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What App and Game Developers Can Learn From Amazon.com
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What App and Game Developers Can Learn From Amazon.com

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Presented by Andreas Weigend, former Chief Scientist at Amazon.com ...

Presented by Andreas Weigend, former Chief Scientist at Amazon.com

For more info on Andreas check out:
http://weigend.com

Join the Social Data Revolution Facebook Group:
http://socialdatarevolution.com

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What App and Game Developers Can Learn From Amazon.com What App and Game Developers Can Learn From Amazon.com Presentation Transcript

  • Kontagent Facebook Developer Garage San Francisco, March 25, 2009 What App and Game Devs can Learn from Amazon.com Andreas Weigend www.weigend.com Andreas S. Weigend, Ph.D. 韦思岸教授 © people & data | www.weigend.com
  • Outline | +1 650 906-5906 | +49 174 906-5906 | +86 138 1818 3800 PHAME  Problem Hypothesis Action Metrics Experiments Examples  User value: Value of user for firm, for network vs value for user © people & data | www.weigend.com Acquisition (viral) vs retention (engagement) ? More info: weigend.com and SocialDataRevolution.com  2
  • Problems | +1 650 906-5906 | +49 174 906-5906 | +86 138 1818 3800 Decisions, decisions…  How to adjust difficulty of your game? How much to charge for a virtual gift? Who to send invites to? Where to place stuff on the screen? … … Q: What problems do you face with your game or app?  © people & data | www.weigend.com 3
  • Result: Right vs Left | +1 650 906-5906 | +49 174 906-5906 | +86 138 1818 3800 对比结果:左还是右 Metrics  衡量标准 Conversion rate: Percentage of visits placing an order 转化率:下订单的浏览者所占的比例 Order size: Number of additional (from the second page) items put into cart 订单大小:(从第二页起)新购商品数量 Result  结果 “Your Shopping Cart” on right is about 1% better than on left © people & data | www.weigend.com “Your Shopping Cart”置于右侧比置于左侧的效果提高1% All customers Existing customers 现有消费者 所有消费者 Cart-adds from 2nd page: Cart-adds from 2nd page: +0.6% +0.8% 从第二页起新购商品数量: 从第二页起新购商品数量: Wishlist-adds: DVD Cart-adds: +1.4% +0.8% 选择礼物清单: 新购DVD: DVD (USD): +1.0% 6 DVD (USD): +1.1%
  • Why Analytics and Data Mining? | +1 650 906-5906 | +49 174 906-5906 | +86 138 1818 3800 Stanford Stats252 “Data Mining and Electronic Business” Mondays 2-5, Gates B01 (first class Spring 2009 is April 6, 2009)  weigend.com/teaching  Data mining  Actionable Insights?  The Past: Someone gives you data, and you do your best Worst: Reporting  Slightly better: Regression analysis  Better: Predictions on new data  © people & data | www.weigend.com Eternal hope: Actions  7
  • 1/3 of sessions only one click! Distribution of visit length: | +1 650 906-5906 | +49 174 906-5906 | +86 138 1818 3800 访问时间分布图 How many clicks per visit? 每次访问有多少点击数? 无法辨认的未购 买行为 Gold 可以识别的未购买行为 Box Web- 可以识别的购买行为 crawlers © people & data | www.weigend.com 内部的未购买行为 内部的购买行为 点击数量 8
  • | +1 650 906-5906 | +49 174 906-5906 | +86 138 1818 3800 How long ago did a customer first look at the detail page of an item eventually purchased? (Conditioned on purchase) © people & data | www.weigend.com 9
  • | +1 650 906-5906 | +49 174 906-5906 | +86 138 1818 3800 © people & data | www.weigend.com $5-10 $20-25 1.2% of all orders are below $5 How much does a customer spend on an order? 10
  • Picking good visualizations is key to seeing patterns | +1 650 906-5906 | +49 174 906-5906 | +86 138 1818 3800 选择正确的形象是识别特征的关键 Traffic by day Heat map   按天计流量 热图 Shows traffic colored from green to yellow Easy to see weekends to red 容易识别周末 用颜色(从绿色到黄色到红色)显示流量 Difficult to see other patterns Utilizes cyclical nature of the week 很难区分其他的特征 利用一周的周期性特点 Ronny Kohavi, Microsoft • Note 9/3 (Labor Day) and 9/11 注意:9/3(劳动节)和9/11 Weekends 周末 © people & data | www.weigend.com 11
  • Actions: Social recommendations | +1 650 906-5906 | +49 174 906-5906 | +86 138 1818 3800 90% of people believe information Social recommendations work passed to them by friends and well because context, content, family and targeted individual 80% of all consumer decisions are (recipient) are chosen by a influenced by social friend recommendations 89% of consumers recommend products or services that they like to others. Context Social recommendations are… © people & data | www.weigend.com  … 9 times as effective as advertising in converting unfavorable or neutral pre- dispositions into positive attitudes Content Recipient … 4 times as effective in influencing consumer to switch brands 12 Tom Gieselmann, BV Capital •
  • Leverage the social graph | +1 650 906-5906 | +49 174 906-5906 | +86 138 1818 3800 Example: New communications service US phone company with deep experience with targeted marketing  Sophisticated segmentation models based on experience, intuition, and data  e.g., demographic, geographic, loyalty data Hill, S., F. Provost., and C. Volinsky. • Network-based Marketing: Identifying likely adopters via consumer networks. Statistical Science 21 (2) 256–276, 2006 . • 4.82 (1.35%) 2.96 © people & data | www.weigend.com (0.83%) 1 0.4 (0.28%) (0.11%) Non-NN 1-21 NN 1-21 NN 22 NN not targeted Response increases by a factor of 4.82 by marketing to nearest neighbors (NN)  From 0.28% based on segmentation, to 1.35% based on social graph 13
  • Metrics: beyond unique users, clicks… | +1 650 906-5906 | +49 174 906-5906 | +86 138 1818 3800 Scarce vs abundant?  What are the real costs? Time vs money?  Social capital and social cost?  Cost of interrupt  Short-term vs long-term?  Should you make user aware of similar games or apps? Amazon.com: Helping people make decisions they don’t regret © people & data | www.weigend.com Local vs global?  MrTweet  Notifications Computational issues Hard-wired vs fluid?  Where can the behavior of people change, where not? 14
  • How real people make real decisions | +1 650 906-5906 | +49 174 906-5906 | +86 138 1818 3800 Will removing an option nobody chooses have any effect?  Dan Ariely, “Predictably Irrational” • All 3 Only 2 16% 68% © people & data | www.weigend.com 0% n/a 84% 32% 15
  • Recap: the PHAME framework | +1 650 906-5906 | +49 174 906-5906 | +86 138 1818 3800  Problem  Hypotheses Ask people, and compare responses to what they do Dating site   Action © people & data | www.weigend.com  Metrics Actionable Accessible Auditable  Experiment 16
  • Outlook | +1 650 906-5906 | +49 174 906-5906 | +86 138 1818 3800 User value  Value of user for your company  Value your app / game has for user  Value user has for other users (Network effects)  Acquisition (viral) vs retention (engagement) ?  Transaction economics  Relationship economics  Optimize for the product: Acquisition * retention Want to know more?  Economics of messaging  © people & data | www.weigend.com Gifting  Virtual item pricing  See weigend.com Join “Social Data Revolution” on Facebook 17