Simplifying campaign management and job ad package comparison
XING’s B2B campaign-management tool and job ad purchasing journey: a legacy desktop product rebuilt around campaign managers’ daily tasks, with pricing restructured so buyers could compare packages before booking.


Summary
Objectives
- Redesign the legacy desktop tool around the core tasks of campaign managers.
- Make XING Job Ads packages, pricing and included value easier to understand and compare.
- Create reusable interface patterns for consistent product development.
Role
Product Designer
Period
2016–2019
Team
1 UX Designer · 1 Product Designer
Product Owner · Tech Lead · 2 Developers · Brand Designer
Key Skills
- UX Strategy
- Product Design
- Information Architecture
- Interaction Design
- Interactive Prototyping
- Design Systems
- Facilitation & Stakeholder Alignment
Impact
↓ 30%
Processing time in campaign management and booking workflows
↓ ~20%
Workflow errors in campaign management
Two product problems shaped the work
The application had grown through engineering-led delivery without a shared design system or reusable UI library. Navigation and workflows reflected the implementation structure rather than the daily tasks of campaign managers.
The pricing journey made package value and differences difficult to scan, adding friction before booking. Users needed a clearer way to compare price, reach and included features.

Redesigning the campaign workspace
I rebuilt the campaign workspace around the tasks business users repeat every day: scanning campaign status, comparing spend with budget and acting without opening individual items. The new navigation and hierarchy transformed an engineering-led table into an operational workspace.

Making campaign controls easier to scan
I separated persistent controls from row-level decisions and made status, type and spend visually comparable. Consistent states for activation, filtering and column setup reduce rework when teams manage many campaigns.


Connecting performance with daily management
I brought performance data into the campaign workspace instead of sending users to a separate report. Teams can switch between the graph and ad list while keeping filters, columns and date context visible.

Simplifying campaign creation
I restructured the campaign-creation flow around persistent navigation, reusable inputs and clear Save draft and Continue actions, so users could pause and resume without losing context.
The AI assistant is a later concept showing how I would extend the original workflow today. It was not part of the released product during my time at XING.

Building reusable foundations
I translated the redesign into shared foundations and reusable components for navigation, forms, actions and campaign states. This gave Engineering one implementation language and prevented the product from growing through one-off UI decisions.


Making package differences comparable
I reordered the landing journey so users first understand reach, outcomes and included benefits, then encounter a focused package choice. This reduces the cognitive jump from the product promise to price.
I aligned price, reach, runtime and included features across tiers, highlighted a clear default and kept comparison actions visible. Users can evaluate trade-offs without opening separate pages or contacting support.



De-risking the workflows before development
Interactive prototypes covered the redesigned campaign list, performance views, campaign-creation flow and pricing journey. Product, Engineering and business stakeholders reviewed the workflows before implementation.
The main risks were structural: whether navigation matched daily operating tasks and whether buyers could understand package trade-offs without additional support. I treated the desktop workflow and pricing journey as separate solution tracks, then aligned them through shared hierarchy, reusable patterns and consistent decision logic.
What I learned
Design the system, not isolated screens
The key was separating the operational desktop workflow from the pricing decision, then connecting both through shared hierarchy and reusable patterns.
Make decisions visible
Interactive prototypes turned open questions into something Product, Engineering and business teams could review together.
Revisit the work with today’s tools
The AI assistant is a later exploration of how generative assistance could support the workflow while preserving user control.