SAMPLE SOLUTIONSCHOICE OF SAMPLING LANDLINE VS MOBILE
IntroductionDual Frame ApproachDual Frame Approach refers to the methodology of combining landline and cell phone numbersi...
Some Mobile MythsOn first glance, it seems to be more expensive to use mobile sample for callingrather than landline sampl...
Get the whole picture!When looking at Ireland, initially one would estimate that in terms of landlinepenetration (43%), it...
What to choose ?As a result the landline penetration per numbering block (eg. 1000) has beenfallen drastically and thus le...
Provider lookupsFurthermore in rural areas (were mobile communication was not fully estab-lished), landline penetration wa...
Summing upThis enables to call mobile phone numbers which have been active and switchedon within the last 24 hours, leadin...
RDD LANDLINE SAMPLEEfficient, Representative and Cost-EfficientRandom Digit Dialing, commonly known as RDD, is a very cost...
RDD MOBILE SAMPLEDo not miss the trend towards towards a mobile populationOur Mobile RDD sample is aligned with the provid...
Get in touch !Request some Trial Sample or ask for consultancyAt Sample Solutions we value long time relationships with ou...
SAMPLE SOLUTIONSSample Solutions Europe  Groothandelsgebouw    3013 AP Rotterdam        Netherlands   Tel: +31 88 1267800i...
RDD Dual frame approach by Sample Solutions
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RDD Dual frame approach by Sample Solutions

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Dual Frame Approach refers to the methodology of combining landline and cell phone numbers in order to account for the different mobile/landline penetration within a certain sampling frame. Several methods do exist on how to actually use the framework, e.g. How to handle households that own both landline and mobile telephones. Nevertheless, there are enough reasons to actually avoid landline numbers and use mobile only, or a dual-frame approach

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RDD Dual frame approach by Sample Solutions

  1. 1. SAMPLE SOLUTIONSCHOICE OF SAMPLING LANDLINE VS MOBILE
  2. 2. IntroductionDual Frame ApproachDual Frame Approach refers to the methodology of combining landline and cell phone numbersin order to account for the different mobile/landline penetration within a certain sampling frame.Several methods do exist on how to actually use the framework, e.g. How to handle householdsthat own both landline and mobile telephones. Nevertheless, there are enough reasons to actuallyavoid landline numbers and use mobile only, or a dual-frame approachWhen what to use ?When clients think of targeting a population within an emerging market, we often receive RFQ´s forlandline numbers since the main advantage seems to be the possibility of geographic tracking, thuswhere a person is located. However in some market, the advantages for mobile sample outweighits disadvantage. This paper will analyze when what to use.About Sample SolutionsSample Solutions Europe is the premier global provider of sampling solutions for survey research.SAMPLE SOLUTIONS EUROPE offers access to more than 50 million business-to-business recordsfor market research and can deliver RDD sample for over 25 markets. Sample Solutions Europe wasestablished by a group of people with decades of experience in the (telephonic) research indus-try. The lack of local sampling knowledge from the main players in the sample industry (for RDDsampling), and the lack of details when providing B2B sample, led to the establishment of SampleSolutions Europe. We aim to provide better, and more detailed, sample, being it RDD or B2B, thanany other multi-market sample provider out there, at the best price-quality ratio possible. Thisphilosophy has lead to more and more clients from the international research industry finding theirway to Sample Solution Europe for their phone samples.01
  3. 3. Some Mobile MythsOn first glance, it seems to be more expensive to use mobile sample for callingrather than landline sample. Calling mobile phones is often more expensive thancalling landlines. Also, it takes roughly 6 times more (working) mobile numbersto reach the same target interviews, compared to mobile numbers. Lastly, thetargeting by region is not always possible, making it difficult to fill regional quo-tas, especially towards the end of a study. “Mobile phone numbers are more costly and harder to reach, so why use mobile?”Before deciding on the sample it is essential to first conduct a small research onattributes of the target population. These factors are the local population data,mobile penetration, landline penetration and geographic circumstances. A goodstart is the CIA Worldfactbook which provides most of this data, an overview oflandline and mobile penetration is provided in Appendix A. Based upon the pen-etration data for landline and mobile, an informed decision can be made whatsource to use. Also a small excursion to numbering frames is needed.02
  4. 4. Get the whole picture!When looking at Ireland, initially one would estimate that in terms of landlinepenetration (43%), it seems reasonable to conduct a study with landline numbersonly from a practical point of view (methodological is a whole other story, whichwe won’t go into within this paper). However as a result of the deregulation ofthe telecommunication sector in Ireland, the main provider Eircom has first ofall seen a decrease of landline penetration from 82% to 69% and the trend willcontinue. Furthermore many landline users changed to different providers whichhave different numbering blocks allocated. Figure 1: Mobile and Landline Penetration for several sample countries03
  5. 5. What to choose ?As a result the landline penetration per numbering block (eg. 1000) has beenfallen drastically and thus leads to a high percentage of dead (abandoned) num-bers. Thus for call-centers not making use of predictive dialers it would be rec-ommended to use mobile sample instead of landline numbers._______________________________________________________________ “There is no exact mathematical equation which indicates preference for landline or mobile sample.”_______________________________________________________________This is due to the fact that when using auto-dialer or power dialer, a lot of callingtime is used for dialing numbers in a row, thus waiting for working numbers toappear. With a predictive dialer several numbers are dialed in parallel thus sig-nificantly reducing the waiting time for agents.CASE STUDY MALAYSIA – REGIONAL DIFFERENCESAnother parameter which is important, is regional differences within a country.Taking Malaysia as an example: initially we provided landline sample as request-ed by the client. During the project however it turned out that in some regionslandline numbers were working well, while in others it was almost impossible touse landlines. What were the reasons for this?After a thorough analysis, it turned out that within urban areas many landlineconnections were in fact used for internet connections, and thus yielding a highnumber of non-working numbers which could not be identified by pre-screen-ing. sented areas is then enabled to ensure a representative geographical spread.04
  6. 6. Provider lookupsFurthermore in rural areas (were mobile communication was not fully estab-lished), landline penetration was significantly higher. The last factor is that manylandline users within the rural areas actually abandoned the landline numbersand thus further decreased the landline penetration, which further reduced theamount the landline penetration in rural areas. In order to overcome these prob-lems, it was decided to call on large scale with mobile phone numbers onlymaking use of a new technique called provider query lookup. This ensured ahigh working rate of mobile phone numbers. Towards the end of a study whenquotas need to be filled, the landline sample for underrepresented areas is thenenabled to ensure a representative geographical spread.MOBILE VERSUS LANDLINE SCREENINGSince RDD sample is randomly generated, there is always a large percentageof dead numbers. Due to the different numbering block density, the fraction ofdead numbers varies. This is why the raw RDD sample is pulsed: in many WesternCountries, the filtering rate is between 30% and 50% (i.e. 30-50% of the num-bers are screened out as non-working), thus leading to more effective landlinesample. However raw mobile phone pulsing only results in around 10% filteringout of non-working numbers, this is why a provider lookup is used. The providerlookup query indicates the following: 1. Is the SIM-card activated? 3. Is the phone switched on? 2. Is the number roaming? 4. Which provider is it?05
  7. 7. Summing upThis enables to call mobile phone numbers which have been active and switchedon within the last 24 hours, leading to more efficient mobile sample to dial on.This is why in many South-East Asian countries, it is preferred to call mobilesample rather than landline sample since the screening rate is a lot higher withmobile numbers, compared to landline. Another factor is that the telephonycosts per minute are almost the same for landlines and mobiles, as opposed toWestern Europe.Conclusion on SamplingThere are several conclusions that we can draw from this paper. It is importantto take several factors into account before targeting a population:- Dialing costs (landline vs. mobile), especially for longer interviews- Landline vs. Mobile penetration rate- Regional differences- Numbering block penetration- Target population (age, gender etc.)- Screening EffectivenessObviously not all these factors are evident straight from a simple lookup. How-ever we are there to help you out with any questions you have.For any questions or enquiries it is possible to contact us via info@samplesolu-tions.eu or me directly via carsten.broich@samplesolutions.eu06
  8. 8. RDD LANDLINE SAMPLEEfficient, Representative and Cost-EfficientRandom Digit Dialing, commonly known as RDD, is a very cost effective method for generating arepresentative sample of households with fixed telephones. It is especially useful when No provisionfor targeting within specific population groups is needed for example: Gender, income, geograph-ical location or religion. Sample Solutions Europe has developed a highly accurate RDD procedurewhile maintaining the representative proportion of the corresponding populations. Some facts about our RDD Sample Fastest turnaround: Covering 30 >95 minutes, when using our online ordering program. countries worldwide Up to 40 Sample variables 07
  9. 9. RDD MOBILE SAMPLEDo not miss the trend towards towards a mobile populationOur Mobile RDD sample is aligned with the provider share of each country, thus still providing arepresentative spread of the target population. Furthermore it is possible via a provider lookup totrach changes of the mobile provider. Our mobile RDD sample can be enriched with geodata usinga postcode linkage thus allowing geographic properties.Facts about our mobile RDD sample Listed RDD for Mobiles are 3 months 65.000.000 Households wordwide, ensuring perfectly targeted cleared respondents. Available in 95 Countries worldwide08
  10. 10. Get in touch !Request some Trial Sample or ask for consultancyAt Sample Solutions we value long time relationships with our cleints. This is why we provide con-sultancy on offline sampling and list features without any charge.SAMPLE SOLUTIONS EUROPE offers access to more than 50 million business-to-business recordsfor market research and can deliver RDD sample for over 25 markets. Sample Solutions Europe wasestablished by a group of people with decades of experience in the (telephonic) research indus-try. The lack of local sampling knowledge from the main players in the sample industry (for RDDsampling), and the lack of details when providing B2B sample, led to the establishment of SampleSolutions Europe.We aim to provide better, and more detailed, sample, being it RDD or B2B, than any othermulti-market sample provider out there, at the best price-quality ratio possible. This philosophy haslead to more and more clients from the international research industry finding their way to SampleSolution Europe for their phone samples.Contact: info@samplesolutions.eu 09
  11. 11. SAMPLE SOLUTIONSSample Solutions Europe Groothandelsgebouw 3013 AP Rotterdam Netherlands Tel: +31 88 1267800info@samplesolutions.eu

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