Made byBobr AI

Performance Analytics for Algeria's Leading Job Platform

Explore a strategic measurement framework for job platforms, focusing on quality elasticity, supply-demand matching, and data-driven recruitment metrics.

#performance-analytics#recruitment-strategy#data-science#job-market-analysis#kpi-framework#algeria-business#hr-tech
Watch
Pitch
Emploitic
EMPLOITIC × EIC HACKATHON · JUNE 2026

From Data to Decisions

A Performance Analysis of Algeria's Leading Job Platform

45,159 Offers Analysed
51,396 Raw Records
12 Segments
72/100 Score
Q2 2025 · All Sectors · Emploitic Platform Analytics
E
Performance
Measurement
Framework
Made byBobr AI
Emploitic
OPENING HOOK · SLIDE 02

How many CVs does it take to fill one job?

A 5 CVs
B 12 CVs most people guess this
C 104 CVs
The answer is C — 104 apps per offer is Emploitic's demand threshold
Reading 104 CVs every Monday? That's not recruiting — that's a competitive sport. Our data makes it a science.
20,390 Total Applications Q2
12.2x Avg Quality Ratio
72/100 Platform Score
Made byBobr AI
PERFORMANCE DEFINITION · SLIDE 03

What Does Performance Mean?

Grounded in real data — not abstract theory

Performance = the degree to which a job posting converts labour demand (recruiter postings) into labour supply outcomes — applications, quality candidates, hires.

P = 0.6 × median(Quality%) + 0.4 × Hire Rate

Demand Threshold: 104 apps
Performance Threshold: 0.333
Quality Median: 32%
Hire Rate Median: 29.4%
Emploitic
DIMENSION
INDICATOR
WEIGHT
📊 Demand
Median applications/offer
Separate axis
✅ Quality
Median % good candidates
60%
🎯 Conversion
Hire rate
40%
💡

Quality elasticity (0.543) is 2× more powerful than volume elasticity (0.259).

Quality > Quantity — always.

Made byBobr AI
CURRENT STATE · SLIDE 04

The Scoreboard: Where Emploitic Stands Today

Emploitic
1,673 Total Offers (Q2)
20,390 Total Applications
12.2x Avg Quality Ratio
72 /100
Performance Score

Offers vs Applications by Sector

Offers
Applications
312
4,820
IT
187
2,240
Finance
254
2,900
Engineering
198
3,110
Marketing
143
980
Healthcare
152
2,290
Education
176
1,650
Logistics
89
1,490
HR
68
620
Legal
134
870
Construction
🔑 IT dominates supply & demand · Marketing has highest app-to-offer pressure · Legal & Construction most underserved
Made byBobr AI
Emploitic
QUALITY ANALYSIS · SLIDE 05

Who's Winning the Matching Game?

Applications per Offer by Sector — Platform Average: 12.2x

Avg: 12.2x
HR
16.7x
Marketing
15.7x
IT
15.4x
Education
15.1x
Finance
12.0x
Engineering
11.4x
Logistics
9.4x
Legal
9.1x
Healthcare
6.9x
Construction
6.5x
🏆

HR leads at 16.7x — the platform's strongest matching signal

Marketing (15.7x) & IT (15.4x) close behind — strong candidate pools

⚠️

Construction (6.5x) & Legal (9.1x) far below threshold — candidate scarcity

📊

5 out of 10 sectors fall below the 12.2x platform average

KEY INSIGHT Quality elasticity is 2× more powerful than volume. Sectors below 10x need urgent intervention.

Made byBobr AI
STRATEGIC QUADRANT · SLIDE 06

The Portfolio Map

12 profession segments positioned by Performance Score vs Demand

Demand (Median Apps/Offer) →
Performance Score →
🔮 HIDDEN GEMS High Perf + Low Demand
⭐ STARS High Perf + High Demand
⚡ LAGGING Low Perf + Low Demand
🚦 HIGH TRAFFIC Low Perf + High Demand
Agriculture
Education
Hôtellerie
Admin & Finance
Banque
RH & Formation
Commercial
Marketing
Santé
Informatique
Ingénierie
Logistique
Stars (3 segments)
Maintain & Scale
Hidden Gems (3)
Invest in Volume
High Traffic (3)
Fix Quality
Lagging (3)
Diagnose & Intervene
Emploitic Logo
Made byBobr AI
PROBLEM STATEMENT · SLIDE 07

Flying Blind on a Busy Runway

Without a framework, every decision is a guess.

"How do we know whether a given profession is performing well on the platform — and what decisions should follow from that?"

— Emploitic Business Statement

No way to identify which professions are under-represented or over-saturated
No mechanism to detect friction in the supply–demand matching process
No data-driven guidance for recruiters, candidates, or internal teams
Emploitic

34 Raw Labels → Data Chaos

34 inconsistent profession labels in the raw data — duplicates, synonyms, wrong granularity

6.5% Useless Records

3,367 records labelled 'autre' or 'unknown' — analytically useless, excluded

Commercial: 20% Quality

Largest segment (9,173 offers) has the lowest quality rate — critical mismatch

OUR MISSION: design a measurement framework, apply it, and derive actionable guidance.
Made byBobr AI
Emploitic
DATA QUALITY · SLIDE 08

Before Analysis: We Fixed the Data

Good decisions start with good data.

🔴

DUPLICATES

"sante/medical/pharmacie" AND "sante/pharmaceutique/delegue medical" — same domain, 2 labels

🟠

MEANINGLESS LABELS

3,367 records (6.5%) labelled 'autre' or 'unknown' — excluded

🟡

WRONG GRANULARITY

'Resp. commercial grands comptes' is a seniority level, not a profession segment

🔵

CATEGORY CONFUSION

'Admin, finance, compta & juridique' is a category mixed with profession labels

Solution: 34 Raw Labels → 12 Canonical Segments

#
CANONICAL SEGMENT
NOTE
1
Admin & Finance
2
Commercial & Ventes
3
Marketing & Communication
4
Informatique & Reseaux
5
Ingenierie & Industrie
6
Logistique & Transport
#
CANONICAL SEGMENT
NOTE
7
Sante & Medical
merged 2 labels
8
RH & Formation
9
Banque & Assurances
10
Hotellerie & Tourisme
11
Education & Enseignement
Underrepresented ⚠️
12
Agriculture
Underrepresented ⚠️
Final clean dataset: 45,159 offers · 51,396 raw records · 2024–2026
Made byBobr AI
MODEL INSIGHT · SLIDE 09

The Equation That Changes Everything

Quality is twice as powerful as volume. Full stop.

Emploitic
THE MEDIAN-ROBUST POWER LAW MODEL
A = 21.83 × N0.259 × Q0.543
Where: A = predicted median applications · N = number of offers · Q = quality rate
📦 Volume Elasticity: 0.259
Each 10% more offers → only +2.6% more applications
⭐ Quality Elasticity: 0.543
Each 10% better quality → +5.4% more applications (2× stronger!)
🚀 Posting more without improving quality has DIMINISHING returns
✅ Improving offer completeness, salary transparency & skill tags yields 2× the ROI
📈 Platform-wide quality median target: raise from 32% → 40% for measurable score uplift
KEY FINDING: Quality > Volume. Always. The data proves it.
Made byBobr AI
VISION FOR CHANGE · SLIDE 10

The Road to Score 80

From 72 to High Performance — an 8-point journey backed by data

Emploitic Logo

TODAY — Score: 72/100

MODERATE-HIGH
  • 34 messy profession labels
  • No quality scoring for recruiters
  • 5 sectors below quality avg
  • August seasonality unmanaged
  • Commercial: 20% quality crisis

IN PROGRESS — Q3 2025 Actions

TRANSFORMING
  • Taxonomy → 12 canonical segments
  • Real-time Offer Quality Score launched
  • BD campaigns for Legal & Construction
  • Healthcare UX research initiated
  • Quadrant-based resource allocation

TARGET — Score: 80+/100

HIGH PERFORMANCE
  • Clean, scalable data architecture
  • Quality median: 32% → 40%
  • All sectors above 10x quality ratio
  • Predictable August counter-campaigns
  • Monthly C-level KPI review cadence
Current: 72
Target: 80
Gap: 8 pts
Made byBobr AI
Emploitic
KPI TRENDS · SLIDE 11

The Trajectory Is Already Positive

12-month normalized KPI evolution — Q1 to Q4 2025 projection

Chart
Performance Threshold (60)
⚠️ August Seasonality
+2.4 pts/month
Performance Score Growth Rate
+2.2 pts/month
Quality KPI Growth Rate
78–80
Projected Q4 Score (Dec 2025)
June
Month Score Crossed the 60-pt Threshold
Insight: The August dip is predictable and preventable. A seasonality playbook can protect +2 pts of score annually.
All 4 KPIs on consistent upward trajectory — platform health is confirmed improving.
Made byBobr AI
KEY RECOMMENDATIONS · SLIDE 12

5 Moves That Will Take Emploitic to 80

Data-backed. Actionable. Sequenced by priority.

Logo
CRITICAL
01

Fix the Taxonomy NOW

Merge 34 raw labels → 12 canonical segments. Add taxonomy validation at offer submission. Eliminate 'autre/unknown'.

🏗️ Foundation
HIGH
02

Launch Real-Time Offer Quality Score

Flag postings below 25% quality. Prompt recruiters to improve. Target: raise platform median from 32% → 40%.

⭐ Quality
CRITICAL
03

Quadrant-Based Resource Allocation

Stars → scale. Hidden Gems → volume drive. High Traffic → quality filter. Lagging → diagnose & intervene. Each quadrant, a distinct playbook.

🗺️ Strategy
HIGH
04

Activate Underserved Sectors

BD campaigns for Legal (68 offers) & Construction (134 offers). Healthcare UX research to fix 6.9x quality ratio. University partnerships for talent pipeline.

📈 Growth
05

Establish Monthly C-Level KPI Review + August Seasonality Playbook

Track all 3 normalized KPIs monthly. Develop counter-seasonal August campaigns: free reposts, featured listings, back-to-school activation. Protect +2 pts of score annually.

📊 Governance
Made byBobr AI
Emploitic
CLOSING QUESTION · SLIDE 13

If quality is twice as powerful as volume — what are we still optimizing for?

Which sector will you invest in first — and why?
What would it take for Commercial (20% quality) to become a Star?
If score 80 is reachable in 8 points — what's the plan for 90?
45,159 Offers Analysed
12 Segments Mapped
72→80 Score Target
1 Framework to Rule Them All
Emploitic × EIC Hackathon · June 2026 · emploitic.com
?
The question isn't
what the data says.
It's what you do next.
Made byBobr AI
Bobr AI

DESIGNER-MADE
PRESENTATION,
GENERATED FROM
YOUR PROMPT

Create your own professional slide deck with real images, data charts, and unique design in under a minute.

Generate For Free

Performance Analytics for Algeria's Leading Job Platform

Explore a strategic measurement framework for job platforms, focusing on quality elasticity, supply-demand matching, and data-driven recruitment metrics.

EMPLOITIC × EIC HACKATHON · JUNE 2026

From Data to Decisions

A Performance Analysis of Algeria's Leading Job Platform

45,159

Offers Analysed

51,396

Raw Records

12

Segments

72/100

Score

Q2 2025 · All Sectors · Emploitic Platform Analytics

Performance

Measurement

Framework

OPENING HOOK · SLIDE 02

How many CVs does it take to fill one job?

A

5 CVs

B

12 CVs

most people guess this

C

104 CVs

The answer is C — 104 apps per offer is Emploitic's demand threshold

Reading 104 CVs every Monday? That's not recruiting — that's a competitive sport. Our data makes it a science.

20,390

Total Applications Q2

12.2x

Avg Quality Ratio

72/100

Platform Score

PERFORMANCE DEFINITION · SLIDE 03

What Does Performance Mean?

Grounded in real data — not abstract theory

Performance = the degree to which a job posting converts labour demand (recruiter postings) into labour supply outcomes — applications, quality candidates, hires.

P = 0.6 × median(Quality%) + 0.4 × Hire Rate

Demand Threshold: 104 apps

Performance Threshold: 0.333

Quality Median: 32%

Hire Rate Median: 29.4%

DIMENSION

INDICATOR

WEIGHT

📊 Demand

Median applications/offer

Separate axis

✅ Quality

Median % good candidates

60%

🎯 Conversion

Hire rate

40%

Quality elasticity (0.543) is 2× more powerful than volume elasticity (0.259).

Quality > Quantity — always.

CURRENT STATE · SLIDE 04

The Scoreboard: Where Emploitic Stands Today

1,673

Total Offers (Q2)

20,390

Total Applications

12.2x

Avg Quality Ratio

72

/100

Performance Score

🔑 IT dominates supply & demand · Marketing has highest app-to-offer pressure · Legal & Construction most underserved

312

4,820

187

2,240

254

2,900

198

3,110

143

980

152

2,290

176

1,650

89

1,490

68

620

134

870

QUALITY ANALYSIS · SLIDE 05

Who's Winning the Matching Game?

Applications per Offer by Sector — Platform Average: 12.2x

Avg: 12.2x

HR

16.7x

Marketing

15.7x

IT

15.4x

Education

15.1x

Finance

12.0x

Engineering

11.4x

Logistics

9.4x

Legal

9.1x

Healthcare

6.9x

Construction

6.5x

🏆

HR leads at 16.7x — the platform's strongest matching signal

Marketing (15.7x) & IT (15.4x) close behind — strong candidate pools

⚠️

Construction (6.5x) & Legal (9.1x) far below threshold — candidate scarcity

📊

5 out of 10 sectors fall below the 12.2x platform average

Quality elasticity is 2× more powerful than volume. Sectors below 10x need urgent intervention.

STRATEGIC QUADRANT · SLIDE 06

The Portfolio Map

12 profession segments positioned by Performance Score vs Demand

Demand (Median Apps/Offer) →

Performance Score →

🔮 HIDDEN GEMS

High Perf + Low Demand

⭐ STARS

High Perf + High Demand

⚡ LAGGING

Low Perf + Low Demand

🚦 HIGH TRAFFIC

Low Perf + High Demand

Stars (3 segments)

Maintain & Scale

Hidden Gems (3)

Invest in Volume

High Traffic (3)

Fix Quality

Lagging (3)

Diagnose & Intervene

Agriculture

Education

Hôtellerie

Admin & Finance

Banque

RH & Formation

Commercial

Marketing

Santé

Informatique

Ingénierie

Logistique

PROBLEM STATEMENT · SLIDE 07

Flying Blind on a Busy Runway

Without a framework, every decision is a guess.

"How do we know whether a given profession is performing well on the platform — and what decisions should follow from that?"

— Emploitic Business Statement

No way to identify which professions are under-represented or over-saturated

No mechanism to detect friction in the supply–demand matching process

No data-driven guidance for recruiters, candidates, or internal teams

34 Raw Labels → Data Chaos

34 inconsistent profession labels in the raw data — duplicates, synonyms, wrong granularity

6.5% Useless Records

3,367 records labelled 'autre' or 'unknown' — analytically useless, excluded

Commercial: 20% Quality

Largest segment (9,173 offers) has the lowest quality rate — critical mismatch

design a measurement framework, apply it, and derive actionable guidance.

DATA QUALITY · SLIDE 08

Before Analysis: We Fixed the Data

Good decisions start with good data.

DUPLICATES

"sante/medical/pharmacie" AND "sante/pharmaceutique/delegue medical" — same domain, 2 labels

MEANINGLESS LABELS

3,367 records (6.5%) labelled 'autre' or 'unknown' — excluded

WRONG GRANULARITY

'Resp. commercial grands comptes' is a seniority level, not a profession segment

CATEGORY CONFUSION

'Admin, finance, compta & juridique' is a category mixed with profession labels

Solution: 34 Raw Labels → 12 Canonical Segments

Final clean dataset: 45,159 offers · 51,396 raw records · 2024–2026

MODEL INSIGHT · SLIDE 09

The Equation That Changes Everything

Quality is twice as powerful as volume. Full stop.

THE MEDIAN-ROBUST POWER LAW MODEL

Where: A = predicted median applications · N = number of offers · Q = quality rate

📦 Volume Elasticity: 0.259

Each 10% more offers → only +2.6% more applications

⭐ Quality Elasticity: 0.543

Each 10% better quality → +5.4% more applications (2× stronger!)

🚀 Posting more without improving quality has DIMINISHING returns

✅ Improving offer completeness, salary transparency & skill tags yields 2× the ROI

📈 Platform-wide quality median target: raise from 32% → 40% for measurable score uplift

KEY FINDING: Quality > Volume. Always. The data proves it.

VISION FOR CHANGE · SLIDE 10

The Road to Score 80

From 72 to High Performance — an 8-point journey backed by data

TODAY — Score: 72/100

MODERATE-HIGH

34 messy profession labels

No quality scoring for recruiters

5 sectors below quality avg

August seasonality unmanaged

Commercial: 20% quality crisis

IN PROGRESS — Q3 2025 Actions

TRANSFORMING

Taxonomy → 12 canonical segments

Real-time Offer Quality Score launched

BD campaigns for Legal & Construction

Healthcare UX research initiated

Quadrant-based resource allocation

TARGET — Score: 80+/100

HIGH PERFORMANCE

Clean, scalable data architecture

Quality median: 32% → 40%

All sectors above 10x quality ratio

Predictable August counter-campaigns

Monthly C-level KPI review cadence

Current: 72

Target: 80

Gap: 8 pts

KPI TRENDS · SLIDE 11

The Trajectory Is Already Positive

12-month normalized KPI evolution — Q1 to Q4 2025 projection

+2.4 pts/month

Performance Score Growth Rate

+2.2 pts/month

Quality KPI Growth Rate

78–80

Projected Q4 Score (Dec 2025)

June

Month Score Crossed the 60-pt Threshold

The August dip is predictable and preventable. A seasonality playbook can protect +2 pts of score annually.

All 4 KPIs on consistent upward trajectory — platform health is confirmed improving.

KEY RECOMMENDATIONS · SLIDE 12

5 Moves That Will Take Emploitic to 80

Data-backed. Actionable. Sequenced by priority.

01

Fix the Taxonomy NOW

Merge 34 raw labels → 12 canonical segments. Add taxonomy validation at offer submission. Eliminate 'autre/unknown'.

🏗️ Foundation

02

Launch Real-Time Offer Quality Score

Flag postings below 25% quality. Prompt recruiters to improve. Target: raise platform median from 32% → 40%.

⭐ Quality

03

Quadrant-Based Resource Allocation

Stars → scale. Hidden Gems → volume drive. High Traffic → quality filter. Lagging → diagnose & intervene. Each quadrant, a distinct playbook.

🗺️ Strategy

04

Activate Underserved Sectors

BD campaigns for Legal (68 offers) & Construction (134 offers). Healthcare UX research to fix 6.9x quality ratio. University partnerships for talent pipeline.

📈 Growth

05

Establish Monthly C-Level KPI Review + August Seasonality Playbook

Track all 3 normalized KPIs monthly. Develop counter-seasonal August campaigns: free reposts, featured listings, back-to-school activation. Protect +2 pts of score annually.

📊 Governance

CLOSING QUESTION · SLIDE 13

If quality is twice as powerful as volume — what are we still optimizing for?

Which sector will you invest in first — and why?

What would it take for Commercial (20% quality) to become a Star?

If score 80 is reachable in 8 points — what's the plan for 90?

45,159

Offers Analysed

12

Segments Mapped

72→80

Score Target

1

Framework to Rule Them All

Emploitic × EIC Hackathon · June 2026 · emploitic.com

The question

isn't

what the data

says.

It's what you

do next.