Integrations Catalog for Data sharing

Design the experience for the unified Contentsquare, Hotjar, and Heap integrations catalog.

Give users a consistent and actionable way to share data between Contentsquare and their current stack.

Integration partner logos

Context

From 2024, Contentsquare merged three distinct analytics products into one cohesive product experience.

Each product with its own integration catalog with different structures, feature sets, visual and design languages.

Goal

The brief was clear:
one catalog, for all customers, across all plans.

But the ambition behind it was larger than unification for its own sake.

Role

Hands-on Product Design Director. I owned the design vision, the information architecture and the end-to-end UX of the catalog.

Worked closely with PM and engineering to align on scope and to deliver.

Bringing it together

Understand what each of the three catalogs was actually good at.
I went through the three experiences with the same question: how to find, install and use the right integration?

This audit surfaced real differences in approach. Hotjar's catalog was lightweight and fast.
Heap's was more data-rich, with stronger filtering logic. CSQ's was more exhaustive but harder to navigate.

One goal: to take what worked best from each and build something more considered.

The Hotjar integrations catalog
The Heap integrations catalog
The Contentsquare integrations catalog
Three catalogs, three experiences

Results

The unified catalog launched progressively between September and October 2025, in line with the broader One App rollout.
By October 20th, 100% of new self-serve traffic across all platforms was routed through the new catalog.

Consolidation & migration

Three catalog frontends collapsed into one system, with its 12 active Heap integrations migrated by real usage, Shopify, Appcues, Chameleon, and AB Tasty first.

Self-serve install

80% of integrations in the new catalog support self-serve install.

This directly reduces support load and shortens the time between a customer discovering an integration and getting value from it.

Foundation

The catalog structure and the contextual awareness layer were in place to support what was next: migrating existing Hotjar and CSQ SMB customers, expanding the library of integrations, and progressively introducing AI-powered recommendations.

The design is built to scale, this was a deliberate decision from the start.

Aligning the team

Before any IA work, the team needed a shared picture of where we were and what was actually blocking us.
A speedboat workshop surfaced that quickly.

Winds, anchors, and destination helped the group align on what was blocking catalog unification and what we were actually building toward.

The output shaped most of the decisions that followed.

Speedboat workshop board: winds, anchors and destination

Journey: from search to active value

I mapped the full journey: land → find → understand → install → data flows.

Each step had drop-off risk. The detail page had to work hard:
show the benefit, reveal what data moves, make setup feel approachable for non-technical users.

Self-serve install was the goal for 80% of the catalog. The legacy catalogs dropped the ball on post-install:
what happens after you connect? Is it working? That gap hurt retention. We fixed it.

Contextual awareness at the catalog level

The catalog already knew which integrations were active for each customer. That was going unused.

The direction shifted from a browsable library to something more active.

A surface that brings the right integration to the right customer at the right moment.

PLG upsell entry points first. More value at each release after that. This was an important competitive angle: turning a passive catalog into a dynamic recommendation surface.

Top recommendations surfaced at the head of the catalog

Upsell embedded in the experience

I worked on a way to surface integrations that were gated by plan.

Design purpose was to turn a locked integration into a conversion moment and not into a frustration.

This is directly connected to the adjacent growth and pricing logic in the overall platform.

A plan-gated integration card presented as an upsell

Tomorrow: AI and automation

During the design exploration, I mapped a medium-term vision for where AI could play a role in the catalog.
The idea was to move toward a catalog that understands a customer's usage patterns and proactively recommends integrations to specific insights they are not currently getting.

That directional work is not yet shipped. It shaped the catalog structure, particularly how integration metadata is organized and how recommendations are surfaced.

Read about the AI + Product concept case.
See the prototype.

The integrations catalog with the Sense AI banner
Integrations + Sense banner

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