AI at Dig Insights
We think of AI as a powerful tool. Like all tools, it is more powerful when wielded by people with the right expertise. Our in-house AI expertise is used to empower our world-class researchers, ensuring that we get the best of both worlds – delivering faster, deeper insights without compromising on quality.
Our perspective on AI
Human driven, AI-enhanced
We design our processes to be human-in-the-loop, harnessing AI to amplify our researchers’ capabilities while ensuring that every insight is both data-driven and contextually grounded, making it more actionable and relevant.
Relentless innovation
We are continuously developing new AI methodologies to stay at the forefront of market research, ensuring that our solutions are not only cutting-edge but also aligned with the evolving needs of our clients.
Decision-centric
Our AI tools are purpose-built to prioritize actionable insights that lead directly to better business decisions, aligning perfectly with our mission to help clients move beyond consumer-centric thinking.
How do we select what to prioritize next?
- Current AI Capabilities: We stay on top of the field to make sure we know what cutting-edge technology and methodologies we have at our disposal. It’s about understanding what AI can do well today—its strengths, limitations, and how it can be leveraged effectively within the scope of market research.
- Human Limitations: We identify the tasks that humans typically struggle with, are inconsistent at, or perform slowly. These are areas where AI can provide significant value, either by automating tedious processes, reducing human error, or speeding up tasks that would otherwise be time-consuming.
- Strategic Value Alignment: We focus on aligning AI projects with the long-term strategic goals of both the company and the product. It’s about choosing projects that not only solve immediate problems but also fit into a larger vision of where the technology and the company are headed.
Examples of how AI is being integrated into our work
Recommendation engine
What: Allows you to lift and shift an idea from one market to another accurately without new fieldwork.
Why it matters: Get more out of your survey results, and faster too.
AI Video Moderator
What: An Upsiide question type that allows anyone to inject voice of the customer into their consumer research.Â
Why it matters: makes rapid qualitative research accessible and allows you to interrogate the say/do gap for yourself in your research.
AI Idea Generation
What: allows clients to generate new ideas, either blue sky or based on previously tested ideas
Why it matters: Smoothly integrates idea generation into platform so you can brainstorm and test ideas within minutes.
Artificial Intelligence
We’re creating radically new respondent experiences: conversational interviews at scale where our AI interviewer follows up and probes, encouraging richer responses.Â
And we’re reinventing data analysis and interpretation: synthesizing open text to identify themes and insights; summarizing, interpreting and finding the story in quantitative data; and allowing users to query their data, using natural language to ask questions and receive answers.
Open Text Analysis
What: we’ve built our own open ended verbatim coding application, which has >90% overlap with human coders.
Why it matters: Allows us to ask more open ends and report faster than ever before
Questions to ask an AI provider (so you know they're legit)
What are their AI credentials? Do they have education or are they jumping on the bandwagon?
In-house expertise ensures that the AI tools and models are not only well-designed but also properly understood and utilized within the context of market research. This depth of knowledge is crucial for customizing AI solutions to specific client needs, maintaining the accuracy of insights, and rapidly adapting to new challenges or trends.
Do they have white papers showing validation of their techniques?
If a provider makes extraordinary claims about their AI capabilities, they should be able to provide extraordinary results to back them up. White papers that detail the validation of their techniques are crucial for assessing the credibility and effectiveness of their AI solutions.
How do you handle the limitations of AI, and what safeguards do you have in place to mitigate them?
Every AI tool has its limitations, and clients should understand how these are managed. This includes knowing what steps the provider takes to prevent overreliance on AI outputs and to ensure that human oversight is maintained.
What is the level of market research expertise among those developing and fine-tuning your AI tools?
The effectiveness of AI solutions in market research often depends on the domain knowledge of the developers. Clients should inquire about the expertise of the team behind the AI to ensure that the tools are tailored to the specific needs of the industry.
What kind of long-term support do you offer for the AI tools you provide, and how do you plan for their evolution over time?
AI tools need to evolve as business needs and technologies change. Clients should ask about the provider’s commitment to ongoing support and updates to ensure the AI remains relevant and effective over time.
Q&A SESSION
Between Two Joels: Synthetic Data Edition
It turns out the hype around synthetic data is both real and exaggerated. During this Q&A session our AI experts along with co-founder Ian Ash discuss what we should and should not be doing as it relates to synthetic data.
Dig’s team is great at building stories around the data. I never have to ask, so what are the numbers telling me? We work on this collaboratively.Â
Want your AI questions answered?