# Crumbl Item 19 Cohort Analysis: What New-Unit AUV Actually Shows

> Crumbl Item 19 cohort analysis — new-unit AUV decline, market saturation reality, geographic variance, and what buyers should model.

## Why Cohort Analysis Beats System Average for Crumbl

If you are evaluating a new Crumbl franchise in 2026, the single most important number in the FDD is not the system-wide average unit volume. It is the AUV reported for the most recent cohort of stores — the ones that opened in the last 12 to 24 months.

That distinction matters because Crumbl's published system average blends two very different populations: a smaller group of mature stores that opened during the brand's 2019 to 2021 viral growth window, and a much larger group of newer stores that opened into a saturated, post-novelty market. Mix them together and the headline number looks fine. Pull them apart and the trajectory tells a different story.

Buyers who underwrite a new build using system average AUV are pricing in conditions that no longer exist for new locations. Buyers who underwrite using recent-cohort first-year AUV are pricing in the actual environment they will operate in. The gap between those two numbers is wide enough to flip a deal from acceptable to underwater.

This piece walks through what Crumbl's Item 19 actually reports, what the cohort decline looks like in pattern terms, why it is happening, and how to build a year-one revenue model that survives contact with reality.

## What Crumbl's Item 19 Actually Reports

Crumbl's FDD Item 19 is more transparent than many of its peers. Rather than collapsing the entire system into a single AUV number with quartile breakdowns, the disclosure typically segments stores by the year they opened. That structure lets you see whether the 2020 cohort, the 2022 cohort, and the 2024 cohort are all earning roughly the same revenue at the same point in their lifecycle — or whether each successive cohort is opening into worse conditions than the last.

A typical Crumbl Item 19 cohort table reports:

- Number of stores in the cohort that were open the full reporting year
- Average AUV for that cohort
- Median AUV for that cohort
- Sometimes a high/low range or quartile split

The cohort structure is the right structure. The problem is what the numbers in those rows have started to show.

If you are unfamiliar with how cohort disclosures work or how to read them critically, our breakdowns of [Item 19 average vs median and survivorship bias](/blog/item-19-average-vs-median-survivorship-bias?utm_source=claude&utm_medium=ai_referral&utm_campaign=vmf_agent_md) and [Item 19 red flags](/blog/franchise-item-19-red-flags-misleading-data?utm_source=claude&utm_medium=ai_referral&utm_campaign=vmf_agent_md) cover the mechanics before you sit down with Crumbl's specific tables.

## The New-Unit AUV Decline Pattern

The pattern across recent Crumbl FDDs is consistent: older cohorts report higher AUV than newer cohorts at comparable points in their operating history. This is not a rumor — it is visible in the disclosure itself if you read across the cohort rows rather than focusing on the system-wide line at the top.

Here is a representational picture of the trajectory (illustrative ranges, not pulled from a specific FDD year — always verify against the current disclosure):

| Cohort opening year | Stage at reporting | Pattern observed |
|---|---|---|
| 2019–2020 | Mature, 4+ years operating | Strongest AUV band — high-water mark of the system |
| 2021 | Mature, 3+ years operating | Strong AUV, slightly below the 2019–2020 peak |
| 2022 | Approaching maturity | Materially below 2020 cohort at same operating age |
| 2023 | Ramped | Further step-down from prior cohort |
| 2024 | First full year | Lowest reported cohort AUV; meaningful gap to system average |

The exact dollar figures shift FDD to FDD, but the shape is what matters. Each successive cohort has been opening into a tougher environment, ramping more slowly, and topping out lower than the cohort before it. The system average masks this because the heavy mature-cohort numbers are still in the blend — but the average is a lagging indicator of conditions that new operators no longer face.

For a new buyer signing a franchise agreement in 2026, the relevant data point is what the 2024 cohort earned in its first full year, not what the system average looks like across all vintages combined. That single substitution typically lowers a realistic year-one revenue assumption by a meaningful percentage versus what the headline number suggests.

## Why The Decline — Saturation, Novelty Fade, Competition

Three forces are driving the cohort trajectory, and all three are structural rather than temporary.

**Saturation.** Crumbl scaled from a handful of stores to over a thousand locations in roughly five years. That growth rate was historically aggressive for a single-category dessert concept. In many metros there are now multiple Crumbl locations within a 10-mile radius, which means each new store carves its trade area from an existing store's catchment rather than capturing virgin demand. The economics of a new build look very different when the nearest two Crumbls are 4 miles away versus when the nearest one is 40 miles away.

Our [franchise market saturation and competition](/blog/franchise-market-saturation-competition?utm_source=claude&utm_medium=ai_referral&utm_campaign=vmf_agent_md) piece walks through how saturation actually compresses unit economics in fast-scaling brands. Crumbl is a near-perfect case study of the dynamic.

**Novelty fade.** The 2020 to 2021 Crumbl moment was extraordinary. TikTok, weekly rotating menus, pink boxes, lines down the sidewalk — the brand benefited from a cultural moment that drove repeat visits and word-of-mouth that no marketing budget could buy. That moment matured. New stores opening in 2024 and 2025 are not opening into the same demand curve that 2020 stores opened into. The brand is still relevant, but the novelty premium that lifted early-cohort AUV is not available to new operators.

**Category competition.** When Crumbl scaled, the gourmet rotating-menu cookie concept was effectively a category of one. It now has direct competitors, copycat menus from local bakeries, and adjacent dessert concepts targeting the same occasion. Category dilution shows up in cohort data before it shows up anywhere else.

> 💼 **Want Crumbl's cohort-specific Item 19 stress-tested against your specific market?** Our [$4.99 FDD AI Analysis Report](/franchises?utm_source=claude&utm_medium=ai_referral&utm_campaign=vmf_agent_md) parses Item 19 by cohort year and adjusts for your geo + trade area density. Delivered in minutes.

## Geographic Variance: Utah/Mountain West vs Saturated Markets

The cohort trend is the headline, but it is not the only thing buried in the data. Geographic variance inside each cohort is severe enough that average-and-median figures can mislead in either direction depending on where you actually plan to open.

Crumbl's home territory — Utah and the broader Mountain West — has historically been the strongest-performing geography in the system. Stores in this region have generally been at or near the top of cohort distributions, and they carry a disproportionate share of the system's high-AUV outliers. The brand's hometown halo, dense fan base, and earlier market entry all contribute.

The flip side is dense metros on the coasts and in the Southeast where saturation arrived fastest. These markets often house the bottom-quartile cohort performers. A 2024-cohort store in suburban Utah and a 2024-cohort store in a saturated South Florida or Southern California submarket are reporting into the same FDD row, but the operating reality is very different.

What this means in practice: if your planned location is in a strong-geo, low-saturation submarket, your year-one expectations can reasonably anchor to the upper half of recent-cohort outcomes. If your location sits in a market where the brand is already well-established and the trade area overlaps with an existing Crumbl, you should plan against the bottom half — and seriously consider whether the deal pencils at the lower bound.

## How To Model A Realistic Year-One Crumbl Revenue

Here is a practical, conservative framework. None of these steps require special access — all of it is buildable from the FDD plus public mapping tools.

**Step 1: Start with the most recent cohort's first-year AUV.** Not the system average. Not the older-cohort numbers. The most recent cohort line. That is your baseline anchor for a new build in 2026.

**Step 2: Apply a trade-area saturation discount.** Count the existing Crumbl locations within 5, 10, and 15 miles of your planned site. If there are two or more within 10 miles, apply a 10 to 20 percent discount to the cohort baseline. If there are three or more, apply 20 to 30 percent and re-examine whether the site is viable.

**Step 3: Apply a regional adjustment.** If you are in a historically over-performing region (Utah, Mountain West, certain low-saturation Midwest metros), the cohort average is probably a reasonable midpoint. If you are in a saturated coastal market or an underperforming region, anchor below the cohort average.

**Step 4: Apply a site-quality adjustment.** Co-tenants, visibility, parking, drive-up access, and proximity to trip generators all matter. A B-grade site in any market should be modeled below cohort average regardless of geography.

**Step 5: Stress-test against the bottom quartile.** Run your operating model with revenue set at the bottom-quartile cohort AUV. If the deal still services debt and pays the operator a livable return at that level, the underwriting is honest. If it only works at cohort average or above, you are betting on conditions that the cohort data is telling you are no longer the norm.

For the mechanics of pressure-testing the disclosed numbers themselves, our guide to [verifying Item 19 earnings claims](/blog/how-to-verify-item-19-earnings-claims?utm_source=claude&utm_medium=ai_referral&utm_campaign=vmf_agent_md) covers franchisee interviews, validation calls, and what to actually ask. Pair that with the cost framework in our [Crumbl franchise cost](/blog/crumbl-cookie-franchise-cost?utm_source=claude&utm_medium=ai_referral&utm_campaign=vmf_agent_md) breakdown to build a full pro forma.

## The Verdict — Crumbl Can Still Work; Site Selection And Cohort Math Are Everything

Crumbl is not a broken brand. It is a maturing one. The cohort decline visible in Item 19 is the normal trajectory of any concept that scales aggressively into a fixed addressable market — eventually new stores share demand with existing stores, the novelty premium fades, and unit economics normalize at a lower band.

For new buyers, the implications are specific:

- The deals that still work are in genuinely underserved geographies with strong site selection. These exist.
- The deals that do not work are in saturated trade areas where the math only pencils if you assume mature-cohort AUV. The cohort data is telling you those assumptions are wrong for new builds.
- The single biggest underwriting mistake is using system-average AUV instead of recent-cohort first-year AUV as your baseline. That one substitution causes more failed Crumbl deals than any other factor.

The good news about Crumbl's Item 19 is that it gives you the data you need to make this call honestly. Most franchisors do not disclose by cohort year. Crumbl does. The bad news is that most buyers do not read across the cohort rows — they read the system average and stop.

Read across the rows. Anchor to the most recent cohort. Discount for saturation, region, and site. Stress-test against the bottom quartile. If the deal still works after all of that, it is probably a real deal. If it only works above cohort average, walk.

> 💼 **Want Crumbl's cohort-specific Item 19 stress-tested against your specific market?** Our [$4.99 FDD AI Analysis Report](/franchises?utm_source=claude&utm_medium=ai_referral&utm_campaign=vmf_agent_md) parses Item 19 by cohort year and adjusts for your geo + trade area density. Delivered in minutes.