Tier Movement · Retention Analysis · PMM Performance · City Intelligence · 10 Periods Analyzed
645
Active Partners
Apr MTD
5.6%
Churn Rate
↓10.2pp
12
Good Churned
all periods
-132
vs Dec Peak
777→645
📋
Data Source Notice
This report is based on the Weekly & MTD Partners Stratification Report shared with frontline teams. Assessment tiers (Good / Average / Bad) are determined by Delivery Completion Rate & Fulfillment Rate as per the standard stratification methodology.
01
Monthly Churn & Growth Movement
Full-month comparisons · Churn trajectory · Net partner change
📌 What This Section Tells You: This section tracks the overall health of our partner ecosystem month over month — how many partners we’re losing (churn), gaining (new), and the net impact. It answers: “Are we growing or shrinking, and how fast?”
📖 Key Definitions:
• Churn Rate = % of previous-period active partners that became inactive
• Net Change = New partners acquired minus partners churned (positive = growth)
• Good / Average / Bad = Performance tier based on Delivery Completion & Fulfillment Rate
• Improved = Partners that moved UP at least one tier
ℹ️ Period Comparison: Jan periods vs Dec · Feb vs Jan (full) · Mar vs Feb (full) · Apr vs Mar (full)
Jan (full) Highest Churn
672
Active Partners
Churn15.4%
-120 churned
+15 new
Net -105
Good lost: 2 · Improved: 15.7%
Feb (full)
630
Active Partners
Churn11.2%
-75 churned
+33 new
Net -42
Good lost: 2 · Improved: 18.9%
Mar (full) Best Growth
641
Active Partners
Churn9.5%
-60 churned
+71 new
Net +11
Good lost: 0 · Improved: 23.9%
Apr (1-18)
645
Active Partners
Churn5.6%
-36 churned
+40 new
Net +4
Good lost: 0 · Improved: 19.5%
Active Partners & Churn Rate Trend
Recovery trajectory: Churn rate dropped 64% (15.8% → 5.6%) while partner count stabilized. Net growth turned positive in March.
Tier Distribution — Good · Average · Bad
Stable proportions: Good ~29%, Average ~39%, Bad ~31%. Ratios consistent despite total fluctuations.
New vs Churned — Net Change Trajectory
Inflection in March: First net-positive period (+11). New partner pipeline accelerated 7x. Churn dropped 70%.
Order Share by Tier (%)
Quality concentration: Good partners (~29% of count) command the largest order share — validating performance tier model.
02
Red Flags & Critical Alerts
Issues requiring leadership attention
🚨 Al Ahsa: Declining 4+ consecutive periods
🚨 Hafar Albatin: Declining 4+ consecutive periods
🚨 Riyadh: Declining 4+ consecutive periods
03
Period Comparison & Interactive Analysis
Select period to explore · Tier shifts · Movement flow · Lifecycle
📌 What This Section Tells You: Interactive deep-dive into any specific period — select a period to explore its complete story. It answers: “What exactly happened in this period? How did partners flow between tiers?”
📖 Key Definitions:
• Tier Distribution Comparison = Previous vs current partner counts by tier
• Movement Flow = Partners by category: Improved / Declined / Stable
• Churn by Tier = How many left from each tier + their churn rates
• New Partner Distribution = Starting tier of newly onboarded partners
• Lifecycle Analysis = Complete per-tier story: stayed, left, joined, gained/lost
Select Period for Deep-Dive Analysis
ℹ️ Comparison Logic: Jan periods compare vs Dec · Feb periods compare vs Jan (1-31) · Mar periods compare vs Feb (1-28) · Apr compares vs Mar (1-31). Each period shows the cumulative assessment at that date vs the full previous month.
Tier Distribution Comparison (Prev vs Current)
Movement Flow Summary
Churn Analysis by Tier
New Partner Distribution
04
Performance Quality · Tier Movement Analysis
Improvement vs decline · Good partner retention · Transformation matrix
📌 What This Section Tells You: Measures the quality trajectory of our partner base — are partners improving or declining? It answers: “Is our partner development working? Are we improving faster than declining?”
📖 Key Definitions:
• Improvement Rate = % of prev-active partners that moved UP at least one tier
• Decline Rate = % of prev-active partners that moved DOWN at least one tier
• Stable Good (Good→Good) = Partners that maintained top performance
• Stuck Bad (Bad→Bad) = Partners that failed to improve — intervention target
• Transformation Matrix = Complete from/to movement breakdown for all partners
Improvement Rate vs Decline Rate
Positive spread: Improvement rate exceeds decline rate in most periods — net quality improvement in the portfolio.
Good Partners Churned per Period
Critical win: Good partner churn dropped from 24 (Dec→Jan) to just 2 (Mar→Apr). Retention program validated.
Healthy movement: More upward transitions than downward. Only 36 churned total, majority being bad-tier.
05
Complete Period-by-Period Summary
All 10 periods · Key metrics side by side
ð What This Section Tells You: Complete side-by-side comparison of all 10 assessment periods — the master reference table. It answers: "How do all periods compare? What’s the trajectory across every metric?" Each row shows one assessment period with its comparison baseline in the "Compare To" column.
All Periods Comparison
Period
Compare To
Active
Churned
New
Net
Churn%
Good
Avg
Bad
Good Lost
Improv%
Decline%
Good Ord%
Jan(1-10)
Dec (full)
664
123
10
-113
15.8%
190
267
207
2
12.5%
24.6%
28.6%
Jan(1-19)
Dec (full)
666
123
12
-111
15.8%
191
267
208
2
13.0%
26.0%
28.7%
Jan(1-31)
Dec (full)
672
120
15
-105
15.4%
192
271
209
2
13.3%
25.7%
28.6%
Feb(1-10)
Jan (1-31)
612
79
19
-60
11.8%
175
245
192
2
17.1%
26.0%
28.6%
Feb(1-18)
Jan (1-31)
626
75
29
-46
11.2%
179
251
196
2
16.4%
24.4%
28.6%
Feb(1-28)
Jan (1-31)
630
75
33
-42
11.2%
181
251
198
2
16.8%
23.4%
28.7%
Mar(1-10)
Feb (1-28)
596
70
36
-34
11.1%
170
239
187
0
17.3%
25.2%
28.5%
Mar(1-18)
Feb (1-28)
624
63
57
-6
10.0%
179
249
196
0
19.0%
23.8%
28.7%
Mar(1-31)
Feb (1-28)
641
60
71
+11
9.5%
185
254
202
0
21.6%
25.9%
28.9%
Apr(1-18)
Mar (1-31)
645
36
40
+4
5.6%
186
256
203
0
18.4%
20.1%
28.8%
Improvement Rate
19.5%
Partners moving up tiers
Decline Rate
21.3%
Partners moving down
Stable Good
110
Good→Good retained
Stuck Bad
111
17.2% of active
Excellent PMMs
0
Score/Partner ≥ 0.5
06
City Intelligence · 17 Cities
Tier distribution · City transformation · Net movement
📌 What This Section Tells You: City-level performance intelligence — which cities are improving, stagnating, or declining. It answers: “Where should we focus? Which cities have structural issues vs temporary dips?”
📖 Key Definitions:
• Net Movement = (Partners improved) minus (Partners declined) within each city
• City Level = T1 (high-volume market) or T2 (developing market)
• Good/Avg/Bad Δ = Change in tier count vs previous period
• Trend (3P) = Net movement over last 3 periods — shows momentum
City Performance — Latest Period (Mar → Apr 1-18)
City
Level
Partners
Good
Avg
Bad
↑ Improved
↓ Declined
Net
Trend (3P)
Status
Yanbu
T2
12
3
5
4
3
1
+2
+0 / -1 / +2
Growing
Jeddah
T1
108
32
43
33
21
20
+1
-10 / -5 / +1
Growing
Jubail
T2
14
4
5
5
3
2
+1
+0 / +0 / +1
Growing
Taif
T2
15
4
6
5
2
1
+1
-1 / -1 / +1
Growing
Al Kharj
T1
11
3
4
4
2
2
+0
+0 / +1 / +0
Stable
Buraydah
T2
13
3
6
4
1
1
+0
-1 / -1 / +0
Stable
Dammam
T1
69
20
28
21
13
13
+0
-1 / -2 / +0
Stable
Hail
T2
7
2
2
3
1
1
+0
+1 / +0 / +0
Stable
Medina
T1
44
13
17
14
12
12
+0
-3 / +0 / +0
Stable
Najran
T2
5
1
2
2
0
0
+0
+0 / -1 / +0
Stable
Hafar Albatin
T2
5
1
2
2
1
2
-1
-1 / -1 / -1
Declining
Jazan
T2
5
1
2
2
1
2
-1
+0 / +1 / -1
Declining
Makkah
T1
45
13
18
14
7
8
-1
+1 / -3 / -1
Declining
Abha
T2
17
5
6
6
3
5
-2
+0 / +0 / -2
Declining
Al Ahsa
T1
29
8
12
9
5
7
-2
-2 / -2 / -2
Declining
Tabuk
T2
11
3
4
4
2
4
-2
+0 / -1 / -2
Declining
Riyadh
T1
235
70
94
71
41
48
-7
-13 / -11 / -7
Declining
City
Jan Good
Jan Avg
Jan Bad
Feb Good
Feb Avg
Feb Bad
Mar Good
Mar Avg
Mar Bad
Apr Good
Apr Avg
Apr Bad
Good Δ
Avg Δ
Bad Δ
Abha
5
9
6
5
6
6
5
7
6
5
6
6
+0
-3
+0
Al Ahsa
9
14
10
9
12
10
8
13
9
8
12
9
-1
-2
-1
Al Kharj
2
3
3
2
4
3
3
4
4
3
4
4
+1
+1
+1
Buraydah
4
5
5
3
5
4
3
4
4
3
6
4
-1
+1
-1
Dammam
22
31
23
21
28
22
20
27
21
20
28
21
-2
-3
-2
Hafar Albatin
2
4
3
2
3
3
2
2
3
1
2
2
-1
-2
-1
Hail
2
2
3
2
2
3
2
4
3
2
2
3
+0
+0
+0
Jazan
1
2
2
1
1
2
1
3
2
1
2
2
+0
+0
+0
Jeddah
32
44
33
28
38
29
30
40
31
32
43
33
+0
-1
+0
Jubail
3
5
4
3
4
4
4
5
5
4
5
5
+1
+0
+1
Makkah
15
21
16
13
18
14
13
18
14
13
18
14
-2
-3
-2
Medina
14
19
15
12
17
13
13
17
14
13
17
14
-1
-2
-1
Najran
1
2
2
1
2
2
1
2
2
1
2
2
+0
+0
+0
Riyadh
69
93
70
70
94
71
71
94
72
70
94
71
+1
+1
+1
Tabuk
3
6
4
3
5
4
3
4
4
3
4
4
+0
-2
+0
Taif
5
7
6
4
7
5
4
5
5
4
6
5
-1
-1
-1
Yanbu
3
4
4
2
5
3
2
5
3
3
5
4
+0
+1
+0
City
G→A
G→B
A→G
A→B
B→A
B→G
G→G
A→A
B→B
Abha
2
0
1
3
1
1
3
3
3
Al Ahsa
3
1
2
3
1
2
4
8
5
Al Kharj
1
0
1
1
1
0
2
2
3
Buraydah
1
0
1
0
0
0
2
3
2
Dammam
4
2
3
7
7
3
14
17
9
Hafar Albatin
2
0
1
0
0
0
0
0
2
Hail
1
0
1
0
0
0
1
1
3
Jazan
1
0
1
1
0
0
0
1
1
Jeddah
11
2
12
7
7
2
17
21
20
Jubail
1
1
2
0
1
0
2
3
3
Makkah
4
2
4
2
1
2
7
11
8
Medina
3
2
4
7
7
1
8
5
4
Najran
0
0
0
0
0
0
1
2
2
Riyadh
27
2
23
19
13
5
42
51
41
Tabuk
2
0
0
2
0
2
1
2
2
Taif
0
0
0
1
2
0
4
4
2
Yanbu
0
0
1
1
2
0
2
3
1
TOTAL
63
12
57
54
43
18
110
137
111
07
PMM Performance Ranking
Score/Partner · Rating · Tier transitions per manager
📌 What This Section Tells You: PMM (Partner Manager) performance ranking — how effectively each manager develops their partners. It answers: “Which PMMs are driving improvement? Who needs coaching?”
📖 Key Definitions:
• Score = Weighted sum of tier movements (improvements earn, declines lose)
• Score/Partner = Score ÷ total managed partners (normalized for portfolio size)
• Rating = Excellent (≥0.5), Good (≥0.2), Average (≥-0.2), Needs Improvement (≥-0.5), Poor (<-0.5)
• G→G / ↑ Up / ↓ Down / B→B = Key transition counts per PMM
PMM Performance — Latest Period
#
PMM Name
Partners
Score
Score/P
Rating
G→G
↑ Up
↓ Down
B→B
1
asadjaved
17
2
→ 0.118
🟡 Average
4
7
4
0
2
faisalalghamdi
24
2
→ 0.083
🟡 Average
3
8
1
5
3
abdullahaldweik
20
1
→ 0.050
🟡 Average
5
5
4
0
4
ahmadalkhatib
4
0
→ 0.000
🟡 Average
0
0
0
0
5
alisaeed02
2
0
→ 0.000
🟡 Average
0
0
0
0
6
shahidali
33
-2
↓ -0.061
🟡 Average
5
6
5
3
7
junaidmunir
24
-2
↓ -0.083
🟡 Average
5
5
3
3
8
mohamedsorour
17
-2
↓ -0.118
🟡 Average
5
5
3
2
9
abdulaziz
18
-3
↓ -0.167
🟡 Average
2
4
3
4
10
goharilyas
17
-3
↓ -0.176
🟡 Average
6
2
2
2
11
mostafasoliman
28
-5
↓ -0.179
🟡 Average
4
2
1
6
12
muhannadatallah
21
-4
↓ -0.190
🟡 Average
0
6
4
3
13
mohammadtalha02
15
-3
↓ -0.200
🟡 Average
3
4
4
2
14
pengbing
29
-6
↓ -0.207
🟠 Needs Improvement
6
5
4
5
15
abdallaahmed02
24
-5
↓ -0.208
🟠 Needs Improvement
2
4
3
5
16
maliknassar
24
-5
↓ -0.208
🟠 Needs Improvement
6
3
5
2
17
abdalbagialtom
26
-6
↓ -0.231
🟠 Needs Improvement
2
5
4
6
18
zamaanchirag
24
-6
↓ -0.250
🟠 Needs Improvement
1
6
5
5
19
lijiahao66
26
-7
↓ -0.269
🟠 Needs Improvement
2
5
7
4
20
adnansiddique
24
-7
↓ -0.292
🟠 Needs Improvement
6
3
5
2
21
amrkhedr
17
-5
↓ -0.294
🟠 Needs Improvement
2
3
5
3
22
aamiribrahim
26
-8
↓ -0.308
🟠 Needs Improvement
9
4
4
6
23
chirayathjoylijoy
14
-5
↓ -0.357
🟠 Needs Improvement
2
1
3
2
24
muzammilahmed
28
-10
↓ -0.357
🟠 Needs Improvement
2
4
3
9
25
anasejaz
21
-8
↓ -0.381
🟠 Needs Improvement
2
2
4
4
26
adilahmedmohammad
23
-9
↓ -0.391
🟠 Needs Improvement
4
4
4
7
27
khubaibsagheer
27
-11
↓ -0.407
🔴 Poor
4
5
8
4
28
ruaaalabdulrahman
24
-10
↓ -0.417
🔴 Poor
5
2
5
4
29
mohammedshoeb
23
-10
↓ -0.435
🔴 Poor
3
4
7
4
30
hamzakhan
18
-9
↓ -0.500
🔴 Poor
2
2
6
4
31
saifradwan
6
-3
↓ -0.500
🔴 Poor
0
0
1
1
32
aliibrahim
23
-12
↓ -0.522
🔴 Poor
4
2
8
2
33
mohammedabdulfateh
14
-9
↓ -0.643
🔴 Poor
4
0
4
2
📐 PMM Scoring Logic & Movement Framework — Click to expand methodology
💡 Why Score/Partner? Raw score favors PMMs with more partners. Score/Partner normalizes for portfolio size, enabling fair comparison between a PMM managing 50 partners vs one managing 10.