An Analysis of Twitter Users vs. Non-Users. An Insight Report Presentation Using DeepProfile Micro-Segmentation January 2014

Transcription

1 An Analysis of Twitter Users vs. Non-Users An Insight Report Presentation Using DeepProfile Micro-Segmentation January 2014

2 CivicScience s DeepProfile Project Goal To compare the key demographic, psychographic, consumer profile and brand preference attributes of people who use Twitter versus people who do not use Twitter. Note: This report was not commissioned or requested by any third-party. This is CivicScience s own analysis. March 2014

3 Question of Interest & Topline Results For this research, CivicScience examined response results to the following question distributed across our polling network: Do you have a Twitter account? Yes No 20% 80% 169,274 total respondents 20% Answered Yes 80% Answered No

4 Basic Demographics: Gender Twitter users are slightly more likely than non-users to be female.

5 Basic Demographics: Age To what broad age group do you belong? No surprise, Twitter users are more likely to be younger, while non-users are more likely to be older.

6 Basic Demographics: Household Income What is your expected annual household income before taxes? Twitter users are slightly more likely to fall at the lowest or highest ends of the income spectrum.

7 Basic Demographics: Education Which of the following is the highest level of education you have attained? Twitter users are more likely to have a bachelor s/associate degree but not more likely to have an advanced degree.

8 Basic Demographics: Parental Status What is your parental status? Twitter users are less likely to have children or grandchildren.

9 Basic Demographics: Urbanicity What type of area do you live in? Twitter users are more likely to live in a city and less likely to live in a rural area.

10 Basic Demographics: Home Ownership What best describes your current residential status? Twitter users are more likely to rent their house/apartment or still live with Mom and Dad.

11 CivicScience DeepProfile Scales: Micro-Segmentation In the following slides, we examine how both groups responded to a number of questions that contribute to eight DeepProfile scales developed at CivicScience Charitable Giving, Discriminating Shopper, Market Maven, Political Engagement, Price Sensitivity, Sports Fan, Tech Savvy and TV Viewing (additional scales available) that aim to highlight how population segments compare to each other according to key metrics. Twitter Users Non-Users

12 Scale: Discriminating Shopper The Discriminating Shopper scale aims to identify the extent to which population segments do research before making purchases, and how easy or difficult they will be to win over. On average, Twitter users are more discriminating when shopping than non-users, placing higher value on brands and using sophisticated techniques to shop effectively. Aggregate Twitter Users 112 Non-Users 91 General Population 100 Individual Attributes

13 Scale: Discriminating Shopper (continued) Individual Attributes Attribute Twitter Users Non-Users Goes to multiple car dealers 39% 41% Always compares prices 48% 49% Not loyal to favorite brands 10% 14% Showrooms across websites 82% 60% Showrooms while in stores 22% 12% Twitter users are more likely than non-users to showroom, consult online reviews before purchases, and research online, but buy in stores. Twitter users are slightly less likely than non-users to compare prices before purchases. Always consults online reviews 36% 23% Researches online, buys in store 84% 68% Visits stores, then buys online 72% 53%

14 Scale: Market Maven The Market Maven scale aims to identify the extent to which population segments adopt new products and brands, and share their opinions with others. Twitter users scored substantially higher on the Market Maven score than non-users and the general population, indicating high rate of early adopters and brand advocates. Aggregate Twitter Users 133 Non-Users 83 General Population 100 Individual Attributes

15 Scale: Market Maven (continued) Individual Attributes Attribute Twitter Users Non-Users Fashion leader 18% 10% Follows fashion trends 54% 33% Tries new products before others 40% 23% Twitter users have higher individual scores for each attribute than non-users. Twitter users are much more likely to follow music trends than non-users. Tells others about new products 65% 44% Follows music trends 57% 30% Writes positive product reviews 68% 43% Writes negative product reviews 52% 43%

16 Scale: Political Engagement The Political Engagement scale aims to identify the extent to which population segments are involved in all levels of politics and civic engagement. On average, Twitter users scored higher on the Political Engagement score than non-users and the general population, though they are less likely to vote regularly. Aggregate Twitter Users 107 Non-Users 97 General Population 100 Individual Attributes

17 Scale: Political Engagement (continued) Individual Attributes Attribute Twitter Users Non-Users Always votes 57% 64% Has made political contributions 45% 40% Reads political websites daily 36% 31% Engaged in politics 70% 63% Twitter users are less likely to always vote, while non-users are more likely to say they always vote. However, Twitter users are more likely to be highlyengaged in civic activity Attends local govt. meetings 17% 13%

18 Scale: Charitable Giving The Charitable Giving scale aims to identify the extent to which population segments consider giving back to various causes to be an important part of their lives and values. On average, Twitter users volunteer and donate to charity more than non-users and slightly more than the general population as a whole. Aggregate Twitter Users 101 Non-Users 92 General Population 100 Individual Attributes

19 Scale: Charitable Giving (continued) Individual Attributes Attribute Twitter Users Non-Users Religious charity donor 50% 58% Arts/culture charity donor 57% 49% Health charity donor 59% 55% Environmental charity donor 48% 41% Educational charity donor 57% 48% Twitter users are more likely than non-users to donate to arts/culture charities, environmental charities, and educational charities. Non-users are more likely to donate to religious charities. Twitter users charitable giving score is very similar to the general population s charitable giving score. Does volunteer work 39% 33%

20 Scale: Sports Fans The Sports Fan scale aims to identify the extent to which population segments are interested in different types of sports. On average, Twitter users are bigger sports fans than non-users and the general population. Aggregate Twitter Users 114 Non-Users 86 General Population 100 Individual Attributes

21 Scale: Sports Fans (continued) Individual Attributes Attribute Twitter Users Non-Users NCAA basketball fan 24% 20% NCAA football fan 31% 28% NFL fan 42% 40% Has played fantasy sports 25% 14% MLB fan 30% 26% Regularly attends sporting events 62% 46% NHL fan 21% 16% Twitter users are more likely than non-users to have played fantasy sports. They are also more likely to regularly attend sporting events and be NHL and NBA fans. Overall, Twitter users are more interested in sports than nonusers. NBA fan 25% 13% Very interested in sports 32% 30%

22 Scale: Tech Savvy The Tech Savvy scale aims to identify the extent to which population segments use their digital devices and are informed and aware of the latest technology available. Twitter users are much more tech savvy than both non-users and the general population. Aggregate Twitter Users 138 Non-Users 78 General Population 100 Individual Attributes

23 Scale: Tech Savvy (continued) Individual Attributes Attribute Twitter Users Non-Users Owns an ereader 37% 23% Reads tech websites regularly 47% 30% Uses multiple media devices at once 54% 20% 'Addicted' to digital devices 71% 43% Owns a smartphone 73% 43% Twitter users are more tech savvy when it comes to all of the individual attributes. The area which Twitter users are much more tech savvy when compared to non-users is using multiple media devices at the same time. Owns a tablet computer 48% 31% Regularly watches TV online 44% 23% Regularly plays video games 31% 20%

24 Scale: TV Viewing The TV Viewing scale aims to identify the extent to which population segments watch various genres of TV and are influenced by what they see on TV. On average, Twitter users scored higher on the TV viewing scale than non-users and the general population. Aggregate Twitter Users 102 Non-Users 94 General Population 100 Individual Attributes

25 Scale: TV Viewing (continued) Individual Attributes Attribute Twitter Users Non-Users Sports Fan 23% 23% Drama Fan 20% 18% Reality Fan 17% 15% Most influenced by ads on TV 41% 58% Travel/Home/Cooking Fan 14% 12% Documentary Fan 10% 8% Twitter users are more likely than non-users to be a fan of all TV genres except for news. Although Twitter users are more likely to be a fan of a variety of TV genres, they are less likely to be influenced by ads they see on TV. Music/Entertainment Fan 34% 23% Sitcom Fan 20% 15% News Fan 30% 35%

26 CivicScience DeepProfile Scales Summary Scale Twitter Users Non-Users General Population Charitable Giving Discriminating Shopper Market Maven Political Engagement Price Sensitivity Sports Fan Tech Savvy TV Viewing When compare to non-users, Twitter users ranked higher on all scales, except for Price Sensitivity. When compared to the general population, Twitter users scored similar scores on the Charitable Giving, Price Sensitivity, and TV Viewing scales.

27 CivicScience DeepProfile Analysis: Other Attributes In addition to the differences in scores on the previously outlined DeepProfile Scales, both groups gave varying responses to a number of key individual questions of interest. The slides that follow cover attributes from the following categories: Entertainment, Media Consumption, Shopping Behavior, and Technology Usage. Twitter Users Non-Users

28 Media Consumption - Music How often do you download music or movies over the Internet? Twitter users are more likely to download music or movies online.

29 Media Consumption Online TV Viewing Do you regularly watch any full television programs online? Twitter users are more likely to watch full TV programs online.

30 Media Consumption Mobile App Usage Do you use location-sharing apps on your mobile device, like Foursquare, Loopt, etc.? Twitter users are much more likely to use location-sharing apps on their mobile phone.

31 Media Consumption Device Usage What type of device do you use most frequently to browse the internet? Twitter users are more likely to use their smartphone, tablet or laptop to browse the internet.

32 Media Consumption Movie Viewing at Home How do you usually watch movies at home? Twitter users are much more likely to stream movies on their computers or gaming consoles.

33 Media Consumption TV Viewing at Home On average, how many hours of TV do you watch each day? All groups watch roughly the same amount of TV each day.

34 Media Consumption Shopping Influence Which of these do you believe has the most influence on what you buy, where you eat, or the movies or TV shows you watch? Twitter fans are most influenced by comments or recommendations they see on social media, while the general population is most influenced by ads they see on TV.

35 Media Consumption Shopping Preference When shopping, what is more important to you: brand or price? Twitter users are slightly more likely to think brand is more important than the general population and non-users.

36 Media Consumption Brand Loyalty How loyal are you to your favorite brands? Brand loyalty is similar among all three groups.

37 CivicScience DeepProfile Analysis: Brands & Issues In the following slides, the DeepProfile compares the likeability of specific brands, TV shows and support for controversial issues among Twitter users and non-users. This allows us to distinguish which brands and issues are more important to Twitter users vs. non-users. Twitter Users Non-Users

38 Over-Indexed Brands Among Twitter Users Select top brands that over-index in popularity among Twitter users compared to non-users. Brand Twitter Users % Non-Users % Difference % Apple ipad 53% 32% 21% Nike clothing 55% 42% 13% Whole Foods 36% 24% 12% Amazon.com 61% 50% 11% Amazon Kindle 34% 23% 11%

39 Over-Indexed Brands Among Non-Users Select top brands that over-index in popularity among Non-users compared to Twitter users. Brand Non-Users % Twitter Users % Difference % Olive Garden 54% 47% 7% Hanes clothing 54% 47% 7% Carhartt 32% 25% 7% Buick 35% 29% 6% Applebee s 47% 43% 4%

40 CivicScience InsightStore Analysis: Brands & Issues Brands/TV Shows/Issues Twitter Users % Non- Users% Difference % Loves/likes Duck Dynasty 28% 35% -7% Loves/likes Cracker Barrel 39% 45% -6% Loves/likes Walmart 45% 47% -2% Loves/likes Target 56% 52% 4% Supports same-sex marriage 58% 35% 23% Offended by Phil Robertson of Duck Dynasty 24% 15% 9% Twitter users are more likely to love/like Target, support same-sex marriage, and to say they were offended by Phil Robertson's controversial comments about race and homosexuality.

41 Contact us for an MTO DeepProfile Report, InsightStore Subscription, and Custom Research Questions for your brand: Appendix Slides Follow March 2014

42 CivicScience DeepProfile Scales Charitable Giving- The Charitable Giving scale aims to identify the extent to which population segments donate to different charity groups, and how much time they spend volunteering. Discriminating Shopper- The Discriminating Shopper scale aims to identify the extent to which population segments do research before making purchases, and how easy or difficult they will be to win over. Market Maven- The Market Maven scale aims to identify the extent to which population segments adopt new products and brands, and share their opinions with others. Political Engagement- The Political Engagement scale aims to identify the extent to which population segments are involved in all levels of politics. Price Sensitivity- The Price Sensitivity scale aims to identify the extent to which population segments are price-conscious when shopping, both as a whole and across specific categories. Social Media- The Social Media scale aims to identify which social media platforms population segments use, and the extent to which they influence their preferences and behavior. Sports Fan- The Sports Fan scale aims to identify the extent to which population segments are interested in different types of sports. Tech Savvy- The Tech Savvy scale aims to identify the extent to which population segments use their digital devices and are informed and aware of the latest technology available. TV Viewing- The TV Viewing scale aims to identify the extent to which population segments watch various genres of TV and are influenced by what they see on TV. Health & Wellness- The Health & Wellness scale aims to identify the extent to which population segments monitor and maintain their health and wellbeing. Environmental Consciousness- The Environmental Consciousness scale aims to identify the extent to which population segments alter their lifestyle for the environment and shows overall concern about environmental issues. March 2014

43 CivicScience DeepProfile: How it works For the segments we re interested in, we look at how those people responded to thousands of other questions in our database, building a contingency table for each pair of questions. For this project we looked at thousands of questions related to: Lifestyle Media consumption Entertainment Technology usage Health and wellness Politics and ideology Other general attributes We calculate each table s Pearson s chi-squared statistic, and then employ the Benjamini-Hochberg false detection rate procedure to screen out likely false positives (i.e., statistically-significant associations that may be due to random chance). The tables that pass through our screening process are then ranked by their Tschuprow s T coefficient, which measures strength of association. March 2014

44 CivicScience Attribute Library Demographics & Profile Over 150 attributes Age, Gender, Race Education, Income Parental, Marital Status Morning / Night Person Geography Religion and Family Entertainment Over 200 Attributes Movies and TV Shows Event attendance Pro & College Sports Reading genres Theater and Culture Cultural Maven Indicators Media Consumption Over 50 Attributes Print vs. Online Newspaper & Magazine TV & Cable Networks Blog Readership Radio and Music Mobile & Streaming Health and Wellness Over 50 Attributes Diet and Exercise Weight and Fitness Ailments and Treatments Medical History Beauty Products Smoking/Drinking Personal Finance Over 50 Attributes Spending/savings Home ownership Employment/Type Insurance and Banking Economic Outlook Spending Outlook Financial Health Indicators Technology Usage Over 100 Attributes Phone and Carrier Smartphone & OS Tablets and PCs Social Media Usage Search, Web, Text Gaming & Consoles Adoption Curve Indicators Politics & Ideology Over 250 Attributes Party Affiliation Issue Positions Political Behaviors Civic Engagement Candidate Preference Shopping Habits Over 150 Attributes In-store vs. Online Coupon usage Spending by category Payment (credit v. cash) Dining Organic / Environmental Mobile & Tablet and many more. March 2014