Example AI processing of a verbatim from a recent Conversational AI study.
Our grounded research and unstructured data expertise allows us to blend in the latest Generative AI advancements.
We started our journey in 2020, with a goal of using open conversational data to extract both quantitative and qualitative insights from the same source. To achieve this, we employed classical research and natural language techniques. Since then, we have expanded our expertise beyond classical AI and have become proficient in leveraging the potential of generative AI. This has enabled us to transform unstructured data into innovative solutions, including the creation of new metrics that make research data more actionable.
We believe in the power of human-AI collaboration to extract the best insights from complex data, and hence we utilize AI tools to support our experienced researchers in problem-solving.
AI analytics finds the actionable layers in unstructured data: the who, what and the why.
AI analytics allows research participants, to describe their hopes, dreams, ideas and fears in their own words, without losing their energy in a tiring grid like survey of the past.
We specialize in analyzing language by delving deep into words, their types, and frequencies. By doing so, we provide a comprehensive understanding of crucial topics, themes, and sub-themes without being limited to predefined notions.
Our approach involves the use of open data, which includes text-based conversations, comments, images, or videos. Through the analysis of open data, we uncover resonant stories that help us comprehend the context of people's decision-making. This approach also helps us understand the emotions, aspirations, hopes, and dreams that motivate us.
Open data reveals nuanced sub-themes and the subtle interplay between them, which is essential for clients who aim to deepen their brand or category understanding. As a team, we at Hello Ara believe in the power of open data and combine top-notch natural language expertise with experienced researchers to uncover the insights and nuances you need.
Hello ARA ESOMAR won the prestigeous Best Paper of the Year 2022 for #EXPLORE: Understanding Future Brand Users
In this paper we used Conversational AI, Computer Vision and AI audio analytics to understand future brand users in South Africa and Kenya.
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"My tracker data has changed, and no one knows why... we can only speculate! 😒"
The power of open conversations lies in capturing people's thoughts in their own words.
We are often asked to investigate issues with existing trackers that have been in use for a long time. This is because in times of rapid change, tracker data can quickly become outdated. Although they may measure aspects that are useful for KPI reporting, they may fail to assess changes and risks in the market. The obsolescence of trackers occurs because of shifting goalposts, triggered by factors such as new economic data, the entry of new competitors, or the introduction of new technologies, products, or influencers.
We believe that the most effective way to understand change is by deeply listening to those who are experiencing it. The key to gathering this insight lies in open conversations and advanced unstructured analytics.
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Hello ARA data hub
We created the Hello Ara data hub, to ensure consistency and scalability. Our data processing capabilites include Conversational survey data, CRM, Social and Employee data.
The Data Hub is a system that processes different types of data such as text verbatims, CRM data, closed questions, images, audio, and video. It extracts meaning and insights from these data and presents them in a consistent format. These insights are then integrated into Power BI for comprehensive analysis.
The Data Hub combines classic Natural Language Processing techniques with the latest in Generative AI-driven insights. Our team has found that open-ended questions provide a more accurate measure of customer experience. Interestingly, we have observed that 20-30% of verbatim responses do not align with the closed attribute ratings provided by customers.
Our team has vast experience in processing CX verbatims with accuracy and care. This ensures that you receive precise and actionable guidance based on your customers' voices. Moreover, by leveraging Large Language Models (LLMs), we're able to generate new, actionable, and trackable metrics that extend beyond traditional sentiment scores.
By Using Conversational Data we can transform Customer Dreams into Concepts, Media, 3D Worlds, and Stories!
We go beyond mere summaries. We map the words of your customers to actionable growth frameworks, bringing their hopes, dreams, and fears to vivid life through images, audio, and interactive experiences.
By leveraging the capabilities of Large Language Models (LLMs) such as ChatGPT, we process and summarize OpenData more efficiently, pioneering new research techniques, like actionable metrics, that enable our clients to find solutions more quickly without compromising on research depth.
Prompt: Cinematic photography of a Vietnamese influencer on a beautiful beach drinking an energy drink, render, ultrarealistic, unreal engine, sharp focus.
The insight: Consumers wanted to connect the softdrink with authentic and relaxing natural experiences.
Case Study
Our Rapid AI wave bot allows you to monitor and action change during an ad campaign. It reinvents tracking - from a tick the box to something useful.
2023
Our Rapid wave bot was usd to measure an ongoing promotional retail campaign.
By combining closed questions, traditional NLU and LLM technology, we created a bot, that was launched, and followed a large series of promotional work for a significant online retailer. On a daily basis, we were able to provide rich reports and an updated PowerBI dashboard to ensure the client was able to optimize language and adjust offers on a daily basis.
The conversational data we collect from Chatbot research is easily leveraged by LLM’s such as OpenAI, or image generation programs such as Midjourney to create new, more accessible and meaningful research.
An LLM, or Language Model, allows us to summarize and quantify unstructured data with less upfront work that was previously required. Additionally, it provides the necessary tools to make our insights more impactful. We do not use Generative AI for everything; instead, we utilize it in areas that play to its strengths. These areas include coming up with tracking measures that go beyond the usual positive/negative, and where we require data visualization for storytelling or collaboration exercises.
In this example, this Generative Avatar is reading out summaries from a recent sustainabiity project, creating a deeper, more inpactful connection with the data. This Avatar can also be brought to life so a client could ask it questions.