From scattered startup data to incubation intelligence

How hubraum centralized data in HubSpot, implemented segmentation and performance analytics to improve incubation programs' effectiveness.

2026-03-12_HubraumTMobile_CaseStudy | HubSpot Video

Watch: hubraum team explain the transformation journey

Automated

MARKETING SEGMENTATION

Real-time

LEAD SCORING

Reliable

CRM DATA

Situation

hubraum runs incubation programs for startups. Data about companies and contacts was scattered across HubSpot, CB Insights, and Tracxn. Scouting and marketing teams used different databases and tools.

Problem

Scouting activities for incubation programs relied on fragmented data, making it hard to quickly identify companies most relevant to each program and contact them efficiently.

Solution

We cleaned and centralized data in HubSpot, introduced buyer personas with segmentation and lead scoring, and built the program's performance dashboards.

Benefit

Teams know which companies to target, see how scouting activities perform, and work with clean, structured data.

The Situation

hubraum is Deutsche Telekom’s tech incubator. It connects startups, ecosystem partners, and corporate teams to drive innovation and business collaboration.

Scouting activities for incubation programs are at the core of hubraum’s operations. However, data supporting these activities lacked structure and visibility.

The Problem

1) Limited visibility into program performance

There was no well-structured overview of attendance, engagement, or performance across key Programs.

2) Limited segmentation for outreach and nurturing

Teams needed to:

  • Select companies for the upcoming program outreach
  • Identify contacts for nurturing campaigns

But lacked reliable segmentation and engagement-based prioritization.

3) No scoring

There was no consistent way to evaluate:

  • Which startups were most engaged
  • Which companies qualified for follow-up
  • Which participants became repeat attendees or potential Advocates

4) Data quality issues

The database contained:

  • Duplicate records
  • Inconsistent property usage in forms
  • Incorrect company names
  • Limited enrichment and incomplete firmographic data

This reduced trust in analytics and campaign targeting.

Our Solution

1) Introduced buyer personas and segmentation framework

We created workflows with clear persona definitions and implemented:

  • Persona-based segments

(Buyer persona assignment workflow in HubSpot - simplified version)

This workflow reads which Buyer Persona segment a contact belongs to (e.g., Partner) and automatically sets their Persona property to the matching value, keeping contacts correctly labelled.

  • Segmentation logic for marketing and scouting teams

(Contact segmentation workflow in HubSpot- simplified version)

This workflow reads a contact's type (e.g., Startup) and automatically copies that value into their professional involvement field.

2) Implemented contact and company scoring

Contact scoring based on:

  • Engagement
  • Persona alignment

Company scoring based on:

  • Engagement
  • Location
  • Custom firmographic properties

We tested enrichment approaches (Clay vs. HubSpot smart properties) to improve scoring accuracy and data completeness.

3) Data cleaning and standardization

We performed structured data cleanup:

  • Merging duplicates
  • Unifying form properties
  • Correcting false company names
  • Establishing consistent enrichment processes for new records

Additionally, we implemented the Data Quality Dashboard to monitor real-time data health.

(Data health dashboard in HubSpot)

4) Program and scouting dashboards

We built:

  • Programs dashboards for attendance and performance tracking

(Program application dashboard in HubSpot)

  • Scouting dashboard for leadership visibility

Business Impact

Program visibility — clear tracking of attendance and performance across key incubation programs.

Prioritized outreach — contact and company scoring guide teams on which startups to target for upcoming programs.

Data reliability — clean data improved segmentation and scouting decisions.

“As our startup ecosystem network expanded, we needed a clearer way to prioritize companies and measure performance. Clean CRM data, segmentation, and analytics gave us a consistent approach to selecting startups and tracking results.”

Tomasz Pazdro

Marketing & Communication at hubraum

CONSULTANT INSIGHT

“The main shift was moving from a contact list to a prioritization system. Once scoring, segmentation, and data cleanup were in place, the team could clearly see which startups to focus on and how programs were performing.”

Dorota Puchlew-Grzelak

RevOps Consultant at MAN Digital