Before you start

Before you start with Dayalogs

This page explains the core concepts, shared terms, and survey lifecycle behind Dayalogs before you jump into setup guides or task-based how-tos. If these basics are clear, the rest of the help center becomes much easier to use.

Short version — Dayalogs separates survey design, audience preparation, LinkSet creation, campaign sending, and response collection. That gives teams more control and lets each project use the workflow that fits best.

Survey design

Questions, blocks, presentation rules, conditions, variables, languages, and quotas define what the survey is.

Fieldwork setup

Audiences, contacts, LinkSets, and campaigns define who gets the survey and how they receive it.

Collected data

Responses are what comes back once the survey is live and respondents start using real links.

How the model fits together

At a high level, Dayalogs works like this: you prepare a survey, decide who should receive it, generate the right links, optionally send invitations, and then collect and export responses.

A quick mental model is: surveys define the questionnaire, audiences define the people, LinkSets define the links, campaigns define the send, and responses define the collected data.

Understanding a few technical terms

You do not need to be technical to use Dayalogs. Still, a few terms appear often in the help center because they make the product easier to explain. Your AI assistant and the Dayalogs MCP handle most of this for you.

MCP

MCP is the connection layer that lets AI tools like Claude, ChatGPT, Codex, Grok or Manus work directly with Dayalogs.

In practice, it means your AI can create surveys, validate them, preview them, manage audiences, and call other Dayalogs features without you doing those steps manually in the admin.

Structured data

Structured data means information stored in a predictable shape, such as contacts, CRM records, product lists, household members, or any other organized dataset.

Most business systems already work this way. Dayalogs can use that structure to personalize surveys, repeat blocks, preload values, and connect responses back to real operational context.

Schema-first

Internally, Dayalogs describes surveys with a clear structured format before anything is rendered or published.

That is why the platform can validate surveys, version them, preview them consistently, and let AI tools work safely. You do not need to hand-write this structure unless you want to.

JSON schema

JSON schema is the formal contract behind that internal survey structure.

When the documentation mentions it, the goal is simply to explain how Dayalogs stays consistent and how the AI knows which shapes are allowed. It is there to support the workflow, not to force users into technical authoring.

Core concepts

Survey

The questionnaire itself: wording, questions, logic, endings, languages, and collection settings.

Everything else in Dayalogs connects back to a survey.

Audience

The pool of people you may want to contact for one or more surveys.

Audiences are built from contacts, tags, and segments.

Contact

An individual person record with fields like name, email, phone, and extra structured data.

Contacts make personalized links and personalized survey experiences possible.

LinkSet

A managed set of links for one survey.

A LinkSet decides whether fieldwork uses one public link, one link per contact, or reusable grouped links.

Campaign

The email send layer that sits on top of a LinkSet.

Campaigns define the sender, subject, template, message, disclaimer, and send behavior.

Response

A stored survey submission, complete or partial depending on the survey rules.

Responses are what you monitor, export, review for quality, and analyze later.

Variables

Named values that the survey can use while it runs.

Variables can come from the survey, URL parameters, contact data, or API calls.

Hidden fields

Values that should travel with the response without being shown as a normal visible question.

They are useful when exports should keep a value at a precise point in the flow.

Quotas

Collection limits that stop responses once a target is full.

Some quotas live at survey level, others live on links or LinkSets.

Blocks

Logical units in the survey flow.

Blocks are where repeats, grouping, and many visibility rules make the most sense.

Pages

The respondent-facing screens that group questions into steps.

Pages shape presentation, but they are not the real flow engine of the survey.

Conditions

The rules that decide whether a block, question, or path should appear.

Conditions are what turn a static questionnaire into a dynamic survey.

Survey lifecycle

Most projects move through the same stages, even when the exact workflow differs by team. Dayalogs keeps those stages visible so people know whether they are still preparing, reviewing, collecting, or closing down a survey.

Draft

The survey exists, but it is still being built, checked, or adjusted.

This is where authoring, imports, wording work, and validation usually happen.

Review

The survey is stable enough to collect internal feedback before fieldwork starts.

Review rounds let stakeholders comment on the preview without treating the survey as live fieldwork.

Publish

The survey is ready to collect real responses through live links.

This is the point where LinkSets and campaigns become operational rather than just preparatory.

Pause

Collection is temporarily stopped without deleting the survey or its history.

Useful when quotas are under review, wording changes are needed, or fieldwork should be held for operational reasons.

Archive

The survey is no longer part of active fieldwork, but its structure and results remain available for reference and export.

Archiving helps teams keep the workspace tidy without losing the project record.

Relationship map

Dayalogs survey lifecycle diagram showing the path from survey draft to preview, review, survey published, LinkSets, campaigns, responses, and exports, alongside audiences and contacts feeding LinkSets.
A simple view of how survey work moves from draft to published fieldwork, and how audiences, contacts, LinkSets, campaigns, responses, and exports connect around that process.

The chart above is the shortest useful way to read the Dayalogs model: a survey moves from draft to published fieldwork, contacts flow in through audiences and LinkSets, campaigns sit on top when you want Dayalogs to send the invitations, and everything ends in responses and exports.

Where to go next

If you want to understand...
Read next...
How AI clients connect to Dayalogs
What questions and patterns a survey supports
How survey text and interface wording behave across languages
How links, contacts, LinkSets, and campaigns work together

Quick reference

You want to...
Think in terms of...
Create the questionnaire itself
Survey + blocks + presentation + conditions + variables
Prepare the people you may contact
Audiences + contacts + tags + segments
Generate controlled links
LinkSets
Send emails from inside Dayalogs
Campaigns
Control who sees what in the survey
Conditions + variables + hidden fields
Cap collection when a target is full
Quotas
Understand whether the project is still being prepared or already live
Draft, review, publish, pause, archive