Reach and Frequency, Bridging the Gap

MLS measurement formulas strive to achieve a balance of statistics and advertising methodology. Statistics are useful for describing advertising objectively. However, some basic comprehension of the process is necessary in accurately analyzing data (and greater knowledge validates a firm’s competitive advantage). Cost effectiveness and relevancy also are major concerns. To alleviate some of the investment risks, the software applies statistics to current advertising formulas.

Our reach and frequency model is a process.  The software runs data to determine the variance between how reach and frequency individually correlate with ratings and the quantity of ads. By using sample points, we are able to identify basic marketing logic relationships and create a Broadcast model using a Curve Fitting approach. The curves generated by the data help inform us on how frequency and reach change as other variables change.  Lines of best-fit help predict and evaluate reach and frequency measurements. In our TV calculations, we use Nielson Ratings to calculate GRPs. With this information, we are able to use our Curve Fitting approach to estimate the reach and frequency for any TV campaign or media schedule.

Hopefully, this explanation begins to bridge the large gap between many marketers and the numbers they analyze. Only by understanding the process, will measurements help decision makers analyze reach and frequency with much more confidence.  Further posts concerning different media types on our software (i.e. Radio, Outdoor, Publications, and Online) are intended to educate. This grants companies the opportunity of complementing subjective analysis with objectivity when buying advertisement spots.

For additional questions, please email Media Link Software™ Director of R&D: Salil Kalghatgi