Explaining the rise of curated shopping

With all the benefits of online shopping such as wide selection, availability and low prices some shortcomings still remain: one can never be sure that the item bought will meet expectations, the shopping experience is still lacking despite "digital showrooms" and while there is maximum simplicity a bit more screen work is often needed. For example, a search for the right digital camera, with the query "digital camera buying advice" on Google returns more than 800,000 results!
 
Another significant shortcoming for online retailers is that if a customer is unhappy with their choice, they rarely come back. For many years, large marketplaces such as Amazon and iTunes have addressed this issue with their use of customer reviews. However, there is now a growing trend that addresses some of the above and is a bit more convenient for shoppers: "curated shopping" lets retailers avoid some of the pitfalls, while improving the online shopping experience for their customers. Here’s a brief overview: 
 
Smart (and social) filters: Hard factors such as colour, brand or size have long been standard choices. New and often more critical queries are based on an algorithm of a user's preferences. Pioneers of this kind of service are hunch.com the platform, which was acquired late last year by Ebay. Other retailers, such as Etsy now also feed their ‘gift finder’ with data from social networks allowing buyers to seek out suitable gifts for friends.

Personal shoppers with a difference: Chick Chick Club, Modomoto or Hipstery remove the customer from the purchasing decision completely. Here, there is a short style check survey to complete (in the case of The Hipstery not to be taken too seriously!) enabling their purchasing consultants to use the customer's preferences to choose items. What you’ve bought, you find out only when you open the package. Often this form of curated shopping is paired with a monthly subscription model and rids the customer completely of the agony of choice overload. 
 
The community advises: Providers such as Modcloth, Threadless or la Fraise decide what is to be included in their collections only after a vote by the community. This minimises the risk that a t-shirt (la Fraise, Threadless) or a fashion line (Modcloth) will not be liked or bought. At the same time the selection process adds an emotional connection with shoppers when the decision is announced. 
 
Personalised shopping magazines: Pose, Svpply, or The Fancy combine the "collective" detection of interesting products and services through the community with added personal recommendations. This creates a personal shopping magazine.
 
Different curated shopping models take advantage of the principle observed in large marketplaces where "smart filters" are set to narrow product diversity and create ease of choice. Providers distinguish themselves as experts in their niche. Some offer favourite products from people like you and me while others are curated by known bloggers, designers, DJs and musicians. The process is enabling these retailers to engage with their customers and offer a more personalised product or service improving the customer experience which is a move in the right direction.
 
Only one thing neither an algorithm nor a style expert can take over - the payment.

 

Comments

Cynthia Holcomb
Cynthia Holcomb March 13, 2013 at 8:05 PM

Philip. Thank you for the article. The filters listed in your very informative article are just filters. The real way to understand a shopper's individual, unique preferences in aesthetic based products is to tap into the shopper's subconscious, there lies the individual's aesthetic and emotional baseline used in choice and product selection. My company, IDDiOO has completed our Alpha Preference Shopping Platform, which is currently in testing. Our technology translates real world shopper behavior into unique personal preference profiles for individuals.

Additionally, I founded, Preference Retailer, a (SAAS) service that captures customer preference analytics, both granular and macular, to use for personalized product recommendations, preference trend analytics, preferred product specifications and individualized preference based ad serves.

I am interested in connecting with others who are impassioned by the opportunities to change the way we shop using preference technologies in-store and online. Thanks for the article!