What if you could talk with your target anytime, about any topic at all? What if you could ask them right now how they'd take in a concept you've just shaped, how they'd react to a name you spent ages weighing, or where they stand on a particular subject? That's exactly what the new synthetic consumer does. After dividing your consumers into segments from the data, it creates a virtual consumer representing that segment, so you can talk with them directly.
Reports got better, too. We've taken the feedback from those who've been using the existing Dataspace AI report (formerly Insight Wiki) and built it right in: the wish to have visualization charts included, and the wish to see the analysis you ran together with Dataspace AI, along with the storyline you proposed yourself, carried straight into the report.
On top of that, we've prepared a feature where AI drafts a one-line key finding for each slide first, an Audience tab that suggests who to research, and seven new countries for overseas panels.
Take a look at this month's updates one by one below.
AI | Talk with synthetic consumers
One of the biggest reasons companies run research and look for data is, in the end, to understand their target and their market. But when you're facing a market you've never explored, no amount of data laid out in front of you makes it clear why these people think the way they do or what drives their decisions. The analysis is finished, yet the sense of understanding never quite arrives.
Now you can create synthetic consumers right inside Dataspace and talk with them directly. The flow is simple. Dataspace AI first finds and suggests meaningful segments from your data, and once you pick the segment you're curious about, a persona representing that group is created. Then you just ask questions as you normally would. The answers aren't loose guesses: when there's evidence in the data, the persona answers based on that evidence, and when there isn't, it reasons from its profile.
Segments aren't drawn on just any basis, either. Only groups with more than 30 respondents are suggested, and only variables that aren't heavily skewed to one side and show a genuinely meaningful difference are used as segments.
A conversation with a synthetic consumer is suggested at three key moments: when you ask for a data summary, after you've created a report, and when you explicitly say you'd like to talk with a certain target. Once the conversation is over, try asking for a summary report. It weaves your quantitative data together with the conversation you just had, so the numbers and the voices live in one place.
🧙 Try it like this
If you're a brand manager considering entry into a new overseas market, you can talk with a synthetic consumer to get an early sense of how that market perceives your category, and use it to form hypotheses for your main study.
If you're a researcher in the stage before collecting new data, when you're not sure what to ask, you can talk with the target persona in advance to figure out what really needs to be asked.
If you want to understand your existing quantitative data more deeply, you can ask the segment's persona directly why segment A answered the way it did, and fill in the context behind the numbers.
If you've ever felt stuck in front of a market or target you couldn't get a read on, this is your chance to talk with a synthetic consumer directly.
AI | Reports with visualization charts
After analyzing in Dataspace AI and landing on a good insight, you'd hit "generate report," only to find that the very story you and the AI had discovered together was missing from it. Pulling several datasets into one report was hard, and without charts, you had to digest everything through text and numbers alone. Even when the overall flow was fine, there was no way to fix just the one interpretation that bothered you.
The truth is, people don't start by building a report. They grasp the key results through conversation, find deeper insights, and only then move on to the report. So now your report carries over the context of that earlier conversation. You can bring several datasets together into a single report without merging them, the key points come in as visualized charts, and anything you're unsure about can be refined through conversation.
Item | Before | Now |
What goes into the report | Generated without the insights found in conversation | Carries over the conversation and reflects those insights |
Combining multiple datasets | Possible only after manual merging | Combined into one report without merging |
Charts | Built separately outside the report and pasted in | Included inside the report as visualization charts |
Editing | Hard to fix just one part | Refine only the part you want, through conversation |
🧙 Try it like this
If you're a trend manager who ran the same study in both 2025 and 2026, you can build a time-series report that shows the change at a glance, without merging the two datasets.
If you're a concept-test researcher who ran option P and option Q separately, you can bring the two divided datasets together as-is into one comparison report.
If you're a practitioner who needs to share results right away, you can pass along the report with its charts already included, without extra editing, and cut down on explanation time.
If your analysis goes smoothly but the reporting step always feels like a chore, try building and refining a report through conversation.
Because the way reports are built has changed, please let us know if anything looks off in the quality. Saving charts as images or exporting in slide form isn't supported yet, but we know it's needed and we're working on it.
Analytics | The Slide tab just got smarter
The headline at the top of a report usually holds a single sentence summarizing the most important pattern or meaning in that slide. Until now, you had to spend time writing it yourself. And even though each question calls for a different set of analysis criteria, you could only apply one set of criteria across every slide. To vary the criteria by slide, your only option was to download the PPT several times, once per criteria set, and stitch them together.
Now AI drafts a one-sentence headline with the key finding for each slide first. It regenerates automatically when more responses come in or when filters and analysis criteria change, and you can also press the regenerate button to get a fresh one. You can edit the generated sentence yourself, and you can review the history of everything generated so far.
You can also set different analysis criteria for each slide. You keep a custom set of criteria that applies only to a given slide, while a default set applies to all the others. No more downloading separate PPTs per criteria set and merging them: you can view or download every slide at once, right in the web.
🧙 Try it like this
If you're a researcher up against a tight reporting deadline, you can build on the AI drafts first and just polish the wording, cutting your headline-writing time significantly.
If your study mixes questions best viewed by gender with ones best viewed by age, you can set different analysis criteria per slide and present each result through the most fitting lens, all within a single report.
If you've been writing every headline by hand and downloading and merging PPTs just to handle analysis criteria, give it a try right away.
Headlines you've edited and custom analysis criteria reset on refresh, just like response filters and confidence level. If you couldn't download while your edits were in place, you can find them in the version history.
Marketplace | Start research right from Audience
To run a consumer panel study, you usually had to already know who you wanted to ask. That's no problem when your target is clear, but when nothing came to mind about who to study, just getting started felt daunting.
Now, in the Marketplace's Audience tab, we predefine groups of respondents with interesting conditions by industry and present them like a menu. Consumers worth paying attention to right now, such as GLP-1 users, pet owners, and wearable users, are displayed as cards. Tap an audience you like to see the details, and tap "Ask this audience with Dataspace AI" to start a chat with that target's conditions already filled in. From there, you create the survey, create a collection group, choose consumer panel collection, and carry on through payment and collection, just as you always do with Dataspace AI.
🧙 Try it like this
If you're curious about new consumer movements but haven't settled on who to research, you can browse the audience list, pick an interesting group, and start a panel study right away.
If you want to find consumers adjacent to your category, you can choose a fitting target from the audiences organized by industry and ask your questions straight away.
If you've wanted to run research but struggled to settle on a target, pick a consumer you like from Audience and start the conversation.
Panel self-survey | Seven new countries for overseas panels
In panel self-survey, you can run overseas panel studies yourself, but until now some of you may have wished a certain country were on the list.
This time we've added seven countries we can supply reliably: New Zealand, Canada, Mexico, Italy, the Netherlands, Poland, and Sweden. On top of the existing 12, you can now choose from 19 countries in total for your overseas panel study.
Item | Before | Now |
Selectable countries | 12 countries | 19 countries (7 added) |
Newly added | - | New Zealand, Canada, Mexico, Italy, the Netherlands, Poland, Sweden |
🧙 Try it like this
If you're looking into the North American market, you can now run a study in Canada alongside the US, all in one place.
If you need to cover Southern Europe together, the addition of Italy lets you bundle Spain and France into a single multi-country study and finish it all within Dataspace.
If you've been putting off overseas research because the country you wanted wasn't available, start right away with the newly added ones.
We'll keep expanding the list, focusing on countries we can supply reliably.
So, what did you think of this update?
The thread running through this month's features is about not stopping at analysis. Instead of ending at laying your data out, you can now talk directly with the consumers behind it and understand them, carry the context from those conversations straight into your reports, and even be offered who to research in the first place. Moving a step closer to understanding markets and people, not just reading numbers, is the direction Dataspace is aiming for.
Next month we're preparing new features to help you understand more deeply and work more easily, so look forward to what's coming.