Year
2026
skills
Product Design
Type
Full-time
Industry
SaaS, Marketing
Different teams. Different questions. The same data. Engauge is designed around two primary user types.
Engauge is designed around two primary user types.
01 — Marketing managers
They need to understand how campaigns are performing, identify valuable customer segments and make informed decisions without spending hours analysing reports.
Their biggest challenge is getting a clear overview and knowing where to investigate further.
02 — Data analysts
They need more control over the information.
They want to explore customer segments, compare cohorts, investigate behaviour and understand the details behind business performance.
Their challenge is finding enough depth without navigating overly complex reporting tools.
Both users work with the same underlying data, but approach it with different goals.
Simple dashboards hide the detail. Complex tools hide the insight.
Most analytics experiences create a trade-off. High-level dashboards make it easy to understand performance but offer limited ways to investigate it.
Advanced analytics tools provide depth but often require users to navigate complex reports, filters and datasets.
The challenge was to support both quick decision-making and deeper investigation without making the product difficult to navigate.
Make every insight a starting point for exploration.
I structured the experience around a progressive exploration model.
01
Discover
Give users a clear picture of business performance through key metrics and visual summaries.
02
Explore
Allow users to investigate campaigns, customer segments and performance patterns.\
03
Understand
Help users interpret behaviour through cohort analysis, customer profiles and AI-assisted insights.
This structure informed the information architecture and connected different parts of the product into a more continuous workflow.
The right level of detail, at the right time.
Engauge is designed around two primary user types.
01 — Performance dashboard
Marketing managers needed a quick understanding of business health.
I designed an overview that brought important KPIs, charts and performance breakdowns into one place.
02 — Customer segmentation
Users needed ways to narrow down large customer datasets.
I explored filtering and segmentation experiences that made it easier to identify specific groups and compare their behaviour.
03 — Cohort analysis
Understanding changes over time requires more than a single metric.
The cohort experience allowed users to investigate customer patterns and compare behaviour across different groups.
04 — Customer profiles
Aggregate numbers don't always explain individual behaviour.
Customer profiles provided a more detailed view of individual records and their associated activity.
05 — SmartBot
Not every user knows where to look or how to interpret a dataset.
SmartBot was designed to make information more accessible by helping users explore and understand insights through a conversational interface.
A connected experience for customer intelligence
The design explored how different analytical workflows could exist within one coherent product.
A shared information architecture for different user types.
Clear navigation between performance & customer analytics
Progressive disclosure for detailed information.
Flexible ways to explore customer segments.
An AI-assisted layer for interpreting insights.
