1. Impact of Mobility and Timing on User-Generated Content Gabriele Piccoli & Myle Ott – September 2014 Page 1/15 Opinions posted via mobile devices are more timely, shorter, more “to the point” and more negative than web reviews.

2. Impact of Mobility and Timing on User-Generated Content Gabriele Piccoli & Myle Ott – September 2014 Page 2/15 Agenda  Mobile Technology Changes  The Research Study  Findings from the Study  Guidelines for Managing Reputation

3. Impact of Mobility and Timing on User-Generated Content Gabriele Piccoli & Myle Ott – September 2014 Page 3/15 Mobile Technology Changes the Nature of User-Generated Content 1/3  On August 13, 2013, under pressure from its 10.4 million users who access the platform each month via mobile devices, Yelp allowed users to post reviews from their mobile devices.  Up to that date, Yelp had resisted enabling such reviews, citing concerns about their short length and overall quality.  The Yelp example suggests that even firms at the forefront of technology-mediated interaction with customers are struggling to manage the impact of new IT devices.

4. Impact of Mobility and Timing on User-Generated Content Gabriele Piccoli & Myle Ott – September 2014 Page 4/15 Mobile Technology Changes the Nature of User-Generated Content 2/3  In the past, a brand manager could carefully craft brand messages that were then delivered to consumers through television, print, radio and static websites.  Today, those same brand messages must compete with user- generated opinions that are published and distributed around the world through social media.

5. Impact of Mobility and Timing on User-Generated Content Gabriele Piccoli & Myle Ott – September 2014 Page 5/15 Mobile Technology Changes the Nature of User-Generated Content 3/3  “Unbiased hotel reviews, photos and travel advice for hotels and vacations”  TripAdvisor  “Unbiased reviews by real people”  Epinions  Publicly expressed opinions may not simply reflect the personal evaluation of the individual posting a comment.  Rather, they are often influenced by the opinions of others and by timing effects.

6. Impact of Mobility and Timing on User-Generated Content Gabriele Piccoli & Myle Ott – September 2014 Page 6/15 Agenda  Mobile Technology Changes  The Research Study  Findings from the Study  Guidelines for Managing Reputation

7. Impact of Mobility and Timing on User-Generated Content Gabriele Piccoli & Myle Ott – September 2014 Page 7/15 The Research Study  Primary data source for this study was all reviews posted on a leading online review platform for travel products in 2012 relating to the 25 largest U.S. markets (n=293,945).  From this data, matched samples of all reviews posted via mobile devices (30,540) and via the web interface (38,248) for the same product on the same day are were extracted.  A machine learning algorithm designed to establish if a review was posted on the same day as the service.

8. Impact of Mobility and Timing on User-Generated Content Gabriele Piccoli & Myle Ott – September 2014 Page 8/15 Agenda  Mobile Technology Changes  The Research Study  Findings from the Study  Guidelines for Managing Reputation

9. Impact of Mobility and Timing on User-Generated Content Gabriele Piccoli & Myle Ott – September 2014 Page 9/15 Findings from the Study 1/5  Reviews Posted via Mobile Devices are Shorter  reviewers posting via the website use, on average, 41.3% more text than mobile users.  After excluding emoticons, reviews posted on mobile devices use less punctuation.  Mobile reviews use more abbreviations and Internet slang than their web counterparts.  Perhaps counter-intuitively, text written on mobile devices has fewer misspellings.

10. Impact of Mobility and Timing on User-Generated Content Gabriele Piccoli & Myle Ott – September 2014 Page 10/15 Findings from the Study 2/5  Reviews from Mobile Devices are Posted Earlier  customers who used the mobile- enabled review system are 2.46 times more likely to contribute their comments on the same day as the service encounter compared to those using the website.  individuals commenting in the months following the service encounter are 1.38 times more likely to do so via the web- based review system.

11. Impact of Mobility and Timing on User-Generated Content Gabriele Piccoli & Myle Ott – September 2014 Page 11/15 Findings from the Study 3/5  Reviews Posted from Mobile Devices are More Negative  Customers posting their commentary through the mobile platform select the worst evaluation (i.e., “terrible”) proportionally 1.66 times more often for their overall rating  The results are similar for “poor” ratings, albeit of lesser magnitude (1.27 and 1.35 times for overall and service ratings, respectively)

12. Impact of Mobility and Timing on User-Generated Content Gabriele Piccoli & Myle Ott – September 2014 Page 12/15 Findings from the Study 4/5  What surprised you the most ?

13. Impact of Mobility and Timing on User-Generated Content Gabriele Piccoli & Myle Ott – September 2014 Page 13/15 Findings from the Study 5/5 What caused this? How to manage it? Negative Earlier Shorter

14. Impact of Mobility and Timing on User-Generated Content Gabriele Piccoli & Myle Ott – September 2014 Page 14/15 Agenda  Mobile Technology Changes  The Research Study  Findings from the Study  Guidelines for Managing Reputation

15. Impact of Mobility and Timing on User-Generated Content Gabriele Piccoli & Myle Ott – September 2014 Page 15/15 Guidelines for Managing Reputation Manage the Essential Nature of Reviews Posted via Mobile Devices  Managers may be able to stimulate positive reviews.  How?  Strategy for responding to negative reviews posted via mobile devices. Recognize the Triggered Nature of Mobile-Posted Reviews  Mobile reviews are 2.46 times more likely to appear on the same day as the service.  Triggers and caution Proactively Manage Communication Channels  Managers should seek to mitigate the need for customers to vent their frustration online – with real world venting options Monitor for Early Signs of Customer Dissatisfaction  Complement customer service strategy with a monitoring system designed to intercept negative experiences from digital data flows.