---
title: "Experiment-Level Language Insights"
slug: "experiment-level-language-insights"
updated: 2025-07-10T16:07:59Z
published: 2025-07-10T16:07:59Z
canonical: "support.jacquard.com/experiment-level-language-insights"
---
> ## Documentation Index
> Fetch the complete documentation index at: https://support.jacquard.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Experiment-Level Language Insights
Jacquard's language insights give you a glimpse into the scientific experiments Audience Optimisation designs for your brand. The automatic insights and data visualisations allow you to see what is being tested and resonating with your audience. Language insights are currently available for broadcast and trigger projects.
This article covers the language insights available at an **individual experiment level**. Check out [this article](/v1/docs/project-level-language-insights) for information about language insight reports at a project level.
## **Where can I find them?**
Language insights are automatically displayed at the experiment level **once the results for your experiment are received** (i.e. completed experiments).
To view the insights for a given experiment, simply open the completed experiment and navigate to the **Insights** tab at the top of the page.
[](https://downloads.intercomcdn.com/i/o/474980984/205fb0f58f9c1a0b1128f827/Campaign_Level_Insights.png?expires=1749503700&signature=00b3b57d29db83ab2b51b6be023b77e52082ee391ba37c140c8159fb0c0aead2&req=cCcjH8F%2BlIlbFb4f3HP0gELjCCGvyoqklxNi0J36BkQH%2BPXIlL9AlfmYBo1r%0AGU0WXR9VvajLYpR8qQ%3D%3D%0A)
## **What am I looking at?**
Experiment-level language insights give you a look under the hood at what sentiments were tested in each send. Jacquard analyses language against seven key positive sentiments found within marketing language.
After Jacquard has received the results of the language test you can:
- Explore the levels of the seven sentiments within your test variants.
- Use the tooltips to gain insight into how you might apply these sentiments across your marketing copy outside of Jacquard.
- Click on the sentiment titles surrounding the chart to see which words in your test variants Jacquard thinks contributed most to each sentiment.
### Jacquard **sentiments**
Sentiment is one of the features of language Jacquard loves to test in each experiment.
Sentiments can be dialed up or down and still be within a given brand's tone of voice. So by testing a wide range, you’re able to see which distribution engaged your customers most and how this changes from experiment to experiment.
The sevenkey positive sentiments found within marketing language are:
| **Sentiment** | **Common sentiment features** |
| --- | --- |
| **Impressed** | - Emphatic adjectives around products or promotions (e.g. amazing prices) - Positive direct address (e.g. 20% off because you’re awesome) - Capitalisation - Exclamative phrases (e.g. OH WOW!) |
| **Helpful** | - Informational or instructional (e.g. save on your trip) - Practical and direct language (e.g. we’re here to help) - Focus on benefit to the recipient (e.g. treat yourself) |
| **Curious** | - Questions (e.g. have you heard?) - Use of ellipses and hanging sentences (e.g. too hot to miss…) - Intrigue over directness and specificity (e.g. we think you’ll like this) - Use of social proof (e.g. find out why everyone’s talking about…) |
| **Excited** | - Capitalisation - Exclamation points - Enthusiastic language (e.g. we’ve got some amazing news) - Building anticipation (e.g. the countdown is on…) |
| **Surprising** | - Mystery and intrigue (e.g. uncover today’s discount…) - Hyperbole (e.g. unbelievable products inside) - Colloquial exclamations (e.g. omg!) |
| **Appreciative** | - Politeness strategies (e.g. a little thanks from us) - Assumption of customer satisfaction (e.g. no need to thank us) - A “you’ve earned it” tone (e.g. you deserve a treat) |
| **Urgent** | - Promo duration specifics (ends in 2 days) - Limited-time language (save before it’s too late) - Limited-range language (save on shoes before they’re gone!) - Use of exclamation marks |
### **Sentiment radar graph**
The radar graph displays the distribution of sentiments within the language variants that you've tested with Jacquard. This lets you see what Jacquard is testing and what your audience is engaging with.
You can hover over the tooltip next to each sentiment to view the common features of that sentiment.
[](https://downloads.intercomcdn.com/i/o/475012049/2530a9bd8c0a2fc952e780ee/image.png?expires=1749503700&signature=1ee9d42a35cb2f4d2e248d3e018a4f78a1d855eaeacda6d37c44e4a835dec49f&req=cCciFsh8nYVWFb4f3HP0gPNqtc51gqB33MvJwguVWxwjIyL%2FvHAPwqTSz%2F3C%0AOpkAT7TXgf%2FOq8WTZw%3D%3D%0A)
By default, Jacquard displays the three top-performing variants on the radar graph. You can change the graph view by selecting or unselecting the checkboxes next to the variants in the table below the graph.
[](https://downloads.intercomcdn.com/i/o/475020607/fb4206254766c64c7043992a/image.png?expires=1749503700&signature=424a857d8e7eae4aeaad14223a6d2a1793ee0e8f49064ceaadebe4fe5a6f791e&req=cCciFst%2Bm4FYFb4f3HP0gCu9ddkR6Tf54T8P5iNBnYoSmNNPhYb4ODGPZBbU%0ACnTX8GG1xRm7CIQoyA%3D%3D%0A)
### **Sentiment variant table**
The variant table underneath the radar graph displays the sentiment scores across all seven sentiments for each variant. The score is out of 10. The higher the score for a particular sentiment, the more prevalent it is in the variant.
You can also click the sentiment titles in the radar graph to highlight the words in the variants Jacquard interprets to contribute to the variant sentiment scores.
## **How does it work?**
The sentiment scores are assigned through the use of a multi-class classification model. The function is similar to the model Jacquard uses power and optimise your split tests - but instead of being trained on performance data, this model is trained to recognise patterns within data that contribute to the underlying meaning of language.
Each tested variant is run through the model, which calculates the degree to which the variant aligns with each of the sentiments - the higher the sentiment score, the more the variant fits into the sentiment.
The second calculation is run to determine which words within the variants are contributing most to the sentiments. This can be seen by clicking on the sentiment titles surrounding the chart.