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Caffeine, Default (caffeinated): ratings leave decaf out. Counts, cost and Caffeinated vs. decaf include it.

All time · Mountain Time

People
  • Per person: Totals and rates ÷ 2: an even split (Bean Conqueror doesn't record who brewed).
  • Household: Everyone's brews together.

Findings

Likely
  • The gap is at least twice its margin of error: about 95% sure it isn't chance.
-0.3 486 noted vs 271 plain brews · Data
Brews you write notes on rate lower
  • Likely the other way round: you write notes when a cup is off.
Likely
  • The gap is at least twice its margin of error: about 95% sure it isn't chance.
+0.3 221 pairs · Data
Your second cup is better
Likely
  • The gap is at least twice its margin of error: about 95% sure it isn't chance.
−3.7 122 bags · Data
Love Letters Charming Coffees Halo Beriti - Special Prep Washed - Ethiopia Washed Process trails like coffees by 3.7
Likely
  • The gap is at least twice its margin of error: about 95% sure it isn't chance.
+0.4 18 brews, 7 bags · Data
Bean's Beans Joocy rates 0.4 above your other brews of the same bags
Likely
  • The gap is at least twice its margin of error: about 95% sure it isn't chance.
-2.6 3 bags · Data
Eymen bags rate 2.6 lower
Possible
  • The gap is 1.5 to 2 times its margin of error: about 87% sure, so it could still be chance.
  • Under 1.5 times its margin of error gets no badge.
+0.2 51 early vs 705 later brews · Data
Brews before 9 am rate 0.2 higher
14 of 14
14 bags · Data
All 14 of your co-ferments are Colombia
100 days At 102g/day. Bought 43.3kg vs brewed 28.4kg in this period. 278 days · Data
10.2kg on hand, about 100 days
  • At 102g/day. Bought 43.3kg vs brewed 28.4kg in this period.
$2.97 A 9+ cup costs $3.39 on average. 1569 brews · Data
$2.97 a cup
  • A 9+ cup costs $3.39 on average.
30%
Shoebox, H&S and Big Sur. Rising: Ceto, 13 of your last 117 bags (7 of 213 before). 323 bags, 44 roasters · Data
Top 3 roasters: 30% of bags
  • Shoebox, H&S and Big Sur. Rising: Ceto, 13 of your last 117 bags (7 of 213 before).
5 brews Slowest: Scenery Peru - Yulisa Carhuallocllo Arévalo's Gesha [Best of Cajamarca 1st Place]
28 of 70 bags Right on brew 1
70 bags · Data
Dial-in takes up to 5 brews
  • Slowest: Scenery Peru - Yulisa Carhuallocllo Arévalo's Gesha [Best of Cajamarca 1st Place]: 5 brews
  • Right on brew 1: 28 of 70 bags
-0.3 Each bag's first brew vs its later brews, mean rating by month. 6 months · Data
Brew #1 gap: -0.8 → -0.3
  • Each bag's first brew vs its later brews, mean rating by month.
1.8 brews Mean brews to settle a bag, by the month you opened it. 69 bags · Data
Dial-in: 1.9 → 1.8 brews to settle
  • Mean brews to settle a bag, by the month you opened it.
-1.7 Mean rating by roast level each month (5+ rated brews). 6 months · Data
Light roasts: 7.7 → 6.0
  • Mean rating by roast level each month (5+ rated brews).
57% Share of brews by roast level each month. 9 months · Data
Ultralight: 11% → 57% of brews
  • Share of brews by roast level each month.
11:44 → 10:21 9 months · Data
Your first brew moved earlier
5.79 Weekdays
5.44 Weekends
Brews per day. 278 days · Data
Weekends aren't binges
  • Weekdays: 5.79
  • Weekends: 5.44
  • Brews per day.
Alpha Switch 81% of Apr 26, CT62 86% of Aug 26, CT62 85% of Oct 26. 9 months · Data
Dripper eras: Alpha Switch → CT62 → CT62
  • Alpha Switch 81% of Apr 26, CT62 86% of Aug 26, CT62 85% of Oct 26.
9 months · Data
Water: now mostly Lotus - Ultralight Mg + K (880mL)
A4Z (Femobook) 95% of Mar 26–May 26, A4Z (Femobook) 96% of Jul 26–Sep 26, 01 w/102Brews 81% of Nov 26. 9 months · Data
Grinder eras: A4Z (Femobook) → A4Z (Femobook) → 01 w/102Brews
  • A4Z (Femobook) 95% of Mar 26–May 26, A4Z (Femobook) 96% of Jul 26–Sep 26, 01 w/102Brews 81% of Nov 26.
$21.49 313 bags · Data
$/100g went from $17.81 to $21.49

This page tests : by chance alone, about 3 would earn Likely.

Top stories

Your first brew of a bag rates below the rest

Likely
  • The gap is at least twice its margin of error: about 95% sure it isn't chance.
-0.4

Brew #1 rates 0.3 below its bag's average; by brew #7+, 0.3 above. The first brew rated below the bag's later brews in 60% of 129 bags.

133 bags See the data →
Story 1 of 4

Myth busters

No clear link between price and rating yet

r = 0.11 ± 0.18 Across 124 bags, $/100g and your bag rating loosely move together (by rank). 124 bags · Data

Longer rest doesn't make a better cup

r = 0.03 ± 0.07 Rest days and rating line up at r = 0.03; with brew number held fixed, r = 0.03. Most brews rested 44–87 days; outside that it can't say. 755 brews · Data

No origin stands out yet

±0.4 All 9 origins with 3+ bags rate within ±0.4 of your other bags; with so few bags each, the margin of error reaches ±1.5. 150 bags · Data

Waiting in the backlog doesn't hurt

r = 0.00 ± 0.18 Across 124 bags, days from roast to first brew and the bag's rating barely move together. 124 bags · Data

Your ratings have settled

1.69 → 1.52 Monthly rating spread (SD) went from 1.69 in Mar 26 to 1.52 in Oct 26. 12 brews in a row rated. 8 months · Data

What if…

100 days to clear · empty on 2027-02-21 10.2kg on hand
Each month
173 brews 3.1kg a cup
a month At / 100g, your last 12 months' average a year

Too early to tell

  • Taste10 brews, 4 bags

    Bean's Beans Joocy runs +0.4 on Ultralight coffees

    Not yet enough to rule out chance.

    100% there
  • Taste10 bags

    Extended Ferment Washed coffees rate 0.8 higher

    With 6 process groups compared, one usually stands out by chance.

    53% there About 9 more bags would settle it.
  • Habits115 brews on 24 Mondays

    Mondays rate 0.2 higher

    With 7 weekdays compared, one usually stands out by chance.

    50% there About 24 more Mondays would settle it.
  • Dial-in70 bags

    Nordic Light is right on brew 1; Light settles by brew 4

    Not yet enough to rule out chance.

    51% there
  • Taste5 bags

    Aviary rates 1.0 below like coffees

    Not yet enough to rule out chance.

    36% there About 9 more bags would settle it.
  • Taste5 bags

    Aviary bags rate 1.0 lower

    With 19 roaster groups compared, one usually stands out by chance.

    33% there About 10 more bags would settle it.
  • Taste12 bags

    Bean's Beans bags rate 0.6 higher

    With 19 roaster groups compared, one usually stands out by chance.

    27% there Too small a difference to settle with your data.
  • Dial-in70 bags

    V60 Neo is right on brew 1; Gabi Master A settles by brew 3

    Not yet enough to rule out chance.

    18% there
  • Dial-in70 bags

    Washed settles by brew 2; Natural settles by brew 3

    Not yet enough to rule out chance.

    19% there
  • Dial-in70 bags

    Lotus - Ultralight Mg + K (880mL) is right on brew 1; Filtered water settles by brew 3

    Not yet enough to rule out chance.

    8% there
Built with help from Claude Code, an AI coding assistant How AI was used Contact

How this site was built

I built Bean Tracker with Claude Code, Anthropic's AI coding assistant. Here's who does what.

What I do

  • Set the direction: which features get built, and in what order
  • Drive the technical decisions, drawing on my experience as a Staff SRE, DevOps engineer, and software engineer: architecture, hosting, testing, and releases
  • Bring nearly all of the coffee knowledge, from recipes, gear, and pour structure to extraction, rest, and water
  • Shape every design: I review each spec and push back on layout, wording, and behavior until it's right
  • Test every change in a live preview, on desktop and on my phone
  • Set the engineering standards: tests at every screen size, shareable links for every view, signed commits, and staged releases
  • Own the data: every coffee, rating, and note, plus the judgment calls on it
  • Run the infrastructure the site lives on: hosting, domains, and backups
  • Act as project manager and technical lead, and decide what gets published, including this note

What Claude Code does

  • Writes nearly all of the code and automated tests, following my direction
  • Drafts the designs, specs, plans, and docs for me to review
  • Researches options and explains the tradeoffs so I can decide
  • Analyzes my brewing data to suggest values, which I confirm or change
  • Releases and deploys changes once I give the go-ahead
  • Often runs several AI agents at once: one builds while another reviews

Nothing ships without my sign-off. I review every change in a live preview, and automated tests plus a separate AI code review check the code itself.

Questions or concerns?

If you have a question, spot a mistake, or want something removed (for instance, a photo of your coffee's label), email me at [email protected].

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