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AI Story Assist 2.0: Ask Asa! Recommended Conversation Starters
AI Story Assist 2.0: Ask Asa! Recommended Conversation Starters

Use AI Story Assist 2.0 to easily explore your datasets with simple, natural language conversations. Get started here.

Updated over a week ago

Asa, the AI-sidekick in AI Story Assist 2.0, allows users to interact with datasets using natural language.

The following conversation starters are designed to help you explore different aspects of your dataset, whether you are summarizing responses, analyzing trends, or generating visualizations. These prompts will guide you in getting the most out of Asa’s capabilities.

  1. Investigate: Ask Asa for a summary of the responses

    1. Provide a concise overview of the main sentiments expressed in the dataset, and what drove those emotions

    2. What are the key takeaways from the feedback regarding our product or service?

    3. How do the responses reflect on our brand's reputation and customer satisfaction?

  2. Investigate: Ask Asa your research goals

    1. What were the main reasons people disliked the soup?

    2. What feedback should we share with restaurant managers so they can improve their location’s NPS score?

    3. What did respondents remember about the ad? Did they recall the correct brand and product?

  3. Compare: Ask Asa about your quantitative data (close-end responses / filters)

    1. Show me a breakdown of gender and ethnicity for the dataset

    2. Which sample had the highest overall opinion ranking? Compare each sample with a visualization.

    3. How did respondents' likelihood to shop in person change over the course of 2023?

    4. Show me a breakdown of NPS group per location.

  4. Compare: Ask Asa about how specific segments responded, and how they compare

    1. What are the main differences between locations? Look at both the verbatim responses as well as respondent metadata.

    2. What are the main themes driving enjoyment of each sample? Give a description of each sample with strengths and weaknesses.

    3. Look at promoters versus detractor responses. What are the main themes driving each group? What’s different or notable?

  5. Compare: Ask Asa to identify drivers of changes in themes over time

    1. Based on the responses, what drove the increase in dislike in March?

    2. How did emotions change between Q1 & Q2, and what are the themes driving those changes? Quantify when possible, and describe what's happening.

    3. What do you think made our NPS score drop 2 points in April? How did feedback change?


    4. ​

  6. Visualize: Ask Asa to create visuals that communicate how different segments responded

    1. Can you create a heatmap showing emotion for each segment?

    2. Create a visual that illustrates the differences in theme prevalence across different rating scores

    3. Create a visual that displays the variation in emotion across different customer types

    4. Create a visual comparing the main takeaways for each location

    5. Visualize the main themes for a dataset, or segment of a dataset.

    6. Show me a breakdown of emotions by gender

    7. Please create a grouped bar chart that shows how job satisfaction differs by store location and length of employment, with an additional breakout by NPS score

  7. Consult: Ask Asa to generate strategic reports or ideation based on responses

    1. Create a SWOT analysis based on the responses

    2. Generate personas based on the responses. Include names descriptions for each persona. Then give quantified reasons for what you included in each persona.

    3. How did men feel about the movie compared to women? Which segment is our ideal target audience?

  8. Consult: Ask Asa to help you identify specific types of example verbatims

    1. Help me find the 3-5 most descriptive verbatim responses for each sample

    2. Can you find verbatims that highlight positive experiences with customer service?

    3. Please identify names of any staff members mentioned in the verbatim responses. For each staff member mentioned, provide the exact verbatim mention(s), as well as a short description of what was said about them.

    4. Surface verbatims that include specific recommendations for product improvement.

  9. Consult: Ask Asa what questions you should ask

    1. What questions should I ask you about the data?

    2. I need to create a report for our weekly insights meeting. What questions should I ask you first to begin my analysis?

    3. Give me a few suggested first prompts to request from you, based on my dataset information.

  10. Consult: Ask Asa what visualizations he thinks would be useful for you create

    1. What visualizations might be useful for my analysis of this dataset? Generate two.

    2. I need to send a report to restaurant managers based on the data. Suggest a few of the best visualizations or charts that I should include.

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