Are online reviews going extinct?
From Yelp to Amazon, reviews these days are good for just one thing: Seeing what others think of a product, service, or business. But are reviews really helpful? Could they be an outmoded one-size-fits-all solution in a world where a user’s interests are increasingly customized and niche-specific? Are they going the way of the dinosaurs?
According to ‘HeyLets‘ CEO Justin Parfitt — an expert on how to use reviews to make good consumer decisions — the next generation of review sites and apps will more intelligently utilize your personal data and contextual preferences to make more thoughtful recommendations.
It’s a perfect example of the Attribute Dependency Technique, one of five in the innovation method called Systematic Inventive Thinking (SIT). It’s a great tool to make products and services that are “smart.” They adjust and learn, then adapt their performance to suit the needs of the user. Attribute Dependency accounts for the majority of innovative products and services, according to research conducted by my co-author, Dr. Jacob Goldenberg.
HeyLets (www.heylets.com) helps you do the following:
1) Shows you a personalized feed of recommendations from users who have similar interests.
2) Uses your social data to inspire you to try new things across the full range of your interests.
Even more impressive, next-generation apps like HeyLets will soon learn over time how you live your life, and be able to do things like:
- Anticipate your needs and propose activities for particular days by using information about past movements and even the weather forecast.
- Automatically disregard reviews from people with distinctly different preferences (i.e. a vegan diner who posts a at a non-vegan restaurant).
- Help you avoid less reliable reviews from “Debbie Downers” — people who only post critical updates and negative content.
To get the most out of the Attribute Dependency Technique, follow these steps:
1. List internal/external variables.
2. Pair variables (using a 2 x 2 matrix)
3. Create (or break) a dependency between the variables.
4. Visualize the resulting virtual product.
5. Identify potential user needs.
6. Modify the product to improve it.