One of the newish lines from the March 2022 Google Product Reviews update, which is now completely rolled out, announcement is where Google said "including original images from tests you performed with the product can be good ways to do this" But writing that you tested a product in your content is not enough to convince Google you actually tested a product.
Alan Kent from Google was asked about this by Vlad Rappoport on Twitter and Alan replied "don't expect big boosts if the review only adds a few sentences saying 'I tested it myself too' with the rest paraphrasing the original product description." So again, just putting a label that you tested the product onsite or writing that you tested it onsite, is simply not enough.
Look at the overall best practices for product reviews from Google to see what Google really wants. Alan also added on Twitter "I would focus on the intent: create useful, authentic, trusted, reviews that bring new insights and deliver value to users. The published best practices are guidance towards these goals, not binary in/out decision points."
So again, this is not about having a couple words that says tested and approved or some meta tag, it is about the content itself showing that you actually tested it. Now, not all reviewers can test all products they review, but the best ones can. They some how manage to get the product, either as a loaner from the manufacturer, or they buy it themselves to test. Heck, I am buying a super expensive Lucid Air and that will help me really be an authority on it for my Lucid Insider blog. But Lucid Motors gave loaners to car reviewers so they can spend time with the car and test it themselves and some even bought the car and spent weeks with it before publishing their reviews. I also looked deep into forums to find feedback from real Lucid Air owners for some of my content. But I won't fully understand this car without owning it myself. It is just the competitive content world we live in these days.
Here are those tweets:
You can certainly create a useful review without eating the product. E.g. people know too much sugar is not good for you. But dont expect big boosts if the review only adds a few sentences saying "I tested it myself too" with the rest paraphrasing the original product description
— Alan Kent (@akent99) April 13, 2022
Given ML models will never be perfect, I would focus on the intent: create useful, authentic, trusted, reviews that bring new insights and deliver value to users. The published best practices are guidance towards these goals, not binary in/out decision points.
— Alan Kent (@akent99) April 13, 2022
Forum discussion at Twitter.
