
L/S Investing Ideas William McLane & Max Howard Substack: https://teapawt.org/t.co/JoHYx51jYu Contact: [email protected]
Joined April 2026
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We are short $SBUX with a PT of $70.76 and a 27% projected NTM IRR with 2.8x R/R. The Street believes Brian Niccol’s “Back to Starbucks” turnaround is a success, extrapolating accelerating SSSG into sustained demand and normalized margins. We disagree. Our geospatial imagery analysis, calls to 300 stores, scrape of 1.2M store-week operating-hour posts, permit filing analysis, scrape of 10,082 Glassdoor employee reviews and 80,777 Google reviews, credit card and foot traffic data covering 150M Americans, and survey of 293 customers reveals that 1) store closures are disproportionately concentrated in trade areas where demand can be transferred to nearby Starbucks locations, inflating SSSG by 483 bps, 2) Emerging beverage brands are increasingly locating directly within Starbucks’ trade areas, with competitor openings associated with 8-10% declines in Starbucks traffic, and 3) the Street erroneously models margins reverting to 2022 peak levels despite shops being drastically understaffed, all while employee sentiment declines precipitously.
Our thesis is threefold:
1. Under Brian Niccol’s “Back to Starbucks” plan, Starbucks closed 627 North American company-operated shops in Q4 2025. Since then, SSSG has accelerated from 1.0% to 7.9%, which the Street views as sustained organic growth continuing into FY2027. We believe management has materially understated the customer transfer impact from store closures on transaction growth, with our analysis showing ~483bps of inorganic transaction tailwinds ending after this quarter, most of which management claims is organic.
2. Starbucks has historically dominated the U.S. specialty coffee and drive-thru beverage market. However, its competitive landscape is rapidly changing, as emerging brands ($BROS, 7 Brew) scale into Starbucks’ core markets. Our channel checks indicate 7 Brew will deliver 60%+ unit growth over the next two years, with 500 and 900 openings in FY2027 and FY2028 respectively, while Dutch continues to grow at 17%+. Our analysis of leasing documents shows that 73% of these emerging brand stores are scheduled to open within a mile of a Starbucks, which based on foot traffic alternative data has historically led to 8-10% volume declines at similar locations.
3. In FY2022, Starbucks averaged 26.8 employees/store before cutting North America employees/store to a trough of 19.8 in FY2024, well below competitors’ staffing. Despite Starbucks’ $500M labor investment, which has since increased employees/store to 21.3 in FY2025, we believe Starbucks’ current staffing levels are unsustainable as it adopts a more service-intensive operating model.
Valuation: We model 483 bps of closure-driven SSSG unwinding as Starbucks laps the FY2025 closure cohort, with 181 bps of offset from the FY2026 cohort. This, combined with increasing competition, drives North American SSSG 174 bps below consensus in our base case and 286 bps in our bear case. This steps up by another ~280/420 bps respectively in FY 2028 as the 181 bps tailwind is lapped and competition intensifies. We model labor intensity remaining structurally elevated, forecasting Starbucks increasing employees/store from 21.3 to 24.0 through FY2027, driving FY2027 EBIT margins 263 bps below Street projections. Utilizing a conservative 18.5x/18.5x/20.0x NTM EBITDA multiple on FY2028 EBITDA, our bear/base/bull cases yield price targets of $48.48/$73.39/$113.95, respectively. Weighted at 35%/50%/15%, this yields a weighted average price target of $70.76.
An in-depth breakdown of our primary research and full theses, along with a catalyst path will be published tomorrow.
Credit Capital retweeted
Congrats to SharpeShooters, Ayush Bobra (Princeton) and Ambilu Sivabalan (Cornell), on winning the 4th Annual Wharton Investment and Trading Group x Fundamental Edge Stock Pitch Competition with their $CPRT short.
All five finalist decks are now up, free, at the link below.
1. SharpeShooters (Princeton/Cornell): Short $CPRT
2. New Line Capital (Wharton): Short $ABNB
3. Credit Capital (Georgetown): Long $BROS
High Gamma (University of Florida): Short $SIG
Cavalier Capital (University of Virginia): Short $COCO
Thanks to @AlphaSense for sponsoring.
fundamentedge.com/witg-2026
I continue to be insanely impressed by the talent of the top undergraduate teams. May the kids are going to be alright...
Credit Capital retweeted
awesome by @marketplunger1 to make this happen, and by @creditcapi putting themselves out there in the first place
this is all exactly how its supposed to go
if you are young and you show courage, someone is going to reward you for it
and none of this is zero sum.
anyone who is throwing ideas out there and defending them against the world, plus showing name/face on podcasts and videos...all those dudes are going to win.
because there just isn't a lot of competition. over and over you see the truth of the statement "80% of life is simply showing up"
worst that happens is ur idea gets destroyed, u get smarter, and u take a loss measured in ego instead of dollars, which is a hell of a lot cheaper
its only upside for everyone involved
perfect execution by all parties 🎯
A sincere thank you to Brandon Beylo (@marketplunger1) for having us on the Value Hive podcast.
In our conversation, we cover:
0:02: Our love of investing, reading, and writing
0:08: AI in our investing process
0:16: Our Starbucks short ($SBUX)
0:33: Thoughts on Dutch Bros ($BROS)
0:47: CQS scores on Reddit ($RDDT)
0:55: Our idea generation process ($ATZ.NE)
0:57: Our investing process
1:04: Lewis and Clark and Steve Schurr
open.spotify.com/episode/5Mt…
$RDDT dumps -26% after Q3 print on decel in US DAUs (-2% y/y). As mentioned in our Substack write-up 7 weeks ago and the podcast a week ago, we predicted this. If you're not familiar, here's a brief, qualitative summary of our ideas:
1. We believe Reddit’s user retention flywheel is broken. CQS (Contributor Quality Score) is Reddit’s spam filter, introduced in early 2024, that sorts every user into one of five trust tiers (lowest to highest). Your score is based on account age, IP and verification, how often and how well you post, and overall activity. Most big subreddits automatically delete posts and comments from anyone in the low or lowest tiers, which is good at stopping bots, but brand-new accounts land in those tiers by default, so a real new user’s first posts get deleted. This is exacerbated by “karma gates,” which require users to have a minimum amount of karma before they can post in a subreddit. So new users need karma to post, try to earn it by commenting, get deleted because their CQS is too low, and eventually give up and leave. You can check your CQS score on r/WhatIsMyCQS
2. Google’s AI Overview adoption has crushed Reddit's traffic. DUAs/WAUs have dropped ~100 bps y/y for the past few quarters, a good indication of the churn, as people are using Reddit less frequently.
A sincere thank you to Brandon Beylo (@marketplunger1) for having us on the Value Hive podcast.
In our conversation, we cover:
0:02: Our love of investing, reading, and writing
0:08: AI in our investing process
0:16: Our Starbucks short ($SBUX)
0:33: Thoughts on Dutch Bros ($BROS)
0:47: CQS scores on Reddit ($RDDT)
0:55: Our idea generation process ($ATZ.NE)
0:57: Our investing process
1:04: Lewis and Clark and Steve Schurr
open.spotify.com/episode/5Mt…
We truly enjoyed being on the podcast and covering everything from investing process to goals we have for the future, as well as some ideas we've been looking at.
Looking forward to the release!
Very excited to release my podcast with @CreditCapi.
Really enjoyed interviewing two young, hungry investors cutting their teeth, sharing their ideas publicly, and striving to become the best investors they can.
Need more of these interviews IMO.
Hope y'all enjoy.
While we believe some alpha remains in granular modeling, particularly for balance sheet heavy companies, we find that now more than ever investigative journalism is at the core of a successful investment process.
Inspired by Steve Schurr, we have found the best way to develop a differentiated edge is to focus on weird, idiosyncratic research. We strive to look where no one else is looking and do the research no one else is doing. As AI proliferates, this will only become more important as 1) people continue to outsource their critical thinking to AI, narrowing the diversity of opinions and 2) AI enables us to conduct unique primary research that would not have been possible before.
Being able to ask the right questions and use an investigative journalistic approach to answer them accurately will be a true differentiator going forward.
There is absolutely no alpha left in being an excel monkey better than anyone else
This was already the case before AI, but more true today than ever before
I am literally watching Claude in Excel build a forecast model better than 80% of analysts while I write this
The hours of work it would take to put together a coherent analysis can now be done in minutes with proper prompting and instructions
All the alpha in the investing world now sits outside of your desk. This includes talking to management teams, experts, former employees, competitors, trying the product itself, and so on
Fundamentally think that the job of an investor will slowly start to resemble that of a journalist
The real work will be done through conversations that an LLM cannot capture in the open web or inside of documents that everyone has access to
Replying to @zero_sum42
Will post this at some point this weekend. Currently working on another short.
Replying to @RMB
Definitely, there's nothing more we enjoy than chatting names
Replying to @BrokenMoats
Replying to @roicincremental @liensofnewyork
Being below the high bar doesn't put you at system average, but it certainly makes it possible, probable even when you factor in third-party traffic data, that our analysis has merit. I have truly enjoyed the debate over this, and we certainly cede that with AUV or retention fluctuations we could be +/- a certain number of bps. If you have a more constructive, data driven way to approach the problem other than just "assume they are below systemwide AUV," we would love to hear it.
Replying to @roicincremental @liensofnewyork
I think you misunderstand our point regarding AUV driver math. Nowhere do we use that to calculate store level AUV, that was simply a representation of these stores being in more attractive trade areas where sister stores can absorb demand.
Outside of all the primary research and alternative data, simply taking a first principles approach to the problem, average stores in these areas have higher operating costs than an average store and thus must have higher AUVs than systemwide stores. Underperformance is benchmarked against this.
Replying to @liensofnewyork
We had modeled ~90% retention rate based on our calls and third party data described in the pitch. We also found that the closed store AUV was slightly higher than expected as these stores were underperforming their surrounding areas, but these areas produced higher AUV locations on average. As mentioned these were denser, urban areas associated with higher costs, so above average costs and AUV.
Replying to @liensofnewyork
Yes, all the AUV driver analysis was showing was that these stores are in denser locations (thus higher rent) with ample sister stores nearby to absorb demand from closures. They were definitely not outperforming stores.
Replying to @liensofnewyork
They aren't closing profitable stores they are closing underperforming stores in profitable locations.
Replying to @zero_sum42
58 bps is derived from the 1.2M store-week database we scraped to back-out weekly hour increases across every North American company-operated store. Using total store hour increases year-over-year combined with some downward adjustment for lower traffic than average hours, you can reasonably arrive at an estimate. We believe the intensifying competitive landscape has led management to try to obscure worse than expected traffic metrics by partially attributing organic growth to inorganic tailwinds and hoping they can reverse the trend in the coming quarters.
Replying to @roicincremental
Costs are higher because the stores are more concentrated in high AUV urban areas where rent, labor, etc. is more expensive. As for the alt data, perhaps we have different providers.
Replying to @roicincremental
First of all, as we had previously discussed, they closed stores that were underperforming on AUV relative to shops around them. These were mostly in high traffic areas where they were running AUV below sister stores but in line with system-wide. Costs were obviously higher for these stores in more attractive areas so they underperformed significantly on 4-wall margin but not on an AUV basis. Also, hours is not double-counting the same traffic, it measures incremental traffic from remaining open longer.
Short $SBUX Full Pitch and Research: We are Short Starbucks with a PT of $70.76 and a 25% projected NTM IRR with 2.2x R/R as of today's sell-off.
Thesis 1: Starbucks’ Store Closures Artificially Inflate SSSG More Than Management Has Disclosed.
Evidence: We mapped all 584 closed U.S. stores using opening and closing data from starbuckseverywhere.net and additional scrapes. Utilizing geospatial satellite imagery analysis, we measured their proximity to surviving Starbucks locations. 62% of closed stores had a company-operated Starbucks shop within 1 mile, vs. 26% of remaining open stores. To determine whether Starbucks disproportionately closed stores in weaker trade areas, we matched the closed shops with 584 randomly selected open stores in equally dense trade areas and compared AUV drivers (# of schools, hotels, office buildings, colleges, etc.) and competitor density using the same geospatial satellite imagery analysis. Counterintuitively, closed shops were located in more attractive trade areas, averaging 128.7 AUV drivers within one mile vs. 107.3 for open stores, while competitor density was effectively unchanged at 44.1 vs. 43.4. The ~250 additional stores announced for closure in Q4 show the same pattern: 52 vs. 43.1 AUV drivers and 34.1 vs. 31.7 competitors, with 56% of stores having a sister within 1 mile. This closure pattern is consistent with Starbucks disproportionately closing stores where demand can be transferred to nearby locations. We corroborated this with interviews across 300 stores: 89% of stores within 0.25 miles of a closure reported becoming “noticeably busier” in September 2025, with traffic up ~27% by employee estimates, and 82% of the Starbucks partners attributed the increase to a nearby Starbucks closure without being prompted. By contrast, only 7% of control stores reported becoming busier, and none cited closures. Our 1.2M store-week database shows that the company-operated stores within one mile of the 2025 closures exhibited a ~6.4-hour-per-week lift y/y vs. ~2.1 for other North American CO shops, consistent with their absorbing the influx of traffic. Interestingly, 63% of stores reported the traffic bump has since faded, suggesting this was a one-time transfer rather than an improvement in underlying demand, which Starbucks will begin lapping next quarter. Based on our survey and third-party estimates, we estimate retention was trending at >90%. This is also in line with traffic growth estimates we heard from store managers in our 300+ calls. Using the average closed store AUV, closures, and customer retention, we estimate ~$1.03bn of annual revenue was transferred to surviving stores, equivalent to ~425 bps of inorganic comp growth. We estimate an additional 58 bps from increased hours at surrounding stores, translating to ~483 bps of total inorganic comp lift.
Thesis 2: Emerging Beverage Chains are Rapidly Taking Share From Starbucks.
Evidence: Using emerging brand store-opening data, construction filings, and 80,777 scraped Google reviews to estimate opening dates, we tracked changes in emerging-brand density around Starbucks locations from 2023 to September 2026. We found that the share of Starbucks company-operated shops that have an emerging brand within a mile has nearly doubled from 8.5% (2023) to 16.3% (Sept. 2026). This expansion is largely incremental to existing coffee shop supply: only 8.3% of units built within the last year replaced another coffee shop, suggesting most new units are adding competition for Starbucks rather than replacing incumbents. We analyzed 191 Texas construction filings for new 7 Brew locations and found that 73% of the 191 next-cohort 7 Brew locations are located within a mile of a Starbucks drive-thru. Former 7 Brew regional managers indicate this is deliberate, citing Starbucks trade areas as attractive locations because of the opportunity to “steal their customers.” Emerging brands’ encroachment coincides with substantial share loss. Our credit card alternative data across 150M consumers shows Starbucks’ share of tracked spend across Starbucks, $BROS, and 7 Brew falling from 83.2% to 66.4% since January 2022, while Dutch Bros increased from 16.7% to 25.3% and 7 Brew from 0.1% to 8.2%. Separately, our foot traffic data shows that when a Dutch Bros or 7 Brew opens within one mile of a Starbucks, traffic at the Starbucks location declines 8-10% on average, providing direct evidence that these brands are substituting for Starbucks. The competitive threat is also expanding beyond Starbucks’ drive-thrus. Channel checks with six Albertsons managers found that Dutch Bros’ newly introduced CPG products have been selling out within weeks and outperforming existing Starbucks offerings. Meanwhile, Dutch, a traditionally suburban only chain, has recently opened its first urban store with a fully walk-up format. This has been one of their best performing locations over the last quarters, with our interviews with Broistas during our site visit in Los Angeles revealing the format’s higher order-ahead mix allows the location to deliver higher throughput than suburban locations. Any Dutch success in this format would cause a huge re-rating for Starbucks as the threat expands into Starbucks core unban markets. Any re-rating is pure upside to our modeled variance.
Thesis 3: The Street Models Labor Investments as Margin Tailwind Despite Structurally Growing Labor Intensity
Evidence: Our scrape of 10,082 Glassdoor reviews since April 2024 shows a clear, growing disconnect between Starbucks’ operating demands and its staffing levels. Employee sentiment has soured against Niccol, with CEO dissatisfaction increasing from 43% to 65% since Niccol’s arrival, amid employee concerns around the company’s historical employee-cost reduction strategy. Glassdoor complaints citing menu complexity and stores being understaffed have nearly quadrupled in the past two quarters, with employees increasingly citing protein drinks, matcha, boba, and other add-ons. Employee outlook has deteriorated particularly sharply in markets facing the most competitive pressure, falling 24% since April 2024 in AZ, TX, CA, TN, OH, and NV vs. 13.5% in other states. The company’s intensifying landscape is pushing Starbucks toward a more complex menu, given the customizability appeal of the share-stealing emerging brands, leading to overworked employees who are becoming increasingly negative about the brand. Furthermore, our store visits to 7 Starbucks locations, spanning 342 timed orders, found an average wait time of 6.8 minutes per order, well above management’s target of 4 minutes or less. Starbucks is attempting to deliver a faster, more service-intensive experience while simultaneously operating with fewer employees per store than emerging competitors: Dutch Bros averages 27.3 employees/store despite ~33% lower average square footage per company-operated shop. We believe Starbucks’ expanding menu and higher service standards make its FY2025 staffing level unsustainable, requiring continued labor investment rather than the normalization that the Street models.
Valuation: We model 483 bps of closure-driven SSSG unwinding as Starbucks laps the FY2025 closure cohort, with 181 bps of offset from the FY2026 cohort. This, combined with increasing competition, drives North American SSSG 174 bps below consensus in our base case and 286 bps in our bear case. This steps up by another ~280/420 bps respectively in FY 2028 as the 181 bps tailwind is lapped and competition intensifies. We model labor intensity remaining structurally elevated, forecasting Starbucks increasing employees/store from 21.3 to 24.0 through FY2027, driving FY2027 EBIT margins 263 bps below Street projections. Utilizing a conservative 18.5x/18.5x/20.0x NTM EBITDA multiple on FY2028 EBITDA, our bear/base/bull cases yield price targets of $48.48/$73.39/$113.95, respectively. Weighted at 35%/50%/15%, this yields a weighted average price target of $70.76.
Risks and Mitigants: Risks include 1) Niccol’s Back to Starbucks Turnaround drives a sustainable recovery in underlying demand, 2) emerging brands are growing the specialty beverage category without stealing meaningful share from Starbucks, and 3) continued store closures recreate the closure-driven SSSG benefit. Mitigants include 1) 63% of stores absorbing traffic from closed stores have already reported the one-time bump fading, coinciding with the share of U.S. store employees expressing a negative outlook rising from 31% to 41%; 2) credit card alternative data shows Starbucks’ share of tracked spend across Starbucks, Dutch Bros, and 7 Brew falling 1,680 bps since 2022, and 3) the September closure wave was smaller and less overlapped than the 2025 cohort, limiting the amount of revenue and customers that can be transferred to surviving stores.
Catalyst Path: Starbucks has an extremely clear catalyst path. Management’s September 2025 closures have materially propped up SSSG by a projected 483 bps, with the comp benefit ending next quarter. As the older cohort of closures rolls off faster than the next cohort rolls on, reported SSSG will begin to reflect the underlying transaction trend normalized for customer transfers. We view Q2 FY2027 as a hard catalyst, where management will be forced to lower their SSS outlook for the fiscal year, resulting in the Street recalibrating its assumptions around a sustained recovery, while continued transaction weakness and structurally higher labor intensity provide further downside to consensus estimates. Store operating expenses will continue to trend higher as Starbucks increases its employees per store, forcing the Street to remodel.
A full financial model will be posted tomorrow. Please contact [email protected] with any questions regarding the pitch or primary research.
Credit Capital retweeted
*STARBUCKS FALLS TO LOW OF THE DAY FOLLOWING TWITTER POST BY WELL ARTICULATED SHORTS AT @CreditCapi






