RDD Sampling for Social Research

On the map below, by simply clicking on the country you are interested in
you can see the suggested cell and landline split which is based on
phone coverage statistics, calculated frame size and experience from previous projects.

Worldwide Social Sampling Cell and Landline Data

Hard to reach audience using SMS

Using an onomastic approach, by blending RDD with list assisted and social media data in order to target certain low incidence audiences within Developed countries

World Poll Gallup

The Gallup World Poll tracks the most important issues worldwide, such as food access, employment, leadership performance, and well-being. Studies were conducted in more than 160 countries that include 99% of the world’s adult population.

SMS Data Collection Sub-Saharan Africa

An experiment conducted together with Gallup that compared SMS data collection with Face-to-face data collection in order to outline mod differences between SMS and Face-to-face.


Tracking American consumer habits on a monthly basis, using a National representative Mobile sample for the entire Mainland US

Countries in Turmoil: Libya & Ukraine

During outbreaks of civil uprisings or wars, it is difficult to collect data face-to-face or online. CATI, however, remains a great way of collecting data for which we provided sampling frames for Libya and Ukraine.

Pew Global Attitude Study

Mobile Sample icon

13,156,055 – RDD phone numbers sold in 2020

174 – In 2020 we provided Sample for 174 countries worldwide

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366 social sampling projects in 2020



In order to generate a Sample that represents the whole population of a country, a dual frame method is used which consists of a combination of cell and landline numbers. This approach is used in telephone surveys for many European countries in order to achieve as high coverage as possible.

However, in most of the developing countries due to the high cost of connecting houses to phone lines, the popularity of cell phones is increasing and there is a wider cellular phone network. In cases like this, we advise clients to use 100% mobile Sample in order to achieve their targets.



Stratified random sampling is a method of sampling that involves the division of a population into smaller sub-groups known as strata. It allows researchers to obtain a sample population that best represents the entire population being studied.

How can Sample Solutions contribute to improving the RDD Sample efficiency?

– Pulsing phone numbers in order to remove the inactive ones
– Screening against business phone numbers

At Sample Solutions we provide stratified sampling for both landline and cell numbers.

RDD Landline Sample stratification

RDD Landline Sample can be stratified based on a country’s various non-geographical strata (network operators) or geographical strata (administrative divisions, geographical regions, Census regions, NUTS regions, etc.), with equal probability of selection within each strata. If the stratification is based on a geographical stratum, the sample is constructed based on the population’s distribution within the strata. Each possible telephone number per stratum is generated and stored together with an incremental id.

RDD Cell Phone Number stratification

RDD Cell Phone numbers can be stratified by provider or provider’s market share.

telephone-sampling process






Simple Random Sampling; randomly selecting a subset of a statistical population in which each member of the subset has an equal probability of being chosen.

Yes, we provide more than 174 countries with mobile and landline RDD Sample covering all continents.

We provide detailed population demographics for all countries, including frame size information and preferred telephone sampling methodology. You can request them by clicking here.

Stratified samples offer a possibility of representative coverage, thus smaller coverage error. With stratified samples, every small region will be included in the sampling, which is not the case with simple random samples where smaller regions might or might not be included.

The expected non working rate is usually less than 15%. Therefore we always provide additional 10% oversampling in order to cover for the possible non working numbers.

We screen all numbers from the telephone frame and then exclude the disconnected numbers from the sample.

Yes, we can provide smaller subsets of the sample that has the same or similar characteristics as the initial sample.

Depending on the volumes and specifications, the default turnaround time for RDD Sample is 2 to 3 working days.