Peter Fader

Professor of Marketing, The Wharton School of the Univ. of Pennsylvania

Peter S. Fader is the Frances and Pei-Yuan Chia Professor of Marketing at the Wharton School of the University of Pennsylvania. His expertise centers around the analysis of behavioral data to understand and forecast customer shopping/purchasing activities. He works with firms from a wide range of industries, such as consumer packaged goods, interactive media, financial services, retailing, and pharmaceuticals. Managerial applications focus on topics such as customer relationship management, lifetime value of the customer, and sales forecasting for new products. Much of his research highlights the consistent (but often surprising) behavioral patterns that exist across these industries and other seemingly different domains.

Many of these cross-industry experiences have led to the development of the Wharton Customer Analytics Initiative, a new research center that serves as a “matchmaker” between leading-edge academic researchers and top companies that depend on granular, customer-level data for key strategic decisions.

Professor Fader believes that marketing should not be viewed as a “soft” discipline, and he frequently works with different companies and industry associations to improve managerial perspectives in this regard. His work has been published in (and he serves on the editorial boards of) a number of leading journals in marketing, statistics, and the management sciences. He has won many awards for his teaching and research accomplishments.

Current papers, course syllabi, and other materials are available at

  • Posted on: 01/10/2017

    Will 2017 be the year of the chatbot?

    Nope. Maybe one day, but not yet. The technology is still clunky and today's grown-ups are pretty set in their ways about their desired shopping experience.Give it another 10 years and we'll likely see a significant shift in this direction. That's fine: a change like this can't happen overnight.
  • Posted on: 11/07/2016

    Will a national loyalty program yield rewards for Whole Foods?

    Every retailer -- especially a grocery chain -- must have a loyalty program. No exceptions. But it should be a *loyalty* program, not a badly-designed discount program that gives people coupons for stuff they don't want and/or coupons for stuff that they were going to buy at full price. Those dumb tactics should not be part of a loyalty program in any setting, and certainly not for Whole Foods.It's all about learning about customers' preferences, changing the product mix and merchandising strategies and giving special treatment to valuable customers who benefit from it. That's what a loyalty program does, and there's no doubt that it could be a terrific asset to Whole Foods -- if they manage it the right way (unlike most grocery chains).
  • Posted on: 10/31/2016

    Why are mobile conversion rates so low?

    Are we still talking about online sales versus offline sales as distinct entities? What happened to all the "omnichannel" talk? Who cares where a purchase is actually consummated -- all that matters is that the purchase takes place. All of these channels/devices contribute to the purchase, so let's stop worrying about these meaningless device-specific conversion metrics.
  • Posted on: 10/25/2016

    It’s the Millennials’ world

    Allow me to expand on Ralph's key point: "not all Millennials are alike" -- in fact they're vastly different. All these efforts to stereotype and target Millennials are doing more harm than good for retailers. Any effort to paint all consumers in a large demographic group with the same brush is a terrible mistake.A modest proposal: let's stop stereotyping and focus instead on finding/leveraging *meaningful* differences across consumers ...
  • Posted on: 09/21/2016

    Is consumer demand really that unpredictable?

    Indeed, as Nikki points out, when you don't have granularity, demand forecasting can be challenging. But many retailers *do* have granularity or at least should be making more serious efforts to achieve it. And when you have such granularity, then forecasting is remarkably easy/accurate/actionable -- if you understand the basic behavioral patterns and choose the appropriate methods to capture/project them. Here is one such example from my predictive analytics firm, Zodiac and I encourage retail analysts to learn more about these methods and their implications for strategic and tactical decision-making.
  • Posted on: 09/16/2016

    Consumers rely on reviews, but they don’t trust them

    I respectfully disagree with Frank. As inauthentic as many reviews are, retailers' responses are generally even worse in this regard. Most reviews should be left alone -- even if they're negative. Retailers should only respond to reviews that truly demand a response.
  • Posted on: 09/15/2016

    Are robo-carts coming to a Walmart near you?

    This is a great example of the old metaphor: "Rearranging the deck chairs on the Titanic." This is not going to help retailers address the problems that are leading to their demise. Retailers should focus their efforts on understanding what their customers are doing instead of obsessing over the location of shopping carts.
  • Posted on: 09/12/2016

    Why are retailers struggling with Big Data?

    It's simple: retailers are obsessed with one and only one thing — operational efficiency. Big Data can be somewhat helpful in this regard but the real payoff from it, as noted in Brian's introductory comments, is in different kinds of personalization/customization. Retailers are notoriously bad at doing this (because these activities go against the grain of operational efficiency).Until retailers are willing/able to change their core strategies in a fundamental manner, they will never reap the rewards of Big Data.
  • Posted on: 08/30/2016

    Retail executives have no clue about digital

    Here's a big source of the problem: retailers are looking in the wrong places to find best-practice examples to follow. Specifically, they're often looking at big-name CPG firms and other manufacturers that have no direct contact with their consumers. So they end up focusing on "one size fits all" branding activities and other tactics that do not leverage their ability to have direct relationships with consumers. Instead, they should be looking to direct marketing to figure out how to move ahead. That's not a sexy industry and the brands may not seem to be as powerful as some of the aforementioned manufacturers. But who cares about the "sexiness" of a brand when you can form direct and profitable relationships with different customers? This is what led to the great (but fleeting) success of Tesco, and underlies much of the Amazon story as well.It's all about customer equity -- not necessarily brand equity, but retailers are looking in the wrong direction to really understand and embrace this distinction.
  • Posted on: 08/15/2016

    Is brick & mortar ready to leverage in-store shopper data?

    If the focal question asked "should" brick-and-mortar stores leverage in-store shopper data, then the answer is obviously yes. But the question really asks whether they're ready to do so, and unfortunately for most retailers the answer is a resounding no. They can't properly leverage their transaction log data, so forget about in-store shopper data. Retailers need to walk before they run: first figure out who's buying what before you worry about who's doing what. Given the disappointingly slow progress on the former, I'm not holding my breath for the latter. But I hope I can be proven wrong in the next few years.
  • Posted on: 08/04/2016

    Would Walmart + be an Amazon killer?

    What a terrible idea! Tying two bricks together won't help either one float. has been a mess since day one. Walmart needs a partner with a proven record of success to find a way to make online work for them. They should steer far away from this losing proposition. They'd be overpaying at even half of the reported price.
  • Posted on: 07/11/2016

    Are self-checkouts dooming impulse purchases?

    Maybe it's true that self-checkout inhibits impulse purchases, but in the long run it could be a great way to create consumer "lock-in" that might be so much more valuable than an occasional candy bar. Retailers really need to think about lifetime value rather than maximizing revenue on single transactions.
  • Posted on: 07/05/2016

    How important is non-transactional data to personalized offers?

    Non-transactional data (NTD) is rarely as important as transactional data (TD), but it can help add additional insights -- assuming that the TD is fully leveraged.Too many retailers believe that the sheer quantity of NTD can compensate for the greater quality of TD -- but that's almost never true. NTD may seem to be more interesting, actionable and insightful than TD, but it's not nearly as predictive (which is what matters first and foremost).Retailers must walk (with TD) before they attempt to run (with NTD). Here's a recent interview that picks up on this same theme: "Big Data: Start with Baby Steps".
  • Posted on: 06/30/2016

    Can retailers sell anything without sales?

    So how do we create the new business model that Ori Marom is hinting at? It's actually pretty easy: judge our efforts (including promotional campaigns) on the basis of the future/projected value created for the customers who participate in the campaign. If we're only appealing to low-value cherrypickers, then the campaign is a failure and we shouldn't do it again. But if it is attracting valuable customers and/or enhancing the value of existing valuable customers, then it's a success.Let's stop evaluating our retail businesses on the basis of volume and costs. It's all about granular value. "Lift" is meaningless if it's not lifting value as well as volume.
  • Posted on: 06/13/2016

    How can online returns be minimized?

    That's the wrong question! The right one is "under what circumstances should returns be minimized?" For the "serial returners," it's a no-brainer, but that's a tiny portion of the customer base. There's are, in many cases, more customers for whom returns can be seen as a *good* thing -- a sign of ongoing engagement and an indication of higher lifetime value. Proper analysis of transaction log data can sort out these issues in a clean, granular manner.By the way, it's exactly the same issue about loyalty program redemptions: do you really want to minimize them, or leverage them to create greater future value?For both of these issues (and countless others), it's important to take the long view about customer value maximization instead of just trying to minimize short-run costs.

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