As part of Logical Position’s ongoing digital transformation and design system initiative, I developed a company-wide Data Visualization Style Guide to establish consistency, clarity, and visual hierarchy across all dashboards, reports, and analytics tools.Before this project, different departments were creating their own reporting layouts—resulting in inconsistent color usage, misaligned legends, unclear typography, and accessibility issues. The lack of standardization made it difficult for clients and internal teams to interpret key metrics at a glance.My goal was to create a unified visual language for data presentation that aligned with LP’s brand system while improving usability and comprehension across internal and client-facing platforms.

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Logical Position’s analytics ecosystem spans multiple tools

(Looker Studio, Quickbase, Google Ads dashboards, and Excel-based reports).

1. Inconsistent use of brand colors for KPIs (e.g., red sometimes meaning “active” instead of “alert”).
2. Mismatched typography and chart labels.
3. Inefficient use of layout space.Accessibility and readability gaps in both dark and light modes.
4. The lack of a shared standard not only affected usability and accuracy but also made it harder for cross-functional teams to collaborate effectively.

Develop a Data Visualization Style Guide that would

1. Establish consistent chart types, colors, typography, and spacing.
2. Improve clarity and accessibility of data visuals.
3. Create a single source of truth for visualization standards in the LP Design System.
4. Streamline the handoff process between design, data, and engineering teams.

I began by auditing dashboards across departments including Paid Search, SEO, and Account Performance. I cataloged the most frequently used visualization types and identified pain points through internal interviews with Account Managers and data analysts.

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Stakeholders struggled to interpret metrics when color meanings varied across reports.Some charts used gradients or overly complex palettes that reduced legibility.Label truncation and inconsistent font sizing made comparison difficult.From these insights, I mapped out a prioritized list of improvements and began defining design principles for data visuals: Clarity, Consistency, and Contrast.

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Collected screenshots and samples from various reporting tools. Grouped them by visualization type (e.g., line charts, bar charts, pie charts, KPI tiles).

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Created color mapping rules for different metric categories (Performance, Spend, Conversions, Engagement).Primary Palette: Brand blues and greens for positive metrics.Secondary Palette: Neutral greys for context and supporting visuals.Alert Palette: Red/orange hues reserved strictly for negative performance or system issues.

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Established consistent use of typography for chart titles, legends, and axis labels using the LP type scale from the Design System.Titles: 16–18ptLabels: 12–14ptLegends: 11–12pt (semi-bold)

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Validated all colors for WCAG AA compliance and tested chart legibility in both light and dark backgrounds using simulators for color blindness.

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Compiled final visual specifications into a comprehensive Data Visualization Style Guide Deck, which was then uploaded to Confluence and SharePoint for company-wide access.Each slide included clear do’s and don’ts, color hex codes, chart spacing rules, and component naming conventions for designers and analysts to follow.

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