What can we learn from analyzing skincare feedback?
L’Oreal is a French personal care company. It’s the largest cosmetics company in the world and has a big presence in hair care, skin care, makeup, etc. Not so long ago they launched a new online shop exclusively for their hair products, hair.com
We were interested in finding out how L’Oreal products are being received online, and see what we could learn about analyzing feedback on skincare products in general. We decided to grab 1 314 reviews from amazon about their Collagen Face Moisturizer. We then ran the reviews through Gavagai Explorer for instant analysis.
Here are 4 things we could see!
The topic “moisturizing” correlates with a grade average of
4,50 / 5. Compared to the overall grade average of the project,
4,23 / 5, it’s mention brings about an increase in the grade-average. It’s mentioned in 12% of all reviews and often in connection to the topic “collagen”.
Another topic that correlates with higher grade averages is the topic “smooth”. It correlates with an increase of grade average by 0,45 / 5 and occurs in 7% of all reviews. The topic is often used in connection to “soft” and “moisturizing”.
Try for free!
Get a free trial for one month. Try out all the Gavagai Explorer features using your own data.
Sign up here
A topic that correlates with a decrease in grade average is “thick”. It correlates with an average grade of 3,82 / 5, compared to the overall average of 4,23. It is used in 8% of all reviews and is often seen in connection with the topic “greasy”. Worth noting is that positive sentiment for the topic “thick” has decreased over time but it’s mentioning rate has stayed constant.
The topic “oily” correlates with the highest decrease in the overall grade average. It occurs in 4% of all reviews and correlates with a grade average of 3,62. Oftentimes it is seen in connection with “thick”, and “greasy”. It follows the same pattern as “thick”, positive sentiment for the topic has decreased over time.
What can we tell from this?
L’Oreals Collagen Face Moisturizer has a good average grade score of 4,23. The data seems to show that the face moisturizer does moisturize. Though we might be seeing a shift in how thick consumers want their face moisturizing creams.
Being “moisturizing” and “smooth” might come at the price of the cream being “thick” and “oily”. Reviewers who mention those topics give worse grades, which might mean that they don’t like those aspects of the product. The data also points to characteristics of thickness and oiliness becoming less appreciated over time. What this might mean is that the face cream market might be (or should be) shifting towards lighter creams.
Want to try this kind of analysis on your own data?
Gavagai Explorer is free to try
(no credit card needed) and works in 46 languages.
Gavagai is a Swedish language-tech company using advanced AI to help businesses analyze text and feedback – so they can understand their customers better. Spun off from the Swedish Institute of Computer Science, our Word Space Technology has grown and improved over 20 years, and our research team has published more than 400 academic papers.