The Yabble Virtual Audiences tool is the ultimate end-to-end AI solution for research. Making insights in minutes a reality.

Yabble’s proprietary augmented data model uses the combined knowledge of Large Language Models (LLMs), relevant and recent trend data, social data, and behavioral statistics to create a unique AI-generated audience to answer your research questions. This unique approach via the Yabble platform provides increased relevancy, accuracy, and recency of data above what a large language model alone can provide.

In each virtual audience project, you’ll have access to:

Yes, Yabble's augmented data tools have a very broad range of knowledge and should be reliable for most topics and markets. If you have a highly specialized topic and need a different research approach, contact the Yabble team via hello@yabble.com

The number of topics you can research is unlimited (2500 credits per Virtual Audiences project). For each topic, there is a limit of 250 completed responses within the Virtual Audiences environment. This gives a good indication of what a market is thinking or feeling on any topic.

In the Yabble platform, you can:

Yabble operates a 'walled garden' approach to data security. When you use the Yabble platform you are covered by Yabble's security and privacy settings which include ensuring that your data is not used by OpenAI or any other LLM to train their models.

Virtual Audiences has lots of different use cases. It's great for kicking off a project when you want to gather a broad understanding of who the customers are in a market and their behaviors. It's also great at looking at market trends, understanding changing behaviors, tastes, and perceptions, and working out what this means for your future products or communications strategies, or even looking at competitive sets and what the market sees as strengths or weaknesses of other players in your industry.

If you're looking at AI-powered insights solutions, you may have heard the terms 'augmented data' and 'synthetic data' used interchangeably. There are some key reasons why Yabble's proprietary augmented data model is superior when it comes to AI-generated data for insights.

Synthetic data is like creating a digital twin of real-world data. Think of it as a simulated dataset, created to resemble the real thing without using any real details.

Augmented data is like giving your data a boost. It's taking the original data and enhancing it to make it more complete and more useful. Think of it as adding extra details or features to existing data to get a clearer picture. This is why we choose augmented data for market research – it is both grounded in reality and optimized for the most profound insights.

Ultimately, anything built on an LLM will have an inherent bias based on the corpus (training data) and how it was trained, specifically with RLHF. However, we don't solely rely on LLMs to create personas, we search proprietary, public, social...etc... data to find the relevant demographic information for people who would be interested in the topic entered into Virtual Audiences. We use this to generate demographic criteria for personas, and then through subsequent steps we begin to fill those criteria.

This does not mean there is no bias - there will always be bias, as there is likely to be with traditional research, but we mitigate the detrimental aspects of bias to the best of our capabilities, as you do with traditional research.

Yabble's Augmented Data model revolutionizes the process of insight generation by integrating diverse data sources, including proprietary datasets, academic content, and real-time web searches, with advanced machine learning algorithms. This method transcends traditional surveys and human feedback, utilizing generative AI to synthesize data into comprehensive knowledge lakes. In this model, data amalgamation serves to create detailed personas, formulate relevant questions and answers, and distill key insights, offering users a nuanced, multi-dimensional view of their topics of interest and delivering precise, AI-driven insights.

Our current model uses open-ended questions to provide you with rich insights into your topic or business question. This model has gone through extensive testing to ensure insights provided are deep and accurate. All open-text answers can be quantified through the Yabble Count tools. This will be done automatically, and you will be alerted when the data is ready for review. Over time, we will introduce new question types once we are confident in the validity of the data from these new question types.

Currently, you can run short text-based concept tests through Virtual Audiences either as a single topic or via the survey questions. In the future, we will introduce the ability to add concept boards and imagery for the Virtual Audience to feedback on.

In cases where you can see duplicates of the same parent URL in your source list, this is because Yabble's augmented data model has visited multiple pages on the same site to get context for your project ie. http://www.transfertravel.com/page1 and http://www.transfertravel.com/page2 etc. We do not currently display the full URLs for sources.

To get the most out of the proprietary data feature of Virtual Audiences, types of data best suited to the tool:

Where possible, provide data in string format i.e. data labels rather than numeric codes.

There is no need for personally identifiable information (PII) in any tool in the Yabble platform – in fact we advise no PII is ever uploaded (using anonymized IDs if required). PII will not add any benefit to the insights Yabble creates.

Yes! You can upload up to 10 files (max file size 2MB each) to one Virtual Audiences project, and they do not need to be the same file type.

There are several different file types that the Yabble proprietary data feature accepts, including .PDF, .CSV, .TXT, .DOCX, and .XLSX (max file size 2MB each).

Virtual Audiences projects can take as little as 15 minutes to complete from topic input to insights output – but this will vary based on the quantity and size of the proprietary data you upload to the project i.e. the more data you provide, the longer the process will take for the AI to read and process the data.

When creating the Knowledge Lake for your Virtual Audience the AI will read across all data provided.

The extent to which it ‘relies’ on your proprietary data to create its personas, synthetic respondents, and answers will vary depending on your data volume, content, completeness, and the relevance of your data to the questions you have asked. As well as the recency of your data.

As all data is multi-dimensional, some data is more valuable to the process than other pieces, and this is decided by the AI on a case-by-case basis depending on the research or business question you have asked. Also, the ability for the data to be cross-referenced/validated between sources.

Yabble will always create the Knowledge Lake using a combination of sources, but the utilization rate of each source will vary dynamically depending on the question being asked.

Yabble’s AI also has a recency bias inherent – so, as an example, if the proprietary data you upload is from 3 years ago, the AI may find more recent information from our other sources.

If you have any specific questions about Virtual Audiences and how this works with your own data to provide insights, contact the team at support@yabble.com.

Yabble’s AI will read across all data provided. It is assumed that you will provide data that is related to the topic, however, if there is some unrelated data, the AI will be able to ‘clean and ignore' this data to an extent.

As the product is in beta, edge cases where data is entirely unrelated may provide poor results.

If you have any specific questions about Virtual Audiences and how this works with your own data to provide insights, contact the team at support@yabble.com.

No, not at this stage – coming soon.

No, not at this stage.

If your data doesn’t include any demographic data, the Yabble AI will recommend and generate target demographics, based on data it has gathered from other sources. This can always be regenerated later by you before you complete the project if you would like to.

Note: The proprietary data will still be used to form the persona’s personality characteristics and behavior even if demographics are absent.

There will be demographic-specific insights and general insights in the proprietary data. Insights specifically relevant to the non-target audiences might be disregarded when generating insights. But, all the relevant information will still be used.

Yes! You can now save groups of personas to your persona library, and use them across your projects. Read more about this feature here.

No, not at this stage. But you can save your personas to your persona library and start a new Virtual Audiences topic with those personas to ask your new survey questions. Read more about this feature here.

At this stage, the AI cannot process images. It can pull some context from text in tables, but it’s not seamless. At this stage, text data is best for all data qualitative or quantitative i.e. labeled data rather than numeric codes.

No, not at this stage. You can download the data from the platform, and then upload it in the Virtual Audiences proprietary data process.

No, that would need to be uploaded separately via the normal import process in Yabble.

Currently, the proprietary data is used as a layer in Knowledge Lake and blended with other data Yabble collects. At this stage, you will not be able to ask the AI-generated personas about specific data you have uploaded.

Currently, Yabble can read closed-ended data that is in string format i.e. data labels rather than numeric. It will look at the question for context i.e. The question must be clear for the model to understand the context of ‘Very satisfied’ for example.

If you have any specific questions about Virtual Audiences and how this works with your own data to provide insights, contact the team at support@yabble.com.