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Strategies for Increasing Online Survey Participation
1. STRATEGIES FOR INCREASING
ONLINE SURVEY PARTICIPATION
M. FOSTER, A. WARNER AND A. FROMAN
Supported by: Federal Economic Development Agency for Southern Ontario (FED
DEV Ontario) Applied Research and Commercialization Initiative
2. OBJECTIVES OF THE PROJECT
• Overall goal:
• To identify strategies for encouraging
online survey participation
• Research questions:
• Existence of segments?
• Characteristics?
• Motivational differences?
• Effective strategies?
3. THEORETICAL FRAMEWORK -
MOTIVATION
• Knowledge sharing
• Trust in virtual community
• Trust in sponsor
• Ability/self-efficacy
• Reciprocity – virtual community
• Reciprocity – sponsor
• Altruism
• Social interaction
• Privacy
4. THEORETICAL FRAMEWORK -
SEGMENTATION
High Information Low Information
High Interaction SMT Mavens Socializers
Low Interaction
Info Seekers Minimally
Involved
6. FACTOR ANALYSIS LOADINGS
Creating Socializing InfoSeeking
Statement α=.840 α=.823 α=.752
Q2_11: Posting content to content sharing sites such as .812
Tumblr, Digg, Reddit, Technorati or YouTube.
Q2_8: Publishing or updating your personal webpage .770
(excluding social networking sites).
Q2_4: Posting to a micro-blogging service such as .745
Twitter.
Q2_1: Writing articles or blogs to post online for others to .722
read and comment on.
Q2_2: Visiting social networking sites, such as .894
Facebook, LinkedIn or MySpace.
Q2_7: Maintaining/updating your profile on a social .754
networking site.
Q2_6: Posting comments to someone else’s social .746
networking page/account.
Q2_12: Reading customer ratings and/or .837
product/service reviews.
Q2_13: Using a search engine to find information prior to .801
a product or service purchase.
Q2_3: Reading online forums, blogs and discussion .632
groups written by others.
8. SMUG SEGMENTS
High Information Low Information
High Interaction SMT Mavens Socializers
(7%) (26%)
Low Interaction Info Seekers Minimally
(18%) Involved
(49%)
9. MEAN MOTIVATIONAL CONSTRUCT
SCORE BY SMUG SEGMENT (P<.000)
Motivational Construct SMT Info Minimally Socializ Total
(The lower, the more the Mavens Seekers Involved ers (n=1501)
construct describes the (n=103) (n=273) (n=730) (n=395)
respondent)
Knowledge Sharing 6.8 7.6 11.3 9.1 9.8
Trust in Virtual Community 7.4 8.9 11.4 9.6 10.2
Trust in Sponsor 6.5 6.4 9.2 7.5 8.0
Ability/Knowledge 6.3 7.6 10.1 8.9 9.5
Sharing Self-Efficacy
Reciprocity Virtual 6.5 7.9 11.6 9.0 9.9
Community
Reciprocity Sponsor 6.2 7.1 10.0 8.2 8.7
Altruism 6.4 7.3 10.0 8.2 8.8
Social Interaction 9.3 11.7 15.6 13.3 13.9
Privacy 9.6 10.3 11.9 10.7 11.1
10. MOTIVATIONAL CONSTRUCT
DESCRIBES ME WELL OR SOMEWHAT
Describes me Well or Somewhat
No. of
Motivational Construct Statements Mean % Mean % Mean %
Total SMT Mavens Info Seekers
Sample (n=103) (n=273)
(n=1501)
Knowledge Sharing 3 35 63 56
Trust in Virtual Community 3 27 53 40
Trust in Sponsor 3 57 66 72
Ability/Knowledge Sharing Self- 3 34 69 53
Efficacy
Reciprocity Virtual Community 3 30 66 51
Reciprocity Sponsor 3 54 72 71
Altruism 3 41 67 58
Social Interaction 4 22 59 36
Privacy 4 53 60 57
11. STRATEGIES EFFECTIVE FOR ALL SMUG
SEGMENTS (30%+ MORE LIKELY TO SHARE OPINIONS –
STRONGLY OR SOMEWHAT)
Information about how the sponsor of the online
community protects the personal information of
its members is prominently displayed.
Members can earn points toward rewards for the
quality of their contributions to their online
community
The online community enforces a code of
conduct.
12. ADDITIONAL STRATEGIES EFFECTIVE FOR
INFO SEEKERS (30%+ MORE LIKELY TO SHARE
OPINIONS – STRONGLY OR SOMEWHAT)
Members can spend their reward points to access information on topics of
interest that are not available to the general membership.
The online community provides tips about how to make your contribution
meaningful (e.g. Structure, choice of words).
The online community allows members with like-minded interests to contact
each other.
Members have the ability to rate the contribution of others on a specific
topic (e.g. A star system).
Sponsor recognizes outstanding contributions online for the whole
community
Members are not limited to written posts to share their opinions, but can post
pictures, videos, etc.
Members have the choice as to whether they reveal their true identity or use
an avatar.
The project was a joint endeavour between Ryerson University and Delvinia. It was supported by a government grant that supports partnerships whose purpose is to gain insight into business problems to improve business outcomes.
This project focuses on how to improve online survey participation. As more marketing research is taking place in the online space, this is an increasingly pertinent question for the industry.Specifically this study seeks to answer the following:Can we group online survey participants into meaningful segments? 2. If segments do exist, what are the general characteristics?3. More specifically, do the segments differ in motivations to participate in online surveys?4. Finally, what strategies will be effective in enhancing online participation in survey research, in general and for specific segments?
Using the literature on knowledge sharing, we identified the following as motivations that have relevance for online survey participation:Knowledge sharing – this includes the desire to read information posted by others and to share their own information with the online community.Trust in virtual community – this relates to trusting the information provided by members in the online community, as evidenced by sharing online information.Trust in sponsor – this relates to being motivated to share if they know and trust the company and/or product/service being asked about.Ability/self-efficacy – this relates to being motivated to share because they believe their opinions/information are important and that they are comfortable expressing themselves in writingReciprocity- virtual community – this relates to being motivated when others in the online community respond to their posts and/or engaging in an online discussionReciprocity – sponsor – this refers to receiving an incentive from the sponsor when opinions are given and/or when the participant knows how his/her feedback affected decision-making.Altruism – this refers to sharing opinions without the expectation of anything in return, just the satisfaction of helping othersSocial interaction – this refers to being motivated by the ability to interact directly with others in the online community and/or the sponsor, and exchange information with those with similar interests.Privacy – this refers being assured that personal information is protected in online interactions.
Two previous studies with large samples of 1000+ have been conducted with young adults 18 to 30 trying to identify if segments exist within the social media users. These studies used both activities undertaken and the frequency of participation. Four distinct segments emerged each with a different combination of activities that relate to interaction and information in social media spaces. This study used the same framework to conceptualize social media user groups, albeit with a sample with a much broader geographical distribution and age range.
Sample:1501 chosen from the 160,000 “Asking Canadians” panel that is maintained by the industry partnerRespondents were representative according to the Statistics Canada on regional distribution, age and genderInstrument: Three components of the survey instrumentMotivational constructs were adapted from previous research – a series of attitudinal questions – describes me/ does not describe me 5 point Likert scaleSegmentation questions adapted from previous research and updated to reflect technological changesStrategies – created by the research team to match motivational constructs
The first part of the analysis focused on identifying segments within social media users. Distinct samples of 750 were used for EFA and CFA. Four indicators were rejected because of cross-loadings. Three first-order constructs were identified: creating, socializing and info-seeking. This table presents the final list of factors that were used to build the model.
This is the final model with a CFI of .950.
Having established three distinct types of online behaviours, we segmented the sample into distinct groups using k-means cluster analysis on the 10 variables identified through the CFA. The results are as follows: SMT Mavens – more likely to be male and an average age of 32 and engage in more types of online activities and applications than other segments.Info-seekers – more likely to be male and an average age of 40Socializers – more likely to be female and an average age of 44Minimally involveds – more likely to be male and an average age of 53These categories are used as the independent variable for the rest of the analysis.
We consolidated the items in each construct (3 or 4 statements) into a single score by creating an additive scale for each segment. The lower the score the more the construct is a motivator for online participation. This table uses ANOVA to compare the mean for each construct by SMUG segment. All differences are statistically significant (p<.000). SMT mavens are the most highly motivated for all constructs, with the Info seekers being the second most likely to be motivated by these constructs, followed by Socializers and Minimally Involveds.
Next we compared the strength of each motivational constructs in terms of whether a majority of respondents identify it as relevant to them. For each construct, we averaged the proportion of respondents who report that the statements associated with that construct describe them well or somewhat. For example, for a construct with three statements, the average is based on six inputs: the proportion of respondents responding either “describes me well” or “describes me somewhat” for each of the three statements. We define an important motivator as one that over 50% of respondents report as describing them.Three motivators emerge for the entire sample:Trust in sponsor – when the survey is associated with a familiar sponsor and one that is revealed to them in advance of participation.Reciprocity sponsor – when respondents receive feedback from the sponsor about the impact of the information provided, and/or when there is a tangible incentive to participate.Privacy – when the respondents’ concerns about the confidentiality or security of responses have been adequately addressed.In addition, the majority of SMT Mavens and Info-Seekers are motivated by:Knowledge sharing – when respondents share opinions to enhance knowledge levels and decision-makingAbility/self-efficacy – when respondents feel they are capable of contributing knowledge.Reciprocity virtual community – when respondents feel they will receive beneficial feedback or responses from their online peersAltruism – when respondents are willing to share without any expectation of return.
Used a 5 point likert scale on likelihood of sharing opinion online.The differences across segments was statistically significant for all options. This table presents the formats and features that are likely to motivate more sharing of opinions across all segments.
Info – seekers also report being more likely to share opinions with the following format and features.
Segments – we were able to identify four distinct segments within the sample group based on type of social media activity and frequency of use. These were consistent with previous research conducted with young adults, suggesting that these are enduring groupings that can be replicated in other research.Characteristics – younger are more active in terms of frequency and types of activities. Females more likely to be socializers. Motivational differences - SMT Mavens and Info seekers report a variety of motivations for participation, compared to socializers and minimally involveds who report fewer motivations for participation. 4. Effective strategies: First, the three top motivations are all within a sponsor’s control and not dependent on peer responses or intrinsic motivators within individuals – sponsors can protect the information provided to them through technical controls, can make their privacy policies prominent and transparent, can provide feedback about how the information is being used for decision-making, and recognize contributions through rewards and incentives.Second, the most effective strategies are linked to the most important motivations. Motivation – trust in sponsor – is related to respondents wanting sponsors to prominently display how they protect and use the opinions provided. Motivation – reciprocity sponsor – is related to respondents wanting to earn points for the quality of their contributions, which can later be used for rewards. Motivation – privacy – is related to enforcing an online code of conduct. 5. Info-seekers may offer most potential for increasing online survey participation because of the number of motivators that are reported as resonating with this segment and the number of strategies that are derived from these motivators that are reported as effective for encouraging more participation. 6. Our industry partner has revised their marketing strategies and positioning to emphasize the three motivations identified and they have increased the number of members in their panel significantly. It is too early to tell if this will also lead to more “quality” participation.