Generative AI is a type of artificial intelligence designed to generate new content, like text, images, audio, or video. Unlike traditional AI systems that rely on explicit programming and rule-based logic, generative AI leverages advanced machine learning techniques to understand and mimic patterns in the data it's trained on.
In the context of language models like GPT-3 (Generative Pre-trained Transformer 3), generative AI is capable of creating coherent and contextually relevant text based on the input it receives. It can understand context, follow the structure of language, and produce human-like responses.
This technology has great potential to automate tasks, enhance creativity, and assist in complex problem-solving scenarios. Especially within the market research and insights space.
Here are 6 ways Generative AI is already being used in market research today:
1. Strategic Research Recommendations
When you’re first beginning your research journey, generative AI can give you initial guidance. Working with an AI consultant (like our very own Ada) you can share some context around your business and product, like objectives, challenges, and target audience (if known). And in turn, personalized receive research recommendations on the right tests and experiments to hep you achieve your goals.
For example, let’s say a startup founder is looking to refine and de-risk their product before launch. They have a strong product design but need to dial in on the pricing, features, and messaging. Working with generative AI, you would learn:
That a Van Westendorp Test will help you determine an optimal price for your product. Feature testing will help you gather feedback on your potential features, allowing you to choose the most needed/preferred by your target audience. This data would also be able to inform your messaging strategy, allowing you to focus on the most popular features of your product.
Once matched, the tests can be automatically generated for you, meaning you only need to fill in the details specific to your product, industry, or brand.
2. Streamlined Survey Creation & Test Building
When there isn’t a test or experiment to match your needs, AI can custom-tailor one to fit! By simply sharing some background about your business and the goals for your research, generative AI can craft tests that give you the answers you need.
Let’s look at another example: let's say a customer success professional at a large SaaS company notices an uptick in user churn. A generative AI research consultant can turn that context into an in-depth survey that aims to understand:
Overall satisfaction with the productWhy a user is leaving the platform And ways they might be able to retain them
3. Sample Size Calculations
No matter what type of research you are conducting, selecting the correct sample size is crucial to the accuracy of your data. If your sample is too small, it will undermine the accuracy of your results. But, on the other hand, if your sample is too large, small differences can quickly morph into (seemingly) significant insights.
Using generative AI tools like Ada, all you need to know is the population size (estimate), your preferred confidence level (we suggest 95%), and the acceptable margin of error (we suggest 5%). From there, AI can calculate the number of respondents your test would need to have significant findings.
4. Deep Analysis
Generative AI can help you dig into your data, without getting lost in the details. With AI’s fast and powerful analysis capabilities, you can instantly get answers to commands like:
“Determine the likelihood of repeat purchases”“Investigate the impact of pricing on customer behavior”“Explore the gender distribution of respondents” “Run sentiment analysis on text data in a question”
This functionality will get you the answers you need quickly, whether you're building a report or sharing insights on a team call.
5. Executive Summaries & Key Insights
Don’t miss the forest for the trees. Generative AI tools are excellent at analyzing and condensing large data sets into digestible information. So, it only makes sense that this skill would be ideal for market research!
You can use generative AI tools to create high-level executive summaries that get straight to the insights that matter. These can be handy to use yourself or share with department heads at your organization to equip them with the information they need to make better product, marketing, pricing, and brand decisions.
6. Product & Marketing Asset Creation
Another one of generative AI’s talents is the ability to generate human-like text based on data, prompts, and context given by the user.
This means that AI tools can scan your test data to generate:
Product descriptions that highlight features your target audience cares about mostAd copy that appeals to your ideal buyersBlog posts that deep dive into your data and explore key insights and themes through your study
AI-Powered Customer Research with SightX
SightX is an AI-driven market research platform that offers you a single unified solution for product, brand, marketing, and pricing research. While powerful enough for insights teams at Fortune 500 companies, our user-friendly interface makes it simple for anyone to start, optimize, and scale their research.
And with our new Generative AI consultant, Ada, you can harness the power of OpenAI’s GPT to transform your marketing research and insights. Collaborating with Ada is like having an expert researcher, brilliant statistician, and ace marketer on your team, helping you ask the right questions, choose the best experiments, pick out key insights, and seamlessly apply them to your business.
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