This is InSpace
At InSpace, we're building NOVA: an AI platform that helps companies stay visible in a world where discovery increasingly happens through LLMs and AI platforms instead of traditional search engines. Our software brings strategy, content creation, technical optimization, publishing workflows, and performance data together in one intelligent system.
As a Data Analyst – Customer Impact & Attribution, you make sure we know not just that content got published, but whether it actually drives engagement and conversion for our clients' end customers on their website, social channels, and in AI answers.
We move fast, experiment continuously, and use AI in everything we build, including how we measure our own impact.
Data Analyst – Customer Impact & Attribution
We're looking for a Data Analyst – Customer Impact & Attributiont who proves what NOVA actually delivers for our clients not by measuring our own product, but by measuring what happens to our clients' end customers.
This is fundamentally an attribution problem on data you don't own. You'll work with clients to get access to their analytics, CRM, and ecommerce systems, define what “engaged” and “converted” mean per client, and build the pipelines that feed that back into NOVA.
This is a role with direct impact on how we prove value to clients, how Product and Marketing make decisions, and how NOVA keeps improving itself. You'll report to the Product Director and work closely with Product, Marketing, Sales, Customer Success, and Development.
What You’ll Do
- Define, per client, what an “engaged” and “converted” end customer looks like, across their website, social channels, and other places their content appears and translate that into one measurement standard for NOVA.
- Build the pipelines and data-sharing agreements that bring end-customer engagement and conversions back into NOVA's data layer, and safeguard data quality.
- Design and own cross-surface attribution models, not single-site web analytics.
- Translate engagement and conversion signals into client-facing reporting.
- Contribute to NOVA's data strategy
- Build internal dashboards (Product, Customer Success, Sales, Management) and external client reports from the same data.
- Establish practices for data governance and privacy across clients.
- Pioneer brand-mention tracking together with the team.
Who You Are
- You have 5+ years of experience in analytics or attribution work on data or channels you didn't own yourself, agency-side analytics, martech/CDP, or attribution work within a multi-tenant SaaS platform.
- You've built multi-touch or cross-channel attribution models spanning more than one surface, not just a single GA4 property.
- You're hands-on with GA4, GTM, and GSC, and comfortable working with client-owned systems you don't control.
- You're curious about, or already experienced with, AI/answer-engine visibility tracking, a field that's still taking shape.
- You can defend an attribution methodology just as easily to a skeptical client as internally.
- Nice to have: SQL/BigQuery, experience with data-sharing agreements, ecommerce platforms, or GEO/AI-search measurement.
- You're available full-time at our office at the High Tech Campus in Eindhoven.
What We Offer
- A central role in how InSpace proves value to clients
- High ownership of a measurement problem with no off-the-shelf playbook
- Direct collaboration with Product, Marketing, Sales, and Customer Success
- Freedom to experiment with AI tools and new measurement methods
- A competitive salary
- 23 vacation days
- Transportation allowance
- An energetic startup environment with team outings and shared wins
Salary range
€50.000 – € 72.000 (annual incl. holiday allowance)
Interested in Building With Us?
No cover letter needed — we'd rather learn from how you think about impact and attribution. Send us:
- Your LinkedIn profile
- 3 short bullets on analytics or attribution projects relevant to this role (e.g. conversion tracking, attribution models, or client reporting)
- 1 example of how you use AI in your analytics workflow
- And: where do you think data could create the biggest impact at InSpace?