Private Shopping Clubs - The Future Of Online Commerce?

Marc Osofsky, ex-McKinsey VP of marketing for e-commerce specialists Optaros has posted a useful review of these member-only shopping clubs where members get access to exclusive online sale events, identifying what makes them work.

With popular e-commerce software such as Magento offering private shopping club modules (video walk-through), private shopping clubs are relatively easy to deploy.  So here’s a top line summary of Marc’s review, listing the critical success factors for setting up a successful private shopping club.

Key Features

• Exclusivity – Invite-only (requires an invitation from a friend to get in)
• Name Brands – quality merchandise not just cheap or out of date items
• Compelling Discounts – priced to drive impulse purchases and loyalty
• Timed Events – limited sales event at which the merchandise is offered until it sells out or a time limit is reached
• Regular Events - Sales events always start at the same time
• One Page Event List – Listing current events to browse
• Viral Invitations - member get member referral program ($10 reward per new (purchasing) member
• Social Network Integration (e.g. Facebook Connect/Twitter) easy login and member referrals
• No Site Search - Focus attention on browsing sale items to encourage impulse purchase (allow filter)
• Single/No Shipping Fee – Orders stay open for several hours to allow shoppers to make additional purchases and pay only one shipping fee (or additional orders are advertised as having free shipping)

Future Features

• Fashion Content (Editorial/Articles) – influencing shoppers through richer content around the products on sale.
• VIP Members - Special club for most valuable members (who have invited groups of people that buy the most) with extra discounts and incentives.
• Customer Idea Communities – for ideas on future sale events and site improvements
• Crowd Visualization – visial representation of shopping crowd at beginning of the events to stimulate impulse pruchases
• Social Analytics – social recommender systems that up-sell and cross-sell based on purchases/browsing patterns of “people like you” (similarity in purchasing history/tastes/social graph)