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.

Will post this at some point this weekend. Currently working on another short.

Definitely, there's nothing more we enjoy than chatting names

Agreed, the recent $CMG M&A news adds some interesting nuance to our original theses. We also don't think this is remotely likely and are still working on the potential effects on our PT, but directionally it seems very poor for $SBUX.

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.

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.

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.

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.

They aren't closing profitable stores they are closing underperforming stores in profitable locations.

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.

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.

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.

$CELH is not leveraged to the same trend. $BROS partially hedges any sector-wide coffee shop risk.

We have access to third-party alternative data.

We have a 12-month time horizon. The PT is a FY2027 PT using a NTM EBITDA multiple on FY2028 EBITDA. SSSG will continue to be inflated by ~181 bps by store closures this quarter, but ~302 bps will roll off into FY2027. With an intensifying competitive landscape we believe SSSG will turn negative towards the end of FY2027 and into FY2028.

Obviously it's not a perfect hedge, we are long a basket of securities that reasonably hedge some exposure to other factors that $BROS does not, however while we are structurally short the coffee space, hence why the position is not fully hedged, we prefer to isolate parts of our exposure to idiosyncratic $SBUX moves rather than the sector as a whole.

Regarding being short into the Q2 print, we believed sentiment on $BROS was way too high. The burden of proof for incremental upside is much higher when sentiment is high. That has completely reversed now.

We were long $BROS back in June, but flipped to short before the print, largely due to an intensifying competitive landscape and some of the factors you have mentioned. When we put on the $SBUX short we went partially long again to hedge some factor exposure. We think the coffee space is a short as a whole, but long Dutch short Starbucks looks attractive to us valuation wise.