A solo ads case study is only worth your time if it shows the numbers you can check: clicks sent, clicks that landed, opt-ins, sales and total cost. Most don't. They show a screenshot, a big percentage and a link to the seller. This guide shows you how to read a case study skeptically, what a useful one contains, and how to run your own small test so the case study you rely on is yours.
We don't publish income claims here, and we won't give you a "this campaign made X" story to copy. A result from someone else's list, offer and funnel doesn't transfer to yours. What transfers is the method.
TL;DR
- Treat any public solo ads case study as marketing until it shows clicks, landing page visits, opt-ins, sales and total spend, all from your own tracking or the author's.
- Email click counts and website visit counts rarely match, because automated spam filters and link checkers often "click" links before a human does.
- Test small first, log every vendor in a spreadsheet, and only reorder from a vendor whose numbers hold up.
- Under CAN-SPAM, hiring a sender doesn't remove your legal responsibility as the advertiser.
Table of Contents
- What a solo ad case study actually is
- Seven checks before you trust a case study
- Why the click count is the first thing to doubt
- A worked example with made-up numbers
- How to run your own case study
- What to do when the case study results are bad
- The legal side nobody puts in a case study
- Our perspective
- Where to go from here
- FAQ
- Sources
What a solo ad case study actually is
A solo ad is a single email, sent by a list owner to their subscribers, with one call to action: click this link. You pay for the send, usually priced per click. A case study in this niche is a write-up of one such purchase, or a series of them, with the results.
That sounds simple, but the format has a built-in bias. People publish case studies when the result is good, when they are selling the traffic source, or when they are selling a course on how to buy it. A failed $100 test rarely gets a blog post. So the sample you see online is skewed toward wins before you even look at the numbers.
That doesn't make every case study useless. Some authors do publish plain breakdowns, including a first $100 campaign write-up with what worked and what didn't and a traffic-source walkthrough using a click tracker. The point is to read them the way you would read a vendor's sales page: look for what is missing.
Seven checks before you trust a case study
Run every case study through this list. If it fails more than two, learn from it but don't base a purchase on it.
- Who wrote it, and who gets paid? If the author sells the traffic, or earns a commission when you click through, the story is an ad. Say that plainly to yourself and keep reading for the data.
- Is the spend stated? You need the total cost, not just the cost per click. Extras such as bonuses, add-on clicks or a second send change the math.
- Are clicks separated from visits? Clicks recorded by the vendor are the vendor's number. Visits recorded by your tracker or analytics are yours. A case study that shows only the first is showing the claim, not the delivery.
- Is the opt-in rate shown with its denominator? An opt-in rate means subscribers divided by clicks, or subscribers divided by landing page visits? Those give different percentages for the same campaign.
- Are sales tied to the campaign? "Sales during the week" is not "sales from the traffic." Look for a tracked link, a unique offer URL or a sub ID.
- Is the time frame long enough? Solo ad subscribers often buy after several follow-up emails. A case study written 48 hours after the send can't tell you about revenue.
- Can the result be repeated? One good send tells you little. A second send to the same vendor, with the same funnel, tells you more.
Why the click count is the first thing to doubt
The number a vendor reports and the number that reaches your page are often different. Part of the gap is innocent. Email security tools and spam filters frequently open and follow links to check them, so raw click volume can be high while real human sessions stay low. Part of it can be deliberate padding. We cover that side in why solo ad vendors inflate click counts.
For you, the consequence is practical. If a case study says "500 clicks, 120 opt-ins," ask which system counted the 500. If it was the seller's dashboard, you can't tell if 500 people arrived.
Standard web analytics is a start, but it isn't a fraud detector. Dedicated traffic quality tools exist for that job, and one published example from a job platform describes a team finding high bot rates in some channels and shifting budget away from them. That case is from recruitment and paid search, not solo ads, and the vendor of the tool wrote it, so take it as an illustration of the principle only: measure traffic quality per source, then move money based on what you measure.
A worked example with made-up numbers
The table below is hypothetical. It is not a real campaign. We use it to show how to calculate the figures a good case study should report.
Say you buy 100 clicks at $0.40 per click, so you spend $40.
| Metric | Vendor's claim | Your tracker |
|---|---|---|
| Clicks | 100 | 100 reported by vendor |
| Landing page visits | not reported | 71 |
| Opt-ins | not reported | 24 |
| Sales | not reported | 1 |
| Commission earned | n/a | $20 (example) |
From these invented figures:
- Click-to-visit rate: 71 ÷ 100 = 71%. Nearly three in ten clicks never became a visit.
- Opt-in rate on visits: 24 ÷ 71 = about 34%.
- Opt-in rate on paid clicks: 24 ÷ 100 = 24%.
- Cost per subscriber: $40 ÷ 24 = about $1.67.
- Early return: $20 earned against $40 spent is a loss so far, but 24 subscribers are still on your list and will receive follow-ups.
Notice what changes depending on how you present it. A case study could headline "34% opt-in rate" or "24% opt-in rate" from the same campaign. Neither is dishonest, but only one is the number you paid for. When you read someone else's results, convert them to cost per subscriber and cost per sale on total spend. Then they are comparable.
How to run your own case study
Your own test beats any public one. It costs little and answers the only question that matters: does this vendor send real people to my funnel?
Step 1: Vet the vendor before paying
Before you place an order, ask the hard questions. Our 21 vetting questions for solo ad buyers cover list source, sending practices and lead theft. If a vendor dodges them, that is data.
Step 2: Set up tracking first
Create a unique tracked link for this vendor and this send. Use a click tracker on your side so you record clicks independently. Our guide on how to track solo ad traffic walks through the setup. Add a sub ID for the vendor name and date so sales can be matched later.
Step 3: Order a small test
Buy a small batch, in the range of 100 to 200 clicks, and ask for no extras. We describe why that range works in our 100 to 200 click test. A small order limits the damage if the vendor is poor, and it's still enough to spot obvious problems.
Step 4: Compare the numbers
When the send finishes, line up three counts: clicks the vendor reported, clicks your tracker recorded, and visits that reached your page. Large gaps are a red flag. Ask the vendor for click logs and look at IP addresses, timestamps, countries and devices. Clusters of identical IPs or clicks seconds apart are not how people behave. For filtering, see our guide to IP filtering for solo ads.
Step 5: Log everything in a spreadsheet
Tracking each vendor in a spreadsheet, with clicks, opt-ins, sales and return, is the reliable way to separate good vendors from bad ones. Use one row per send. Suggested columns:
| Column | What it holds |
|---|---|
| Vendor and date | Who, when |
| Amount paid | Total, with extras |
| Vendor-reported clicks | Their claim |
| Tracker clicks | Your count |
| Landing page visits | Your analytics |
| Opt-ins | From your email platform |
| Cost per subscriber | Spend ÷ opt-ins |
| Sales and revenue | Matched by sub ID |
| Notes | Refund response, log quality |
Step 6: Wait, then decide
Give subscribers time to move through your follow-up sequence. Only then judge the sale numbers. If a vendor passed the click comparison and the subscribers are opening your emails, reorder a slightly larger batch and log it again. If not, stop. One failed test costs you far less than a big first order.
What to do when the case study results are bad
A weak result doesn't automatically mean the vendor was bad. Work through the cause in order:
- Traffic problem: tracker clicks far below the vendor's number, or logs full of repeated IPs. This points at the vendor. See our click fraud prevention guide and the explainer on what click fraud means.
- Conversion problem: clicks and visits line up, but opt-ins are low. The vendor delivered people; your squeeze page didn't convert them. Change the page, not the vendor.
- Quality problem: opt-ins arrive, but they never open emails or buy. Check for fake sign-ups and ask about the vendor's list. Our guide to fake conversions in solo ads covers the signs.
- Offer problem: subscribers are real and engaged but don't buy. That is a funnel issue and no vendor can fix it.
Separating these four is the real value of keeping records. Without them, every bad result looks like "solo ads don't work."
The legal side nobody puts in a case study
Case studies talk about clicks and revenue. They almost never mention email law. In the US, the CAN-SPAM Act sets rules for commercial email, and the FTC states that advertisers can be liable when affiliates or senders break the rules, including requirements for a valid physical postal address and a clear opt-out. The FTC also notes that penalties can reach $53,088 per violating email. The agency's guidance says you can't contract away your responsibility by hiring someone else to send.
If you are unsure how this applies to your affiliate offers, read our CAN-SPAM guide for affiliates, and speak with an attorney who handles advertising law for your specific situation. This is general information, not legal advice.
Our perspective
We have seen the same pattern for years. A buyer reads a glowing case study, orders a large batch on the first purchase, and finds out afterward that half the clicks never reached the page. The case study wasn't necessarily a lie. It just wasn't theirs.
So we tell buyers the same thing every time: the best case study is the one in your own spreadsheet. We assume most traffic sellers overpromise, and we'd rather you verify than trust, including when you read us. That means tracking before you spend, a small test before a big order, and a vetting checklist before any of it. We don't promise returns, because nobody honest can promise them for your funnel.
If a vendor gets angry when you ask for click logs or a test order, that tells you more than any testimonial.
— Philip Coble
Where to go from here
If you want the full process in one place, start with our 21-question vendor vetting framework on SoloAdsGuide.com, then work through the tracking and click log guides above. They are written for buyers, so they focus on what to check before you spend, not on what to buy.
It also helps to look outside solo ads for how others evaluate paid traffic. For instance, a Meta Ads campaign structure breakdown shows how performance marketers judge spend against measured results, and the same discipline applies to any paid channel.
FAQ
Are solo ads case studies real?
Some are real and some are staged to sell traffic or courses. Check whether the author shows total spend, tracker data and sales matched to the campaign. If it only shows a dashboard screenshot and a link to the seller, treat it as an ad.
How much should I spend on a first solo ad test?
Keep it small enough that losing it won't hurt. We suggest a batch of 100 to 200 clicks from a vendor you have vetted. The goal of the first order is verification, not profit.
Why do my clicks and website visits not match?
They come from different systems, and email security tools often follow links automatically. A gap is normal, but a very large one is worth investigating with click logs. Compare the vendor's count, your tracker's count and your analytics visits.
What numbers should a solo ads case study include?
Total spend, clicks sent, tracker-verified visits, opt-ins, opt-in rate with its denominator, sales, revenue and the time frame. Without cost per subscriber and cost per sale, you can't compare it to your own results.
Sources
- CAN-SPAM Act: A Compliance Guide for Business, FTC
- Data discrepancy between Ortto and Google Analytics, Ortto Help Center
- JobNinja traffic quality case, fraud0
- My First $100 Solo Ad Campaign, Bohemian Publishing
- Case Study: 7DaysBuyer's Traffic Source, CPV Lab Blog
Recommended
- Solo Ad Buyers: 50–200 Click Test and 21 Questions to Verify Leads
- Solo Ad Buyers: 21 Questions to Vet Fake Conversions
- How to Test Order Solo Ads Without Wasting Your Budget
- Protect Your Budget: 21 Question Solo Ad Red Flags for Buyers
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