Statistical significance
Statistical significance is whether a result from an ad campaign is real enough to trust or just random chance. When you test an ad and get promising numbers, significance helps you know if those numbers mean something or if they could have happened by accident.
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Judging an Ad That's Already Run
The two-week ad slump, and how to tell fatigue from a bad ad.
An ad that runs well and then stalls after a handful of exposures per viewer is usually fatigue, not a flaw in the ad, but they look identical on a dashboard and call for opposite fixes.
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Advertising on a Real Budget
A pre-spend checklist for whether you're ready to advertise at all.
Most small businesses that decide advertising doesn't work never had a fair test: the site wasn't converting, the follow-up was too slow, or they judged results after two weeks and 40 clicks. Check readiness first.
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Judging an Ad That's Already Run
Which ad metrics actually tell you the creative worked.
Most post-campaign numbers grade your targeting and your budget, not your ad, meaning they tell you who saw it and what you paid, not whether the ad itself worked. Here's the short list that actually tells you if the ...
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AI in Advertising, Honestly
Predicting a winner and evaluating an ad are not the same job.
AI can tell you an ad follows patterns that worked before, and it can tell you an ad looks convincing, but neither is the same as telling you it will sell, and mixing up the three is where ad budgets get burned.
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Judging an Ad That's Already Run
What counts as a good click-through rate depends on who's asking.
A dentist and a real estate agent can run equally well-built ads and land 4 percentage points apart on click-through rate (the share of people who see an ad and click it), because the benchmark moves by industry, by y...