Here are the Eight Rules discussed in the Master Classes on “Big Data, Smart Metrics and Customer Centricity” in Shanghai, Singapore, London, and at Stanford in January 2012:
Hi there, here is the 20-minute audio of the keynote on “The State of the Social Data Revolution” at the 2011 Predictive Analytics World in San Francisco.
Would love to get your comments. Thanks!
Hello, you can do four things with the speech I gave at the 2010 World Innovation Forum in New York:
It was exciting to be part of the World Innovation Forum, an event packed with insights and a turnout of more than 800 thought leaders and a fantastic line-up of speakers. I had great company on stage, speaking between Chip Heath (who I went to grad school with) and Biz Stone (who co-founded Twitter).
I have put up the audio of my talk [mp3, 35 min, 32MB], the transcript [pdf | docx], and the slides [pdf | pptx]. And in terms of press commentary, check out what The Huffington Post, FastCompany, HSM, OnInnovation, and Steve Todd write about it, and please add your own thoughts via the comment box at the bottom of this post.
I am fortunate to present the insights on WIF2010 and the Social Data Revolution by two guest writers: Noah Burbank, a student in Stanford’s Social Data Revolution class this Spring, and Ted Shelton, the CEO of Open-First. And, as always, please do tell us what you think by leaving a comment below. Thanks!
How the Social Data Revolution Changes (Almost) Everything
Andreas S. Weigend, Ph.D.
Thursday, 17 September 2009
5:00 pm Lecture, 6:00 pm Reception
NTU (Nanyang Technological University, Singapore)
Lecture Theatre 25 (South Spline 1, B2-1)
Visionary companies are starting to design products and services based on social data – data individuals generate and share about their attention, intention, location, and situation. Read the rest of this entry »
Download the mp3 of the World Marketing Forum keynote (45MB, 50 minutes, Mexico City, July 1, 2009).
Ladies and gentlemen, it is an honor for me to be here and to talk to you about what I think it the most interesting, the most exciting thing I can talk to you about. Read the rest of this entry »
This keynote at the Facebook Developer Garage shares insights from Amazon.com that are relevant for app and game developers. The event was organized on February 25, 2009 by kontagent, a San Francisco startup I am advising.
Abstract:Technology affords companies unprecedented opportunities to interact with customers and employees. In any of these interactions, data is created. Yet most firms neither capture nor fully utilize those data to impact their bottom line and strengthen relationships with their customers. Product recommendations and behavioral targeting are early examples of leveraging new sources of data to predict customer behavior and preferences. The next iteration of these interactions, for example mobile phones, empowers owners to access richer data and discover new opportunities – with the possible inclusion of location data that enables companies to predict mobility patterns for marketing and planning purposes. Learn from the former Chief Scientist of Amazon.com how to create a comprehensive data strategy through:
In honor of the (approximate) 10th anniversary of the Cluetrain Manifesto, The Conversation Group organized a day of speeches and breakout sessions. They invited me to present my thoughts on Conversational Data.
ANDREAS WEIGEND SPEAKS AT SAP
Wednesday, April 16, 2008
3:30pm Networking Mixer (refreshments will be provided)
4:00pm – 6:00pm Presentation and Discussion
Building D, Southern Cross Room
SAP Labs, 3410 Hillview Avenue, Palo Alto, CA 94304
The production, aggregation, distribution, and consumption of data is changing dramatically. Traditionally, paid specialists actively collected data for a specific purpose. Now, we are flooded with data streams of intention, attention, situation, and location of individuals, plus data about personal relationships. In addition to these implicit traces of behavior, people contribute data explicitly on platforms for mapping, housing, automotive, and salary data.
The money is where data influence decisions. Most firms believe in internal transparency, basing decisions on data they collect. Few understand how they can benefit by extending this transparency to the outside. What data should the firm share with its customers so some of them can actually help the firm? A sound data strategy has become central to most firms.
Barriers to data business used to be high, including expensive infrastructure and complex business relationships. Infrastructure has now been commoditized; information asymmetries are being reduced by those companies that understand the new consumer data revolution. Relevant questions in today’s marketplace include: How can we set up a system (including incentives) so that people actually do contribute useful and truthful data? What properties does the market need to have so that collective intelligence emerges? What value can the firm create for the contributors to drive participation? It is their perception of this value that will decide whether they demand to be paid for their contributions, or whether they are willing to pay themselves? Finally, what should be the currency of the payments: money, attention, or even more data?