Why Analytics Now? - Elea McDonnel Feit, Wharton Interactive Media Initiative
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Elea McDonnell Feit gave a keynote at the Online Marketing Summit in Philadelphia on July 8, 2010 titled "Why Analytics Now?". She discussed how data analytics can provide surprising insights into consumer behavior online, with social media, user-generated content, and beyond. Research from the Wharton Interactive Media Initiative has shown that what customers say online matters, the crowd provides value, social networks can predict purchases, influencers are effective locally, and freemium pricing works well. Data analytics provides opportunities for marketers to make better business decisions and increase profits.
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Why Analytics Now? - Elea McDonnel Feit, Wharton Interactive Media Initiative
- 1. Online Marketing Summit PHILADELPHIA| JULY 8, 2010 Why Analytics Now? Elea McDonnell FeitResearch DirectorWharton Interactive Media Initiative 1
- 2. Why analytics now? Marketing insights revealed in the data Elea McDonnell Feit, PhD Research Director, Wharton Interactive Media Initiative Lecturer in Marketing The Wharton School University of Pennsylvania
- 3. Summary Today - more than ever before - every marketer has the opportunity to use data to drive better business decisions and greater profits. In this keynote Dr. Feit will review surprising findings on e-consumer behavior, social media, user-generated content, and beyond that have been revealed by the data-driven research conducted by the Wharton Interactive Media Initiative.
- 9. Wharton Interactive Media Initiative
- 10. WHARTON INTERACTIVE MEDIA INITIATIVE Brings a passionate data-driven perspective to media businesses (content distribution and information acquisition) in a way that no other business school in the world can match. Distinguishes itself with a tight focus on the interaction between content provider and user, capitalizing on the wealth of individual-level data that is exploding at the crossroads of commerce, technology, and entertainment. Is dedicated to bringing world-class research rigor to better understand these complex interactions in order to drive new business strategies and tactics that will reshape the media landscape.
- 11. Events Social Networking Jan 2009 Impact and Emergence of UGC Dec 2009 Interactive Retailing Mar 2010 Future of Publishing Apr 2010 Cross-Platform Data Dec 2010 Mobile Marketing TBD 2010
- 12. Global network of research partners Wharton Lab for Publishing Innovation WIMI Research Student Placement Partners
- 13. What WIMI-Supported Researchers are doing with the data
- 14. Use analytics to explore the relationship between brands Text mine consumer posts Mine Your Own BusinessMarket Structure Surveillance through Text Mining Feldman, Goldenberg, Netzer Customers are telling us things for “free” Perceptual Map of US Car Makes
- 15. wharton research on ugc , 2009 Does Chatter Really Matter? Dynamics of User-Generated Content and Stock Performance Tirunillai and Tellis What your customers are saying matters (if you own stock)
- 16. CrowdsourcingNew Product Ideas Bayus The value of the crowd is in the “crowd” “The goal is for you, the customer, to tell Dell what new products or services you’d like to see Dell develop.” Daily: Feb 2007 – Feb 2009 7,100+ ideas 4,300+ ideators 170 ideas implemented
- 17. Modeling Connectivity in Online Networks Social network data helps to improve predictions of behavior above and beyond just behavior More popular social networkers are also more active Online popularity is a more important correlate of online behavior than offline Ansari, Koenigsberg & Stahl Knowing a customers social graph helps predict their purchases + > >
- 18. Econometric Modeling of Social Interactions Hartmann Consumers bring additional value through their community Fraction of customer’s value that derives from others in the group Direct Value 65% Indirect Value 35%
- 19. Opinion Leadership and Social Contagion in New Product Diffusion Target social influencers Physician most often nominated by his peers as influential is targeted and is persuaded to increase his/her prescription by 10 units Iyengar, Van den Bulte, Valente Influencers work, but slowly and “locally” v. Across the board promotion Each physician is given an additional detailer visit
- 20. Popularity begets popularity; but how do you get it? But, free is free! Pricing Digital Content Iyengar, Abhishek, & Bradlow Fremium works!
- 21. Summary Customers are telling us things for “free” What your customers are saying matters The value of the crowd is in the “crowd” Knowing a customers social graph helps predict their purchases Consumers bring additional value through their community Influencers work, but slowly and “locally” Fremium works!
- 22. Eleanor McDonnell Feit, PhD Research Director, Wharton Interactive Media Initiative Lecturer in Marketing The Wharton School University of Pennsylvania
- 23. 23 Thank You Visit www.onlinemarketingsummit.com for more information Follow us @OMSummit
Notas do Editor
- Going to talk a little about history to put things in perspective, but I’m not a historian, I’m a statistician. I may be cherry-picking from history, but I assure you I’m doing it to make a point
- Let’s talk about the old days, way before there were advanced analytics, before there were degrees in statistics, before there was a Wharton School. Many people in small towns purchased much of what they needed from a single retailer: a general store. This is a system with: Regular interaction between the seller and the customer across a wide variety of categories – the clerk doesn’t just observe the purchase, but the clerk has to assist you even to examine a product – and through those discussions, he gets a rich sense of your preferences as a consumer. Community of customers who use the store not only as a place to buy stuff, but also as a platform for sharing knoweldge Knowledge of other aspects of the customers’ lives (who’s out of work, who’s doing well)And you better believe that successful store-owners used the information he gathered in the course of doing business to make business decisions such as What to stock What products and prices to (individual) offer customers Designing promotions Cross promoting with other organizations
- And then, what happened to the general store? Well, for many reasons, we moved to the “self-service” store and mass media became ubiquitous, and this was a revolution – just as big as the digital revolution we are living through today. which put a lot more distance between the marketer and the consumer. This is actually about the time when the field of “marketing” came into its own as distinct from “sales”. Stores are organized into chains with a central marketing department who handled all that mass advertising. Even within the store, the stock-boys fill up the shelves at night and customers shop during the day. Checkout is done by any army of checkout clerks who certainly weren’t tracking purchases, let alone what people were looking at on the shelves. There is very little interaction between the consumer and employees of the company. So, how does a marketer learn about his consumer?
- Well, we invent an entire new discipline of Marketing Research, where we take a very clinical approach to learning about our consumers. So this nice guy who is probably not even an employee of the company comes and gives you a survey. They ask a “scientific” sample of consumers what they think and then we take that small amount of data back to some office and study it and then present managers with research reports that tell them what consumers think and want.
- Well, we’re not going through another massive shift in media and retailing. And this shift has a lot of the same features as the general store. This is a system with: Regular interaction between the seller and the customer across a wide variety of categories – the clerk doesn’t just observe the purchase, but the clerk has to assist you even to examine a product – and through those discussions, he gets a rich sense of your preferences as a consumer. Community of customers who use the store not only as a place to buy stuff, but also as a platform for sharing knoweldge Knowledge of other aspects of the customers’ lives (who’s out of work, who’s doing well)And you better believe that successful store-owners used the information he gathered in the course of doing business to make business decisions such as What to stock What products and prices to (individual) offer customers Designing promotions Cross promoting with other organizationsIt isn’t revolutionary…it’s a throwback.
- We’re going back to the general store, and you should think of that analogy in all your marketing efforts: How do I use the steady flow of information that I can get about my customers to make better decisions?But the difference today is that information about customers is available to us on a massive scaleMore peopleMore countriesMore categoriesSo companies like Amazon and Google are taking us back to the general store concept, but at a massive scale. And the scale of things really necessitates methods for sifting through all that data. And that’s why we need analytics today. But the goal remains the same as it was back in the general store. Leverage the information you collect about your customers/users/etc. in the course of doing businessSo every time you are out there on the front lines: How can I structure the digital environment to get more data from my customers?How can I use that data to make better decisions about What to stock What products and prices to (individual) offer customers Designing promotions Cross promoting with other retailers
- Highlight the conferences on Social Networking and UGC
- Sentiment analysis – a powerful new tool of the digital era (which, by the way is essentially a way of listening in on those conversations around the wood-stove in the general store)
- Methods: Empirical IOMention focus on measuring customer value“We were therefore left with 193 groups consisting of 152 pairs, 34threesomes, and 7 foursomes.”
- In both models, the effect of a general detailing impulse declines smoothly overtime (due to the partial carry-over), whereas that of the network intervention is very small at firstbut increases steadily over time.
- Mention razor and blade