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Key Advantages of Advanced Cellular Frame (ACF) Over Traditional RDD

In a previous blog we introduced you to one of Marketing Systems Group’s newer products, Advanced Cellular Frame (ACF). This time, we will discuss how the frame is compiled and the key advantages it brings you compared to traditional RDD by itself.

Let’s start with a few key facts. When we do a traditional RDD sample of a county or group of counties, the telephone numbers within that frame are defined using rate center geography. The RDD frame has zero bearing on your ability to place numbers geographically outside of a rate center geography. It’s just not built for that capability.

With ACF, we have a better ability to actually place numbers within the correct geography, because we have more known information about more of the numbers (approximately 45% of them).  

The Power of Split Frames

ACF can split an RDD frame into two pieces:

  • The listed / matched phone numbers we have information about for a particular geography
  • Everybody else, including unlisted / unmatched

The listed component we can put precisely within whatever target geography you’re doing, if it’s a ZIP Code, county or a CBSA.

The unlisted or unmatched numbers get pulled in using the old traditional rate center methodology, but we pull only the unlisted ones. All listed and matched numbers are excluded from this component.  

A County-level Example

To illustrate how this all works, check out our Coffee Quip videos, specifically episode #3 featuring Subject Matter Expert David Malarek. There you will see him explain a case involving Multnomah County Oregon, home to the city of Portland.

The ACF frame does a better job targeting an RDD sample within Multnomah county. Dave shows how you can take the listed and unlisted portions and create a split frame, in which you can sample the listed’s independent of the unlisted’s or unmatched.

The ACF RDD universe is about 1.5 million numbers. About one-third of them are listed. We know they are in Multnomah county. The balance of the records (993,000) are coming from the rate centers that best fit Multnomah county geography.

But remember, rate center geography does NOT conform to any census geography we are accustomed to. It doesn’t conform to counties or city boundaries. Rate center geography is really just based on where the telephone companies run their wire lines.

This means you will have some over coverage and some under coverage, because you could miss a spot within the county or flow into adjacent counties outside the county.

With a split frame, you get the two components of ACF RDD that best fit Multnomah county.

How We Address the Migration Problem with ACF

Now we hit the biggest advantage of ACF: how it addresses migration — people who have a cell phone in one part of the country then move to another part of the country but keep the old cell number tied to the old rate center geography.

For the “known” listed cellular telephone numbers, ACF allows us to identify people who have migrated from other parts of the country into Multnomah County, Oregon. Conversely, we can exclude from the frame everybody who moved out of Multnomah County.

If you had defined the frame by rate center and just did a traditional cellular RDD sample, a huge chunk of those listed numbers would actually be outside the county. And you would be excluding 27% of the numbers inside Multnomah county from your sample frame. Not good.

Simply put, ACF does a better job in terms of getting the people who really live in your target geography into the sample frame and leaving out the people who’ve left.  

What About Lower-level Geographies?

ACF is great for smaller geographies, especially city limits not easily defined by rate center, which tend to be fairly large. Rate centers might serve four or five dozen different communities; whereas with ACF (at least for the listed portion) you can pinpoint a town or city you want to sample and exclude the other towns around it.

You can see why we are so excited about Advanced Cellular Frame; it enriches the sample and empowers you to target smaller geographies with more precision.

For more details, check out Coffee Quip episode #3, with Subject Matter Expert David Malarek or click here.