14th February 2024
Relationship Driven Data Specialists
Exploring Mobile RDD: Expanding Reach in Telephone Sampling
Up next in our series of introductory blogs is a brief overview of our Landline RDD sister product: Mobile RDD. As the name suggests, it also involves randomly generated telephone numbers—only this time, they’re for mobile phones.
As of 2020, the percentage of UK households with a working landline dropped to 73% (Statista, August 2022 – source). Additionally, the age demographic of landline users has skewed towards older age groups, meaning that standard Landline RDD severely limits the reach to younger people in any RDD sample. Listed consumer data has traditionally been the fallback option in this scenario, offering the ability to target younger audiences directly on their mobile phones. However, even this approach has started to face challenges, as the availability of younger respondents (specifically 18–24-year-olds) on marketing databases dwindles each year. This is where Mobile RDD steps in.
In today’s world, it’s almost a given that young people have mobile phones. In fact, 98% of those aged 16 to 24 owned a smartphone as of 2023 (Uswitch UK Mobile Phone Statistics 2024 – source), making Mobile RDD an ideal way to reach them for nationwide telephone research projects (more on why it’s particularly suited for nationwide projects below).
Yes and no. The basic premise is the same, but there are differences in the specifics. For Landline RDD, the area’s dialling code provides the foundation (or “stem”) from which we generate the rest of the number. In Mobile RDD, however, we use the network prefix as the stem—e.g., 07000 1 for Vodafone. Similar to Landline RDD, we start with the first 5-8 digits, then randomise the remaining numbers. Finally, we clean the generated numbers using a process known as an HLR (Home Location Register) lookup.
An HLR lookup is a service that verifies the status of a mobile number. It checks if the number is active, switched on, and identifies the network it’s assigned to. It also provides information about the operator and network associated with the number. These checks are performed in real-time, providing an up-to-the-minute status report on each mobile phone number. For a more in-depth explanation, you can read a full white paper on HLR Lookups [here].
Unfortunately not! Because of how mobile numbers are assigned in the UK, it’s impossible to generate Mobile RDD with geographic specificity. During the cleaning process, the only geographic indicator available is the country of origin for each number. It isn’t possible to achieve a more targeted geographic sample.
For nationwide representativeness, we generate Mobile RDD based on network share, which provides broad coverage across all networks. This approach, in theory, results in a balanced sample across ages and geographic areas.
Yes, we believe we can. With our expertise in marketing data, particularly mobile numbers, we’ve developed techniques to increase the likelihood of including younger people within our Mobile RDD sample. Our clients have verified these methods in real-world applications.
For more detailed information, or to explore how our Mobile RDD can support your research projects, we’d love to set up a call to discuss your needs in more detail. Simply reach out to a member of our team via our Contact Us page.
We love data, but we love our clients more! Being part of their team, meeting their needs no matter how challenging and solving their data problems is fundamental to who we are and why we are here.
