Dataford
Interview QuestionsInterview GuidesExperiencesMock InterviewsPricing
Get started

Design Story-Driven Analytics Visualizations

EasyProduct Sense00:00
Practice interviewer
In session
5 left
00:00

Your question is Design Story-Driven Analytics Visualizations. Take a moment with it on the right.

Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).

You need to log in / sign up to chat or submit.

Problem

Company Context

InsightFlow is a B2B analytics platform used by 4,000 mid-market companies to build dashboards for sales, marketing, and operations teams. The product is growing quickly, but customer feedback shows that many dashboards are visually polished yet hard to interpret, which reduces adoption among non-technical users.

Problem

InsightFlow's leadership wants to improve how users create visualizations so charts tell a clear story instead of simply displaying data. Internal research shows that 58% of dashboard viewers abandon a dashboard within 2 minutes if they cannot identify the key takeaway, and support tickets about "confusing charts" have increased 22% over the last two quarters. Today, the product offers flexible charting tools but limited guidance on chart selection, annotations, narrative structure, or audience-specific templates.

You are the PM for the visualization experience. Your goal is to define how the product should help users create clearer, more decision-oriented visualizations without making the tool feel restrictive for advanced analysts.

Deliverables

  1. Define the primary user segments and the core jobs they are trying to accomplish when building or consuming visualizations.
  2. Identify the biggest user pain points that prevent dashboards from telling a clear story.
  3. Propose and prioritize a product solution or MVP that improves storytelling quality in visualizations.
  4. Define success metrics and explain how you would validate whether the solution improves user outcomes.
  5. Discuss key trade-offs, especially between flexibility vs guidance and speed vs quality.

Constraints

  • You have 1 designer, 4 engineers, and 1 data scientist for the next 10 weeks.
  • The MVP must work across existing chart types; a full charting engine rewrite is not possible.
  • Enterprise customers expect customization, so the solution cannot force a single dashboard format.
  • Any new experience should add no more than 10% extra time to dashboard creation for experienced users.