Framing product recommendations in online stores

Most online shops feature recommendation bars to make consumers aware of suggested purchases. The way of presenting these suggestions differs significantly from webstore to webstore. Their suggestions are framed in simple terms such as “more …. ” (Ikea), “others also bought” (H&M), “if you like this, your might also be into this” (Urban Outfitters), to more advanced suggestions helping customers to find related products “frequently bought together” (Amazon), or “do more with your purchase” (Best Buy). How effective is the framing of related products of these websites? Does the way it is framed matter? Nearly every webstore has a slightly different name for the recommendation – which seems to point to a specified strategy.

Recommendations of Urban Outfitters of similar products (this is not upsetting since the suggested items are not more expensive or profitable)
Recommendations of Urban Outfitters of similar products (this is not upsetting since the suggested items are not more expensive or profitable)

 In the end, besides helping customers navigate through a dizzying number of products on offer. Whether mentioning it is recommended for them, for the product they have selected or a favorite of other customers, these efforts have the goal to sell more products. They aim at either cross-selling or upselling (Moth, 2012). Cross-selling means that users are shown additional items they can use in combination with the selected product, or that are identical to the selected item. Upselling of products means that a similar product of better quality or with more features is suggested. Whereas cross-selling only drives 0.2 percent of the total number of purchases, upsales drive 4% of the purchases (Moth, 2012).

Example of cross selling from Amazon
Example of cross selling from Amazon

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Customer information and promotions: Quid pro quo

Ahold is an international retailer that operates supermarket chains in various countries, amongst which Albert Heijn (Netherlands) and Giant Food Stores (United States), in which they implemented BonusCard programs, respectively introduced in 1998 and 2000. Both cards are required to receive discounts, but while the AH card can be kept anonymous, Giant card holders have to reregister their card, giving their full name and home address every fall, to avoid deactivation. It appears that the amount of personal information required in these programs is directly related to the discounts that can be obtained. The more information is required, the more discounts are awarded.


Whereas in US, customers’ privacy concern seems relatively low when the BonusCard was just introduced it faced active protests. These ranged from mass e-mailings to Giants then CEO, to online BonusCard swaps where people could exchange their cards’ barcodes. This probably has to do with the many advantages of the card, which does not only give discounts but which through the A+ school rewards program also donates 1% of the total purchase price of each customer to a school of their choice. On top of that, the card also gives significant discounts on gas, up to $2.20 discount per gallon (which amounts to a 60% discount) at Shell.

The Albert Heijn’s customers received the BonusCard with more suspicion. Of the 10 million new BonusCards that were handed out since bonuskaartOctober 2013, only 2.5 million were activated online. Each customer receives discount if they have a card, but if they link this to their e-mail address they can also view the groceries they have purchased in the past, which of these are on promotion, and receive personalized promotions. Entering further personal details is not required.

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My Starbucks Idea (revisited) – Consumers’ feedback in product design

Every day, several dozens of Starbuck’s customers share their idea online about how to improve the customers’ experience at their favorite coffee place. They do so on MyStarbucksIdea, a simple but well-designed website that somewhat resemble a blog.  Up to now, more than 190,000 ideas have been collected on MyStarbucksIdea.  Besides allowing the customers to offer possible products or concepts, Starbucks also engages its customers through daily survey, test, games, etc…


But what’s new with this website? One might say that it’s simply another way to collect and monitor the customers’ feedback and satisfaction. The difference with a regular customers’ feedback tool has a twofold nature. Firstly, the extent of the customers’ feedback breaks apart from the previous habits. The customers not only grade and comment the new products but also offer ideas for the next step the corporation should take. Secondly, the extent of the following innovation taken by the firm is new. On average, 3 new products, concepts or variation are tested somewhere every week due to an idea posted on MyStarbucksIdea.

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Like a Thousand Ants Working as One

As more and more scientific research in, for example, astronomy and biology uses computers more and more intensely, computer calculating time has become scarce. Of course, the calculating power has come a long way from when mental calculating still outran the best computer, but running thousands of simulations of how a certain drug molecule docks with HIV proteases  within a limited timeframe is still outside the realm of even the best supercomputers. And this is where the consumer steps in.

Millions of people have computers connected to the internet nowadays. You start yours up in the morning (at least I do), check your email, maybe work a few hours on Word, check out some websites, etc. Then, after dinner, you might really get into it and play a MMORPG  for some hours, before shutting down the computer. Computer use? Like what they say about your brain: about 10%. The only time your computer is actually working hard is when playing that demanding online game. Now how about using the remaining 90% for the good of humanity? And this is where the World Community Grid (WCG) by IBM steps in.


The WCG offered volunteers the possibility to (in)directly aid in scientific research by ‘lending’ some of their computer’s calculating space to research projects. All you do is download a programme that will run in the background, uses processor cycles that are currently not being used. It runs a simulation, packs up the data afterwards and sends it back. Next simulation. Since its start, the WCG has used thousands of years of calculating space, saying that they’ve done “the equivalent of hundreds of thousands of years of research in less than a decade” (1). The projects the WCG runs range from looking for HIV medicines to improving the efficiency of solar cells to the search for low-costs water filtering systems.

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