Ecommerce Browsing

Title: Objectified Ecommerce Browsing

Abstract: "Objectified navigation" may help to improve discovery and upselling when browsing in an online shop.

Context

ecommerce browsing: email (selection/curation), search, browsing

Purchase drivers

Why do you buy something?

• Offers: You become aware of a great offer and you buy mainly because of the price advantage. You would have not bought it if you'd had not stumbled upon that offer.
• Particular need: You know exactly what you need and you need to buy it immediately or within a certain close date (a Christmas present, a bag for your next trip, a costume for this weekends party).
• Ample need: You need to buy something but you you know only the category and are not in a hurry (new tires for your bike, a blender, a TV).

Discovery drivers

How do you buy something?

• Primary:
  • Email: you receive an email from an online vendor
  • Search: you know what you need and search for it (you normally start with a search engine to do a little price comparison; or you go to your top of mind seller for that category)
  • Browsing: you use the classic hierarchical category tree (mixed with search) to find and refine results.

• Secondary:
  • Recomendations: inline, email (retargeting)

Other topics to explore: Conversion drivers (When do you buy)

Limitations of browsing

There are "classic" problems and limitations with browsing which have hardly been overcomed or experimented with:

• You don't always know in which category is the product you are looking for
• The hierarchical classification made by the shop made not match with your mental model
• Switching categories is costly and tiring: browsing in lots of different categories because you can't find what you want, or because you may be interested in items located in lots of different categories is tiring and leads to a an abandoned cart
• ...

2 user cases to ilustrate:

• 1) You are browsing for an "ample need" good. You have choosen it and are ready for checkout. You could buy items from another category if they were suggested to you (but not from the same category, which are the items that would appear in "recommendations"). Just being exposed to the standard global category navigation is not enough (and in fact is hardly done).

• 2) ...

Problem: upselling/recommendations are limited to products in the same category or a very near one. What when a user may be interested in products from other categories? How can we

Examples:

• You are buying tires for your bike. Your brake pads are starting to need replacement. After adding the tires to the cart and previous to checkout you are only recommended other tires or pushed to checkout; you don't remember other items because you are just exposed to them or to some clue that might make you remember.
• You are buying a blender. You could also buy a good knife and other kitchen complements, but you are only exposed to "also bought with" which is a selection of very similar products.

• • Proposed solution**:

• • Downsides**:
• You are diverting people from checkout, which could result in a lost sale.

Business implications

• Development cost: it may be expensive to implement.
• Oportunity cost: of not showing other more effective ways of navigation.

References

• Social Media Lags Search, Email in E-commerce Conversions