
Co-Founder @storeheroapp helping DTC Brands grow profitability
NYC
Joined May 2012
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Last night’s queue right before kick-off at Shopify New York 👇
Our biggest turnout yet, not entirely surprised given the topic at hand and the speaker lineup.
AI is front and centre in every conversation right now, not just in DTC, but across every industry.
In DTC alone, I’m seeing it used for everything from creative ideation and ad copy, to building complex Excel formats and onsite merchandising etc!
Huge thanks to our speakers last night — @obviceo , @johnhickey1970 , Chris Maliwat — and the brilliant @Velstar_ duo, Joe Lyon & Greg Hughes, who flew in from the UK and will be around NY all week.
We’re closing in on 800 members in the DTC Builders New York group. If you're in NYC, get involved — some big events coming up 👊
meetup.com/shopify-e-commerc…
Double delight ! What a year for the men from Shanaway Road . Captain Cian Rynne hoists the Pappy Callaghan Cup .
#ThereIsNoHeroLikeALocalHero
@BannerGAAEnnis
Thomas Gleeson retweeted
JUST IN: Zuck reveals shopping has become the biggest use case for Meta's Muse AI, with over 25% of users shopping through the agent & average purchase exceeding $200.
Thomas Gleeson retweeted
HIGHLIGHTS: @BannerGAAEnnis are into the Clare Intermediate Football final after a last minute winner to beat @KilrushShamrock
@GaaClare
Thomas Gleeson retweeted
Loved how easy @StoreHeroApp 🤝 @claudeai integration is.
Are you using something like this?
If you (or your agency) are still using Google Sheets and/or spending time (and tokens) on building internal tools for this purpose - I am really curious about the upside.
NOT a Paid Promotion.
Haven't made a dime shilling StoreHero.
Met @GleesonThomas in @_lscommunity years back, we kept chatting on DTC finance, always enjoyed seeing the platform evolving & spreading the word to reach the right brands who'd benefit from this.
Founders who have worked with me will tell you I have a way of reviewing the numbers, pointing out the loopholes in the business that need fixing, and the opportunities worth prioritizing.
If you think you are at a stage that needs a second pair of eyes on your numbers, send me a DM.
Thomas Gleeson retweeted
"GET YOUR ASS INTO THE SimGym!"
- Unc Tobi
Easily the most interesting feature that @Shopify announced today in their Winter '26 Edition was the "SimGym". It allows you to unleash thousands of AI personas on your store to test changes before a real human ever sees them.
Driving the cost of learning to zero.
Here are the 10 simulations to run on Day 1 to improve your contribution margin:
1. The Elasticity Stress Test: Take your top 5 bestsellers. Simulate a 5%, 10%, and 15% price increase. Find the exact breaking point where the drop in conversion rate outweighs the gain in margin dollars.
2. The Free Shipping "Thresholdbreaker": If your free shipping threshold is $75, simulate moving it to $100, $125, and $150. Find the maximum AOV lift the AI will tolerate before cart abandonment spikes.
3. The Offer Structure Deathmatch: Stop arguing about whether "Buy 2 Get 1 Free" is better than "25% Off." Run the sim. Which offer generates more net profit dollars (not just revenue) after accounting for the cost of goods?
4. The "Discount Detox": Simulate turning off your 10% welcome pop-up completely. Does the increase in full-margin sales outweigh the drop in list growth and conversion?
5. The Aggressive Cross-Sell: How much friction can you add to the cart? Test aggressive, multi-step upsell flows in checkout. Find the line between "AOV boost" and "rage quit."
6. The Returns Policy Squeeze: Simulate a stricter return policy (e.g., adding a small restocking fee or shorter windows). If front-end conversion only drops 0.5% but you save 4 points of margin on returns, that’s a massive win.
7. Merchandising for Margin (Not Volume): Re-sort your collection pages to prioritize your highest % margin products first, rather than your bestsellers. Does demand shift profitably, or do users bounce?
8. The "Subscription Default": Simulate making "Subscribe & Save" the pre-selected default option on PDPs instead of "One-time purchase." Measure the impact on immediate conversion vs. projected LTV.
9. The High-Ticket Lander Validation: Before you drive paid traffic to a new bundle page designed to spike AOV, run it through the simulator against your standard PDP. Validate the economics before you validate the ad spend.
10. SKU Rationalization Sim: Take your lowest margin SKU. Simulate deleting it entirely. Does that demand shift to a higher margin alternative, or does it leave the store?
eCom is moving from a creative industry to an engineering discipline. Stop guessing. Start simulating.
This is a huge step in progressive truth.
Thomas Gleeson retweeted
Every week I hear: “We're trying a new attribution tool.”
And every time I think, “That won’t fix your signal.”
StoreHero’s guide to tracking puts numbers to the problem:
Browser-based tracking is now missing 30-40 % of conversion events.
Ad blockers, ITP, cookie limits, browser lockdowns. The browser is the weakest link in your data pipeline.
Attribution tools do not fix that.
They analyse the data. They do not repair it.
If your tracking is:
❌ Leaky
❌ Incomplete
❌ Blocked
…then every ROAS model you build on top is already wrong.
The sequence has to be:
1. Fix the signal
Move tracking server-side so every Shopify checkout, subscription, and upsell is captured, even when the browser drops out.
This is exactly where Littledata focuses: a reliable server-side Shopify data layer that ad platforms can trust.
2. Then layer attribution on top
Tools like StoreHero become far more useful once the inputs are accurate. That is when you get real answers to:
✔ Are these campaigns actually profitable?
✔ What is our true ROAS once costs are included?
✔ How much can we afford to spend to acquire a new customer?
❌ Bad signal → Bad attribution → Wasted spend
✅ Clean signal + Profit clarity → Sustainable scale
Thank you to Thomas Gleeson for including Littledata in the guide. Worth a read: storehero.ai/server-side-tra…
Thomas Gleeson retweeted
Curious what people are buying this Black Friday? Just talked about it on @CNN Early Start
Nice job @aloyoga, @cozyearth, Merit
Thomas Gleeson retweeted
Hungary 🇭🇺 2 Ireland 🇮🇪 3
Ireland has qualified for the World Cup playoffs with a goal in the 96th minute.
Congratulations Ireland!!
Thomas Gleeson retweeted
The next wave of 9 figure exits in eCommerce won’t be Brands, SaaS or agencies. They’ll be SEANs — Software Enabled AgeNcies.
The line between software and service is disappearing, and a new hybrid model is emerging in its place. A SEAN combines the scalability and predictability of SaaS with the human leverage and outcome-orientation of an agency.
It’s the inevitable result of two business models, software and agency, collapsing into one. (And yes, the name is a wink to DTC Twitter’s favorite @seanfrank, because he is the hired spokesperson for every “SEAN”.)
The convergence is a result of tectonic shifts in our landscape. SaaS is under pressure. In the mid-market and lower tiers of eCommerce, the expectation of value per dollar is so high that monetizing pure software has become nearly impossible. The dream of self-serve software, like Slack, where users can derive value in a completely autonomous manner doesn't exist. Most brands can’t extract value from software without guidance. And the truth is they don’t want tools; they want outcomes.
At the same time, agencies are evolving. AI and automation have made them faster, leaner, and more consistent. Internal tools, scripts, and proprietary systems are replacing headcount. The best agencies now behave like SaaS products, predictable, scalable, and data-driven. But they also possess a critical feature that most SAAS doesn't, accountability for the outcome.
These two forces are colliding. SaaS companies are adding services: onboarding, customer success, weekly strategy calls. Agencies are adding software: proprietary dashboards, AI layers, internal platforms. Both are converging on the same destination, SEAN. Modern examples include Haus, Fulfill, Fermat, Saras Analytics, Icon and US (CTC) each blending automation, software, and human expertise into a single, productized experience.
The economics are the key to understanding what is happening. SaaS was prized for revenue quality and scale, predictable ARR, great retention, and strong LTV/CAC (3:1). SEANs achieve similar economics through a slightly different route and with slightly less total scale. Gross margins drop from 90% to something closer to 60-70% as you add the human component, but net revenue retention still exceeds 100%, growth rates remain healthy, and operating expenses shrink thanks to AI and systemization. The market rewarded SaaS not for its form but for its financial model, and SEANs can come close to replicating that performance through a hybrid structure.
The benefit of eCom SAAS becoming SEAN's is that it reframes the pricing comparison for brands. Currently, SaaS sells into a brand’s software budget, maybe 1–3% of revenue. Agencies sell into the labor budget, often more like 10–12%. SEANs have the potential to reframe pricing around labor replacement, not software cost, expanding TAM and aligning pricing with true value delivered.
Investors are beginning to see it too. Many “SaaS” businesses are actually SEANs pretending to be pure software for the multiple, but the market is catching up. SAAS multiples are experiencing compression. Meanwhile, agencies that leverage technology are seeing multiple expansion as their margin and predictability increase. The two curves are converging toward a shared financial reality.
Ultimately, customers don’t care whether it’s software or service, they care if it works. The delivery model that can guarantee outcomes through automation, human intelligence, and proprietary systems will win.
The best SaaS companies will look like agencies. The best agencies will look like SaaS. The winners will be SEANs, Software Enabled AgeNcies, owning the middle ground where revenue quality meets operational leverage and customer's take home the lion's share of surplus value creation.
After a lot of conversations with StoreHero customers, I decided to put together a quick blog on new customer offers! (low CAC is not your friend)
storehero.ai/blog-how-to-bui…
Thomas Gleeson retweeted
Stellar article by @collision detailing how the Irish government is now just a bloated mess that does nothing, slowly
All progress stalls due to an epidemic of committees, NGOs, Quangos all of whom myopically focus on self preservation and local metrics.
irishtimes.com/life-style/pe…
Banner GAA have won the Clare Junior A Hurling Championship after overcoming Ballyea’s challenge. Result @BannerGAAEnnis 2-15 @ballyea_club 0-15. Photographs by @eugemccafferty.
Thomas Gleeson retweeted
I have been thinking a lot about product-market fit over the past year. Watching hundreds of brands come into Workspace6 has given me a strange front row seat. Some brands take off fast. Some grind for years. And the thing that is always fascinating is how little most founders really understand why they are winning or losing.
It is almost like educated or skilled luck.
Here is what I mean.
Brand A launches. They get to $1M in revenue. Then they stall. They cannot push through the ceiling. The founder grinds for years, often alone. They cannot afford real talent. They cannot afford real agencies. They are holding it all together with duct tape and stamina. Pure survival mode.
Brand B launches. From day one, the pull is obvious. Customers love it. Margins are strong. Word of mouth spreads. They grow fast. Suddenly, they need help. They have the budget to hire an agency or an in-house team. The agency steps in, rides the wave, and writes a case study about how they scaled the brand. The founder is now on stage at conferences. Podcasts invite them on to share their “tactics.” Everyone points to the ad account structure, or the retention strategy, or the TikTok creative.
But here is the truth. The spark was already there. The agency and the ops team just poured gasoline on a fire that was already burning.
That is what survivor bias looks like in ecommerce. We celebrate the winners and try to reverse engineer their steps, but in most cases the thing we are trying to replicate was never really visible in the first place.
Even the successful founders often do not know what really made it work. They just had some kernel of PMF. And when that kernel hit the right mix of team, supply chain, creative, and ad spend, it exploded. But the real question is always: what created that initial fire?
That first fire is everything. It sets the natural ceiling. The ops team, the media buyers, the creatives, the agencies, the retention playbooks—all of that just widens the aperture. If the kernel is weak, the fire never gets big. If the kernel is strong, the fire is almost impossible to contain.
And here is the hard part. That kernel is ephemeral. Experienced operators can often sense it. They can feel it when a product or a brand has that energy. But very few can create it on demand. It is slippery.
So I have been obsessed with trying to break it down. What are the actual components of PMF? What are the things that must exist in the DNA of a brand before anything else matters?
Here is where I have landed.
Core PMF Components:
Timing – Is the market ready now or are you too early or too late
TAM – Are there enough people who could want this to sustain real growth
Product Quality – Does it actually solve the problem well and hold up in the real world
Positioning – Are you targeting the right specific segment, not the whole world
Problem-Solution Fit – Is this solving a problem people feel urgently enough to act on
Price-Value Alignment – Does the price feel fair or premium in the right way, and will people actually pay it
Luck – Did all of these things line up in perfect harmony
Then there are the supporting components. These are the things that widen the aperture and let the fire spread higher.
Supporting PMF Components (that open or close the growth valve):
Channel Fit: Can you actually reach your target customers efficiently through the right channels
Unit Economics: Do the margins and payback windows support sustainable growth without needing insane amounts of capital
Offer Design and AOV: Can you structure the cart with bundles, upsells, thresholds, and cross-sells to fund your CAC
Conversion and Experience: Is the site simple, fast, trustworthy, and easy enough to buy from without friction
Retention: Do customers come back naturally without needing heavy discounts or constant bribery
Message and Creative Resonance: Do your value props actually land and convert in ads and content at scale
Operational Fit: Can your supply chain and fulfillment actually deliver consistently when volume increases
Availability: Are you easy to recall in the mind of the customer and easy to purchase in the moment they are ready
Data and Feedback Loops: Do you have systems to learn quickly, iterate, and forecast without guessing
Practical Ops Limits: Are there hidden ceilings like vendor capacity, 3PL mistakes, or cash cycle crunches waiting to choke growth
The uncomfortable truth is you can do everything right on the supporting side and still stall if the core is not there. You can have the best ops, the cleanest ad account structure, the slickest creative team, the smartest retention plays. If the kernel is missing, you are still going to grind uphill forever.
And the flip side is just as true. You can make a ton of mistakes and still feel unstoppable if the kernel is strong. You can run messy ops, mediocre creative, broken funnels. But if that core PMF is powerful enough, you will still scale.
This is the part most people do not want to acknowledge. Because it means you cannot always “tactic” your way into success. Sometimes you just did not have the kernel. And the people who did often do not even know it.
That is why I keep coming back to product market fit. It is not a checkbox you tick. It is the invisible ceiling on your entire business. And everything else we do is just about how wide we can open the aperture on the fire that is already burning.
From a UK based client, +40% contribution margin YTD with @StoreHeroApp



























