Dynamic Data: Designing User Footprints ✦ No-Code DB Design #3

Hi, I’m Jian from ARCOA. 👋

In Part 1 and Part 2, we explored why database design matters to designers, and how static data builds the “rulebook” of a product.

Today, we move to the other half of the story — the part that actually moves.

If static data defines the world of your product, dynamic data captures how users live inside that world.

1. What Is Dynamic Data?

Dynamic data refers to everything a user does inside your app — every choice, every action, every moment they leave behind.

Static Data

• Defined once, rarely changed
• Categories, scoring rules, settings
• Operator
• Product logic & rules

Dynamic Data

• Continuously generated by users
• Search logs, requests, history, actions
• User behavior
• Understanding user behavior

Static data is the structure.
Dynamic data is the story.

Both are necessary for building a real product.

2. Modeling User Behavior as Data

No matter what the app is, dynamic data tends to follow a universal pattern:

• User
  Basic profile, preferences, onboarding information

• User-specific data
  Favorites, bookmarks, saved lists

• Action Log
  Every meaningful interaction: view, click, filter, open

• History / Snapshot
  A preserved copy of the state at a specific moment
  (e.g., a recommendation result, a selected filter set)

The exact naming may differ, but the conceptual flow remains the same.

3. Data Flow = UX Flow

Designing dynamic data is essentially designing the journey a user takes.

Onboarding → Browsing → Action → Request → Review

And each of these moments maps directly to a database entity:

• User joins → User

• Browses content → Browse_log

• Searches → Search_log

• Requests something → Request_log

• Gets a result → Snapshot

• Returns later → History

You can think of it like this:

If a moment matters in the user journey,
it should exist as data.

When UX flow and data flow are aligned, analysis, optimization, and personalization become effortless.

4. Real-Time Data vs Snapshot Data

This distinction is crucial in no-code development, yet often misunderstood:

Real-time data

• Always up to date

• Represents the current state

• Example: the filter selected right now

Snapshot data

• A “saved frame” of the past

• Represents a fixed moment

• Example: a recommendation result shown yesterday

Snapshots matter because real-time data changes constantly.

If you only store real-time values, you lose the ability to:

• Reconstruct past states

• Debug unexpected behavior

• Analyze before/after effects

• Provide consistent history to users

5. Turning Interactions into Data

Every interaction on your UI is a data relationship waiting to be captured.

• Button click → Action_log

• Page open → Page_view_log

• Scroll → Interaction_log

• Apply filter → User_setting update

• Save a result → Snapshot

• Return to app → History reference

This is why designers must understand dynamic data:

Interfaces disappear.
Data remains.

What remains should be intentionally designed.

6. Why Good Dynamic Data Design Changes Everything

When designers model dynamic data well,
the product gains:

• Clear insights for improvement

• Accurate user-behavior analytics

• Reliable personalization

• Stronger retention

• Easier debugging

• Better A/B testing capability

• A shared language between design & development

Dynamic data becomes a way for designers to “listen” to their users.

✦ Designer’s Summary

Dynamic data is the trace of real user experience.
Design the traces well, and your product will reveal its truth.

🔗 Series — Designer’s No-Code DB Design

Part 1 — DB Design: The Backside of UX
Part 2 — Static Data: The Product’s Rulebook
Part 3 — Dynamic Data: Designing User Footprints(This post)

Part 4 — Firestore Mapping: Connecting Static and Dynamic Data(Next)
Part 5 — Speaking in Data: A Designer’s Guide to Metrics & Insights