authority requires PR. Checkout involves engineering.
Create a weekly operating cadence. Not quarterly planning. AI shopping moves fast. Weekly review of visibility metrics, gaps, priorities, and shipped improvements. Treat it like performance marketing, not brand strategy.
Brands winning in AI shopping have this rhythm. Test weekly. Identify what's broken. Fix it. Measure improvement. Repeat.
Metrics that matter
Traditional KPIs like CTR and bounce rate don't translate to AI shopping. Track these instead:
Visibility rate for top buyer intents For the 5-10 high-intent problems your products solve, how often do you show up in recommendations? Your equivalent of share of voice.
Attribute completeness for hero SKUs What percentage of top products have complete, structured data? Not just title and price. All attributes an AI agent needs. Leading indicator of whether you can compete.
Credible source coverage For top products, how many trusted publications or reviews mention and recommend them? Your source authority metric. Harder to measure than backlinks, but matters more in AI shopping.
Agent to checkout conversion For traffic from AI shopping channels, what percentage completes purchase? Tells you if checkout is optimized or if you're losing people to friction.
Revenue from AI shopping The lagging indicator. By the time you have meaningful revenue, you're either winning or behind. Leading indicators let you course correct early.
The first 90 days
Week 1: Baseline Run visibility checks for top buyer intents. Audit product data. Identify top three to five gaps clearly holding you back.
Weeks 2-4: Planning Get alignment with merchandising on fixing data. Start engineering conversations about instant checkout. Reach out to reviewers and editors.
Weeks 5-8: Execute first fixes Ship attribute improvements. Get one credible source to feature top products. Test checkout for agent-initiated purchases. Prove the work drives results.
Weeks 9-12: Scale Expand to more products. Test more intents. Build more source relationships. By day 90, measurable improvement in visibility and proven process for continuous optimization.
Resist the urge to boil the ocean. You're not fixing the entire catalog. You're proving the model with hero products, then scaling.
Risks and how to avoid them
Analysis paralysis - Waiting for perfect data and perfect tools before starting. AI shopping moves too fast. Start now with imperfect information and iterate.
Treating this like brand awareness - AI shopping is measurable. You can see where you rank. Track improvement. Tie to revenue. If you're not measuring, you're doing it wrong.
Fragmented ownership - If data lives in one silo, source authority in another, checkout in a third, and nobody coordinates, you'll ship slowly and miss opportunities. Centralize ownership.
Neglecting current performance - Don't let core channels degrade while chasing AI shopping. The budget reallocations suggested are intentionally small. Fund the future without breaking the present.
Why this matters now
In two years, every DTC CMO will have an AI shopping strategy. The ones who start now will have compounding advantages. Better data. Stronger source authority. More refined checkout. Higher visibility.
The ones who wait will be playing catch up. And in a channel where only top three to five recommendations matter, being late is expensive.
You don't need all the answers today. But you do need to start. Allocate the budget. Hire the person. Build the operating rhythm. Test and iterate.
The brands that win will be the ones that recognized the shift early and moved decisively. Make the investment now. Protect your core engine. But build for the future at the same time.