From scattered startup data to scouting intelligence

How Hub:raum centralized data in HubSpot, implemented segmentation, and performance analytics to improve scouting programs' effectiveness.

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

Tomasz Pazdro
Marketing & Communication, hub;raum

Automated

MARKETING SEGMENTATION

Real-time

LEAD SCORING

Reliable

CRM DATA

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Situation

Hub:raum runs scouting programs for startups. Data about companies and contacts was scattered across HubSpot,  CB Insights, and Tracxn.

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Problem

Scouting activities relied on fragmented data, making it hard to select companies for future programs and measure their performance.

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Solution

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

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Benefit

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

The Situation

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

Hubraum hero secttion

Scouting activities are at the core of Hub:raum’s operations. However, data supporting these activities lacked structure and visibility.

The Problem

1) No visibility into program performance 

There was no clear 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 clear persona definitions and implemented:

  • Persona-based segments

(Buyer persona workflow in HubSpot) 

  • Segmentation logic for marketing and scouting teams

Hubraum Segmentation workflow in HubSPot

 (Segmentation workflow in HubSpot)  

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.

Hubraum data health reports

(Data health dashboard in HubSpot)

4) Program and scouting dashboards 

We built:

  • Programs dashboards for attendance and performance tracking

HubRaum Performance Reports

 (Program application dashboard in HubSpot) 

  • Scouting dashboard for leadership visibility

HubRaum - scoutign reports

 (Scouting dashboard in HubSpot) 

Business Impact

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

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

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Data reliability — clean data improved segmentation and scouting decisions. 

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

Tomasz Pazdro

Marketing & Communication at hub:raum

Consultant insight icon

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

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