How marketers can increase quantity of quality using customer lifetime value

(Originally posted on Medium.) Customer lifetime value has been an interest of mine for several years: cohort and survival analysis, revenue models, unit economics, and innovation through experiments. It is a fascinating space populated by smart people publishing new findings built on decades of research originating, in part, from database marketing thought leaders. But while the academic research…
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Changing the Twitter conversation (again)

(Originally posted on Medium.) Earlier this week Shira Ovide made the argument that, despite the negative sentiment around Twitter in both tech and finance circles and some unexplained deceleration, their sales growth is cause for optimism: How unusual is Twitter’s revenue clip? Out of more than 100 technology companies with at least $2 billion in…
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The hockey assist and what digital marketers can learn from sports analytics

(Originally published on Medium.) While Moneyball was a critical success it also made sports analytics more accessible to the general public. Digital marketing is not likely to see similar box office success but practitioners can learn a lot from the adoption of analytics in sports — the history and evolution of different measures, the emotional reactions, the continued…
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Data-driven attribution: the hype, the hope, and reasonable expectations

(Originally posted on Medium.) Last week eMarketer released new data highlighting the slow adoption of multichannel attribution among US marketers (subscribers only). Despite increasingly complex customer decision journeys less than half of those surveyed use attribution models that value assisting touchpoints. To quote Cindy Liu of eMarketer: Advanced attribution modeling is used to track and score…
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Digital attribution as a means to an end

(FYI: cross-posted on Medium in response to A Case for Ambiguity in Data-Driven Marketing.) Until we are studying motivations, even as we frame our tests in the context of generating the revenue that keeps our companies or clients afloat, we are condemned to do our work amidst the uncertainty of an infinite array of possibilities for why our campaigns…
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Predictive analytics, five years later

This week I am at Predictive Analytics World Boston to learn from leaders in statistics, data mining, and related analytical disciplines. Much has changed since I attended the inaugural PAW conference over five years ago but many of the core challenges and techniques remain the same. While it’s clear that demand for predictive analytics has increased significantly over the last several years—measured in part…
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The rise and fall of prediction markets

Yesterday I saw an announcement for Microsoft Prediction Lab which allows users to predict upcoming events such as elections. While prediction markets are nothing new—the Iowa Electronics Market has been operational since 1988 and, over time, has routinely outperformed traditional polls—I have not heard about them as much recently. Google Trends seems to validate the idea that their popularity has waned, with a slow…
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Measuring marketing value through incrementality experiments

Last week Google released CausalImpact, an open-source r package that both improves and simplifies incrementality analysis of time series data. For marketers who do not always have the luxury of A/B tests but still want to be data-driven, this package should be a core part of the toolkit. Based on original research, the model establishes what’s called a…
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Not all impressions are created equal

Links are at the heart of the internet so it’s no surprise that digital marketers primarily focus on clicks. Clicks are comfortable—especially for direct response marketers who grew up in direct mail, telesales, etc.—despite new devices, new content formats, and new consumer behaviors. Earlier today, Chartbeat’s Tony Haile posted about the challenges of moving beyond click measurement:…
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