Applying Text Analytics to Decision Making in Marketing
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Presented at the 2015 New York Text Analytics Summit, the presentation discusses leveraging text analytics on social chatter for decision making by marketers.
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Applying Text Analytics to Decision Making in Marketing
- 1. Insights from Social Chatter Text Analytics Summit 2015, New York City
- 3. Context
- 4. Marketers most often analyze consumer behavior based on transactional history and demographic characteristics.
- 5. USUAL SUSPECTS • Transaction History • Demographic Data • Satisfaction Surveys • Brand Tracks • Attitudinal Surveys • Campaign Responses • Browsing Behavior
- 6. Understanding your customer’s personality is much trickier . . .
- 7. Benefits
- 8. Why use social chatter? Shortest turn around time proxy for a new campaign Large number of conversations Real conversations Personal, diverse Early Response Unconditioned Natural Volume Narrative
- 9. What the consumer is thinking? Career Government Celebrities Chat LoveLoans Concert Partying Home
- 10. What you can learn about me? New York Times Gun Control Game of Thrones INDIA
- 11. Applications
- 12. Applying the knowledge A B C F E D Identify media placement opportunities Targeting Design customized offers based on consumer wishes Offers Sniff trends and product ideas White Space Craft communication which appeals to your audience Messaging Learn category insights by carefully crafting search topics Competitive Intelligence The most infamous use of social media by a brand’s consumers Feedback
- 13. Method
- 14. An iterative process PROCESS STEPS Get Data Structure Term-Documents | Tokenizing | Classification Review & Adjust Change Data? Reduce Sparsity? Add stop word? Increase n-grams? Infer What have we learnt? Prepare Data Duplication | Graphical | Date- time | Spammers | Hyperlinks | Sparsity | Stop-Words | Stemming Exploratory Analysis Volume | Timeline | Word count | Word cloud Analyze Term associations | Topic Modeling | Clustering | Sentiment Act Decision-making Sources | Stream | Hygiene | Search fields
- 15. Comparing Search Topics with Social Chatter Themes Search Social Chatter Applying text analytics Natural Language Processing Data Science Search Keywords convey Intent – proxy for consumer needs Social Conversations – momentum, industry need
- 16. Discovering themes vegan shopping making day made increase diets365 farmers market nutrition • Determine source & query parameters Get Text • Inspect & cleanPrepare Text • Tokenize & make TDM Structure • Exploratory analysis Determine frequency & correlation threshold • Graphviz • Cytoscape Plot
- 17. Considerations
- 18. Cadence Incorporating in the brand’s planning cycle? Relevance Is social media the right place to hear your audience? Scaling Dealing with big data, automating Noise Separating the wheat from the chaff Spam Hashtag hijackers, free-riders, bots
Editor's Notes
- There are a limited number of data sources from which we try to decipher the lives our customers. As counter intuitive as it sounds – this is true. Ask a marketer if they have reams of data- the answer is yes. Ask them is the data is rich in behavioral insights – you’ll hear their tale of woes We judge behavior by what customers buy from us – when they buy – how much they pay - Consider trying to map consumer purchase decsion journey – the path is usually a black box
- In the case of media – we have product ownership, district, ethnicity, ratings, age, gender, marital status, In case of retail – much the same – instead of ratings – purchases
- Planners, Strategists are inadvertently bogged down by unrealistic profiles. For e.g.: Attitudinal surveys are exactly that – surveys. Not natural responses but carefully considered answers where you say who you think you are and how you want to behave. E.g.: Media company example. I’m not contesting validity and methodology. Merely making a point about difficulty.
- Targeting: Whether you want to target digitally or on TV or print – you can sense the media habit of your audience. Messaging : Meme, Theme, Emotions, Cats – Dogs, Offers : Are customers looking for something? Appealing? Competitive Intelligence : Sore points when dealing with competing brands? What do customers dislike when dealing with my category? Be careful if you are a cable company or airline when exploring this one. White Space: Opportunities