R2.3 Million in 90 Days Here's Exactly How We Did It
Veldora, an international home appliance retailer was drowning in traffic that wasn't converting. In 90 days we turned that traffic into R2.3 million in verified revenue. We're showing you every step.
R2.3M
Revenue in 90 days
2,847
Purchases
306,765
Sessions
81.3%
Engagement rate
- Every figure verified in Google Analytics 4
- No estimates, no projections
- Client identity kept confidential under agreement
Performance marketing is advertising where you only pay for results: sales, leads, or clicks. Every rand of spend is measured. In this engagement, Mashilo Digital ran the full system: Meta Ads, Google Ads, conversion tracking, and landing page optimisation, all reporting into one Google Analytics 4 view. Nothing in this case study is projected. Every figure below comes directly from the client's own analytics.
Executive Summary
The Engagement at a Glance
Client
Veldora home appliance & electronics e-commerce retailer
INDUSTRY
Home appliances & electronics (high-ticket, long consideration cycle, load-shedding-driven demand)
DURATION
90 days (Apr 12 – Jul 2, 2026)
GOAL
Convert existing traffic into revenue and lower the cost of every new customer
KEY RESULT
R2,300,000 verified revenue · 2,847 purchases · 81.3% engagement rate
The one-line proof
In 90 days, Mashilo Digital generated R2,300,000 in revenue and 2,847 purchases for a South African e-commerce retailer, verified in Google Analytics 4.
The client had the hardest part of e-commerce already solved: people were coming. 238,872 users landed on the store during the engagement. The problem was what happened after they arrived.
The Challenge
Traffic Wasn't the Problem. Conversion Was.
Low conversion rates despite high traffic
Thousands of shoppers visited the store every week, but the percentage actually buying stayed stubbornly low. High traffic with weak conversion means you're paying for visits that never become revenue.
Lower Google Ads Cost Per Click
We cut wasted spend by targeting high-intent search terms, not broad keywords that drain budget
Rising customer acquisition costs
Every new customer cost more than the last. The store was spending more to acquire each buyer while margins stayed flat. That's the classic sign of ad accounts running on guesswork instead of data.
Transparent Google Ads Pricing
No hidden fees or vague retainers. You see exactly what you're paying for and what it's generating.
No unified measurement framework
Google Ads, Meta Ads, and the website were reporting into separate silos. Nobody could say which rand of spend actually produced a purchase, so optimisation was impossible. You can't improve what you can't measure in one place.
Weekly Performance Reviews
Every campaign reviewed and optimised weekly, not left to run on autopilot.
These three problems feed each other. Weak tracking hides wasted spend. Wasted spend drives acquisition costs up. Rising costs make every unconverted visitor more expensive. Another ad account would only add noise. The fix was a system.
Our Strategy
Most agencies sell you channels. We built the client one connected machine where ads, measurement, and landing pages pull in the same direction. Four layers, each feeding the next.
The Full-Funnel System We Built
Weeks 1–2
Measure First
- Google Tag Manager deployed across the store
- Conversion tracking wired to actual purchases, not just clicks
- Client identity kept confidential under agreement
- GA4 configured as the single source of truth
Weeks 2–6
Fix the Conversion Leak
- Landing page optimisation so driven traffic actually converted
- High-intent pages rebuilt around the buyer's question, not the spec sheet
- Faster load times, clearer pricing, sharper calls to action
- Mobile-first: most of this traffic was on phones
Weeks 4–12
Acquire With Both Engines
- Meta Ads: catalogue + prospecting creative aimed at people comparing appliances
- Google Ads: high-intent search for buyers ready to purchase
- Budget shifted weekly toward whatever channel produced revenue
- That's the "performance" in performance marketing
Every Week
Optimize Continuously
- Bid adjustments, audience narrowing, creative refreshes
- Product-level analysis: which SKUs converted, which wasted budget
- One GA4 dashboard reviewed weekly
- Decisions from data, not opinions
KEY RESULT
The timeline is honest: the first 90 days buy you a measurement foundation, a converted website, and a scaled acquisition engine. The revenue came because every layer of the system was working at once. There was no single magic campaign.
Five pillars, one system. Each one depended on the others. That's why the results hold up to scrutiny.
Execution
What We Actually Ran
PILLAR 01
Product catalogue ads for appliances people were actively comparing, plus prospecting campaigns to find new buyers. Weekly creative and audience refreshes to fight ad fatigue.
Lower Google Ads Cost Per Click
We cut wasted spend by targeting high-intent search terms, not broad keywords that drain budget
PILLAR 02
High-intent search campaigns on the exact queries shoppers type when they're ready to buy. Google Shopping fed by the product catalogue. Bidding optimised toward purchases, not clicks.
Lower Google Ads Cost Per Click
We cut wasted spend by targeting high-intent search terms, not broad keywords that drain budget
PILLAR 03
Every campaign pointed at a page that answered the shopper's question and made buying easy. We removed friction between "I want this" and "I've bought it."
Lower Google Ads Cost Per Click
We cut wasted spend by targeting high-intent search terms, not broad keywords that drain budget
PILLAR 04
Google Tag Manager for clean, tag-free marketing operations. Every click, view, and purchase flowed into one dashboard without manual tagging errors.
Lower Google Ads Cost Per Click
We cut wasted spend by targeting high-intent search terms, not broad keywords that drain budget
KEY RESULT
These are screenshots of the client's real GA4 dashboard. We can say this because it's true: every number on this page is verifiable in the client's own analytics account.
Revenue generated in 90 days
The Big Number R 2,300,000
2,847
Purchasers
238,872
Users
306,765
Sessions
81.3%
Engagement rate
≈ R808
Average order value (calculated: R2.3M ÷ 2,847 purchases)
R9.69
Avg purchase revenue per active user (GA4)
Real Time Google Analytics 4 Data
