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In any design project that involves tabular data, the prototype must reflect how users will interact with rows, columns, and controls. Figma offers components, variants, and smart animation features that let you simulate sorting, filtering, and pagination without writing code. Start by mapping the data table layout as a grid of cells, headers, and action controls. Create separate components for header cells, data rows, and toolbars, then assemble them into a single frame. By layering interactions onto these components, you can observe how state changes propagate visually when a user sorts a column, applies a filter, or navigates between pages.

Begin with a clear data schema that defines column types, possible values, and the expected behavior of each control. Build a set of variants for headers (default, sorted ascending, sorted descending) and use interactive components to switch between states. Establish a local data mock that resembles real content but remains lightweight for fast iteration. Use overrides to swap data quickly without breaking the structure of the prototype. Document interaction expectations within notes or a dedicated frame so stakeholders understand how the prototype maps to actual product requirements, especially the edge cases like empty results or loading indicators.

To test sorting behavior, create a sortable header interaction that triggers a visual change in the corresponding column and reorders the data rows in the mock. Treat the action as a reversible toggle, allowing designers to demonstrate how users can re-sort with a single click or tap. Use a small animation to convey the transition, but ensure it remains fast to keep the demo realistic. Record the intended outcome for each sort action in a companion note so testers know what to expect when the feature reaches development. This approach helps verify that the UI communicates the sorting state clearly.

For filtering, design a compact filter panel that sits above the table. Include common controls such as checkboxes, dropdowns, and a search field. The key is to reflect how the filter affects visibility of rows without altering the overall layout. Wire up the panel to a set of filtered data rows in the prototype, demonstrating how counts update and which rows are hidden. Use clear cues like badges, subtle fades, and a consistent color rule to indicate active filters. Ensure that clearing filters returns the table to its original state.

When prototyping pagination, model a realistic page size and navigation controls at the bottom of the table. Show next, previous, and page number actions that adjust the rows visible within the frame. Keep the design consistent with the sorting and filtering states so transitions feel cohesive. Include a loading indicator if data retrieval might be asynchronous in the real product. This helps testers assess perceived performance and understand how the interface responds during data fetches, refreshing the content, or when limits are reached.

To preserve clarity, group related controls into a predictable geometry: headers at the top, the data grid in the middle, and controls at the bottom. Use consistent typography, spacing, and color language across all states. Create a legend that briefly describes what each state represents, including sort direction, active filters, and paging status. Consider accessibility from the outset by maintaining sufficient contrast and keyboard navigation paths within the prototype. Map interactions to real user tasks to ensure the flow remains intuitive, enabling testers to complete common scenarios without confusion or guesswork.

Pair each interactive element with a concise label that communicates purpose. For example, a header cell might show a tiny caret to indicate sort direction, while filter controls display contextual hints when focused. Use consistent microcopy for error states or empty results so testers know what the system will say in those moments. In Figma, leverage component variants to keep these messages synchronized with state changes, reducing the risk of misalignment between the header, filters, and the data grid. The goal is to create a believable, accessible experience that mirrors the final product and supports reliable testing outcomes.

As you prototype, incorporate test prompts that guide participants through typical tasks. For instance, ask users to sort a column, apply a specific filter, and then navigate to another page. Capture qualitative feedback on how smooth the transitions feel and whether the results are immediately understandable. Use a dedicated frame to collect impressions, noting where users hesitate or misunderstand controls. This approach helps you refine your design before development, ensuring that the table interactions remain intuitive and aligned with user expectations.

Use annotations to describe the logic behind each interaction, such as “ascending sort applies to numeric data only” or “string filters are case-insensitive.” Annotations should stay concise yet precise, offering developers a clear translation of the designer’s intent. Include screenshots of the desired outcome for each state, so even someone unfamiliar with the project can reproduce the effect. In Figma, you can attach comments directly to elements, making it easier to track decisions and reasoning as the prototype evolves. This level of documentation reduces back-and-forth during handoff and helps testers focus on real usability questions.

Consider creating a conformance matrix that maps interactions to expected outcomes, acceptance criteria, and potential edge cases. For example, specify what happens when a filter returns no results, or when a user switches rapidly between sort orders. Use this matrix to guide both the prototype and the subsequent usability testing plan. By establishing clear expectations early, you enable testers to validate the design against measurable criteria rather than subjective impressions. This discipline supports more reliable feedback and faster iteration cycles.

When you prepare for user testing, assemble a small, focused set of scenarios that reflect real-world tasks. Include a baseline scenario with no filters, a second scenario with multiple filters, and a third that tests paging and sorting in combination. Present these scenarios within the same Figma file to keep all observations in one place. Provide a simple scoring rubric or checklist so observers can consistently evaluate ease of use, clarity, and efficiency. The stability of the prototype is critical so testers can complete tasks without technical hiccups or inconsistent states.

Finally, iterate based on feedback by adjusting state transitions, label wording, and the visual emphasis of active controls. Refine the data mock to better reflect realistic content, including varied data lengths and occasional missing values to challenge sorting and filtering. Update notes to reflect changes and rationales so future contributors understand the evolution of the design. By maintaining a living prototype with clear documentation, you create a valuable reference that teams can reuse for testing new table configurations or for onboarding new designers into the project’s workflow.