RELIABLE

Publisher Grows Its Subscription Funnel Thanks to Data and Campaign Expertise

High-quality data and precise target audience selection form the foundation for tailored campaigns at U+U. This enables the publisher to boost the effectiveness of marketing and subscription campaigns—efficiently, scalably, and sustainably.
  
Read on below …

 

 

 

Leinfelden-Echterdingen/Stuttgart, July 31, 2026 – Every media product has its own target audience. What works for a regional daily newspaper is by no means guaranteed to be successful for specialized information or digital offerings.

For the U+U Group—which publishes, among other titles, the *Staatsanzeiger* and the *Ludwigsburger Kreiszeitung*—the challenge was to precisely reach the relevant target audiences for subscription and marketing campaigns. After all, the success of a campaign depends on addressing precisely those people for whom the respective offer is actually relevant.

For over two years, Capaneo has been supporting U+U with data-driven target audience selection, thorough data cleansing, and target-audience-specific email campaigns. This results in highly tailored campaigns based on high-quality data, aligned with U+U’s requirements and goals.

Challenge

In the publishing industry, the success of subscription and marketing initiatives depends on how effectively the target audience is addressed: Different media products (print, digital, specialized information) require clearly defined target audiences and tailored communication strategies.

For U+U, the focus was therefore on:

  • to target private households precisely
  • to reach relevant B2B target audiences (companies, public institutions, decision-makers) in a structured manner
  • Reducing wasted reach and scaling campaigns in a predictable manner

 

Solution: A combination of data, quality, and campaign support

Capaneo supports U+U with a data-driven approach that seamlessly combines consumer and B2B targeting.

Target audience selection based on individual criteria
Selection of consumer and B2B addresses based on, among other things:

  • Region and Catchment Area
  • Industries and Company Characteristics
  • demographic factors
  • Potential for Use / Relevant Segments

Data Quality as a Key Success Factor
All data is systematically checked and cleaned in advance—including to identify people who have moved, deceased individuals, duplicates, and those who have opted out of advertising
–> Result : higher deliverability and lower wastage.

Supplementary Email Campaigns
In addition to providing data, Capaneo implements target-audience-specific email campaigns to further increase reach and response rates.

Flexible Implementation & Reliable Delivery
U+U receives the required address lists in compliance with data protection regulations and on time—tailored to the campaign objective, product, and region.

Added Value for U+U

This partnership provides U+U with a scalable foundation for successful campaigns:

  • More precise targeting of audiences in the consumer and B2B sectors
  • Measurably better campaign performance:
  • Double-digit percentage increase in response rates
  • A significant reduction in the return rate, accompanied by a sustained increase in the delivery rate
  • Significant growth rates in conversion within the subscription funnel
  • Reduced wastage thanks to verified and cleaned data
  • Flexible scalability across products, regions, and campaigns
  • A reliable data foundation for long-term marketing and sales planning

 

Conclusion

With Capaneo as its data and campaign partner, U+U enhances the effectiveness of marketing and subscription campaigns. Through precisely selected consumer and B2B data, along with accompanying email campaigns, the company is able to effectively reach relevant target audiences—efficiently, scalably, and sustainably.

“Capaneo has been providing us with reliable support for over two years in targeting our readers and business customers. Carefully selected consumer and B2B data, along with accompanying email campaigns, form the foundation of our successful marketing efforts.”

Matthias Rühle
Head of Reader Market, Reader Services, and Customer Center, Ludwigsburger Kreiszeitung

 

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Revolutionary

TVB Stuttgart Uses AI Agents for Sponsor Acquisition

udo matches the target audiences of potential partners with consolidated club data and provides solid reach metrics for sponsorship discussions.

Continue reading below …

 

 

Leinfelden-Echterdingen/Stuttgart, July 30, 2026 – TVB Stuttgart, a Handball Bundesliga club, is using the AI-based sponsor agent from Capaneo’s data intelligence platform, udo. The agent analyzes potential sponsor companies, develops probabilistic target audience profiles based on this analysis, and compares them with TVB’s consolidated club data. This provides the sponsorship sales team with concrete insights into how many fans and contacts align with a company’s target audience. Instead of generic reach promises, the club can now base its sponsorship offers on reliable target audience information.

BACKGROUND

TVB Stuttgart has begun consolidating and cleaning its data in udo. Fan, ticketing, membership, and reach data—which were previously scattered across various systems and lists—have been consolidated into a clean, unified database in udo. This gives the club, for the first time, a reliable overall picture of its reach—the foundation for everything that follows.

CHALLENGE

In sponsorship sales, the traditional selling points have been visibility, emotion, and gut feeling: perimeter advertising, jersey branding, and arena atmosphere. What companies expect today, however, are solid answers to a simple question: Am I actually reaching my target audience through the club—and if so, to what extent? Until now, very few clubs have been able to provide exactly that answer.

THE SOLUTION: THE SPONSORSHIP AGENT IN UDO

The sponsorship agent supports TVB’s sales team in three steps:

1 Company Research. The agent researches the potential sponsor company: industry, products, positioning, regional presence, and typical customer base.

2 Probabilistic target group. Based on this information, the agent creates a probabilistic target audience profile—a probability model that identifies which people are relevant to the company as customers. The probabilistic approach is not a detour, but rather a prerequisite: Neither TVB nor udo has access to the sponsor’s customer data—nor do they need it. The AI derives the target audience profile solely from company research. This makes the approach immediately applicable for any company, without any data exchange whatsoever. At this stage, the profile is a well-founded hypothesis.

3 Mapping to the TVB data. Now comes the crucial step: The agent maps the probabilistic profile to the consolidated, real-world club data in udo. The probabilistic assumption becomes a verifiable statement—namely, how many of TVB’s fans and contacts actually match the company’s target audience.

The result: The sales team no longer approaches prospects with a generic sponsorship brochure, but rather with a deterministic line of reasoning — by mapping to real data, a probabilistic approach becomes a data-driven, robust statement tailored to the specific company and backed by concrete reach figures for the club’s sponsored products.

SUCCESS

The level of preparation and depth of argumentation fundamentally change the nature of the discussions. A traditional sponsorship pitch becomes a business discussion among equals: The TVB can demonstrate the target audience reach associated with each sponsored product.

“The feedback from sponsors has been overwhelming. Companies have rarely seen such a strong case and level of preparation from other clubs.”
Martin Jux, B2B Sales and Partner Management, TVB 1898 Handball GmbH & Co.KG

CONCLUSION

The TVB Stuttgart case study demonstrates what’s possible when a club consolidates its data and makes it usable in a smart way: With udo, scattered data sets are transformed into a clean database—and with the Sponsor Agent, a sales tool that turns reach into measurable metrics. Sponsorship thus shifts from gut instinct to data-driven decision-making.

 

udo is Capaneo’s data intelligence platform. It consolidates, cleans, and refines corporate data, making it directly usable in day-to-day operations via AI agents.

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Data-sovereign AI in CRM

AI revolutionizes CRM when data protection is integrated: Private data clouds and indirect LLM access ensure data sovereignty and efficiency.

Artificial intelligence (AI) has the potential to radically change customer relationship management, marketing and sales. Modern systems can do far more than just databases with customer data: they can recognize patterns, provide recommendations for action and even take over entire work steps that used to be time-consuming and error-prone.

But while the euphoria about new possibilities is great, the most important critical question is: How can I use AI solutions in a compliant and data protection-compliant manner without using personal data unlawfully or revealing trade secrets?

 

The music of AI benefits is now blaring from all channels. Whether it’s simple target group selection, hyper-personalization of marketing, optimized risk/churn detection, cross-channel coordination, appropriate recommendations for action, etc. – the list of appropriate terms is long. They all have one thing in common: AI solutions are not just intended to make life easier for marketers. Rather, the marketing department should be given unprecedented power and a previously unimagined depth of information from the open AI worlds. However, this is where every responsible marketing expert is confronted with the dangers of using AI tools, which can be expressed in one question: Do I know which of my company’s data ends up where?

And indeed, simply dumping customer data into the chat GPTs of this world doesn’t feel good, regardless of the tempting results. Is the provider who loads my data directly into the Open APIs really trustworthy and knows what they are doing?

 

The other side of the coin: data protection & regulation

 

As great as the opportunities are, the risks are just as high if customer data is processed carelessly with AI. The direct use of large language models (LLMs), which access raw data unfiltered, is particularly problematic.

Central dangers:

  • Uncontrolled data transfer: Prompts to external AI services can reveal personal data.
  • Storage by third-party providers: It often remains unclear whether inputs are stored permanently or even used for further model development.
  • Lack of transparency: LLMs cannot provide a complete explanation of their results.
  • Violation of the GDPR principles: Purpose limitation and data minimization can hardly be complied with if all data is simply “dumped into the AI”.
  • Legal risks from the EU AI Act: In the near future, this will set clear requirements for transparency, risk classification and governance.

A company that uses AI uncontrolled in CRM and marketing consequently risks high fines, loss of trust from its customers and far more than annoying damage to its image if most of the risks can be eliminated in advance with little transparency and expertise from the provider.

 

The right way: AI without direct access to raw data

 

The solution is to design AI architectures in such a way that customer data remains protected and controlled. Two principles are crucial:

  1. Use private data environments
    Customer data should be stored in a private cloud controlled by the company – not on the servers of external providers.
  2. Only allow AI access to aggregated analyses
    Instead of processing raw data, AI works on aggregated, anonymized or already interpreted data. This preserves sovereignty over sensitive information.

This means that the use of AI is not a risk, but a secure enabler for modern customer management.

The mixture of retaining (customer) data sovereignty at all times and at the same time using the essential essence of the AI world in a legally compliant manner is the path that, albeit on a new technical footing but with logical steps, makes the use of AI tools a profitable experience and not a persistent nightmare.

 

AI intelligence on a secure data basis

 

One example of this data protection-friendly architecture is SaaS platforms that combine the possibilities of LLMs with consistent data sovereignty.

How it works:

  • Private Data Cloud: All customer data remains in a protected, company-owned data environment.
  • Indirect AI access: LLMs only access analyses already created by the platform – not the raw data itself.
  • Auditable results: Every suggestion, every recommendation is transparently documented and traceable.
  • Regulatory future-proofing: The architecture is designed to be compatible with the requirements of the GDPR and EU AI Act.

The advantages at a glance:

  • Data protection-compliant and future-proof
  • Maximum data sovereignty for companies
  • AI functionality fully usable, without security risks
  • Trustworthy basis for marketing, sales and CRM

With the legally compliant use of AI, it becomes a real benefit for CRM, marketing and sales – efficient, intelligent and legally compliant at the same time.

 

Conclusion

 

Artificial intelligence can take CRM, marketing and sales to a new level. Intelligent segmentation, personalized communication and automated workflows increase efficiency and impact enormously.

But those who ignore data protection and regulation run the risk of creating more problems than benefits. The future therefore belongs to solutions that combine both: AI power and strict data sovereignty.

 

Published on 21.10.2025 in the Marketingbörse.

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DATA INTELLIGENCE PLATFORM WITH AI AGENTS

udo turns data into concrete opportunities for marketing and sales

Meet udo — a data intelligence platform with AI agents and its own data universe!

Watch this short video to see what makes udo so unique and how udo’s marketing and sales teams benefit from it.

 

udo video

 

Contact us

udo = universal data orchestration:
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Acquiring new customers across all channels

Stage 4: Campaigns

In a short video, we show you how you can use our unique data universe for your new customer acquisition across all channels – B2B and B2C!

 

Video data quality

 

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Answers to all your questions

Stage 3: Data analysis

In a short video, we show you how we recognize relevant patterns in your data and give you answers to all your questions about your customers, target groups and untapped potential!

 

Video target group analysis

 

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Want to know more than just the purchase history?

Stage 2: Data enrichment

In a short video, we show you how enriching additional information from our data universe provides you with valuable customer insights. Finally get to know your customers!

 

Video data enrichment

 

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Clean data is the basis for your success in sales & marketing

Stage 1: Data fusion & data cleansing

In a short video, we show you why correct data is so important and how we can help you get your database under control.

 

Video data quality

 

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Data-sovereign AI in CRM

AI revolutionizes CRM when data protection is integrated: Private data clouds and indirect LLM access ensure data sovereignty and efficiency.

Artificial intelligence (AI) has the potential to radically change customer relationship management, marketing and sales. Modern systems can do far more than just databases with customer data: they can recognize patterns, provide recommendations for action and even take over entire work steps that used to be time-consuming and error-prone.

But while the euphoria about new possibilities is great, the most important critical question is: How can I use AI solutions in a compliant and data protection-compliant manner without using personal data unlawfully or revealing trade secrets?

 

The music of AI benefits is now blaring from all channels. Whether it’s simple target group selection, hyper-personalization of marketing, optimized risk/churn detection, cross-channel coordination, appropriate recommendations for action, etc. – the list of appropriate terms is long. They all have one thing in common: AI solutions are not just intended to make life easier for marketers. Rather, the marketing department should be given unprecedented power and a previously unimagined depth of information from the open AI worlds. However, this is where every responsible marketing expert is confronted with the dangers of using AI tools, which can be expressed in one question: Do I know which of my company’s data ends up where?

And indeed, simply dumping customer data into the chat GPTs of this world doesn’t feel good, regardless of the tempting results. Is the provider who loads my data directly into the Open APIs really trustworthy and knows what they are doing?

 

The other side of the coin: data protection & regulation

 

As great as the opportunities are, the risks are just as high if customer data is processed carelessly with AI. The direct use of large language models (LLMs), which access raw data unfiltered, is particularly problematic.

Central dangers:

  • Uncontrolled data transfer: Prompts to external AI services can reveal personal data.
  • Storage by third-party providers: It often remains unclear whether inputs are stored permanently or even used for further model development.
  • Lack of transparency: LLMs cannot provide a complete explanation of their results.
  • Violation of the GDPR principles: Purpose limitation and data minimization can hardly be complied with if all data is simply “dumped into the AI”.
  • Legal risks from the EU AI Act: In the near future, this will set clear requirements for transparency, risk classification and governance.

A company that uses AI uncontrolled in CRM and marketing consequently risks high fines, loss of trust from its customers and far more than annoying damage to its image if most of the risks can be eliminated in advance with little transparency and expertise from the provider.

 

The right way: AI without direct access to raw data

 

The solution is to design AI architectures in such a way that customer data remains protected and controlled. Two principles are crucial:

  1. Use private data environments
    Customer data should be stored in a private cloud controlled by the company – not on the servers of external providers.
  2. Only allow AI access to aggregated analyses
    Instead of processing raw data, AI works on aggregated, anonymized or already interpreted data. This preserves sovereignty over sensitive information.

This means that the use of AI is not a risk, but a secure enabler for modern customer management.

The mixture of retaining (customer) data sovereignty at all times and at the same time using the essential essence of the AI world in a legally compliant manner is the path that, albeit on a new technical footing but with logical steps, makes the use of AI tools a profitable experience and not a persistent nightmare.

 

AI intelligence on a secure data basis

 

One example of this data protection-friendly architecture is SaaS platforms that combine the possibilities of LLMs with consistent data sovereignty.

How it works:

  • Private Data Cloud: All customer data remains in a protected, company-owned data environment.
  • Indirect AI access: LLMs only access analyses already created by the platform – not the raw data itself.
  • Auditable results: Every suggestion, every recommendation is transparently documented and traceable.
  • Regulatory future-proofing: The architecture is designed to be compatible with the requirements of the GDPR and EU AI Act.

The advantages at a glance:

  • Data protection-compliant and future-proof
  • Maximum data sovereignty for companies
  • AI functionality fully usable, without security risks
  • Trustworthy basis for marketing, sales and CRM

With the legally compliant use of AI, it becomes a real benefit for CRM, marketing and sales – efficient, intelligent and legally compliant at the same time.

 

Conclusion

 

Artificial intelligence can take CRM, marketing and sales to a new level. Intelligent segmentation, personalized communication and automated workflows increase efficiency and impact enormously.

But those who ignore data protection and regulation run the risk of creating more problems than benefits. The future therefore belongs to solutions that combine both: AI power and strict data sovereignty.

 

Published on 21.10.2025 in the Marketingbörse.

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Simply fill in the form with your details and your request. We will get back to you as soon as possible. Alternatively, you can also make an appointment directly via Calendly.

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Discover a world full of knowledge and opportunities!
To take your business to a new level, you will receive in our newsletter

  • up-to-the-minute insights
  • groundbreaking trends
  • exclusive content and
  • access to valuable discount promotions

 

Register now and experience how data and digitalization go hand in hand for your success.

Success Story

How La Biosthétique is transforming e-commerce with data-driven marketing

The culture of beauty meets the culture of data.
udo von Capaneo (formerly Schober) has once again written a success story. This time, our platform has transformed e-commerce at La Biosthétique Paris.

Read on below …

 

 

B2B under control – B2C still has a lot of potential

La Biosthétique Paris is internationally renowned for high-quality cosmetic products and works exclusively with owner-managed hairdressing and beauty salons. Over-the-counter sales are flourishing – but the B2C online store in 13 countries has fallen short of expectations.

The challenge:

  • Hardly any internal resources for e-commerce analysis
  • No networked data landscape (many silos)
  • High proportion of guest orders suspected
  • Only limited customer insights – no segmented approach
  • No business intelligence or automated processes

The goal was clear: more sales in the online store, targeted new customer acquisition and activated existing customers.

 

The solution: Data Value Management with udo

 

With the support of Capaneo GmbH (formerly Schober Information Group Deutschland GmbH), La Biosthétique decided to use the udo data value management platform.
The path to data-driven e-commerce excellence was paved in four consecutive steps:

 

Specifically: Data Value Management in four stages for La Biosthétique:

 

#1 Data cleansing & integration

  • Consolidation of fragmented data sources (CRM, ERP, e-mail system)
  • Duplicate matching, address correction, plausibility checks
  • Basis for clean customer scoring

Advantage: The cleansed data is later used as a learning data set for AI-based lead prediction

 

#2 Data enrichment

  • Expansion to include external consumer characteristics, interests, purchasing power, etc.
  • Link to Capaneo database: over 70 million consumer profiles
  • Differentiation between occasional vs. regular customers (who are the guest shoppers?)

Advantage: The broader the database, the better the AI

 

#3 Segmentation & Customer Insights

  • Development of four behavior-based customer segments such as:
    • Segment 1 – The Occasional Explorer (rare customers)
    • Segment 2 – The Loyal Enthusiast (committed, regular customers)
    • Segment 3 – The Lapsed Loyalists (reactivatable ex-buyers)
    • Segment 4 – The Devoted Connoisseur (loyal frequent buyer)
  • Use of AI & machine learning for purchase probability analysis

Advantage: Better understanding optimizes the approach

 

#4 Campaign automation & personalization

  • Automated, segmented e-mail routes
  • Reminder campaigns: e.g. “Is your shampoo empty?”
  • Cross-selling, seasonal topics & next-best-product recommendations
  • Reduction of guest purchases through new checkout & account focus

The results: Clearly measurable – and convincing

 

La Biosthétique was already able to make significant progress in the first year after the start of the project:

  • Significant increase in sales in the B2C online store
  • +9.88 % higher basket value
  • Reduction of guest purchases through optimized checkout
  • Establishment of company-wide B2C controlling
  • Roll-out to France & Italy – other countries to follow

 

The journey continues: self-learning systems & continuous progress

 

With udo, La Biosthétique has not only implemented a technical solution, but also anchored a new data-driven mindset in marketing. The algorithms used are continuously improving – through real customer reactions, intelligent segment shifts and dynamic campaign adaptation.

 

Conclusion

 

With Capaneo as a partner, La Biosthétique was able to sustainably drive its transformation in the B2C business – with clear results and a scalable infrastructure for future growth.

“With udo, we not only got to know our customers better – we now understand them better.
Thanks to data-based marketing, we communicate more individually, more relevantly and more efficiently.
This allows us to create real proximity, address needs more specifically and offer tailor-made solutions.
The result: significantly stronger customer loyalty and noticeably more sales.”

– Edwin Teiber, Head of E-Commerce, La Biosthétique Paris

 

Curious about how your company can benefit from udo?

Talk to us. We’ll show you how data value management can boost your sales with automated processes.

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Discover a world full of knowledge and opportunities!
To take your business to a new level, you will receive in our newsletter

  • up-to-the-minute insights
  • groundbreaking trends
  • exclusive content and
  • access to valuable discount promotions

 

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