Cameroon Informal Jobs Barometer — Q4 2026

Name: Cameroon Informal Jobs Barometer — Q4 2026
Published: 2026-10-01
License: https://creativecommons.org/licenses/by/4.0/

Real figures from the SangoServices platform (observation period: March – September 2026). In Cameroon, 86.6% of employed people work in the informal sector (INS, EESI 3, 2021), yet almost no data is published about these trades. This quarterly barometer fills that gap.

Published 2026-10-01

1242

registered workers

cities covered

job categories

Registered workers by city

City	Registered workers (n)
Douala	582
Yaoundé	242
Buea	55
Bamenda	37
Bafoussam	29
Limbe	24
Bertoua	10
Kribi	10
Kumba	10
Ebolowa	9
Ngaoundéré	9
Maroua	8
Garoua	7

Supply: available workers by trade

Workers with a complete profile offering each service (one worker can offer several services).

Trade	Workers (n)
Cleaning	470
Babysitting	299
Cooking	268
Manual labor	253
Delivery	233
Errands	201
Teaching	198
Helper	189
Moving	159
Event staffing	108
Laundry	95
Repair	81
Gardening	70
Elderly care	52
Driving	47
Security	24

Demand: trades employers search for most

Searches in the public directory (window: July 1 – September 30, 2026).

Trade	Searches (n)	Zero-result searches
Cleaning	359	8%
Babysitting	284	17%
Cooking	211	23%
Delivery	111	14%
Driving	96	22%
Helper	80	16%
Teaching	80	21%
Moving	50	12%
Repair	45	Insufficient data (n = 45)
Security	43	Insufficient data (n = 43)
Event staffing	41	Insufficient data (n = 41)
Errands	40	Insufficient data (n = 40)
Gardening	39	Insufficient data (n = 39)
Manual labor	39	Insufficient data (n = 39)
Elderly care	33	Insufficient data (n = 33)
Laundry	23	Insufficient data (n = 23)

Trades in shortage

Demand exceeds visible supply for: Driving. If you work one of these trades, now is the time to publish your profile.

Daily rates (FCFA) — observed on published profiles

Rates displayed by directory workers, n profiles per trade (see the methodology).

Trade	P20	P80	Median	n
Cleaning	3 000	10 000	7 000	166
Babysitting	3 000	10 000	6 000	114
Cooking	3 000	10 000	8 000	103
Delivery	3 000	10 000	6 000	92
Manual labor	3 000	10 000	7 000	91
Errands	3 000	10 000	4 000	88
Helper	3 000	10 000	7 000	80
Teaching	3 000	10 000	4 500	72
Moving	3 500	10 000	7 000	52
Event staffing	4 000	10 000	10 000	42
Laundry	3 000	10 000	7 000	37
Repair	Insufficient data (n = 25)			25
Gardening	Insufficient data (n = 23)			23
Driving	Insufficient data (n = 18)			18
Elderly care	Insufficient data (n = 18)			18
Security	Insufficient data (n = 7)			7

Daily rates by city (FCFA)

One rate per worker, however many trades they offer; n profiles per city (see the methodology).

City	P20	P80	Median	n
Douala	3,000	10,000	8,000	199
Yaoundé	3,000	10,000	7,000	99
Buea	Insufficient data (n = 25)			25
Bafoussam	Insufficient data (n = 11)			11
Bamenda	Insufficient data (n = 11)			11
Limbe	Insufficient data (n = 11)			11
Ebolowa	Insufficient data (n = 5)			5
Kribi	Insufficient data (n = 4)			4
Ngaoundéré	Insufficient data (n = 4)			4
Bertoua	Insufficient data (n = 3)			3
Garoua	Insufficient data (n = 2)			2

Read the analysis →

Worker sign-ups by month and region

Region of the worker’s city; “no city”: profile without a location.

Month	Douala	Yaoundé	North-West and South-West	Other cities	No city
2026-03	117	4	0	0	12
2026-04	98	20	5	5	33
2026-05	37	23	2	7	37
2026-06	41	14	3	5	22
2026-07	47	41	19	13	54
2026-08	122	65	45	24	37
2026-09	117	74	50	25	15

Read the analysis →

Supply by trade in Douala and Yaoundé

Workers with a complete profile offering each trade. Other cities are in the CSV file.

Trade	Douala	Yaoundé
Cleaning	248	113
Babysitting	170	67
Cooking	146	64
Manual labor	134	61
Delivery	132	57
Errands	113	55
Teaching	112	43
Helper	108	44
Moving	82	44
Event staffing	66	28
Laundry	56	20
Repair	43	22
Driving	35	4
Elderly care	34	14
Gardening	31	17
Security	18	3

Read the analysis →

What gets a worker called

Numbers revealed per 100 profile views, by what the profile shows (as of the extraction day).

Profile	Workers	Views (n)	Numbers per 100 views
Photo and pitch	330	1863	11.3
Photo only	234	831	6.9
Pitch only	111	274	4.0
Neither photo nor pitch	329	1039	3.7
ID verified	93	1158	14.2
ID not verified	911	2849	5.3

Read the analysis →

When employers reveal a number

Numbers revealed by time of day (Douala time) and day of the week.

Time of day	Numbers (n)
00:00–06:00	26
06:00–09:00	38
09:00–12:00	43
12:00–15:00	52
15:00–18:00	48
18:00–21:00	53
21:00–24:00	58

Day	Numbers (n)
Monday	61
Tuesday	50
Wednesday	50
Thursday	40
Friday	34
Saturday	24
Sunday	59

Read the analysis →

Searchers per available worker

Distinct addresses that searched the trade, divided by the available workers offering it. One address can stand for several people: it is a relative measure between trades.

Trade	Searchers (n)	Workers	Searchers per worker
Cleaning	141	453	0.31
Babysitting	73	289	0.25
Cooking	64	257	0.25
Delivery	47	225	0.21
Driving	47	45	1.04
Moving	36	156	0.23
Teaching	33	191	0.17
Helper	31	183	0.17
Event staffing	28	104	Insufficient data (n = 28)
Gardening	25	69	Insufficient data (n = 25)
Manual labor	25	250	Insufficient data (n = 25)
Repair	25	79	Insufficient data (n = 25)
Security	23	22	Insufficient data (n = 23)
Errands	22	196	Insufficient data (n = 22)
Elderly care	19	51	Insufficient data (n = 19)
Laundry	19	93	Insufficient data (n = 19)

Read the analysis →

Methodology

Figures come from the SangoServices production database: worker registrations (excluding test accounts), complete profiles per category, the public directory search log and, from the Q4 2026 edition, profile views and revealed numbers (bots excluded). Daily rates are observed on the rates directory workers display on their profile (outliers excluded): 20th percentile, median and 80th percentile per trade, published only from 30 profiles (n per row). A rate of exactly 5,000 FCFA is set aside (297 workers): it is the value the sign-up form suggested until September 2026, and 41-59% of profiles showed it in every trade, which describes the form, not the market. Every figure states its n, the number of records it rests on (for a count, the count itself). A zero-result share is published only from 50 searches, an observed rate only from 30 profiles; below that, the cell reads "insufficient data" with its n. Data downloadable as CSV, licensed CC BY 4.0: free to reuse, with attribution. Next edition: Q1 2027. To cite this barometer: "Cameroon Informal Jobs Barometer, SangoServices, Q4 2026".

Download the data

This edition's tables as CSV (UTF-8, an n and a method column on every row), licensed CC BY 4.0

Key figures (barometre-2026-q4-summary.csv)
Workers by city (barometre-2026-q4-workers-by-city.csv)
Supply by trade (barometre-2026-q4-supply-by-category.csv)
Demand by trade (barometre-2026-q4-demand-by-category.csv)
Daily rates (barometre-2026-q4-day-rates.csv)
Daily rates by city (barometre-2026-q4-day-rates-by-city.csv)
Sign-ups by month and region (barometre-2026-q4-signups-by-month.csv)
Supply by city and trade (barometre-2026-q4-supply-by-city-category.csv)
Numbers revealed by profile (barometre-2026-q4-contact-rate-by-profile.csv)
Numbers revealed by hour and day (barometre-2026-q4-contact-timing.csv)
Searchers per available worker (barometre-2026-q4-searchers-per-worker.csv)

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