DTC Podcast

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Full Glass Wine Co.

Neha Kumar joins the podcast to break down how Full Glass Wine Co. acquired 7 DTC wine companies, integrated them under one operating system, and scaled to a $200M platform in under two years.

This wasn’t a “buy brands and hope” strategy. Neha explains how COVID-era DTC brands overbought inventory, ignored unit economics, and optimized for growth over profitability — creating one of the biggest acquisition opportunities in modern ecommerce.

For DTC founders scaling from $5M–$50M who want to improve retention, fix unit economics, and build operational leverage across brands.

Inside the episode:
Why subscription models quietly broke a lot of DTC wine businesses
The exact operational changes Full Glass uses to make acquisitions profitable in 60–120 days
How they centralized shipping, finance, SMS, and retention while preserving each brand’s identity
Why retention, not acquisition, became the core growth engine
The hidden downside of emailing subscription customers too often
How Wink’s 7M-email quiz funnel became a massive acquisition asset
Why customer segmentation matters more than product assortment in brand acquisitions
The “three legs of the tripod” framework for building durable DTC companies: marketing, finance, and operations
Neha’s “Year of Yes” mindset shift inspired by Willy Wonka that changed how she built companies

Who this is for:
Operators, retention marketers, DTC founders, PE-backed ecommerce brands, acquisition entrepreneurs, and anyone trying to scale profitably after the cheap-CAC era ended.

What to steal:
Move from monthly shipments to higher-AOV quarterly bundles to fix shipping economics
Centralize infrastructure, not brand voice
Treat retention like the business engine, not an afterthought

Timestamps:
0:00 Intro to Full Glass Wine Co
2:18 Why DTC wine brands struggled after COVID
6:12 How Winc collapsed from inventory overload
8:05 The 3-part formula for profitable DTC brands
10:05 What Full Glass looks for in acquisitions
13:05 Centralizing customer service across wine brands
15:02 Building brands around customer identity
17:42 The Willy Wonka “year of yes” mindset
21:58 What happens after acquiring a company
24:45 Why subscription models don’t work for wine
29:12 Storytelling vs transactional retention emails
32:18 How Full Glass approaches retention marketing
35:05 Managing inventory and cash flow in wine
37:15 Trusting intuition as an operator
40:18 How Full Glass is using AI internally
42:05 Are the next generation of entrepreneurs ready?
45:00 What’s next for Full Glass Wine Co

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Meta attribution has changed, and most brands are still reading performance the same way they were a year ago.

Jacob, Head of Socials at Pilothouse, walks through what’s different now. Click-only attribution, incremental measurement, and how those shifts affect the way conversions show up in your dashboard.

If you’ve noticed numbers feeling off lately, this will help you understand why and what to actually pay attention to.

For DTC founders and marketers spending $50K–$500K/month on Meta who want to understand what’s actually driving conversions.
What click-only attribution removes from reporting
How incremental attribution works in practice (without the fluff)
Why conversion numbers feel different even when performance hasn’t changed much
Where Meta data and third-party tools start to diverge
How Pilothouse is thinking about reporting and decision-making now

Who this is for:
DTC operators, performance marketers, founders scaling paid social

What to steal:
Check incremental conversions alongside total before making changes
Look at channel performance in context of total revenue, not in isolation
Use Meta data as one input, not the final answer

Timestamps:
00:00 Intro
02:28 Meta’s New Attribution Shift
05:03 How Incremental Attribution Works
08:11 Conversion Windows and Optimization
10:15 Why Better Signals Improve Meta Performance
13:02 Agentic Ads Explained
16:02 AI Business Agents and Customer Conversations
18:05 Setting Up Meta’s AI Agents
19:28 AI Ad Automation and Testing Strategies
21:14 Q2 Meta Performance Trends
23:02 Why Meta Reduced Over-Attribution

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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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