Using social media for market research and new product development: the case of Hallmark: - Evaluating the use of social media data as a research tool. - Sharing what we learned and observed from a specific project: what worked and what didn’t. - Highlighting paradigms of traditional research that are seriously challenged by the use of social media data.

1. Hallmark’s Journey into Social Media Experiences and Learnings

2. LISTENING J.C. Hall (1891 - 1982)

3. Social Media Listening 2000 - launched first consumer community for the purpose of research. 2005 – pilot w/ Umbria to understand the Hallmark brand in the social space. 2007 - pilot with Spiral 16 to understand Influential Bloggers. 2009 - major RFP with 8 vendors – find partner for research and marketing. 2010 - consulted with Ben Smithee; contracted with Collective Intellect for a look into holidays, ornaments.

4. 1 Hard Question“Is there a framework we can use to understand social media data?” 3 “Simple” Questions “Can we use social media sources to get new product ideas?” “Can we use social media data to create marketing interventions ‘in season?’” “Could we use social media data to help understand people and their lives?”

5. Hard Question“Is there a framework we can use to understand social media data?”

6. Social Media Analysis Space? Discovery Understanding people Uncovering white space Topics + dashboard What you’re trying to accomplish Specific Topic Open Search Ways of approaching the data “Ocean” of Data Small “pond” of data Brand Reputation KPI’s Monitoring Source: Hallmark CU&I, 2010

7. Consumer Leads Focus We Lead Single Stakeholder Multiple Stakeholders Breadth of Learning Hallmark Social Media “Listening” Activities

8. Consumer Initiated Conversation Hallmark Initiated Conversation Single Stakeholder Multiple Stakeholders Breadth of Learning Listening audit showed that activities are many and varied Focus of Conversation

9. 9 Dimensions of listening Feedback is more about the brand and rational Discovery is more about the consumer and emotional Source: CEB

10. Listening activities tend to fall towards feedback and tactical Source: CEB

11. Research Landscape Structured Data – it is what we made it PA’s Multivariate Trackers …… Focus Groups Communities Ethnography Observation Qualitative Quantitative Social Media Unstructured Data – it is what it is Where does social media data play in the research landscape?

12. 3 “Simple” Questions “Can we use social media sources to get new product ideas?” “Can we use social media data to create marketing interventions ‘in season?’” “Can we use social media data to help understand people and their lives?”

13. What Did We Conclude? Getting “New” Product ideas is very hard! If you do lots of traditional research and ideation, chances are you’ve heard of thought of everything you will uncover through social media.

14. Some Thoughts on In-Season Marketing Twitter promotional sweepstakes generated major spikes in Hallmark Ornament Mentions Hallmark Gold Crown store visits emerged as a conversational theme - how could that be leveraged? Emotional connection to Hallmark brand ornaments vs. those bought in Wal-Mart or Target – how could that be leveraged? Focus on connecting the troops and their families – what would that look like?

15. What Did We Conclude? Beware of making any marketing suggestions without having Marketing in the design and analysis discussions! Research in social media begins to “rub up against” Marketing and can create friction!

16. Thoughts Going Forward

17. What Have We Learned About Social Media? There are new vendors emerging daily in the social media listening space. Most vendors provide the same capabilities – it is hard to find differentiation.

18. What Have We Learned About Social Media? Social media data is messy (spam, advertising, porn, context) and requires significant validation and cleaning – suppliers are getting better and better at this, but it is still an issue. Text analysis capabilities vary from vendor to vendor – you have to know what questions to ask to know what you’re getting. Sentiment analysis is about 75-85% accurate (based on external research) and everybody does it at some level. It is of limited value. It is difficult to classify individual contributors – but not impossible, and it costs more. This capability is still emerging.

19. What Have We Learned About Social Media? Clear and specific listening objectives are essential to getting meaningful data and information from listening efforts. Social media conversations can be very rich and could support many different aspects of our business. Getting meaningful learnings and insights is very time and labor intensive, despite the software tools. There is a learning curve!

21. Participants who create social media content must opt-in or choose to participate.

22. They may or may not represent your target consumer.

23. They do not necessarily constitute a “probability sample” of the population.

25. Social Media Data is… + Longitudinal and Instance-based – Tradtional MR is usually instance-based feedback/insights, social media research can represent “flow of life.” There is a constant stream, or flow, of social media data continually being created.

26. Social Media Data is… + Self-recording/Archival – Conversations, both public and private, within the social media environment are archived and available for others to consume at will. Conversations with people in traditional research methods are recorded, but are generally only available to permission-based viewers/listeners. This creates an interesting blend of liability and value to researchers and brands.

29. Blurring of Qualitative and Quantitative –

30. Re-thinking Sampling –

33. Food for Thought Resources: People, Time, & Money Spectrum of Desired Outcomes

34. Social Media Research White Paper http://www.slideshare.net/CuratingPixels/utilizing-social-media-to-understand-people http://bit.ly/UnderstandingPeople

35. QUESTIONS? Tom Brailsford – Hallmark Cards, Inc. tbrail@hallmark.com 816-274-3989