> For the complete documentation index, see [llms.txt](https://resource.consumr.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://resource.consumr.ai/release-notes/release-notes-library/september-2026.md). # September 2026
Release (Features)StatusDate of Release
Brand Track TimelapseLiveSep-07-2026
APIs for MavenLiveSep-07-2026
Creative Tweaking (New Model) for Video, LP & Copies - Multi creative CompareLiveSep-07-2026
Creative Tweaking (New Model) for Video, LP & Copies - Single CreativeLiveSep-07-2026
Brand Guidelines - ManualLiveSep-07-2026
Competitor TwinsLiveSep-07-2026
Category PortfolioLiveSep-07-2026
Maven - OverlapLiveSep-07-2026
Maven - CompareLiveSep-07-2026
Maven - Market FinderLiveSep-07-2026
Maven - TrendsLiveSep-07-2026
Omnibox - Market Finder & SniperLiveSep-07-2026
IAM - Active Admin role + Bug FixesLiveSep-07-2026
## Brand Track: Timelapse In the last releases, we announced the brand track reports and the ability to schedule a brand track report to recur every month, that can enable brands to track how they fair as compared to their competitors, over a selected period. In this release we will also bring a distinct analytical view in form of a comparative report of brand track. A user can select a Brand track report and select a range of date, to pull up all the brand tracks that were created and see various displays of brand trends across multiple dimensions. Give it a spin and let us know what you think.
### What's New Brand Track can now be scheduled as a recurring study across multiple waves. Each wave applies the same questionnaire to the same defined audience at a selected interval, and every completed wave is saved as a dated reading. Awareness, Familiarity, Consideration, Preference, Intent and Endorsement can now be followed across time rather than viewed in isolation. Brand perception across Customer Support, Innovation, Premium Feel, Trust and Value for Money is tracked between waves in the same way. The initial release supports tracking a brand alongside up to five competitors. ### Before and After Running waves before and after a campaign shows how brand health metrics changed across that period. Because the audience definition, competitor set, questionnaire and measurement framework stay constant, the comparison is reliable in a way that separate studies never quite are. What the trend gives you is whether perception moved and in which direction. Why it moved is a different question, and one that Qualitative Research is better placed to answer. The two work well in sequence: the trend identifies where something happened, and the qualitative work explains it. ### Why This Matters for Research Teams Brand Track Over Time turns a point-in-time measurement into a continuous view of brand health. Teams can monitor whether their position is strengthening or weakening, identify the funnel stages where movement is occurring and understand how their trajectory compares with competitors over time. Instead of relying on an isolated score, researchers gain a consistent history that shows where deeper investigation is needed. ## API for Maven Maven exists to remove the distance between a question and a research-backed answer. For organizations building their own products, there is still one gap left: their users have to come to Maven to get that answer. Our new API suite release closes it. Maven's capabilities can now run inside the products your organization has already built. ### What’s New Organizations can integrate consumr.ai intelligence directly into their own products and workflows through the API. The end user works within a product they already know, without a separate consumr.ai login and without managing consumr.ai credits themselves. What reaches them is the answer, delivered in a context they were already operating in. A sandbox environment is available alongside it, so development teams can test requests, review responses and understand the available workflows before committing to a production integration. The organization owns the experience. How the capability is surfaced, what it is called, where it sits in the product, what the user sees when the answer arrives: all of that stays with the team building the integration, consumr.ai supplies the research and intelligence underneath. ### Why This Matters Every additional platform a user has to visit is a point at which the work can stall. Consumer intelligence is most useful when it is available where decisions are already being made, not in a tool that has to be opened separately and learned first. Maven was built to make research accessible to people who are not researchers. The API extends that reach further, putting consumr.ai's intelligence into the products and workflows where teams already spend their time. ## Creative Tweaking: Video, Landing Pages & Ad Copies Ask what makes a creative good and the honest answer is: good at what? A video that holds attention for thirty seconds has succeeded at something a landing page never needed to attempt. A landing page that clearly answers the question someone arrived with has done work that ad copy has no space to do. These are not variations on the same problem. They are different problems, and the difference is not stylistic. It changes what should be measured. In the last release Creative Tweaking got an updated and sound model for assessing ad images. With this release, videos, landing pages and ad copy join them, each assessed against the terms that actually apply to it.
### Objectives That Belong to the Format An ad image can be tested for Awareness, Consideration, Conversion or Post-Purchase. A video is tested for something else entirely: Attention Harvesting, Mental Availability, Problem and Solution Framing, Objection Liquidation, Immediate Intent. Landing pages are assessed against what a page is genuinely capable of doing, whether that is communicating a value proposition, educating a visitor, building trust, reducing objections or driving a transaction. Ad copy is measured against campaign outcomes: reach, traffic, engagement, video views, lead generation, sales, app installs, store visits. The objective selected does more than label the study. It decides which aspects of the creative are examined closely. A video submitted for Attention Harvesting is scrutinized on its opening seconds, how early the brand becomes visible, the strength of the visual hook, its pacing, and whether it holds interest past the first few seconds. The same video submitted under a different objective would be read differently, because a different question is being asked of it. ### What Teams Get Back Not a preference. The AI Twins assess the variations head-to-head and the report explains why one performs more effectively than the others, what each variation contributes, where each one loses ground, and which elements should carry into the next version. That last part matters more than the verdict. A team that knows which creative won has learned something. A team that knows why, and knows which specific elements produced the difference, has learned something they can act on. ### Why This Matters for Creative Teams Most creative decisions have been made on general preference because structured feedback was only available for some of what teams produce. Extending comparative assessment across formats closes that gap. Whether the question is which video to run, which landing page converts or which line of copy earns the click, the answer now comes from how well each option serves its purpose with the selected audience. ## Creative Tweaking - Single Creatives for all types Not every creative evaluation begins with a set of options. A team often has one direction, early in the process, and the question is not which of these is strongest but whether this one is working at all. Comparative assessment cannot answer that. It needs something to compare against. Creative Tweaking also evaluates a single creative on its own terms, across every format it supports.
### One Creative, Read Closely A single ad image, video, landing page or piece of ad copy can be submitted by itself without variations alongside it. The creative is assessed against the objective selected for its format, and the report identifies the strongest and weakest aspects of the execution, explains how it performs across the relevant parameters and gives an overall reading of whether the direction is holding up. An ad video submitted on its own is examined for the strength of its opening, how quickly the brand becomes visible, whether attention is sustained across its length and whether the message survives without sound. A landing page is read differently again. The assessment changes with the format so that each creative is judged on what it is actually being asked to do. ### From Diagnosis to Next Steps The output does not stop at assessment. Findings are translated into a focused action plan covering what should be retained, what needs clarifying and what should change in the next version. A team with one creative and an unclear read on it comes away with a specific direction for the second. ### Why This Matters Audience feedback has typically entered the creative process late, once there were enough variations to compare. Single creative evaluation moves that earlier. Teams can test a first direction before investing in alternatives, identify what is not landing while changes are still cheap to make, and build the next version from evidence rather than assumption. Between the two, Creative Tweaking now supports both halves of creative development: understanding one creative in depth, and choosing between several once the options exist. ## Brand Guidelines – Manual A brand is not only what it looks like in an advertisement. It is the identity through which products, campaigns, consumer perceptions and research findings are understood. That identity is built from connected elements: logos, colours and typography, but also imagery, tone of voice, messaging priorities and the principles that determine how a brand presents itself. When those elements live in separate files or remain undocumented, different teams begin working from different interpretations of the same brand. For consumr.ai, a brand name and an uploaded logo have never been enough context. What the platform needs is a shared understanding of what the brand is meant to look, sound and feel like.
### What’s New Brand Guidelines can now be created directly within the platform, bringing a brand's visual and verbal system into one structured profile. Teams can define logo assets, colour roles, fonts, text styles, imagery direction, visual examples, tone of voice, messaging hierarchy and guidance for graphic elements, all held in a single place and attached to the portfolio it belongs to. Guidelines do not need to be exhaustive to be useful. Only the essential information is required to begin, and further detail can be layered in over time as the organization's own understanding of the brand develops. ### Context That Travels With the Portfolio Defining the brand at the portfolio level means that context is available wherever that portfolio is in use. It does not need to be re-established at the start of each study, and it holds steady regardless of who set the study up or what question is being asked. Creative Tweaking is the most immediate application. An evaluation can now consider whether a creative holds the brand's identity alongside whether it connects with its audience, which is a more complete question than either half on its own. The value is not limited to creative work, though. Any research conducted under that portfolio benefits from a platform that understands not just which brand is being studied, but the visual language it uses, the way it communicates and the identity it is working to maintain. ### Why This Matters Research is strongest when every study of the same brand begins from the same premise. A single shared definition, one that grows with the portfolio rather than being reconstructed each time, keeps research, evaluation and future brand decisions grounded in the same identity. That consistency holds even as the people conducting the work, the questions being asked and the assets being studied change over time. ## Competitor Twins Every category contains consumers who chose someone else. They evaluated the same options, weighed the same considerations and arrived at a different conclusion. Their reasoning is some of the most useful information available to a brand, and it sits entirely outside research conducted through that brand's own audience. Portfolios have carried competitor definitions for some time. This release turns those definitions into research participants.
### Building Twins From the Competitor Set Competitor brands defined during portfolio creation can now be selected at the point of AI Twin creation. The resulting Twins carry the perspectives, expectations and decision patterns associated with those competitor audiences, and they participate in research the same way any other Twin does. A concept, a message, a product direction or a creative can now be tested against consumers who are not currently inclined toward the brand. Their responses come from a different starting position, which is precisely what makes them worth having. ### A Different Question Than Competitor Analysis Most competitor research examines the competitor: their positioning, their messaging, their product decisions, their spend. It is analysis of a company. Competitor Twins ask about the people instead. What are these consumers getting that keeps them where they are? What would need to be true for them to reconsider? Is a new proposition compelling to someone with no existing relationship with the brand, or does it only land with an audience already predisposed to hear it? A brand's own audience cannot answer any of this, and their agreement can be misleading precisely because they were always going to agree. ### The Wider Read on the Market Research through a brand's intended audience tells you how to hold what you have. It reveals what your consumers value, where satisfaction sits and what would risk losing them. That is necessary work and it has limits. Competitor Twins extend the frame. They expose the expectations a brand is not currently meeting, the differences between audiences that a single-sided study flattens, and the territory where an idea has room to move someone who is not already listening. For teams working on growth, entering adjacent spaces or building propositions meant to expand rather than defend, that is the more valuable half of the picture. ## Category Portfolio Some research questions do not begin with a brand. Before a team can decide how a brand should be positioned, what proposition it should carry or which audience it should pursue, there is often an earlier question: what is actually happening in this category? Who participates in it, which needs shape it, how do consumers choose between the alternatives available to them, and where is something new beginning to form? Anchoring that inquiry to a single brand too early narrows it. The findings arrive already filtered through one company's position in the market, which is useful later and limiting at the start.
### A Portfolio Built Around the Category consumr.ai now supports Category Portfolios alongside Brand Portfolios. A Category Portfolio organises research around the wider market rather than requiring every study to proceed from the vantage point of one brand. It holds shared context for examining category consumers, their behaviours, the competitive set and the opportunities taking shape across the space. ### Two Different Starting Points A Brand Portfolio asks how a particular brand is understood within its market. It is the right structure when the brand is the subject and the question concerns its position, perception or performance. A Category Portfolio asks what is happening across the market before any brand becomes the focus. It creates room for exploratory work: understanding consumer needs on their own terms, mapping competitive dynamics without a designated protagonist, examining category behaviour and identifying emerging areas of opportunity. The findings are not routed through one brand's existing position, which means they can point somewhere that position does not currently reach. ### Deciding Where to Enter The practical value shows up in sequencing. Teams can investigate the market first, understand the forces and consumer needs shaping it, and then use that understanding to determine where a particular brand, product or proposition should enter the conversation. That order matters for anyone working on category entry, portfolio expansion, whitespace identification or early-stage strategy, where the answer to which brand belongs here depends on first knowing what here actually is. ## Maven – Overlap An Overlap report describes the audience sitting at the intersection of several signals: the people who hold all the selected interests rather than any one of them. That audience is usually the more revealing one, because the combination itself says something about how these people live. Reading that report is one thing. Working out what it means for a decision is another, and until now it was work the user had to do themselves.
### Overlap Reports Come Into Maven Maven can now analyze Overlap reports built in app.consumr.ai. The report is created the way it always has been, through the Behaviour Report builder with Overlap enabled. What changes is what happens next: instead of interpreting the output manually, users can bring the report to Maven and ask what it means. Maven works from the report's own signals rather than reading it as a document. The behaviours, affinities and characteristics defining the intersecting audience are available to it as data, which is what allows the analysis to hold up. ### Precision Changes the Profile The value of an Overlap report is rarely the report itself. It is what the intersecting audience tells you about who to target, what will resonate and where an opportunity might sit that a broader definition would have flattened. That translation, from a set of behavioural signals to a decision someone can act on, is what Maven is built for. A user can ask what distinguishes this audience, what it suggests about positioning or messaging, or how it should shape a campaign, and receive an answer rather than a data set to interpret. ### Why This Matters Overlap has always produced precise audiences. Making sense of that precision required either research experience or the time to develop it. With Maven analyzing these reports, the audiences hardest to describe become the ones easiest to understand. The intersection is defined in app.consumr.ai, and the meaning is drawn out in Maven, which keeps the depth of the platform available to teams who need the answer more than they need the apparatus. ## Maven – Compare An Intelligence Report gives a thorough reading of one audience or research context. Two of them give two thorough readings, and the relationship between them is left to the person holding both. Which differences matter, which are incidental, and what the pattern across them suggests: that is analytical work, and it sits outside the reports themselves. ### What’s New Maven can now compare Intelligence Reports generated in app.consumr.ai. The reports are created as they always have been. What is new is the ability to bring several of them into a single analysis and ask Maven where the findings align and where they diverge. This currently applies to Intelligence Reports and does not extend to other report types. ### Interpretation, Not Juxtaposition Placing two reports next to each other is not the same as comparing them. Maven reads the relationship between the reports and identifies which distinctions actually bear on the question being asked, rather than cataloguing every point where the readings differ. That selectivity is where the value sits. Any two Intelligence Reports will diverge in dozens of small ways, most of which change nothing. The differences worth surfacing are the ones that would alter a decision, and separating those from the rest is precisely the part of the work that consumes time and requires judgement. ### What Comes Back The output covers differences in audience characteristics, behaviours, interests and the wider intelligence held within the selected reports, with the context of each report preserved rather than collapsed into a summary. For teams weighing audience strategy, positioning, messaging or the direction of further research, moving from several separate readings to one comparative assessment shortens the distance between having the intelligence and being able to act on it. The depth stays in app.consumr.ai. The answer arrives through Maven. ## Maven – Trends A report describes what was true when it was produced. On its own it cannot tell you whether the audience has moved since, whether an interest that mattered then still matters now, or whether something has been building quietly across the months in between. That only becomes answerable when the same source of intelligence is refreshed repeatedly. Successive readings of the same audience turn a set of separate outputs into evidence of movement, and movement is what most strategic questions are actually about. ### Asking Maven What Changed Maven can now assess change over time within portfolios that contain a scheduled Intelligence Report or an AI Twin updated on a regular basis. The user selects an eligible portfolio, asks what has shifted, and Maven examines the available readings as a sequence rather than treating the latest as the whole picture. The dependency is worth stating plainly. Trends is not a summary of research history. It works where intelligence has been refreshed over time, because the analysis comes from reading those updates against each other. ### Change Rarely Announces Itself Reviewed one at a time, each updated report looks perfectly reasonable. Nothing appears wrong, so nothing prompts a closer look. The shift only surfaces when the readings are held together, and by that point the direction may have been established for some time. A team can now ask directly how an audience's interests, behaviours or stated priorities have moved across those updates, and get back an assessment of what is gaining ground, what is fading and what has changed in a way that matters. ### Why This Matters Scheduling a report or keeping a Twin current has always produced something valuable. What it has not produced is a view: the readings existed as separate artefacts, each requiring its own interpretation. Trends closes that gap. The archive becomes something a team can question directly, which turns recurring intelligence from a series of updates into a continuous read on how the audience is changing. ## Maven – Market Finder A Market Finder report identifies where consumer affinity toward an audience or interest runs strongest, and Sniper narrows that view to the states, cities and postal areas within a chosen market. The output is geographic, granular and often extensive. Reading it is straightforward enough. Knowing which of those markets deserves attention first, and why, is the harder question, and it depends on what the team is actually trying to decide. ### Market Finder Reports Come Into Maven Maven can now analyse Market Finder reports built in app.consumr.ai. The report is created as it always has been, through Omnibox, using the context available in Behaviour Insights. What is new is that the output can be brought to Maven and questioned directly. Maven works from the report's underlying affinity data rather than reading it as a finished document, which is what allows it to weigh markets against each other rather than simply restate what the report already shows. ### From Geography to Priority A ranked list of markets answers where affinity is concentrated. It does not answer where to go first, which market suits the proposition, or how a shortlist should be sequenced against budget and ambition. Those are the questions teams actually have, and they require the geographic data to be read alongside the decision it is meant to inform. A user can ask Maven which markets to prioritise for an expansion, how a set of cities compares for a particular product, or what the concentration pattern suggests about where demand is genuinely forming. ### Why This Matters Geographic affinity data has always been available. Turning it into a market entry recommendation, a regional plan or a retail strategy required someone able to interpret it in commercial terms. With Maven analysing these reports, that interpretation is part of the workflow rather than a separate exercise. The geography is established in app.consumr.ai, and the decision it supports is worked out in Maven, which is the pattern across everything Maven is designed to do. ## Market Finder Identifying a promising market is the beginning of a question, not the end of one. Knowing that affinity is strongest in a particular country still leaves open where inside that country the audience actually concentrates. Those are two different problems, and answering them has historically meant two different pieces of work. ### What’s New Market Finder and Sniper are now available through Omnibox. These capabilities use the context available through Behavior Insights, including first-party audiences and selected interests, to examine consumer affinity across geographies. Market Finder provides the broader view by identifying the countries or markets where affinity toward the selected audience or interest is strongest. Sniper then narrows the analysis within a selected market to find areas with a higher concentration of that audience, including states, cities and ZIP codes where available. A team studying a specific segment can use Market Finder to determine which countries show the strongest affinity. It can then use Sniper to drill down to which states, cities, and ZIP codes stand out within the country. ### Why This Matters Geographic affinity has typically been treated as a media question, answered at the point of building a campaign. Market Finder and Sniper make it available earlier and for broader purposes. Market prioritisation, regional planning, retail strategy, expansion research and the discovery of concentrated niche audiences are all geographic questions that arise well before anything needs to be launched. Teams can now investigate them directly, without campaign creation as the entry point. ## IAM: User Permissions for Org admins An organisation on consumr.ai is rarely one kind of user. Researchers building portfolios and running studies need different access from the people responsible for the organisation itself, its structure, its users and the decisions that affect everyone working inside it. Granting the same permissions to both groups makes one of them over-provisioned.
### What’s New consumr.ai now supports role-based access, with permissions determined by the role assigned to each person. The distinction separates everyday platform work from organisation-level administration. Users operate within the permissions their role allows, conducting research and working across portfolios without unnecessary friction. Admins retain oversight of administrative actions and any request that carries consequences beyond a single piece of work. ### Requests Route Rather Than Execute The practical effect shows up at the boundary between the two roles. If a portfolio needs to be created under a separate sub-organisation, that request now reaches an Admin for review instead of altering the organisational structure automatically. Structural decisions belong with the people accountable for the structure. Routing them there preserves that accountability without blocking the person who raised the request. ### Why This Matters as Organisations Grow A small team can operate on shared access because everyone knows what everyone else is doing. That stops being true as users, portfolios and sub-organisations accumulate, and the cost of unstructured access rises with each addition. Role-based access gives organisations control over who can act administratively while leaving research work unrestricted. Permissions stay aligned to responsibility rather than being applied uniformly to everyone, which is what allows an organisation to grow without its access model becoming a liability.