Lloyd Melnick


I lead the social gaming initiatives at PokerStars/Full Tilt, part of Amaya Gaming. Previously, I was Sr Director on Zynga's social casino, building out the VIP and loyalty programs for Hit It Rich! slots and Zynga Poker. I came to Zynga from Spooky Cool, where I was Chief Growth Officer and before that, GM International Publishing at Playdom/Disney and co-Founder and CCO of Merscom (which we sold to Playdom). My passions are customer behavior and analytics.

11 responses to Lifetime Value Part 9: Uncertainty and LTV


    Hi Lloyd, good post to introduce the uncertainty concepts behind LTV. Using confidence intervals around predictions is a good way to ensure better understanding by the end users.

    What are your thoughts on whether confidence intervals can be generated for user level LTV? The reason I ask is that in Sonamine analysis of many games, LTV tends to follow a power law distribution, instead of the “normal” bell shaped distribution.


Trackbacks and Pingbacks:

  1. LTV presentation to Yetizen « The Business of Social Media - April 25, 2013

    […] and the predictive nature of LTV. Other than the final section on uncertainty, which echoes my blog post on Tuesday, the presentation is largely consistent with the one posted earlier that I gave at Groundwork Labs […]


  2. Finding the influencers with influence « The Business of Social Media - May 2, 2013

    […] to do with it. Researchers call them “confounding factors.” This finding is consistent with one of the problems I identified last week in determining LTV (and predictions in general), the ove…. In that post, I argued that your predictions could be less reliable because factors that fit the […]


  3. Do not mistake the unfamiliar for the improbable « The Business of Social Media - May 29, 2013

    […] based decisions is mistaking the unfamiliar with the improbable. A few weeks ago, I wrote about how Nate Silver influenced my understanding of how to incorporate uncertainty into your LTV calcula…, Silver also did a great job of showing that we must consider contingencies we may not even have […]


  4. My favorite posts of 2013 « The Business of Social Media - January 2, 2014

    […] Uncertainty and LTV Part of my LTV series, focusing on Nate Silver’s discussion of uncertainty. […]


  5. How startups should use metrics « The Business of Social Media - April 1, 2014

    […] I have written before, many early results will just be noise. They will be caused by correlated activities even though the activities are not unrelated. With an […]


  6. Lifetime Value Part 11: How to calculate LTV « The Business of Social Media - April 17, 2014

    […] your users’ or players’ lifetime value, the key components and how to impact them and techniques to increase the accuracy of your customer lifetime value (LTV) predictions. I intentionally did not publish a formula for calculating LTV—while it is always a factor of […]


  7. Lifetime Value Part 13: Managing users and customers profitably « The Business of Social Media - May 6, 2014

    […] have written before about the importance of understanding that LTV is a prediction, not a value. As a prediction, it could end up higher or lower, thus a potentially profitable customer might […]


  8. Summer reading list « The Business of Social Media - June 24, 2014

    […] Finally, another thought-provoking book that helps you understand much better how to use analytics, and not misuse them, is The Signal and the Noise: Why So Many Predictions Fail-but Some Don’t by Nate Silver. Nate Silver, best known for being the best prognosticator of the past two elections, destroys many of the fallacies around predictive models and provides a broad infrastructure on how metrics can help (read my post on the lessons I took away from the book). […]


  9. Why Excel is just as bad as Powerpoint « The Business of Social Media - January 27, 2016

    […] I would add an important remedy to the Excel problem is using more qualitative data. One thing many analysts and executives forget is that qualitative data is still data and should be built into your decision-making. It represents additional data, and I have never seen a model where more data is worse than less data. Thus, the spreadsheet may look great for Farmville, but if it looks like an old game that you no longer want to play, that is an important data point also to take into consideration. In 2013, I wrote about the value of qualitative data in LTV calculations and noted that Billy Beane, the father of Moneyba…. […]


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