Purpose of the Document
To create a high-level document that explains Geopath’s R/F methodology, what those metrics do, and how they’re useful in day-to-day selling and buying.
Target Audience
The average Insights Suite user/Geopath member - someone who is not necessarily a “power user” and needs good talking points for selling and understanding reports.
Specific Examples and Use-cases to show change
High reach for single units
Reach for street furniture in large markets showing low reach
example from Nolan Panno
...
Reach and Frequency are powerful metrics for understanding the impact of an OOH campaign. This document provides a brief guide on:
The importance of Reach & Frequency within a campaign
How Geopath validates our Reach and Frequency approach
What are Reach and Frequency?
When someone is looking to measure a campaign’s effectiveness at reaching their target audience, some helpful metrics to do this are Reach and Frequency. Reach is the percent of your target audience that has seen your campaign, and Frequency is the average number of times the ad was seen over the course of your campaign by the target audience. Reach Net is the unique number of people who have seen your campaign. Reach and Frequency occur in an inverse relationship to each other at a constant TRP level. Within such a campaign, as Reach goes up, Frequency goes down, and vice versa.
Simply put, Reach x Frequency = TRPs.
How Geopath Estimates Reach and Frequency
To start, we utilize rich neighborhood profiles to understand the demographics and behaviors of people across the country. In the past, Geopath’s Reach & Frequency approach was built around highly aggregated, anonymous carrier data. This mobile data was used to determine average frequency and understand general home locations, which allowed us to look at the footprint of audiences in different markets. However, there was no device-level data available to us at the time for validation of the approach. This lead to outputs from the existing methods that were misaligned for some packages of inventory, where higher package-level Reach across the market should have been reported.
Using observed movement data from a panel of mobile devices, today we are able to more specifically understand the trips that people take throughout a market – the purpose, the distance, the approximate route, and more. The observed device-level movement data is then matched to actual roadways in the market – this allows us to understand more precise pathways that people take and the frequency of those trips.
Once we have validated the routes, and the counts of people on those roadways, we factor in visibility information to understand the likelihood that an ad was seen.
How did Geopath previously estimate reach and frequency and why was there a need for an improved method?
How
Limitations
What is fundamentally different in the new approach?
Existing: used mobile data to determine average frequency and home location (highly aggregate)
Improved: uses observed mobile trip data at the device level and can cross examine various scenarios at the unit and package level for validation
Include an Example
Validating Reach and Frequency (why is it correct)
Why is this new methodology valid?
reach and frequency validation over time (seasonality, 2019 vs 2020 vs 2021)
How is this more valid than the past methodology?
We validate this trips volumes with actual vehicular traffic counts on roadways and foot traffic at points of interestcross-examine many scenarios at the unit and package level. The results are more accurate and in line with observed data, which may result in lower Reach percentages than what was seen in the legacy measurement.
Validating Reach and Frequency (Why is the approach correct?)
We first make sure that the panel of mobile devices is a representative sample for determining home location and trips, by observing the mobile signal and rest patterns. Roughly 83k devices observed over the 50 day period qualified for frequency analysis in Los Angeles. From there, we compare the observed mobile data with traffic counts on particular roadways from different DOTs, and live traffic counts. At this stage, we know there is a high level of alignment between the mobile data and the DOT data. Additional information on the methodology and validation can be found here.
Once we are confident in the trip volume, and that we’re able to observe a device over time, we are therefore able to evaluate the frequency of trips over time as devices pass by OOH inventory. Knowing that the panel of devices is representative of the movement in the market, we can then conduct Reach and Frequency analysis based around this. Device-level data allow us understand Reach and Frequency more closely, as we’re able to understand duplication and model at the device and inventory level.
Key Takeaways (considerations for the industry)
How does this new methodology fit into omni channel/ cross media strategies
What is the impact on considering OOH in MMM
Mark Costa what’s actually being done for RF in other channels?
What should users expect to see upon release of this new R&F?
Though impressions are OOH’s most core measurement metric, including Reach and Frequency allow for a deeper understanding of the impact of a campaign. Utilizing campaigns with high Reach can allow you to effectively get your message spread widely throughout a market among your target audience. Frequency can be well utilized for campaigns that benefit from repeat exposures, like for a newly introduced or seasonal productGeopath’s revised Reach & Frequency approach provides optionality for media planners that has been previously unavailable in the OOH ecosystem. This revised model allows planners to optimize for a reach percent of a target audience, or optimize for frequency of exposing their message.
These improved methods allow for a greater level of precision and accuracy in our ratings that reflect the true audience delivery. For example, higher frequency can now be observed when spots in a package are clustered in a localized area, and higher reach can be observed in a package of more widely-dispersed spots.