Pulse SA - Executive Summary

One sentence: We pay township youth R5-R15 per micro-survey to collect economic data that Stats SA cannot, stitch it with national datasets, and sell the intelligence to banks, FMCGs, and government who are currently making billion-rand decisions blind.


1. What Do We Have?

We have a working prototype with four connected pieces:

Piece A: A Mobile App for Township Youth ("Data Gigs")

A simple phone app where young people in townships earn airtime or cash by completing quick surveys:

Each survey takes 2-3 minutes. They get paid instantly via airtime top-up or Capitec CashSend.

Piece B: A "Credit Score" for Informal Traders

When the same vendor gets logged repeatedly over weeks, we build a digital track record for them - even though they have no bank statements or VAT number. We verify their numbers using three methods:

This gives Nedbank or Capitec enough confidence to offer her a small stock loan (R3,000-R10,000) that she could never qualify for today.

Piece C: A Macro "Data-Gap Map" for Institutions

A dashboard showing decision-makers where the real opportunities are in the informal economy. It combines:

The key finding: Everyone is fighting over spaza shops (Trade & Retail). But the fastest-growing sectors - community services (childcare, tutoring, security) and informal finance (stokvels, mashonisas) - have almost zero fintech or analytics products serving them.

Piece D: A "Digital Twin" of Township Economies

A network graph that maps how everything connects: which traders depend on which water pipes, which transport routes feed which market areas, which wholesalers supply which shops. When you simulate a water shutdown, you can instantly see which businesses go down and how much cash flow is at risk.


2. Why Do We Have It?

The Problem

South Africa has 1.9 million informal businesses generating trillions of Rands. But:

What Banks/FMCGs Need What They Currently Have
Real-time prices in township shops Nothing - Stats SA surveys are annual
Which brands are on spaza shelves Nothing - FMCG visibility ends at the wholesale depot
Which traders are creditworthy Nothing - no bank statements, no tax returns
Which sectors are under-served Nothing - everyone piles into spaza retail because it's familiar
What happens when water/transport breaks Nothing - they find out from the news

Nobody has stitched these data sources together. Stats SA has macro numbers. FinScope has survey data. FMCGs have wholesale delivery logs. But none of them talk to each other. We are the integration layer.

Why Not Just Use Stats SA?

Stats SA tells you what happened nationally last year. We tell you what is happening in Ward 15 of Soweto right now. They count businesses. We map cash flows, supply chains, and infrastructure dependencies in real-time. We don't compete with Stats SA - we use their data as the macro benchmark and fill in everything they can't see.


3. How Does It Work? (End-to-End Flow)

Step 1: Youth agent opens phone app
        ↓
Step 2: Completes a 2-minute survey (e.g. logs achar vendor's prices)
        ↓
Step 3: Gets paid R15 airtime instantly
        ↓
Step 4: Data flows into our dashboard
        ↓
Step 5: Dashboard updates in real-time:
        * The vendor's credit score improves
        * The food inflation chart updates
        * The ontology graph adds/updates the node
        ↓
Step 6: Institutional client (Nedbank, Tiger Brands, City of Joburg)
        sees the aggregated intelligence on their dashboard
        ↓
Step 7: They make better decisions:
        * Nedbank approves a stock loan for the vendor
        * Tiger Brands redirects delivery trucks to under-stocked areas
        * City of Joburg prioritises water pipe repairs in high-impact zones

4. How Do We Get It Live?

The prototype works locally. To get it into real users' hands, here are the steps:

Phase 1: Validate (Month 1-2) - Cost: ~R50,000

Phase 2: First Paying Client (Month 3-4) - Cost: ~R100,000

Phase 3: Scale (Month 5-12) - Raise seed funding


5. How Will It Generate Revenue?

Four revenue streams, from easiest to most valuable:

Stream 1: Data Subscriptions (Easiest to start)

Who pays: FMCG companies (Tiger Brands, Unilever, Coca-Cola) What they get: Weekly/monthly reports on brand availability, shelf pricing, and competitor activity across mapped spaza shops. Why they pay: They currently have zero visibility into what happens after their delivery trucks drop stock at wholesale depots. A major FMCG company would pay R50k-R200k/month for this. Comparable: Nielsen and Kantar charge millions for formal retail audits. We do the same thing for informal retail at a fraction of the cost.

Stream 2: Credit Underwriting Data (Most Valuable)

Who pays: Banks and micro-lenders (Nedbank, Capitec, Lulalend, Retail Capital) What they get: Verified alternative credit profiles for informal traders - wholesaler purchase history, consistency scores, foot-traffic verification. Why they pay: The informal economy represents trillions in turnover that banks currently cannot lend into because they have no data. Even a 1% penetration of that lending market is worth billions. Model: Revenue share on every loan originated using our data (2-5% of loan value), or a monthly data API subscription (R100k+/month).

Stream 3: Infrastructure Intelligence

Who pays: Municipalities and utilities (City of Joburg, Rand Water, Eskom) What they get: Real-time, ward-level infrastructure status reports (water outages, road conditions) reported by our agents faster than their own monitoring systems. Why they pay: Municipal call centres are slow and unreliable. Our agents provide a distributed sensor network that maps problems in real-time and shows economic impact. Model: Annual SLA contract (R500k-R2M/year per municipality).

Stream 4: ESD and Impact Intelligence

Who pays: Corporates with Enterprise & Supplier Development (ESD) obligations, and DFIs (Development Finance Institutions like the IDC, NEF, SEFA) What they get: Verified impact data - proof that ESD spend actually reached and supported informal businesses, with auditable digital trails. Why they pay: Companies spend billions on ESD compliance annually but struggle to prove real impact. Our platform provides the evidence trail. Model: Per-programme fees (R200k-R1M per ESD programme tracked).


6. Is It Viable?

The Numbers (Conservative Estimate)

Item Monthly Cost
200 agents × 50 surveys/month × R10 avg payout R100,000
Cloud hosting & SMS costs R15,000
2-person core team (founder + developer) R80,000
Total Monthly Burn R195,000
Revenue Source Monthly Revenue (Year 1 target)
2 FMCG data subscriptions R200,000
1 bank pilot R100,000
1 municipal pilot R50,000
Total Monthly Revenue R350,000

Break-even is achievable within 6 months of first client.

Why It Works in SA Specifically

Risks (Being Honest)

Risk Mitigation
Agents submit fake data Wholesaler cross-checks + foot-traffic verification + anomaly detection
Institutions won't pay for informal economy data Use the Data-Gap Map as proof that the opportunity exists and they're currently blind
Competition from bigger players We have a ground-level agent network they can't easily replicate. No global intelligence platform has 200 people in Soweto.
Scaling agent payments is expensive Agent costs scale linearly with data volume, but data revenue scales with client count - one FMCG client pays for 200 agents

7. Can It Go to Market?

Yes. Here is why:

What's Ready Today

What's Needed to Launch (Minimum)

The Go-to-Market Play

You don't cold-pitch. You walk into the meeting with the Data-Gap Explorer already showing their blind spots. The conversation goes:

"I'm not here to sell you a product. I'm here to show you something nobody else has mapped. Here's the informal economy broken down by sector growth versus fintech coverage. See this top-left corner? Community services and informal finance are growing fastest but have almost zero products. Your competitors are all fighting over spaza shops in the bottom-right. Now let me show you how we actually collect this data on the ground..."

Then you flip to the PWA simulator tab and show them the youth agents logging live data. Then you flip to the ontology graph and show them how one water shutdown cascades through the network.

The intelligence-first playbook: Don't sell software. Bring intelligence that demonstrates the platform's value before anyone signs a contract.


Summary Table

Question Answer
What is it? A data platform that pays township youth to collect economic intelligence and sells it to institutions
Why does it exist? R-trillions of informal economy activity is invisible to banks, FMCGs, and government
How does it work? Youth log micro-surveys → data feeds dashboards → institutions buy the intelligence
How do we get it live? 20 agents, 1 township, 1 pilot client. ~R150k to validate.
How does it make money? Data subscriptions, credit underwriting fees, infrastructure intelligence contracts
Is it viable? Yes - break-even within 6 months with 2-3 paying clients
Can it go to market? Yes - the prototype is demo-ready, the go-to-market is "show, don't pitch"