After a period of rapid growth online research has entered a period where concerns about data quality have led to widespread questioning of its validity. As a consequence, clients increasingly seek assurances that the results we produce with online studies are reliable enough to use as the basis for important business decisions. This paper considers panel data quality issue from the client's perspective and suggests a limited set of issues for clients to consider as part of a fit-for-purpose test for online. These extend beyond the usual concerns about panel recruitment and management practices. They include the interplay between the research topic and Internet penetration, the potential for mode effects, and the evaluation of online results in the broader context of other sources of industry, business, and marketing information.
After the rapid and widespread emergence of online access panels, we are currently witnessing a new trend towards online custom panels that are specifically built, used and managed for research purposes of one company or its brand(s). This study compares the online access panel 'XL Online Panels' with a dedicated and branded online research panel from Heinz, generating conclusions on the relative advantages and disadvantages related to using either of them. Specific attention is paid to panel member conditioning (broadly defined as changes in response patterns over time due to learning) and quality. Differences in conditioning and quality in the Heinz and control panel are highlighted and the implications for online market research and panel management are discussed.
With the growth of Internet-enabled mobile devices (mobile phones), online surveys can be carried out regardless of location or access times. This study will give an insight into the extent to which it is possible to achieve a faster response by using Internet-enabled mobile devices for market research and whether this does have a positive effect on the quality of the results. In addition, the study will also provide an overview of which research issues are best suited to the use of mobile data collection in terms of the technological possibilities and differences between the various mobile devices.
It is time to rethink the traditional panel business model (from completes to Cost per View / Cost per Lead) and look at value we can add for clients at higher levels. Developing proprietary panels of users by leveraging in-house competencies on community building and combining them with state-of the art information elicitation techniques (also known as Intuitive Response Systems or IRS) enables clients to improve their bottom line. We will illustrate this with a case study on improving Vodafone's employer branding while boosting hard recruitment response.
Online panels provide researchers with a range of tools for obtaining customer feedback in a time-sensitive and economical manner. The success of the panel comes, in large part, from the commitment of the client and supplier team to closely monitor the panel, respect panel members, constantly improve the website to keep members engaged, and be responsive to business needs. To illustrate a panel's key benefits of timeliness, affordability, and actionability, we will describe in the Business Needs session a case study from the dual perspective of client and supplier. Owned by The Parenting Group (a division of Bonnier Corporation) and managed by RSG Inc., MomConnection is a thriving panel community of over 5,000 mothers and soon-to-be-mothers of young children. We will show how The Parenting Group has successfully leveraged MomConnection to support editorial planning and add value to its advertising programs. Now in its sixth year, the panel reflects rich data from more than 200 surveys and enables quick-turnaround yet advanced research capabilities such as ad/concept testing, product testing, and brand positioning.
This methodological case study illustrates differences in data quality resulting from different online panel recruitment methods. Survey data from two B2B online panels were compared to each other and to data collected from a phone-to-Web sample. One of the online panels was developed via targeted solicitations to B2B Web sites (similar to the non-probability sampling most seen in use today), whereas the other was an ongoing online panel that had been originally recruited by telephone using probabilistic sampling. Many of the problems attributed to online panels (such as "straightlining" or "flatlining") were markedly reduced in the online panel using telephone recruitment with probabilistic sampling, and data from that panel were more robust in statistical analyses. We use this case study to illustrate these differences, and present guidelines for building panels that produce high quality data.