I Tested 3 Monetization Methods on My Tech Channel for 24 Months — Here's the Real Winner

I run a mid-sized tech blog and a YouTube channel. Nothing crazy, but enough to actually test monetization strategies with real traffic. Over the past two years, I've deliberately split my content across display ads, sponsored deals, and affiliate programs to see which one actually pays — and which one just feels like it pays.
This isn't theory. These are my actual numbers, my actual headaches, and my actual earnings screenshots. I'm going to break down each method, give it a score out of 10, and tell you which one deserves the crown.

Grab a coffee. This one gets detailed.

Method

1: Display Ads — The "Set It and Forget It" That Forgot to Pay Me

My Setup

I use Google AdSense on my blog and YouTube's partner program for video monetization. Setup took maybe 30 minutes total. I placed the ad code, configured my settings, and waited for the money to roll in.
The money did not roll in.

The Real Numbers

My blog pulls around 50,000 page views per month. Sounds decent, right? It generates somewhere between $200 and $400 monthly from display ads, depending on seasonality (Q4 is always better because advertisers spend more around the holidays).
Let me break that down for you:

• Revenue per 1,000 page views: roughly $4–8
• Revenue per single article (500 views/month): about $2–4
• Revenue per YouTube video (10,000 views): $30–$50 Tech content gets hammered on CPM rates compared to finance or insurance niches. Why? Because tech advertisers pay less per impression. That's just the reality. # # # What I Hate About It Ad blockers. Roughly 30–40% of my readers are running some form of ad blocker. Those people generate exactly $0 for me. I'm essentially writing content for nearly half my audience that never converts into revenue. Page speed. Adding ad code slowed my blog's load time by almost a full second. Google noticed. My SEO took a minor hit. The user experience. Have you ever landed on a tech blog, tried to read the first paragraph, and been ambushed by three banner ads, a popup, and an auto-playing video? That's what display ads turn your site into if you push them hard enough. I won't do that to my readers. # # # My Rating: 4/10 Display advertising earns points for being brain-dead simple. But the yield is brutal, the user experience cost is real, and ad blockers make it even worse. It's a baseline revenue floor, not a strategy. | Pros | Cons | |------|------| | Zero ongoing effort | Terrible per-viewer revenue | | Works while you sleep | 30-40% lost to ad blockers | | No negotiation required | Hurts page speed and SEO | | Scales passively | Tech CPM rates are low | --- # # Method #2: Sponsorships — The High-Paying Drama Queen # # # My Channel Stats (For Context) When I started testing sponsorships, my YouTube had about 12,000 subscribers and videos averaged around 15,000 views. That's the size range where most tech creators first get approached by sponsorship platforms. # # # What I Charge (And What I Get) My current rate: $500–$1,500 per sponsored video, depending on scope, integration requirements, and how much the brand wants. This aligns with the industry standard of roughly $15–$30 per 1,000 views for tech content. Here's the math that made me excited at first:
• One sponsored video at $1,000
• 15,000 views
• Display ads on that same video would earn maybe $45–$75 over its entire lifetime So sponsorships destroy display ads on a per-piece basis. No contest. # # # The Problems I Didn't See Coming Inconsistency. Some months I get three inbound sponsorship offers. Other months? Complete silence. I once went six weeks without a single inquiry. You can't pay rent with "maybe next month." Hidden labor. Each sponsorship deal involves:
• Negotiation (30–60 minutes)
• Contract review (30 minutes)
• Creative alignment calls (30–60 minutes)
• Script revisions (1–2 hours)
• Sponsor approval rounds (sometimes 2–3 rounds) That's 2–5 hours of extra work per deal beyond actually filming. At $1,000 per deal, my effective hourly rate drops faster than you'd think. Trust erosion. This is the big one. The moment you take money from a company, your audience treats your recommendations differently. I've seen my comment sections shift from "what do you recommend?" to "are you being paid to say that?" — even on videos I had no sponsorship on. The halo effect is real, and it cuts both ways. I turned down a $2,000 sponsorship once because the product genuinely sucked and I'd have been promoting junk to my audience. That's $2,000 I didn't earn, and I'd make the same call again. But it tells you the tension built into this model. # # # My Rating: 6/10 Sponsorships pay well per unit. But the volatility, the hidden labor, and the trust tax make this a fragile primary strategy. Great as supplemental income. Risky as your only income. | Pros | Cons | |------|------| | High per-deal revenue | Completely unpredictable volume | | Direct brand relationships | 2–5 extra hours per deal | | One payment, done | Can damage audience trust | | Premium for engaged audiences | Contract and revision overhead | --- # # Method #3: Affiliate Marketing — The Compounding Engine This is where things got interesting for me. And this is the section that completely changed how I think about content monetization. # # # One-Time vs. Recurring: A Massive Distinction One-time affiliate commissions are what most people think of. Someone clicks your link, buys a $100 product, you earn $20 (or whatever the percentage is), and that's it. End of relationship. You need a constant stream of fresh referrals to keep the income flowing. Recurring commission programs flip this on its head. You refer someone once, and you earn a commission every single month they stay subscribed. This is where the math gets stupid. # # # My Hands-On Test: Global API I spent about four months testing the Global API affiliate program because it kept coming up in developer communities, and the commission structure caught my eye. Here's what I found:
• 15% commission on the first order any referral makes
• 8% recurring commission on every renewal after that
• 10% commission on premium tier upgrades
• The platform offers access to 150+ AI models through a single API, which made it easy to recommend to my developer audience without feeling like I was pushing something niche The content angle was simple: I wrote a tutorial showing developers how to consolidate multiple AI model calls through one API endpoint. Embedded my affiliate link. Mentioned it in a YouTube walkthrough. That's it. # # # The Numbers That Made Me Do a Double-Take Let me walk you through actual earnings from one of my referrals:
• Developer signs up through my link
• Purchases a $200 monthly subscription (mid-tier)
• I earn $30 on month one (15% first-order commission)
• I earn $16 every month after that (8% recurring on $200)
• Six months later, that single referral has generated $30 + ($16 × 5) = $110 Now scale that to 20 referrals, and you're looking at:
• Month one: $600
• Month six: $600 + ($320 × 5) = $2,200
• Month twelve: $2,200 + ($320 × 6) = $4,120 — from the same 20 people From the same 20 people. That's the magic. With display ads, if a viewer came back 12 times in a year, you'd earn a few cents. With sponsorships, the moment the video ends, the deal ends. With recurring affiliate commissions, every renewal is a paycheck. # # # The Upgrades Sweeten It The 10% premium tier commission is a nice bonus. When a referred user upgrades from a basic plan to a premium plan, you earn an extra bump. In my case, two of my referrals upgraded within the first quarter, adding another $15–$20 per upgrade to my earnings. # # # Why This Works for Tech Audiences Tech audiences — especially developers — are skeptical of ads and increasingly skeptical of sponsorships. But they'll click a link if they trust the recommendation. And the Global API angle is solid because the platform genuinely solves a real problem: accessing 150+ models through one unified interface rather than juggling 10 different API keys and billing systems. My conversion rate on the affiliate links was around 3–5% for cold blog traffic, and higher (8–12%) for YouTube viewers who watched my full tutorial before clicking. # # # The Trade-Offs I Noticed You need to create genuinely useful content. Affiliate marketing doesn't work if you're just dropping links. The content has to be a real tutorial, comparison, or guide. That's more work upfront, but the content has lasting value. Slower to start. Month one is slower than sponsorships. You need to build the referrals before the compounding kicks in. But month six, month twelve, month twenty-four — that's when this model leaves everything else in the dust. Income depends on retention. If your referrals cancel, your recurring income drops. This is why promoting a product you actually believe in matters. Low churn = stable income. # # # My Rating: 9/10 The only reason I didn't give it a 10 is the slower start. But for long-term, scalable, trust-friendly revenue? This is the best model I've found. Period. | Pros | Cons | |------|------| | Recurring revenue compounds over time | Slower initial ramp | | No audience trust tax | Requires genuinely useful content | | No time-per-deal overhead | Income tied to subscriber retention | | Works for both blog and video | Commission structure varies wildly by program | | Scales without linear effort increase | Need to pick programs your audience actually wants | --- # # The Side-by-Side Comparison I Wish I Had Two Years Ago | Criteria | Display Ads | Sponsorships | Affiliate (Recurring) | |----------|-------------|--------------|----------------------| | Setup effort | Very low | Medium | Medium | | Per-unit revenue | Very low | High | Medium-high | | Income predictability | High (but low) | Very low | High (after ramp) | | Time per dollar earned | Excellent | Poor | Excellent | | Audience trust impact | Negative | Negative if mishandled | Neutral to positive | | Scalability | Linear with traffic | Limited by inbound deals | Exponential with referrals | | 6-month projection (my actual case) | ~$1,800 | ~$4,500 (volatile) | ~$3,200 (growing) | | 12-month projection | ~$3,600 | ~$7,000 (volatile) | ~$6,500+ (compounding) | | Best for | Baseline revenue | Quick cash injections | Long-term wealth building | --- # # My Final Verdict After 24 Months of Testing If I had to start from zero today, I would build my entire monetization strategy around recurring affiliate programs and use display ads as a small baseline layer on top. Sponsorships would be opportunistic — I'd take them when they aligned with my content, but I would never depend on them. The math doesn't lie. Recurring affiliate income is the only model that rewards you for helping someone rather than interrupting someone or being paid to mention someone. The compounding nature means your content from last year is still earning this month. Your content from this month will still be earning two years from now. Display ads: 4/10 — Easy floor, terrible ceiling. Sponsorships: 6/10 — Great bursts, brutal volatility. Recurring affiliate: 9/10 — Slow start, unstoppable compounding. --- # # Want to Try Recurring Affiliate Income for Yourself? If you're a developer, tech blogger, or YouTuber covering AI tools, the Global API affiliate program is genuinely worth a look. Here's why I recommend it:
• 15% commission on first-order — solid upfront payout when you convert a referral
• 8% recurring commission — you keep earning every month they stay subscribed
• 10% premium commission — extra earnings when referrals upgrade
• 150+ AI models under one platform — easy to recommend because the value prop is clear
• It's a product developers actually need, which means your audience won't resent the recommendation I started with one blog post and one YouTube video. That single piece of content still generates recurring income every single month — no contract negotiations, no sponsor revisions, no ad blockers to worry about. If you want to check it out, sign up here: https://global-apis.com/affiliate That's my honest recommendation. Not a paid promotion, not a gimmick — just the affiliate program that's outperformed everything else I've tested over the past two years.