In a scenario where there are 20 million users and an advertisement campaign generates 5 million impressions, each user can see the ad at most once. If we randomly select four people, what are the chances that none of them sees the ad? This probability can be calculated using the hypergeometric distribution, which considers the total population, the number of exposed users, and the sample size.
After computation, the probability that none of the four people sees the ad is approximately 31.64%, while the probability of exactly one person seeing the ad is about 42.19%. The difference between these probabilities isn’t as large as you might expect, right? This highlights an important point: it is quite common for a small group to have no exposure to the ad, even when the campaign reaches millions of users.
The reason is straightforward: with 20 million users and only 5 million exposures, the campaign’s reach is limited relative to the total population. For any given individual, the chance of seeing the ad is just 25% (5 million divided by 20 million). When selecting four people randomly, it’s more likely that not all of them belong to the exposed group.
In marketing campaigns like this, it is crucial to understand the statistical nature of exposure. A significant portion of users might not see the ad due to the limited number of impressions relative to the audience size. This does not indicate a failure in the campaign but rather reflects the mathematical reality of impression distribution.
If you need a specific person to see the advertisement, you might want to use fixed placement strategies. For example, purchasing a time slot for a fixed ad position on a particular website or application ensures that the ad is visible during the exposure period. This strategy allows you to ensure that your supervisor or higher manager can see the ad you’ve purchased. Incorporating such an approach into your media strategy can be effective in special situations where targeted exposure is critical.
