Analytics Retention: 30 vs 90 vs 365 Days
One of the least glamorous but most consequential decisions in analytics is: how long do you keep the raw click data? Shorten it and you save money and reduce privacy risk, but you lose the ability to compare year-over-year. Extend it and you get richer trends, but storage grows and you hold more personal data.
There's no universal answer — it's a trade-off between insight, cost, and privacy. This guide helps you choose the window that fits your needs.
What retention actually controls
Retention is the length of time raw click events (each individual scan or click) are kept before they're deleted or rolled up. It governs:
- How far back your detailed analytics go (per-event data: device, referrer, time).
- How much storage and query cost you pay.
- How much personal data you hold (IP hashes, user agents, referrers).
Note the difference between raw events and aggregates: you can keep a summarized daily/weekly count forever, even if you delete the underlying detail.
The three common windows
30 days — recent performance
- Covers "how did this week's campaign do" and month-over-month.
- Cheap — minimal storage.
- Low privacy surface — you hold ~a month of detail.
- Trade-off — you can't see quarterly or yearly trends, and seasonal patterns are invisible.
Best for: fast-moving campaigns, low-cost operations, or privacy-minimal setups where you only need to report recent activity.
90 days — quarterly
- Covers a full quarter, so you can compare one campaign cycle to the previous one.
- Moderate storage and cost.
- Lets you see medium-term trends and catch issues that take a few weeks to surface.
Best for: most marketing teams that report quarterly and need enough history to spot trends without keeping everything forever.
365 days — annual
- Enables year-over-year comparison (essential for seasonal businesses).
- Higher storage and query cost, especially at scale.
- Larger privacy surface — you hold a full year of detailed events.
Best for: businesses with strong seasonality, longer sales cycles, or regulatory or audit needs that require a year of history.
The cost dimension
Click events accumulate fast. At high volume, storing every event for a year means a lot of rows. Considerations:
- Storage — raw events are small each, but there are many of them.
- Query performance — scanning a year of detail is slower than a month unless you aggregate.
- Cost — pay-per-query or per-storage providers charge more the longer you keep.
A common strategy is tiered retention: keep 30–90 days of raw detail, then roll it up into daily summaries you keep for a year. You get trend history without holding a year of raw events.
The privacy dimension
Click data can include an IP hash, a user agent, a referrer, and a timestamp — personal data under many regulations. The principle of data minimization says: keep only what you need, for only as long as you need it.
- Shorter retention = less personal data held = lower risk and simpler compliance.
- Longer retention = more personal data = you need a legitimate reason and a stated policy.
If privacy is a priority, prefer shorter raw retention plus long-lived aggregates, and document your policy. (Privacy-friendly analytics platforms default to short raw retention for exactly this reason.)
How this applies to link analytics
For a link/QR analytics platform, the practical guidance:
- Day-to-day and campaign reporting needs 30–90 days of detail.
- Year-over-year needs either a year of detail or a year of daily rollups.
- Aggregate counts (total clicks per link) can be kept forever cheaply — the detail is what costs.
So a sensible default is: keep raw events for 30–90 days, keep daily rollups for a year, and keep lifetime totals per link indefinitely. This balances everything.
How to choose
Ask three questions:
- What decisions do you make from the data? Recent-only → 30d. Quarterly → 90d. Annual/seasonal → 365d.
- What's the volume and cost? At scale, prefer rollups over raw detail.
- What are your privacy obligations? Prefer minimization; keep aggregates, delete detail.
The takeaway
Retention is a deliberate trade-off between insight, cost, and privacy. Match the window to the decisions you actually make: 30 days for recent performance, 90 days for quarterly, 365 days (or a year of rollups) for annual trends — and remember you can keep cheap aggregates forever while pruning the expensive raw detail. The right policy keeps your analytics useful without overpaying or overcollecting.
For related reading, see how to read traffic sources correctly and why bot-filtered click counts give you a truer number to retain.