Business Tools
Build a brand tracking platform
Kliv is an AI app builder. Describe your brand tracking process — survey waves, awareness metrics, competitor cuts, mentions, and board readouts — and it builds the app around your data.
Just enter your idea into the text box and AI will build it for you
What is Kliv?
Kliv isn’t a panel vendor or a reporting dashboard you rent — it’s an AI that builds software for you.
You describe the app you need in your own words, and Kliv builds it: the database, the logic, the dashboards, the access rules, and the screens. What you get is a real app that’s yours. You can use it, change it later by asking, and run it on your own accounts. It isn’t a template with your logo on it.
On this page, that app is a brand tracking and analytics platform. Kliv builds all kinds of web apps; this is one example.
Why a PDF is not a tracker
A quarterly panel report can answer the questions it was built to answer that week. It is much worse at answering the question someone asks months later: how consideration moved in Austin after the rebrand, or which campaign lined up with a change in Denver.
A tracker keeps each wave, respondent cut, formula, competitor, and mention as data. The answer is a query with its source attached, not a hunt through old decks. Kliv builds the database, dashboards, readouts, and sign-in around the way your brand keeps score.
What one wave records
The tracker keeps the quarter as data, not slides.
The wave
Each fielding window has its sample size and quotas per metro. Responses land as rows tied to the wave, so quarters can be compared consistently.
The metric ledger
Unaided awareness, aided awareness, and consideration are computed from responses by formulas that live in the app. If a definition changes, the record shows when and why.
The competitor set
The same questions can be asked about the brands you compete with. Share of preference is computed from the same tables, not treated as a separate study.
The mentions log
Press hits and creator posts are filed with reach, tone, campaign tags, and who logged them. Coverage numbers keep their source.
The readout
The quarterly report is a page in the app. Charts draw live from the ledger, commentary sits alongside them, and older readouts stay searchable.
An example: Tomás’s sparkling-water brand
Here’s how one brand team might use it. It’s only an example — you would describe your own markets, metrics, competitors, campaigns, and reporting rhythm.
He starts with a baseline
Tomás fields the first wave through the panel provider’s links. 1,200 responses land as rows with market and demographic cuts intact. Consideration is 14% overall and 19% in Denver.
The rebrand stays measurable
The next wave overlaps the can redesign. Because fielding dates are on every response, Tomás can split who saw the old cans and who saw the new ones.
The Austin push gets its own view
After three months of sampling events and shelf buys, Austin moves from 11% to 17% while Denver stays flat. The dashboard shows the change market by market.
Mentions connect to the readout
Press hits and creator posts are logged with campaign tags. When the board asks whether the creator campaign did anything, Tomás can put coverage and consideration on one page, with a note about what correlation can and cannot prove.
The next question is answerable
Months later, he can ask how a metric moved and get the chart, the formula, and the rows behind it instead of opening four slide decks.
Describe what you want to build
Kliv builds from your description, so the more detail you give, the closer the first version. Include your waves, markets, formulas, access rules, and reporting needs. Here are three to build on:
Quarterly brand tracker
Survey waves, respondent cuts, and computed metrics.
“Build a brand tracker for our beverage brand with quarterly survey waves in Denver, Austin, and Portland. Import responses tagged by market, age band, and wave. Compute unaided awareness, aided awareness, consideration, and preference against three named competitors.”
Mentions and coverage log
Press and creator posts with source details.
“Build a media mentions log where our team files press hits and creator posts with URL, reach, tone, market, campaign tag, and who logged it. Create a monthly coverage summary by market and campaign.”
Board readout portal
Live readouts with scoped access.
“Build a board portal where directors sign in to read quarterly brand readouts with live charts and commentary. Raw survey responses should be visible only to the insights team, while directors see summary metrics and published readouts.”
The instruments behind the readout
Dashboards read your own rows. A chart like “consideration by metro, by wave, against the competitor set” is drawn from the ledger, not pasted from an export. If a number looks wrong, you can click through to the rows that made it.
Access can match the organization. Directors read readouts, the insights team reads everything, and an agency contractor can see only the mentions log. A forwarded link opens a sign-in screen, not a spreadsheet.
Monthly reports can run on schedule. A scheduled job can assemble the coverage summary on the first of each month and email it to stakeholders on your template.
The same analytics discipline can apply to your own storefront. Analytics on Kliv covers visitors, conversion, revenue per channel, and custom events defined in plain words.
Common questions
What exactly is Kliv?
Kliv is an AI that builds custom web apps from a description. For brand tracking, that can mean survey data, formulas, dashboards, mentions, and readouts in one app your team owns.
Do I get a real app, or a template?
A real app. Kliv builds the database, dashboards, access rules, and screens for your tracking process. It is not a prebuilt report theme.
Can I change it after it’s built?
Yes. You can ask for changes in plain words, such as adding a market, changing a metric formula, or creating a new board view.
Does Kliv supply the survey panel?
No. You field through your panel provider or your own lists. Once responses arrive, they live as rows in your tracker.
Is there automated social listening?
Not from a scraper. Mentions enter because a person filed them or an import brought them in. That is why each coverage number can say where it came from.
Can we load old waves?
Yes. Historical responses can import with their original fielding dates, and the formulas can recompute the metric ledger across the full history.
What keeps the board out of raw responses?
Access rules. A director can read readout pages and summary metrics while individual responses remain unavailable to that session.
Can formulas be versioned?
Yes. Metric definitions can live in the app, and changes can be recorded with dates and reasons so old and new numbers are explainable.
Can we track competitors?
Yes. If your survey asks the same questions about competitor brands, the tracker can store those responses and compare metrics over time.
Can I use my own domain?
Yes. The app can run on your own domain if you want stakeholders to access it there.
Can I move off Kliv later?
Yes. The code syncs to your own Git repository, and your data can be exported.
Do I need a separate reporting tool?
No. The app can hold the data, dashboards, readouts, and admin screens together.
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Ask the tracker, not the archive
Describe your markets, waves, metrics, competitor set, mentions, and board readouts in as much detail as you like. Kliv builds the tracker around them.