Automate your work using Customer Sentiments
Facial expression, tone of voice or body language are all clues that improve oral communication but are lacking in online interactions. Yet, knowing how a customer feels could greatly improve the quality of your customer service.
How it works
The good news is, Gorgias automatically detects your customers' sentiment! Is the customer angry, in a rush or simply grateful for the service? Here's how you can figure all of that in a single glance using customer sentiments through rules.
List of customer sentiments
Gorgias currently handles the following sentiments. Stay in touch as more may come!
Name | Description |
positive | Customer is satisfied about the product, the service, or shows positive feelings about something you posted on social media. Example: "Okay that's perfect, thank you!", "That looks gorgeous!" |
promoter | Customer shows intense satisfaction about the product, the service or the brand Example: "I LOVE IT SO MUCH!!!!!! This is utter perfection, thank you thank you! I've been telling all my friends about your products" |
negative | Customer shows general dissatisfaction about a product or the service. Example: "I just received the package and I'm very disappointed." |
threatening | Customer is threatening take legal action, buy elsewhere or post a negative review. Example: "Refund me now or I will sue you." |
urgent | Customer shows impatience (multiple unsuccessful contacts) or mentions an urgent need (cancel or change an order before it ships, ....) . Example: "Ordered the wrong item. Need to cancel ASAP!" |
offensive | The message contains offensive language or inappropriate adult suggestions. |
As per the screenshot below, more than one sentiment can occur at the same time:

Setup instructions
Tagging tickets with customer sentiments
The recommended way to benefit from the feature is to apply specific tags to the tickets so that you can figure out easily if some tickets require that extra attention. Here's how to create a simple rule to tag tickets using customer sentiments.
- In Settings, go to Rules and click Create new rule
- Select WHEN new message in ticket and/or ticket created as a trigger
- Click on THEN, and select an IF statement
- Select message -> sentiments -> contains one of -> "negative"
- Click on following THEN, select Add tag as an action, and type "negative"
- Click Save
- Don't forget to activate the rule!
Negative tickets
This example shows a simple rule tagging negative tickets using both the "negative", "threatening" and "offensive" sentiments.

Urgent tickets
You can set up a rule to auto-tag the ticket if the customer is showing impatience or mentions an urgent need. Example: "Ordered the wrong item. Need to cancel ASAP!"

To go further...
Here are some other rules ideas:
- Tag
negative
/positive
feedback for one product line (use the sentiment crossed with keyword) - Auto-hide
negative
comments on social media - Auto-like/close
positive
comments on social media - Flag
promoter
customer to retarget them in the future - Modulate your auto-response depending on sentiment (if sentiment is
urgent
ornegative
, don't auto-respond)
You can also combine customer sentiments with customer intents! See our other article: Automating your work using customer intents.

FAQs
Can customer sentiments recognize emojis as well?
Yes, the sentiments detection model can recognize emojis
Can a message be positive and negative at the same time?
No, the model will highlight the "main" sentiment of the message.
For example, if the message is "I like the shirt but it started losing its color after 2 washes, I am so disappointed...", the detected sentiment will be negative
Supported languages
Intent detection works in a number of most commonly spoken languages which is a huge advantage! The feature supports 16 most commonly spoken languages, so even if the customer is writing over to you in another language, we can detect the keywords and trigger the rule.
The currently supported languages are:
- Arabic (ar)
- Chinese (PRC) (zh)
- Chinese (Taiwan) (zh-tw)
- Dutch (nl)
- English (en)
- German (de)
- French (fr)
- Italian (it)
- Portuguese (pt)
- Spanish (es)
- Japanese (ja)
- Korean (ko)
- Russian (ru)
- Polish (pl)
- Thai (th)
- Turkish (tr)