How can generative AI optimize your daily workflow?

💡 Artificial intelligence vs. generative AI: why the distinction?

According to BPI France, generative artificial intelligence is a subfield of AI focused on independently creating new data and content. It differs from traditional AI, which typically handles specific tasks like classification, prediction, or data-driven problem-solving. Instead, generative AI aims to produce novel outputs such as text, images, or music that closely mimic human creation.

Since their emergence, generative AI models like ChatGPT and Gemini have gained massive traction within the market research industry. By automating routine processes, these freely available technologies can significantly accelerate research lifecycles, allowing professionals to shift their focus toward high-value, strategic tasks.

Drawing from our own experimentation, here is how research managers can integrate these models into their workflows to maximize productivity:

🎯 Calculate incidence rates

Determining the incidence rate of your target population is a critical step in study planning. Unlike models with static knowledge cutoffs, Gemini's access to real-time information makes it easy to estimate these rates by querying specific audience parameters. You can then calculate the exact incidence rate against the total population of your target geographic area data Gemini can readily provide.

This preliminary data provides research managers with an informed perspective when defining their methodology or finalizing sample selection criteria.

✏️ Writing your questionnaire

Writing a structured questionnaire is a delicate step, but generative AI can be a valuable help.

By clearly defining the study objectives, insights managers can solicit its assistance to:

• generate a relevant set of questions tailored to their research structured into a complete questionnaire. Specify your prompt to allow the AI to respond precisely to the need: length of the questionnaire, number of questions, themes to cover, number of open/closed questions, etc...
• generate answer choices for closed questions adapted to the target population and exhaustive. This will help notably reduce biases discussed in this article!
• translate it into a hundred languages; today the results are as qualitative (if not more) as with DeepL or GoogleTranslate.

This collaboration facilitates the design process of the questionnaire, while optimizing the quality of the collected data.

📐 Correctly formatted

It is often said that form should serve function. And this is also true for marketing study questionnaires. The formatting of a questionnaire is crucial to ensure the consistency of responses. Generative AI can help effectively organize questions from a rough version of the questionnaire, while ensuring clarity and logic in the flow to achieve optimal structuring. It allows for adapting the tone to a specific target if necessary: more or less familiar, more or less formal, informal / formal address, with or without emojis...

In this case, our conversational technology requires a specific format punctuated with emojis and a familiar tone to ensure respondent engagement: this is something ChatGPT can also assist with (we’ll provide our prompt tips at the end of the article)!

🔎 Analyzing study results

Once the data is collected, the analysis phase can also be greatly assisted by ChatGPT.

To facilitate the analysis of quantitative data:

• By providing it with a dataset, it can write a synthetic analysis of this quantitative data. At Episto, we are already envisioning facilitating the analysis of closed questions with comments integrated into our platform generated exclusively by AI. Stay in touch for this new feature 😉

But especially to save time on the analysis of verbatims:

• Cleaning a set of verbatims by detecting those of poor quality to eliminate the least engaged respondents
• Coding the verbatims by identifying themes and classifying each of them. This also allows reading responses to open questions in chart form (by theme or occurrence for example)
• Synthesizing by accessing a summary of responses to an open question with one click (already available with the Summarize feature on the Episto platform)
• Querying the database by simply asking a question (Explore feature on the Episto platform)

This assistance speeds up the analysis process, allowing professionals to focus more on interpreting results and formulating strategic recommendations.

In conclusion, the integration of generative AI into the daily work of research managers offers a series of advantages, ranging from planning to result analysis. By leveraging these capabilities, insights professionals can optimize their operational efficiency and make the most of HUM (human intelligence) for different types of missions, thereby enhancing their strategic contribution within their organization.

Find all our prompts to help you in your daily life in our guide !

* Photo taken by Welcome to the Jungle from Marie (Customer Success Team Lead) and Quentin (Fullstack Developer) at Episto