Innovation in Retail: Virtual “Brick and Mortar” Stores

Happy New Year! My most popular post so far has been about Tesco bringing grocery shopping to Korean subway. Here is another example of retail innovation (hat tip – Benn Konsynski). Yihaodian a Chinese company using augmented reality to build a 3D virtual store. Their stores exist only on a smartphone screen, but otherwise it’s a fully immersive experience.

Interestingly, customers still need to go to a store, augmented reality works only at specific locations. At first, it seemed odd – why limit consumer experience? Perhaps the company is betting on association with the trendiest locations. Another reason why Yihaodian is doing this might be studying how consumers move about the store and applying it for improving store layout. Given Yihaodian’s effective merger with Walmart, I would not be surprised if the virtual store browsing data is applied for traditional brick and mortar store design.

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Is Amazon.com cashing on consumer behavior?

I am very much tempted to answer – YES. The genesis of this post is the recent report by NPR’s Stacey Vanek Smith; the case under consideration is Amazon.com potentially raising the cost of its Prime membership from $79 to $99 per year or more.

Prime membership gives consumers free shipping on their orders and free access to numerous books, movies, and TV shows. The volume of Prime subscribers is estimated to be well over 10 million and growing rapidly. Could it be that Amazon.com has decided to curtail the growth of membership? This could be sensible if Amazon has reached capacity limitation for shipping or content streaming. Neither seems likely, though. So what is the logic behind the (possible) decision?

The report offers this explanation:

But the rationale for raising prices, may not be fast cash, speculates Michael Levin, co-founder of Consumer Intelligence Research Partners in Chicago.

“At Amazon, nothing is ever what it seems,” he laughs. “If they charge more, I think customers are probably going to spend more. So quite ironically, by raising the price of this membership, they may end up getting people to shop there even more.”

A more expensive Prime membership equals a customer who is all the more motivated to get his or her free-shipping’s worth.

Having done some research on the topic of consumer behavior, my explanation for this phenomenon is the so called Sunk Cost effect. This is a well-known phenomenon in Behavioral Economics. In simple terms, the effect occurs when consumers continue to use products that have become obsolete. Moreover, the usage increases if consumers spent more money to purchase these products. As such, this behavior is irrational in the classical economic rationality sense: a decision to use a product should depend only on the current or future cost and benefit, but not on a past one.

So by raising prices of the Prime membership, Amazon.com could be just targeting our irrational tendency to recover sunk costs. Even if there is an identical product couple of dollars cheaper, Prime members would still buy from Amazon, driven by the (sunk) cost of membership.

Has Wall Street overreacted to LULU quality issues?

Last couple of weeks have been eventful for CEOs, COOs, and quality managers. Boeing is trying to fix faulty batteries in their 787, Fisker Automotive is in dire straits and expected to file bankruptcy after quality issues with their car batteries. And another company is about to face harsh consequences of quality mismanagement — a yoga-oriented retailer Lululemon Athletica.

Ten days ago Lululemon (LULU) made an announcement of the quality issues with their yoga pants, and lost $600M or 7% of their $9B market capitalization. Ouch. More details and numbers in this video.

What fascinates me in this situation is how the stock market reacts to these kind of events. During the earnings call LULU has reported that the pants issue is going to cost them ~$15M in revenue, which seems not too big of a deal given that their latest quarter revenue was $485M. Later on they made an amendment saying that more pants currently in production and sea-shipments are affected, so that greater revenue losses are expected, but they still should be confined to the 2nd quarter. Still, they are not going to lose all Q2 revenue – so are the markets overreacting in slashing $600M from LULU’s value? Let us try a quick calculation.

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Innovation in retail: How do you bring a grocery store to people?

The picture to the left is actually a storefront of Tesco in Korean subway. Watch the video to see how it works – the idea is pretty neat: you put a full size picture of store shelves, it serves as an ad, and it connects shoppers to the online store. Nothing else changes, customers are simply given another more convenient entry point to the online store. If Tesco can also put an interactive screen displaying price promotions there, the shopping experience will be almost as good as in a real store.

Do we wait too long?

As the school year starts in Atlanta, so inevitably does this blog. With a backlog of articles to write about, I decided to take on this recent one published by Alex Stone in NY Times. Its basic premise is not new: people feel they wait longer if they are not doing anything during that time. Thus, managing the perceived wait is just as important as managing the actual wait (if not more).  What is interesting, though, is the examples that the author gives to make the point.

SOME years ago, executives at a Houston airport faced a troubling customer-relations issue. Passengers were lodging an inordinate number of complaints about the long waits at baggage claim. In response, the executives increased the number of baggage handlers working that shift. The plan worked: the average wait fell to eight minutes, well within industry benchmarks. But the complaints persisted.

Puzzled, the airport executives undertook a more careful, on-site analysis. They found that it took passengers a minute to walk from their arrival gates to baggage claim and seven more minutes to get their bags. Roughly 88 percent of their time, in other words, was spent standing around waiting for their bags.

So the airport decided on a new approach: instead of reducing wait times, it moved the arrival gates away from the main terminal and routed bags to the outermost carousel. Passengers now had to walk six times longer to get their bags. Complaints dropped to near zero.

This strategy must have worked especially given the fact that people overestimate the wait by 30 to 40% if they are idle. Another example speaks to perennial lines to cash registers at supermarkets. Retailers are pretty reluctant getting rid of them, even though a single line served by all cashiers would be much faster. There are good reasons for that. First, a longer snaking line might scare customers away. Second, is the opportunity to sell a customer something during this wait: chocolate, gum, magazine. These impulse buys, it turns out, account for $5.5bln per year in sales.

ABC retailing

Letters ABC have a special relationship with retail. For instance, there is a chain of grocery stores called ABC Stores on the islands of Hawaii, that sells delicious chocolate covered macadamias. They are so widespread in Oahu, that some people say that “ABC” there stands for “all blocks covered”. They are also pretty often photographed, and for that reason for some people it stands for “always bring camera”.

Another meaning of “ABC” in retailing comes from inventory analysis – it is a classification system often used for products sold at a store – those that are “Type A” generate the most revenue, “Type B” generate some, and “Type C” – would be some obscure stuff kept on bottom shelves. And while those macadamias are surely Type A for the Hawaiian chain, the question is what are the type A products for a typical American grocery store?

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To queue or not to queue?

I wanted to write about this for a while. Our economy has become more service oriented than ever (in fact 76.7% of its GDP is services, about 1% is agriculture and the remainder is manufacturing). The problem with services is something called simultaneity, that is they are consumed as they are being provided. It typically means that a server can serve one customer at a time and if there are more customers, well, they have to wait.

Waiting is not very pleasant. So companies go all sort of distances to reduce it or at least manage the perception of waiting. A classical example (and a success story) is Disney’s fast pass where you can basically take a ticket and come back at a pre-specified time to enjoy an attraction. What is interesting is that retailers have joined the pack and now they use something called “queue busters”. They have been doing snaking lines, express lines, and self check-outs for a while, but queue busting goes beyond this. This WSJ video and article explains how (hat tip to Richard Gaines, alum of my 351 class, for this link). It also has a quite nice infographic.

Vodpod videos no longer available.

First, two facts from psychology of waiting. It turns out if men wait for more than 2 minutes  our perception of wait actually doubles. For women such inflation happens after 3 minutes of waiting. And if we feel like we are waiting a lot we may skip the purchase altogether. What do retailers do about it?

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On the power of randomization: Selling diapers to pregnant women

I posted before on how Priceline uses randomization to conceal the minimum price they would be willing to accept in the Name your own price channel. Here is another example on putting randomness to work. This one is from retail.

Whether we like it or not, retailers do accumulate a wealth of data about our purchasing patterns. Every time you use a credit card, coupon, or a loyalty card, transaction data is logged and stored. The data is obviously used to send you more coupons, ads and peddle new products. Now, how much can retailers learn from this data? It turns our quite a lot. As this article from the forthcoming NY Times magazine describes, Target can actually predict whether a woman is pregnant just by analyzing change in her shopping patterns.

Pregnancy is a sensitive matter, however, so when a week after shopping a bunch of coupons for maternity clothing and baby products arrives in mail, women can get upset. It also looks awful lot like spying – does not it? Lesson #1 – one has to be very careful with this kind of data. Lesson #2 – even if data suggests something, do not necessarily pursue the opportunity at full speed. Here is what Target does: they randomize. Put a coupon for wine glasses next to diapers and office furniture next to pacifiers. Combinations seem to be quite ironic. But it does seem to work – the same article reports substantial growth in maternity and baby product sales for Target after they started doing this.

Labels and supply chains

Interesting information you can get from reading product labels. And I am not talking about food ingredients. What I am talking about is how long does it take from the moment a product is manufactured until it is sold? Or even, how long can a manufacturer afford this lead time to be? Lead times are tricky and rarely reported by firms. Longer lead times mean more working capital and pose challenges for forecasting, because firms have to decide how much to produce well in advance. In fact, in this paper I argue that retail sales forecasts (and inventory budgeting) for the next year are done 6 to 12 months before it starts. Anyways, because lead times are so tricky, I always welcome first hand data that documents them.

In this case the data comes from two product labels – one from Ikea and the other is CB2. Both related to furniture bought by me in the beginning of February. It turns out that Ikea manufactured that product (it was a chair) on May 26, 2011 in Mexico. Moreover the cover for that chair was made on the 16th week in 2011 (that is around Apr. 20). The chairs from CB2 were made in Taiwan by vendor Elegant Products and shipped from there on Aug. 4, 2011. Which gives almost 9 months lead time for Ikea and 6 months for CB2. Again these are the lead times after the product is manufactured. Actual decision about manufacturing them had to be done before that.

Give or take, it seems that Ikea’s lead times are about 50% more than CB2’s. And it makes sense, given that Ikea’s assortment rarely changes (aside from seasonal items) and CB2 tries to follow the contemporary trend.