Crafte Sessions analysis 2026 09 29 2026 10 29

sessions_analysis-2026-09-29-2026-10-29.csv · 2,246 rows · 15 columns · definition v3 saved 29 Oct 2026 14:08

Segments v25 built 29 Oct 2026 16:28 on feature set v6

A newer feature set (v8) exists. These segments were built on v6.
Segments found
5
fixed
In a segment
99%
2,223 of 2,246 snapshots
Unknown
1.0%
0 history · 0 between · 23 novel
Rules match the model
96%
for named segments
device was evened out: each snapshot was compared with others in the same device group.

What to do

From these segments' numbers. Setting buttons fill in the Build segments tab (then Build segments); merge buttons change the table below (then Save labels, no refit).
  • Worth doingS5 is very small (17 snapshots)

    Under 30 snapshots, a segment's rates swing with a couple of people. Merge it into the segment it's most like (S5 → S3). Keep one only if it's a group you specifically care about.

  • Fine as isUnknowns: 1.0% of snapshots

    A small unknown share means nearly everyone fits a segment, while the odd ones aren't forced in.

  • Fine as isordered: use S2, S3 as the targets on Outcomes

    S2, S3 hold 83% of ordered in 31% of the snapshots (2.7× the overall rate). Leaving out S1 (64% of snapshots) would also leave out 6% of ordered: that's the trade-off of the reduction.

Segments

Name them, merge near-duplicates, or send one to unknown. Nothing is refitted.
SegmentLabelSnapshotsShare What sets it apartMerge intoUnknown
S1 1,43163.7% Slightly more often landingPage is /
S2 45020.0% More often landingPage is other; higher pages; slightly more often source is Direct
S3 23710.6% Much longer-standing (returning); much more visits so far; more often landingPage is /product/474-port-and-prune-pudding-800g-log-in-cloth
S4 883.9% Much more often landingPage is /product/79-chocolate-fruit-cake-500g-boxed
S5 170.8% Much lower newVisitor; much less often source is Facebook; much more visits so far
? Unknown: fits no segment 231.0% high actions[add_recommended] (+5.3 sd), high pages (+2.5 sd), high landingPage=/product/75-christmas-cake-boxed (+1.8 sd)

Outcome concentration

Share of each segment's snapshots whose entity eventually had the outcome. Lift = rate ÷ overall rate.
S2 has the highest rate: 11% for ordered, 2.9× the overall 3.8%.
SegmentSnapshots Shareordered
RateLiftCaptured
S11,43163.7%0.3%0.1×6%
S245020.0%11.1%2.9×58%
S323710.6%8.9%2.3×24%
S4883.9%3.4%0.9×3%
S5170.8%0.0%0.0×0%
Unknown: fits no segment231.0%30.4%7.9×8%
Everyone2,246100%3.8%

How each segment differs

Average of each input, in standard deviations from everyone. Red higher, blue lower.
landingPage=/product/79-chocolate-fruit-cake-500g-boxed separates the segments most: from -0.2 sd in S1 to +4.9 sd in S4.
S1S2S3S4S5Novel
newVisitor+0.1+0.1+0.1+0.1-8.7-1.5
source=Facebook+0.2-0.6+0.2+0.2-5.4-0.7
actions[add_recommended]-0.1-0.1-0.1-0.0+0.1+5.3
landingPage=/product/79-chocolate-fruit-cake-500g-boxed-0.2-0.2-0.2+4.9-0.2-0.2
rows-0.3-0.3+2.1+0.0+3.8+0.9
tenure_days-0.3-0.3+2.1-0.0+2.9+0.6
pages-0.4+1.1+0.1+0.4+2.5+2.5
source=Direct-0.2+0.5-0.2-0.2+2.4+0.8
landingPage=/+0.4-0.4-0.5-2.2+0.3-1.0
landingPage=/product/75-christmas-cake-boxed-0.1-0.1+0.7-0.1-0.1+1.8
minutes-0.4+0.9+0.1-0.0+1.7+1.7
actions[add_search]-0.0-0.0-0.0-0.0-0.0+1.6
actions[sub_start]-0.0-0.0+0.0-0.1-0.2+1.4
landingPage=other-0.2+0.7+0.1-0.2-0.2+1.1
landingPage=/product/474-port-and-prune-pudding-800g-log-in-cloth-0.1-0.1+1.0-0.1-0.1+0.4
device=desktop-0.0+0.0+0.0-0.1-0.4+0.4
device=mobile+0.0+0.0-0.0-0.0+0.0-0.4
device=tablet+0.0-0.1+0.0+0.1+0.3+0.1

Movement between segments

Where each entity's next snapshot lands, as a share of the row
There are 232 steps from one snapshot to the next. 31% stayed in the same segment, so people often change segment between visits.
From ↓   to →S1S2S3S4S5Novelmoves
S196%4%98
S283%4%8%6%52
S393%2%5%58
S456%44%9
S5100%10
Unknown: fits no segment20%20%60%5

Segments over time

Share of snapshots per week
From the first week (05 Oct 2026) to the last (26 Oct 2026), S3 grew the most (+16% points) and S1 shrank the most (-32% points).
S1S2S3S4S5Unknown
0%25%50%75%100%05 Oct 2026 · S1: 334 snapshots (81%)05 Oct 2026 · S2: 62 snapshots (15%)05 Oct 2026 · S3: 6 snapshots (1%)05 Oct 2026 · S5: 4 snapshots (1%)05 Oct 2026 · Unknown: 4 snapshots (1%)05 Oct12 Oct 2026 · S1: 530 snapshots (73%)12 Oct 2026 · S2: 132 snapshots (18%)12 Oct 2026 · S3: 47 snapshots (6%)12 Oct 2026 · S5: 8 snapshots (1%)12 Oct 2026 · Unknown: 9 snapshots (1%)12 Oct19 Oct 2026 · S1: 343 snapshots (52%)19 Oct 2026 · S2: 153 snapshots (23%)19 Oct 2026 · S3: 107 snapshots (16%)19 Oct 2026 · S4: 52 snapshots (8%)19 Oct 2026 · S5: 1 snapshots (0%)19 Oct 2026 · Unknown: 5 snapshots (1%)19 Oct26 Oct 2026 · S1: 224 snapshots (50%)26 Oct 2026 · S2: 103 snapshots (23%)26 Oct 2026 · S3: 77 snapshots (17%)26 Oct 2026 · S4: 36 snapshots (8%)26 Oct 2026 · S5: 4 snapshots (1%)26 Oct 2026 · Unknown: 5 snapshots (1%)26 Oct

ordered rate by week (grey: under 20 snapshots, unreliable)

05 Oct12 Oct19 Oct26 Oct
S10%1%0%0%
S216%17%6%8%
S333%6%7%10%
S44%3%
S50%0%0%0%
Unknown25%22%20%60%

How good are these segments?

Separation 0.49 (reasonable) and stability 0.41 (shaky). Least stable: S2, S3, S5.
Separation
0.49
reasonable
Stability
0.41
shaky
Confidence
100%
average placement
SegmentSeparationStabilityConfidence
S10.80 clear0.72 fairly stable100%
S2-0.19 overlapping0.32 shaky100%
S3-0.06 overlapping0.45 shaky100%
S40.61 clear0.69 fairly stable100%
S50.14 weak0.39 shaky100%

Choosing the number of segments

The number of segments was fixed at 5, so there's nothing to compare.

Fixed at 5 segments, so there was nothing to compare.

The unknowns

23 snapshots (1.0%) are unknown: 0 too little history, 0 between segments, 23 fit no segment.
KindSnapshotsNearest segment
Unknown: fits no segment
Doesn't resemble any segment. Worth a look: new patterns and fraud often start here.
23S3 (18), S5 (4), S2 (1)

Boundary rules

How to recognise each segment
Together the rules agree with the model 96% of the time: good enough to use as a description.
Each segment gets its own short rules for picking it out from everyone else, in each feature's own units. Taken together, simple rules reproduce 96% of the assignments. Rules show where the lines fall, not why: use the profile above for what defines a segment. Unknowns have no rules; they come from how well a snapshot fits, not from where it sits.
S1 1 rule covering 96% of the segment
  • pages ≤ 1.5 and landingPage = / and rows ≤ 1.5 · covers 96% of the segment, 99% correct
S2 2 rules covering 88% of the segment
  • pages > 1.5 and tenure_days ≤ 0.177 and landingPage is not /product/79-chocolate-fruit-cake-500g-boxed · covers 81% of the segment, 98% correct
  • pages ≤ 1.5 and source is not Facebook and source is not Crafte · covers 7% of the segment, 97% correct
S3 3 rules covering 100% of the segment
  • rows > 1.5 and source = Facebook and landingPage is not /product/79-chocolate-fruit-cake-500g-boxed · covers 83% of the segment, 100% correct
  • rows ≤ 1.5 and landingPage = /product/474-port-and-prune-pudding-800g-log-in-cloth · covers 10% of the segment, 100% correct
  • rows ≤ 1.5 and landingPage is not /product/474-port-and-prune-pudding-800g-log-in-cloth and landingPage = /product/75-christmas-cake-boxed · covers 7% of the segment, 100% correct
S4 1 rule covering 100% of the segment
  • landingPage = /product/79-chocolate-fruit-cake-500g-boxed · covers 100% of the segment, 100% correct
S5 1 rule covering 88% of the segment
  • source is not Facebook and device is not desktop and tenure_days > 0.508 · covers 88% of the segment, 100% correct

Compare runs

Find the best segmentation
The pick is v20: its targets hold 83% of ordered in 25% of snapshots (3.3× the rate), with target stability 0.52.
RunFeaturesGroupsShapeSegmentsUnknownSeparationStabilityTargetsCapturedLiftTarget stability
v29
30 Oct 2026 12:50
v8device evened outFull81.1% 0.640.88 S2, S5, S633% in 12%2.8× 0.96 ★
v28
30 Oct 2026 09:20
v7device evened outDiagonal81.3% 0.540.92 ★ S2, S3, S5, S681% in 30%2.7× 0.66
v27
29 Oct 2026 17:17
v6device evened outDiagonal81.3% 0.540.92 ★ S2, S3, S5, S681% in 30%2.7× 0.66
v26
29 Oct 2026 16:29
v6-Diagonal51.0% 0.450.59 S3, S419% in 5%3.4× ★ 0.21
v25
29 Oct 2026 16:28
v6device evened outDiagonal51.0% 0.490.41 S2, S383% in 31% ★2.7× 0.39
v24
29 Oct 2026 16:27
v6device separatelyDiagonal151.0% 0.66 ★0.54 S5, S6, S731% in 10%3.1× 0.62
v23
29 Oct 2026 16:26
v6device ignoredFull50.7% ★ 0.630.37 S2, S341% in 18%2.2× 0.42
v22
29 Oct 2026 16:26
v6-Full51.0% 0.440.60 S3, S419% in 6%3.4× 0.21
v21
29 Oct 2026 16:26
v6device separatelyFull151.0% 0.650.51 S5, S627% in 9%3.0× 0.57
v20 pick
29 Oct 2026 16:24
v6device evened outFull51.0% 0.500.27 S2, S483% in 25% ★3.3× 0.52
v19
29 Oct 2026 16:22
v6-Full51.0% -- --- -
v18
29 Oct 2026 16:20
v6-Full51.0% -- --- -
v17
29 Oct 2026 16:20
v6-Full51.0% -- --- -
v16
29 Oct 2026 16:19
v6-Full51.0% -- --- -
v15
29 Oct 2026 14:10
v6-Full51.0% -- --- -
v14
29 Oct 2026 14:09
v6-Diagonal41.0% -- --- -
v13
29 Oct 2026 14:08
v6-Diagonal91.1% -- --- -
v12
29 Oct 2026 14:08
v6-Diagonal71.0% -- --- -
v11
29 Oct 2026 14:01
v5-Diagonal71.0% -- --- -
v10
29 Oct 2026 13:10
v4-Diagonal71.0% -- --- -
v9
29 Oct 2026 13:10
v4-Diagonal789.8% -- --- -
v8
29 Oct 2026 13:10
v4-Diagonal101.0% -- --- -
v7
29 Oct 2026 13:09
v4-Diagonal71.0% -- --- -
v6
29 Oct 2026 12:51
v3-Diagonal71.0% -- --- -
v5
29 Oct 2026 12:51
v3-Diagonal101.0% -- --- -

Search results

49 setups · 30 Oct 2026 12:43 · judged on ordered

Best: K-means · device evened out (8 segments). Its target segments (S2, S3, S4) hold 77% of ordered in 20% of the training snapshots, 3.8× the overall rate, and come back at 0.96 stability when refitted.

Every setup was fitted on the same 1,828 training snapshots (1,611 people); the 20% of people held out for testing weren't used, so Outcomes can still test the winner honestly.
#SetupSegments UnknownSeparationStabilityCaptured LiftTarget stabilityScore
1K-means · device evened out81.3% 0.640.9677% in 20%3.8× 0.962.93
2Bayesian Gaussian mixture · Diagonal · device evened out81.0% 0.540.6384% in 31%2.7× 0.752.25
3Bayesian Gaussian mixture · Full · source ignored81.0% 0.600.6978% in 27%2.9× 0.542.23
4K-means · device separately181.3% 0.730.9057% in 14%3.9× 0.942.23
5K-means · source evened out81.1% 0.630.7659% in 16%3.7× 0.722.19
6Gaussian mixture · Diagonal · device evened out81.0% 0.550.6381% in 31%2.6× 0.722.14
7Gaussian mixture · Full · device evened out81.0% 0.550.6181% in 31%2.6× 0.782.13
8Bayesian Gaussian mixture · Diagonal · device ignored81.0% 0.670.8181% in 31%2.6× 0.772.11
9Gaussian mixture · Full · device ignored81.0% 0.660.7781% in 33%2.5× 0.722.00
10Bayesian Gaussian mixture · Full · device evened out81.0% 0.550.5978% in 31%2.5× 0.742.00
11Gaussian mixture · Diagonal · device ignored81.0% 0.670.8478% in 31%2.5× 0.751.99
12Gaussian mixture · Full · device separately191.1% 0.670.8262% in 20%3.1× 0.561.96

Settings

One segmentation with exactly these settings. To try many automatically, use Find the best.
Feature set

The inputs to segment on.

Number of segments

Search a range and let the fit decide, or fix it.

When to say "unknown"

Rather than forcing everyone into a segment.

Groups

A column such as device or caseworker that should be treated differently in this run.

Each segment count is fitted 2 times on up to 60,000 snapshots. A range of 8 counts on 20,000 snapshots takes about half a minute; "Diagonal" is several times faster.