DTC Podcast

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We surveyed 540+ DTC operators on how they plan and forecast. This episode, we break down the data and see why most brands are stuck reacting. We’re joined by Laura Thompson, co-founder of Three Ships Beauty, one of the few who's figured out how to run a tight, fast, 8-figure brand without drifting into chaos, and Mike Chiasson, Senior Solutions Engineer from Keen Decision Systems, to pressure-test the Three Ships Beauty playbook against the data.

Grab your free copy of the report here: https://www.directtoconsumer.co/thereactiveloopreport

In this episode:
The biggest gaps in how DTC brands plan
Why "revenue is a lagging indicator"
The bottom-up forecasting Three Ships uses
The KPI ownership system across the whole team
When scenario planning is worth the time, and when it's just noise

If you’re a DTC operator past $5M who wants to stop reacting and start running a solid plan, this episode is a must listen.

Timestamps
0:00 Planning vs reacting in ecommerce
2:03 Why most brands only plan 1–6 months ahead
4:02 Bottom-up forecasting vs top-down forecasting
6:06 Scenario planning and external market risks
9:02 When media spend actually works harder
11:01 The reactive loop hurting DTC brands
14:03 Why brands over-invest in bottom funnel
15:06 Weekly KPI reviews and forecasting systems
18:02 The danger of reacting to noisy data
20:04 Leading vs lagging indicators in ecommerce
23:02 How talent impacts business performance
24:58 Product launch delays and forecasting pivots
26:53 Scenario planning for tariffs and supply chain risk
31:55 Should brands worry about oil shocks?
35:34 The biggest gap between planning and execution
38:02 KPI systems that drive accountability
42:16 The right way to plan for growth
44:02 Why reactive brands fall behind

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Helen Smith built Roo & You from hand-sewn mask lanyards in 2020 into a 100,000+ customer brand, and didn't touch paid ads for the first 3.5 years. In this episode she walks through the Facebook community that became her growth engine, how she landed Warner Bros and Harry Potter as a licensing partner without a media buyer, and what scaling through a tariff war actually looks like behind the scenes.

For DTC founders scaling from $1M to $10M who want to lower CAC and build a real retention moat.

What we cover:
The mask lanyard side hustle that funded her first container of play couches
How a private Facebook group became Roo & You's primary growth engine
The one-strike kindness rule that keeps the community alive
Cold-DMing Warner Bros on LinkedIn (and getting a yes)
Why licensing is a marketing channel, not a revenue play
Adding tariffs as a line item instead of a stealth price hike
Launching an affiliate program in November for existing customers

Who this is for: Founders leaning too hard on paid, or operators who want to build a community moat before they scale spend.

What to steal:
Show up in other people's communities for months before launching your own
Set strict community rules on day one, not after things go sideways
Make tariffs a visible line item to keep customer trust intact
Hand affiliate codes to existing customers before paying creators who've never used the product

Timestamps:
00:00 Building a brand through community
02:00 Using data to make better decisions
04:00 Handling tariffs and margin pressure
06:00 Launching through Facebook groups
08:00 Early demand and product expansion
10:00 Finding manufacturers and testing products
12:00 Pricing, value, and product longevity
14:00 Organic growth without paid ads
16:00 Transitioning into paid advertising
18:00 Leveraging community for content and growth
20:00 Licensing deals and brand partnerships
24:00 Structuring better partnership agreements
27:00 Challenges with licensing approvals
29:00 Why partnerships are for marketing not growth
30:00 Founder confidence and building in public
37:00 Expanding into the US market
40:00 Choosing the right marketing agency
42:00 Turning customers into advocates
47:00 Advice for founders building a brand

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Amazon’s AI assistant Rufus is already in ~40% of shopping sessions, and according to Amazon CEO Andy Jassy, customers who use it are 60–100% more likely to purchase.

Most brands haven’t adjusted.

Tyler Mazur (Head of Amazon @ Pilothouse) breaks down what Rufus is actually changing inside Amazon — from how products get discovered to how listings are interpreted across text, images, and context.

For DTC founders and Amazon operators who want to stay visible as AI-driven discovery becomes the default

What we cover:
What Rufus is actually doing inside the Amazon shopping experience
Why product discovery is shifting from keywords → problems
The marketing words that add zero value (and what to say instead)
Why Rufus reads your product images for context
How backend keywords should be used now
A simple 3-part plan to improve visibility this week

Who this is for:
Brands selling on Amazon that want an edge beyond just spending more on ads

What to steal:
Replace vague adjectives with real use-case language
Add context everywhere: PDP, backend, images
Make your listings easier for AI to understand, not just humans

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http://coyuchi.com

Coyuchi is a premium bedding brand with a long purchase cycle and high AOV. That changes how you approach growth, attribution, and retention.

Vicki Williams-Grahan (Brand President) explains how they tested Meta’s impact by turning it off, how they think about LTV in a low-frequency category, and why product selection inside ads matters as much as creative.

For DTC operators scaling high-AOV brands with long purchase cycles who need to rethink CAC, LTV, and attribution.

In this episode:
What happened when they turned off Meta for 6 weeks
Why Google Analytics 4 underreported performance vs platform data
How segmentation (via Decile) changed acquisition
Why entry-level products lowered overall performance
How they use daily forecasting and contribution profit

Who this is for:
Operators in high-AOV categories (home, furniture, luxury, etc.)

What to steal:
Run incrementality tests (or dim market tests)
Prioritize high-LTV acquisition, not just conversion rate
Track contribution profit daily

Timestamps
00:00 Introduction and evolving customer profile
02:00 Coyuchi brand overview and DTC shift
04:30 Challenges of high AOV and long purchase cycles
07:00 Customer segmentation and tools like Decile
09:30 Meta ads experiment and going dark
13:00 Attribution insights and incrementality testing
15:00 Daily forecasting and contribution profit focus
17:30 Product strategy and high LTV vs entry products
21:30 Retention storytelling and non-sales emails
25:00 Brand repositioning beyond sustainability
32:00 Bringing paid social in-house and creative speed
35:00 Using AI in marketing and creative testing
36:30 Channel testing including podcasts and CTV

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Meta changed attribution in March — and suddenly every brand’s ROAS looks worse.

Chris Richards from Pilothouse breaks down what actually happened, why performance appears to have dropped 30–45%, and how brands should respond without damaging long-term growth.

For DTC founders and operators scaling from $5M–$50M who rely on Meta as a core channel.

In this episode:
What Meta’s attribution change actually did
Why social proof no longer shows up the same way
How to interpret rising CPA and falling ROAS
Why MER is a better north star right now
The risk of over-retargeting after performance dips

Who this is for:
DTC founders, CMOs, and media buyers trying to make sense of Meta performance

What to steal:
Shift from ROAS to MER as your primary KPI
Keep funding top-of-funnel even when numbers look worse
Use consistent attribution (MTA) to guide spend decisions

Timestamps
00:00 Meta attribution change explained
02:00 Click vs engaged attribution breakdown
04:00 Impact on ROAS and CPA metrics
06:00 Social proof and ad performance insights
08:00 Why engagement optimization can backfire
10:00 Importance of multi-touch attribution tools
12:00 How campaign strategy is shifting
14:00 MER as a new performance north star
16:00 Omnichannel and ecosystem thinking
18:00 Meta automation and future attribution trends
20:00 What brands should do right now
22:00 Strategy mistakes and growth risks

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