Privacy-first analytics
FAQ.

It can, but it does not have to. Many teams start by using Deeplitic beside an existing analytics tool so they can compare a privacy-first baseline with a consent-dependent report before deciding what becomes their default.

The first step is a small site script or a first-party proxy. Start with one property, verify the events you care about, compare the first report with your existing view, and then expand the data into the workflow your team already uses.

A developer is helpful for a custom proxy or event plan, but a basic pageview setup is intentionally small. The important part is agreeing on the collection contract before adding optional events.

Yes. A single-property pilot is the best way to validate the measurement plan, event names, reporting questions, and privacy review before you apply the setup across a larger portfolio.

The product is designed to support a small script or a first-party proxy for teams that want more control over delivery. Choose the approach that matches your hosting, security headers, and operational capacity.

Deeplitic is designed to measure aggregated traffic without cookies or long-lived visitor identifiers. Always review the current configuration and your organization’s own privacy requirements before production launch.

No. The product is built around traffic and event aggregates rather than persistent visitor profiles, cross-device journeys, or a personal history.

The privacy-first design avoids keeping raw IP address histories as part of the analytics model. Network data may still be processed transiently for delivery and security, so consult your deployment and processing documentation for the exact configuration.

Deeplitic is designed around a collection model without cookies or visitor identifiers, but consent requirements depend on jurisdiction, purpose, configuration, and your organization’s legal assessment. Product design is not a blanket legal conclusion.

No analytics vendor can make compliance automatic for every organization and use case. Deeplitic is designed to reduce the data surface and make the collection contract clearer; your team still needs to review its configuration, notices, processors, retention, and legal obligations.

Use a documented allowlist of paths, events, and properties, and keep sensitive values out of URLs and event payloads. For regulated or high-risk projects, complete a privacy and security review before sending production traffic.

It means the system starts with the minimum useful signal: pages, sources, campaigns, trends, and selected events. It avoids adding identity just because identity can make a report more detailed.

You can measure pageviews, referrer groups, campaign parameters, device classes, country-level location, and business events that you deliberately define. The exact dimensions depend on your plan and implementation.

Yes. Keep the event vocabulary small, stable, and tied to a decision. Document the trigger, properties, owner, retention, and downstream use before adding it to the site.

Yes. Use consistent campaign parameters, keep personal or sensitive values out of URLs, and review the attribution model before interpreting the report. Aggregated campaign reporting usually answers the practical marketing question without a person-level journey.

Different tools can count different things and apply different filters, timezones, bot rules, consent boundaries, and event definitions. Compare the same page, date range, and question before deciding that a gap is an error.

Yes. Use a comparison contract: write down what each system counts, align the date range and filters, inspect the implementation path, and look for stable patterns rather than one surprising day.

The dashboard is designed for fast updates rather than a visitor-by-visitor live feed. The goal is a useful current baseline that remains aggregated and explainable.

Yes. The product is designed around portable data: use the Stats API for summaries, the Export API for records, or move a snapshot through CSV and JSON.

Deeplitic is built for EU-hosted infrastructure. Confirm the active region, processors, retention, and contract terms that apply to your organization before production launch.

Retention should be chosen for the reporting decisions you actually need and reviewed regularly. Use the current product configuration and your organization’s retention policy as the source of truth.

The Stats and Export APIs are intended to make aggregated reporting portable. A warehouse integration should preserve the event definitions and collection boundary alongside the rows.

The collection request is designed to stay small and asynchronous so it does not block the page. Validate the script, proxy, security headers, and failure behavior in your own production setup.

Analytics should fail quietly and never prevent a visitor from using the site. The ingestion architecture separates collection from reporting so operators can monitor retries and lag without making the browser wait for a database write.

The content and API model are designed for separate properties and portable reporting. Confirm the current workspace, permissions, and account limits for your agency setup before rollout.

Yes. Deeplitic is designed with Stats and Export APIs so teams can read summaries, move records, and connect analytics to the tools they already use.