Everyone loves relevant, up to date, honest specialisms and reviews. A size fits all 5 star ranking mentality fails to work as we need to compare apples with apples. Time, location and specialism relevance is the key to making it work
INTRODUCTION
When you compare two things, it should be apples to apples, not apples to pears. An example. Two restaurants, one a Michelin 1-3 star, vs a local cafe. Both are excellent what they do, both are given 5 stars. Same ranking but are they the same? They differ in kind, scope, and obviously how much you can afford.
Ranking becomes irrelevant to someone wanting to choose between establishments close to their location. A local specializes in certain venues, in a certain city been there recently knows things better than someone who isn’t or doesn’t.
MAIN ARGUMENT
- RATED REVIEWS ONE SIDE OF THE COIN
Is a good idea in principle. It can be improved as it ignores recency, specialism and authority.
- SPECIALISM IS AUTHORITY
If you review a large quantity of a certain establishment / thing type, Google keeps big data on ‘restaurant type’. So, if the user excels at certain establishments / things in certain post codes they’re likely to know their stuff.
e.g. they deal with various banks for home business every week and love Asian food for example. This suggests specialism. Regular good feedback from someone who knows X is better than a layman's interpretation.
A local guide is supposed to be local, postcode or city driven (LA for example is huge). They should also know what is 'un-authentic' vs. 'authentic' experiences for local food etc.
There is a lot of over positive and misleading reviews. Take ‘the best’ burger / pizza etc in a location. It cannot be true.
Why?
- An inquisitive local guide is always trying to find something better. Writing 'the best X' in location reviews are misleading, finite and stuck in time (see next main point).
- Conclusion: Specialism is location based. If a person from X location with X knowledge should mean, they know their stuff vs, person Y talking about X, who has not done X before.
This happens a lot with foreigners who post more than locals. Thus, high ratings are given, which are not relevant for locals.
- FREQUENCY AND RECENCY IS RELEVANCY
If content and reviews are fresh, then what is reviewed is fresh (think Google Caffine).
If a person visits and revisits a place and frequently, the standards should stay the same or go up. This person also is closer to the subject matter. Thus an expert.
Nowadays, we must reedit a post. Why not allow a second review and have threads of how the review changed. So.. users can see evolving reviews and hopefully a business getting better, or not 😉
SUMMARY & SOLUTIONS
Big data can solve specialisms, local locals, and frequency. Updated reviews can be threaded ( the owner can reply to each review and each is saved). The app could showing an increase or decrease in rating via another view. Equally, it could show which places are very popular with local guides and which ones not. There's lots of possibilities.
The big difference between my suggestion and other apps isL the app says what you’re good at, you don’t choose your specialism.
The present rating system favours long term kings, rather than grass roots local specialists. Using behind the scenes data gives credibility to local guides and should be a good move against false or paid for posting. Finally, the top or first to see review may be interchanged between ‘local, regular, relevant specialists.
What do you think?
2022
