Tag Archives: Online

Aggregating user reviews across online services

In the offline world, you often don’t know the background of who you’re transacting with. To gain insight into this, you perform reference checks by asking people who you do know whether they know the person you’re about to transact with, and if so what their past experiences in dealing with that person have been.

Many online services allow for anonymity. This makes it more difficult to transact on such services than in the offline world.

However, an even greater share of online services, often based on real world identities, offer a more trustworthy environment for transactions than that provided by the offline world. They do so by aggregating and displaying the collective transaction reviews of a particular person for the viewing of future individuals who are considering transacting with that person. They effectively make available the references provided from people beyond your own network, and this makes it easier to reference check the person you’re about to transact with.

User reviews on sites like Amazon, Uber, and Airbnb are great examples of this.

The shortcoming of the user reviews made available by current online services is that these online services operate in siloes. When transacting on Amazon, you can only see the Amazon reviews of the person you’re transacting with. You cannot see the reviews of the same person on Uber. The same is true for other services.

So existing services miss the opportunity to reflect a more comprehensive and therefore representative view of the online trustworthiness of their users, new services miss the opportunity to jump start their service by reflecting the track record of their new users from the existing services that these users use, and individual users of one service either miss the opportunity to benefit from their good track record on other services, or are able to hide a poor track record to potentially abuse a new service.

This presents an opportunity for a company, likely new and independent but also potentially an existing company with a large number of reviewed users and user reviews, to aggregate people’s user reviews across online services, and make available this complete picture of an individual’s online trustworthiness.

Toys R Us’ bankruptcy

I remember how I used to always look forward to going to the local Toys R Us store when I was a child. I was therefore suprised, and disappointed, to read the news that Toys R Us is filing for bankruptcy earlier this week. I imagine that many adults who relied on the retailer for their childhood toys felt the same way.

Most of the stories covering the bankruptcy have focused on Toys R Us’ inability to pay off its debts as the source of the bankruptcy. While that is indeed the final manisfestation of the problem which led to the company’s bankruptcy filing, this final manifestation of the problem is actually the result of the company’s profits not being large enough to cover its debts.

And the shortfall in profit is the result of the primarily offline toy retailer losing sales to two alternatives. The first is online toy retailers and the second is smartphone and tablet apps that offer children an alternative source of entertainment to toys. These are the core problems, and both of these core problems are examples of technological progress.

As tough as it is to see Toys R Us go, the fact that technology is responsible both for the company’s departure and as an alternative to the products it sold, is a small consolation.