Claude Hopkins: When Science Met Advertising 🔬

Case Studied

How this advertising legend brought scientific testing to the ad world

If you’ve ever run an A/B test on an ad, you’ve benefited from Claude Hopkins’ work. As an advertising pioneer, Hopkins introduced scientific concepts into ad strategy in the late 19th and early 20th century.

In doing so, Hopkins was able to prove advertising’s quantitative value to business leaders and usher in a new way of testing that’s still widely used in advertising and marketing to this day.

This week, Case Studied takes a look at how advertising legend, Claude Hopkins, conceived of the most cost-effective method for designing and revealing the highest-performing ads and how you can apply this historical context to your marketing.

The Brief:

In his introduction to Hopkins’ book, Scientific Advertising, David Ogilvy wrote, “Nobody, at any level, should be allowed to have anything to do with advertising until he has read this book seven times.”

In the acclaimed book, Hopkins introduced many advertising concepts that are now commonplace—brand images, sampling, and, you guessed it, test campaigns. It was the first time anyone brought scientific methodologies to a non-laboratory environment—and companies have been reaping the rewards from it ever since.

Test campaigns allowed businesses to find the most profitable ads in a way that wasn’t particularly expensive (especially when you consider the potential return).

The Execution:

Since he was advertising back in the day, the test campaigns Hopkins ran were pretty straightforward. He mailed several versions of an ad for a specific product to multiple cities, using different headlines, promotions, and offers.

Hopkins tracked the success of each ad by key coding coupons, another strategy he’s credited with revolutionizing. Thanks to the key codes, Hopkins could precisely measure the sales and cost-per-sale of each version of the ad.

From there, all he had to do was track the codes to identify the most successful version of the ad. He had data-driven insights that verified what worked, what didn’t work, and how much everything cost.

This was the birth of A/B testing. A novel concept that enabled advertisers to determine, with extreme confidence, what variables were having an impact on the performance of their ad budgets.

All this meant that when it came time to run a larger campaign, Hopkins could leverage the top performers from the test campaigns, provide data about costs, and advise more accurately on KPIs.

The Results:

When Hopkins explained test campaigns in his book, he said, “Now we let the thousands decide what the millions will do. We make a small venture, and watch cost and result. When we learn what a thousand customers cost, we know almost exactly what a million will cost. When we learn what they buy, we know what a million will buy.”

When Hopkins was creating test campaigns in the late 1800s and early 1900s, it effectively achieved a few key goals:

🤔removed guesswork

📝identified effective headlines and offers

📈revealed cost-per-customer

🫰clarified sale-per-customer

Of course, the ad landscape is much more complicated today than it was back then but the core methodology of test campaigns still has practical applications. There are plenty of advertisers who still send coupons via snail mail. And even those who don’t can benefit from the concept of AB testing.

Whether you’re testing a call-to-action or ad imagery, it helps achieve similar goals about what’s working and what isn’t.

The Takeaways:

It’s difficult to even quantify how much has changed in the world since Claude Hopkins made his mark on the ad industry. But his test campaign insights can be applied in the modern landscape in many ways.

Here are a few:

1. Measure twice, cut once

As Hopkins exemplified, our tests are only as valuable as our ability to quantify them. Ensuring you have the proper data tracking in place is vital to the integrity of your tests.

Make sure to do a few rounds of quality assurance with your developers for any digital testing, so that technology like Google Analytics and other tools are set up correctly.

2. Experiment design is everything

While measurement helps you determine if a test is successful, Scientific Advertising teaches us that just like in the laboratory, having a sound testing structure with both a test and control group, makes for conclusive results.

3. Testing is channel agnostic

Whether it be direct mail in Hopkins case or perhaps Facebook advertising in yours, A/B testing or other scientific forms of measurement can and should be employed to help you achieve repeatable results.

As your team explores new channels and opportunities for testing, setting up test and control audiences for your new marketing initiatives will help you reach success faster.

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