Reach is a crucial metric in advertising and media analysis, representing the unique number of individuals exposed to an advertisement or content. The reach curve illustrates the relationship between the number of content impressions and reach, vital for evaluating the efficacy of advertising campaigns across various platforms, such as TV and websites.
This application employs a methodology outlined in the research paper "Estimating reach curves from one data point", which provides a technique for estimating the entire reach curve using just the total number of GRPs and the total reach. This simplification of the relationship between marginal cost per reach, average cost per impression, and frequency enables advertisers to more accurately determine the cost of an additional reach point, thus facilitating more informed advertising strategy decisions.
To enhance the accuracy of the model, users have the option to specify the 'k' value, which represents frequency. The inclusion of 'k' allows the model to account for the number of times an individual is exposed to the advertisement, providing a more detailed and accurate reach curve estimation.
This reach curve generator tool enables you to estimate the reach curve from a single observation, with the option to input the 'k' value for frequency. When providing one data point, it's recommended to use the highest GRP/Reach combination available. If the specified observations are not feasible for the given frequency, such as an overly optimistic reach, the algorithm will recalibrate to an achievable reach for the given frequency.