01 / UNDERSTANDING
Kundensignale auswerten
Mit AI aus Feedback, Daten und Marktsignalen bessere Customer Insights gewinnen.
University certificate course · Online
Chief Customer
& AI Manager
Verstehen Sie Ihre Kunden besser und übersetzen Sie Customer Insights mit AI in konkrete Maßnahmen. Entwickeln Sie Ihren eigenen Customer-AI-Use-Case mit messbarem Nutzen.
- Customer Insights mit AI schneller gewinnen
- Digital Customer Twins entwickeln und validieren
- Kundenerkenntnisse in wirksame Maßnahmen übersetzen
CertifiersPartners
About the course
This certificate course combines Customer Centricity, Digital Customer Twins, Customer-in-the-Loop, and Generative AI into a practical management approach for modern customer orientation within the company.
Participants learn to gain customer insights faster, evaluate them better, and translate them into concrete actions, AI use cases, and measurable customer impact.
The course is aimed at executives, managers, and decision-makers who want to understand customers better, use AI effectively, and derive concrete improvements for marketing, sales, service, product development, innovation, and management from insights.
During the course, participants work on their own relevant Customer AI use case and develop a concrete implementation approach for their company from it.
What you can do afterwards
Vom Kundenverständnis zum Customer Impact02 / VALIDIEREN
Digital Customer Twins gestalten
Kundenmodelle entwickeln und Hypothesen mit echten Kundensignalen prüfen.
03 / HANDELN
Insights in Maßnahmen übersetzen
Use Cases nach Kundennutzen, Machbarkeit und Business Impact priorisieren.
04 / TRANSFER
Eigenen Use Case umsetzen
Ownership, Erfolgskriterien und einen Transferplan für das Unternehmen entwickeln.
All learning objectives in detail
Practical understanding of how modern customer centricity is implemented with AI in the enterprise
Clearer guidance on how to generate better customer insights from customer data, feedback, behavior, and market signals
A sound understanding of digital customer twins as the next evolutionary stage of classic personas
Methods to validate hypotheses, measures, and decisions with a customer-in-the-loop
Concrete approaches to derive effective actions, use cases, and business impact from insights
Structured tools for customer-centric processes, roles, responsibilities, and success measurement
A custom customer AI use case with clear value, ownership, and a transfer plan for your own company
Result for participants
Result for participants
Upon completion of the course, participants will have a clear understanding of how to practically apply customer centricity using AI and digital customer twins in the company.
You can gain customer insights faster, evaluate them better, and translate them into concrete actions. You are empowered to think and act in a customer-centric way, build suitable use cases with clear added value, and assume responsibility within the company as the owner of these initiatives.
Upon successful completion, participants receive the certificate:
Certified Customer AI & Digital Twin Manager
This title documents the ability to apply modern customer centricity, AI-powered customer insights, digital customer twins, and customer-in-the-loop methods within the company.
Participants can use this to demonstrate to supervisors, teams, and stakeholders that they are capable of translating customer insights into concrete actions and measurable business value.
Corporate result
Corporate result
Companies benefit from managers and employees who better understand customer needs, do not view AI in isolation, and can derive concrete results from insights.
The training course helps companies to,
making customer-centric decisions faster,
to use customer insights more systematically,
identify relevant AI use cases,
integrating customer feedback more strongly into processes,
Aligning teams to customer impact,
To more effectively connect innovation, marketing, sales, service, and product development.
Ihr Durchgang im Frühjahr 2027
Zehn Module · Workshop · AbschlusspräsentationSpring semester 2027
03.02. bis 10.05.2027
Online · mittwochs 17:00 bis 18:30 Uhr
Workshop am 06.05. · Abschluss am 10.05.
2.900 €per person, plus statutory VAT.
Book now
Pro members: Discount code VENTUREAI10
View all lesson schedules
03.02.2027, 17.00 – 18.30 Uhr – Kick-off
10.02.2027, 17.00 – 18.30 Uhr – Modul 1
17.02.2027, 17.00 – 18.30 Uhr – Modul 2
24.02.2027, 17.00 – 18.30 Uhr – Modul 3
03.03.2027, 17.00 – 18.30 Uhr – Modul 4
10.03.2027, 17.00 – 18.30 Uhr – Modul 5
17.03.2027, 17.00 – 18.30 Uhr – Modul 6
07.04.2027, 17.00 – 18.30 Uhr – Modul 7
14.04.2027, 17.00 – 18.30 Uhr – Modul 8
21.04.2027, 17.00 – 18.30 Uhr – Modul 9
28.04.2027, 17.00 – 18.30 Uhr – Modul 10
06.05.2027, 09.00 – 17.00 Uhr – Workshop
10.05.2027, 17.00 – 18.30 Uhr – Abschlusspräsentation
Preise pro Person, zzgl. 19 % Umsatzsteuer. Regulär: 3.451,00 € brutto. Pro-Preis: 3.105,90 € brutto. Ausschließlich für Unternehmen und beruflich Selbstständige.
Der Pro-Preis setzt eine aktive Pro-Mitgliedschaft im Bundesverband für KI-Transformation e.V. voraus. Mit der Verwendung des Rabattcodes VENTUREAI10 bestätigen Sie diese im Checkout. Wir prüfen die Berechtigung nach der Buchung. Besteht sie nicht, berechnen wir die Differenz zum regulären Lehrgangspreis nach.
Anbieter und Vertragspartner: VentureX Team GbR. Es gelten die Course conditions and Datenschutzhinweise der GbR.
The program
Zehn Module in fünf ThemenblöckenCustomer Centricity, AI & Customer Impact
Module 1: Customer Centricity in the Age of AI
- Why traditional customer centricity is often not enough
- New customer expectations, new touchpoints, and new decision-making logics
- From Customer Experience to Customer Impact
- The Role of AI in Marketing, Sales, Service, Product and Innovation
- What managers need to know about Customer AI today
Module 2: Customer in the Loop
- Meaning and principle of Customer-in-the-Loop
- How hypotheses, decisions, and actions are customer-validated
- Difference between inside-out and outside-in thinking
- How customer signals are integrated into management decisions
- Customer impact as a key performance indicator
Personas of tomorrow & Digital Customer Twins
Module 3: From Personas to Digital Customer Twins
Limitations of traditional personas
Building dynamic customer profiles
Customer needs, jobs-to-be-done, barriers to decision-making, and behavioral patterns
How Digital Customer Twins are used as thinking, testing and simulation models
Which data, signals, and hypotheses are relevant for this
Module 4: Digital Customer Twin Design Lab
Development of a proprietary digital customer twin concept
Definition of relevant customer segments and usage contexts
Development of prompt and analysis frameworks
Simulation of customer reactions, objections, and needs
Validation with real customer signals
AI-powered customer insights
Module 5: Faster and better customer insights with AI
- what customer data is already available in the company
- AI-assisted analysis of interviews, feedback, reviews, CRM, and service data
- Research with Generative AI
- Identifying patterns, pain points, opportunities, and segments
- Quality assurance, bias, data protection, and limitations of AI insights
Module 6: From Insight to Decision
- Evaluation and prioritization of customer insights
- Which insights are truly actionable
- Derivation of hypotheses, measures, and experiments
- Customer Journey, Value Proposition, and Use Case Prioritization
- Connecting customer insights with business goals
Actions, Use Cases, and Measurable Customer Success
Module 7: Developing Customer AI Use Cases
Use cases for marketing, sales, service, product development, and innovation
Evaluation based on customer value, feasibility, and business impact
Building a Customer AI Use Case Canvas
Definition of owners, processes, and success criteria
From idea to actionable pilot project
Module 8: Deriving successful actions from insights
Translation of insights into concrete actions
Experimental design and test logic
Customer-in-the-Loop Feedback Loops
Measurement of impact and customer success
Scaling successful measures within the company
Roles, processes, and transfer into the company
Module 9: Becoming an Owner of Customer-Centric AI Processes
- Welche Rolle ein Customer AI & Digital Twin Manager im Unternehmen übernimmt
- Establishment of appropriate processes and governance
- Collaboration with business units, Data, IT, Legal, and Management
- Convincing stakeholders and making customer impact visible
- Communication of personal and corporate added value
Module 10: Practical Workshop and Graduation
- Presentation of your own customer AI use case
- Feedback from instructors and peers
- Assessment of customer value, feasibility, and business impact
- Transfer plan for the next 90 days
- Graduation with a certificate
Structure and learning concept
Setting up the course
Der Lehrgang verbindet zehn Module mit einem Kick-off, einem Workshop und einer Abschlusspräsentation. Sie arbeiten an einem eigenen Customer-AI-Use-Case. Der Umfang beträgt 40 Lerneinheiten à 45 Minuten einschließlich 10 Lerneinheiten Selbststudium.
What it is about
Customers are changing faster than traditional market research, static personas, and isolated data analyses can capture. Today, companies need a new understanding of what truly motivates customers, what needs will emerge tomorrow, and how to turn these insights into better products, services, communication, and business decisions.
Our goal is to provide you with a sound understanding of how to practically apply customer centricity, AI-driven customer insights, digital customer twins, and customer-in-the-loop within your company.
You will learn how to recognize, evaluate, prioritize, and translate relevant customer signals into concrete actions. The focus is not on technology for technology's sake, but on a central management question:
How do we make better decisions by truly understanding customers, placing them at the center of our actions with new AI options, and consistently involving them in hypotheses, measures, and outcomes?
Teaching methods
As a participant in this course, you will receive a structured, practical approach to key questions of modern customer centricity in the AI era: from customer insights and digital customer twins to generative AI and customer-in-the-loop, as well as use cases, processes, governance, and measurable customer success.
You work on real-world issues from your company, reflect on existing customer assumptions, and develop concrete approaches to improve customer understanding, decision-making quality, and implementation speed.
What makes this course special
Modern customer centricity rarely fails because companies talk too little about customers. It fails because customer insights emerge too slowly, provide too little guidance for action, or are not consistently translated into decisions, processes, and responsibilities.
This is precisely where this course comes in: it combines customer centricity with AI, digital customer twins, and customer-in-the-loop. Participants learn to better understand customers, test assumptions more reliably, and derive concrete measures with measurable benefits from them.
In addition to understanding core methods, participants gain a realistic picture of how customer AI initiatives are implemented in companies: with suitable data, clear roles, robust use cases, governance, data protection awareness, and a consistent focus on customer impact.
At the same time, the course offers a practical approach to generative AI, digital customer twins, AI-supported analytics, and the development of concrete customer AI use cases. This creates a program that combines customer understanding, technology, implementation, and entrepreneurial added value.
- From Customer Understanding to Customer Success: The course does not stop at analysis, personas, or tools. It shows how customer insights are turned into concrete decisions, experiments, measures, and results.
- Digital Customer Twins as the next evolutionary stage of personas: Participants learn how static persona profiles can be developed into dynamic, data- and hypothesis-based Digital Customer Twins.
- Customer-in-the-Loop as a management principle: Hypotheses, measures, and results are consistently linked with customer signals and validated.
- AI as an accelerator for customer insights: Generative AI, data analysis, customer feedback, interviews, CRM data, support data, research, and market information are combined to create a faster insight process.
- Own use case with clear ownership: Each participant works on their own relevant use case and develops a concrete implementation approach from it.
- Measurable customer impact: The course helps make impact visible and communicate customer success to management, business units, and stakeholders.
- High reliance on transfer payments: The goal is not only the acquisition of knowledge, but also its reflective application in the respective corporate context.
Their professors
Frank RauchfussLecturer
Oliver GerstheimerLecturer
Jörn DickhautLecturer
Frequently asked questions
Welches Zertifikat erhalte ich?
Mit erfolgreichem Abschluss erhalten Teilnehmende das Zertifikat „Certified Customer AI & Digital Twin Manager“. Dieser Titel dokumentiert die Fähigkeit, moderne Kundenzentrierung, AI-gestützte Customer Insights, Digital Customer Twins und Customer-in-the-Loop-Methoden im Unternehmen anzuwenden.
Brauche ich AI-Vorkenntnisse?
Keine spezifischen AI-Vorkenntnisse erforderlich. Sie arbeiten an einer realen Fragestellung aus Ihrem Unternehmen.
How do I sign up?
Book course
Klicken Sie auf „Jetzt buchen“. Pro-Mitglieder geben im Stripe-Checkout den Rabattcode VENTUREAI10 ein und erhalten 10 % Nachlass. Ohne Rabattcode gilt der reguläre Preis. Jede Buchung gilt für einen Platz und eine teilnehmende Person.
Direkt über Stripe buchen
Prüfen Sie im Checkout Ihre Rechnungsdaten, den Gesamtpreis und die Kursbedingungen. Mit erfolgreichem Zahlungsabschluss ist Ihre Buchung verbindlich. Die Rechnung wird elektronisch über Stripe bereitgestellt.
Informationen zum Lehrgang
Die GbR informiert Sie über die weitere Organisation und den Zugang zur Lernplattform. Wenn Rechnungskunde und teilnehmende Person voneinander abweichen, teilen Sie uns deren Namen und geschäftliche E-Mail-Adresse unter team@bundesverband.ai mit.
Do you have any questions?
Feel free to use the chat feature at the bottom right of this page.