ABOUT ME
MarTech Solution Architect
for SaaS & Marketplaces
As Solution Architect for Marketing Technology, I design and orchestrate modern marketing technologies using solid data structures. As the link between marketing, BI, and IT, I enable AI-driven decisions and scalable, cross-functional marketing impact.
Marketing Technology
CR17 Process
{exemplary simplified process scenario}
Empowering Enterprises to Unlock Actionable Data at Scale with AI powered Automation
Objective: Anchor core values and guiding principles as the foundation for collaboration
We base our collaboration on clearly defined values: interdisciplinarity, individuality, and trust. By developing tailored KPIs that reflect each client’s unique goals, we ensure our approach is both personalized and results-driven. We handle all customer data with strict confidentiality, strengthening long-term loyalty and fostering genuine partnerships built on mutual respect and trust.
Start
Objective: Define a compelling use case and quickly demonstrate value through pilot project and quick wins
We define a clear use case and establish measurable goals to set a focused direction for the initiative. By proactively involving key stakeholders from the outset, we ensure strong buy-in and shared ownership. We then launch a targeted pilot project designed to achieve quick wins, demonstrating tangible value early on and securing the necessary funding for broader rollout.
Weeks: 4-6
Milestone 1
Objective: Enable seamless automation, integrated personalization, and transparent content management across the entire value chain
We automate systems, personalize user experiences, and manage content with full transparency. By aligning on clear OKRs and defining roles—especially appointing a dedicated FTE owner—we enable effective cross-functional teamwork. To ensure lasting transformation, we apply structured change management practices that proactively address resistance and foster strong adoption across the organization.
Weeks: 4-8
Milestone 2
Obejctive: Build a robust, actionable data foundation and establish consistent, precise reporting
We systematically validate data at multiple checkpoints—during entry, transformation, and before output—to ensure accuracy and reliability throughout the entire data lifecycle. By standardizing data formats and implementing consistent terminology across all systems, we minimize confusion and reduce errors when integrating information across different platforms. We introduce robust data governance frameworks with clearly defined responsibilities, access controls, and automated validation tools to maintain data integrity while reducing human error. Building on this foundation, we create actionable dashboards and real-time reports that transform validated data into clear business insights, enabling truly data-driven decisions across the organization.
Weeks: 8-12
Milestone 3
Objective: Integrate AI into automation and data processes to create a real competitive advantage
We integrate AI into our automation and data processes using a structured, step-by-step roadmap that aligns with our business objectives. By systematically evaluating and piloting AI tools—especially for marketing automation—we ensure each solution fits our workflow and delivers measurable value. We connect legacy systems with modern, API-based integrations to create seamless information flows across platforms. Throughout, we use benchmarking to track our performance against industry standards, ensuring continuous improvement and competitive advantage.
Weeks: 12-16
Milestone 4
Objective: Ensure sustainability and continuous improvement of marketing automation and personalization
We establish a robust governance framework to ensure the long-term sustainability of our initiatives. By providing ongoing training and encouraging continuous feedback, we drive adoption and foster a culture of knowledge sharing across teams. We regularly review and adjust our KPIs, processes, and technologies to stay agile and aligned with evolving business goals.
ongoing
Milestone 5
Accelerate Your Market Entry: Transforming Data, Automation, and Personalization into Scalable Revenue
Objective: Project charter with defined objectives, scope, and measurable KPIs
We start by aligning with your leadership and GTM teams to define clear business objectives and target outcomes. Through stakeholder interviews and workshops, we map your current tech stack, data sources, and existing sales and marketing workflows. Together, we identify your unique value proposition, key customer segments, and the most promising use cases for automation and data enrichment.
Start
Objective: Unified, enriched data layer ready for workflow automation
We audit and integrate all relevant data sources—such as CRMs, marketing tools, and third-party data providers. We implement AI-powered research agents to automate data enrichment, uncover unique insights, and ensure data quality. Our focus is on consolidating your GTM stack to reduce complexity and costs, while boosting the accuracy and coverage of your prospect and customer data.
Weeks: 3-4
Milestone 1
Objective: Automated, personalized GTM workflows live and integrated across teams.
With a robust data foundation in place, we design and deploy flexible, iterative workflows tailored to your GTM objectives. Using conditional logic and automation platforms, we enable highly personalized outreach, lead scoring, and campaign execution at scale. Integrations with your CRM, email sequencers, and marketing automation tools ensure seamless data flow and real-time actionability.
Weeks: 3-5
Milestone 2
Objective: Secure, compliant GTM platform operational and monitored
We ensure your new GTM processes are fully integrated with your existing tech stack, leveraging APIs and pre-built connectors for maximum interoperability. Enterprise-grade security and compliance measures (SOC 2, GDPR, CCPA, ISO 27001+) are implemented from day one, safeguarding your data and building trust with stakeholders.
Weeks: 3-5
Milestone 3
Objective: Pilot success with measurable ROI and stakeholder advocacy
We launch a targeted pilot project in a high-impact segment—such as outbound sales or customer onboarding—to demonstrate immediate value. Early results are measured against agreed KPIs, and quick wins are communicated to secure buy-in and unlock further investment.
Weeks: 4-12
Milestone 4
Objective: Organization-wide rollout, with continuous optimization and measurable business impact
Based on pilot results, we develop a scaling roadmap to expand automation, enrichment, and personalization across additional teams and use cases. Ongoing training, feedback loops, and performance benchmarking ensure adoption and continuous improvement. We regularly review KPIs, processes, and technologies to keep your GTM strategy agile and ahead of the competition.
Weeks: 4-6 (ongoing)
Milestone 5
Empowering Enterprises to Unlock Actionable Knowledgeat Scale with RAG
(Retrieval Augmented Reality)
Objective: Anchor core values and guiding principles as the foundation for collaboration
Base collaboration on clearly defined values: interdisciplinarity, individuality, and trust. Develop tailored KPIs and handle customer data with strict confidentiality to build long-term loyalty.
Start
Objective: Understand your business context, data landscape, and define actionable goals
The process begins with in-depth stakeholder interviews and requirements gathering to align on business objectives and technical needs. We conduct a thorough audit of all relevant data sources—including SharePoint, wikis, ticketing systems, and product documentation—to map the information landscape. This is followed by an assessment of your organization’s knowledge management maturity and existing business processes, ensuring we identify both strengths and areas for improvement. Together, we pinpoint the most valuable business cases for implementation, such as customer support, compliance, or sales enablement. Finally, we define clear success metrics and KPIs—like research time reduction or improved accuracy—to ensure measurable outcomes and track progress throughout the project.
Weeks: 2 -3
Milestone 1
Objective: Lay a robust foundation for high-precision retrieval
During data preparation, we begin by analyzing and prioritizing all relevant data sources, ensuring each is properly structured for downstream use. We then clean the data to eliminate redundancies, standardize formats, and maintain high quality throughout. To enhance discoverability and contextual relevance, we enrich the documents with targeted metadata. Finally, we segment the content into optimal chunks and generate vector embeddings, laying the foundation for precise and efficient retrieval in the RAG system.
Weeks: 3-4
Milestone 2
Objective: Build a scalable, secure, and future-proof RAG infrastructure
We begin by selecting and deploying the most suitable vector database—such as Pinecone, Weaviate, or Milvus—to enable efficient and scalable data retrieval. This infrastructure is then seamlessly integrated with your enterprise systems using robust APIs, security protocols, and monitoring solutions. Next, we select and configure the optimal large language models, including options like deepset Haystack, OpenAI, or Vertex AI, to power advanced retrieval and generation capabilities. Custom pipelines are developed to orchestrate these components, while comprehensive access controls and compliance measures are implemented to ensure data security and regulatory alignment throughout the system.
Weeks: 3-5
Milestone 3
Objective: Validate value in a real-world setting and ensure seamless adoption
In this phase, we select and deploy the optimal vector database—such as Pinecone, Weaviate, or Milvus—to support scalable and efficient information retrieval. Seamless integration with enterprise systems is ensured through robust APIs, security protocols, and monitoring tools. We then select and configure the most suitable large language models, including options like deepset Haystack, OpenAI, or Vertex AI, to power advanced retrieval and generation workflows. Custom pipelines are developed to connect these components, while comprehensive access controls and compliance measures are implemented to safeguard data and meet regulatory requirements.
Weeks: 3-4
Milestone 4
Objective: Measure, optimize, and expand RAG capabilities across the organization
We systematically analyze performance against defined KPIs—including accuracy, time savings, and user satisfaction—to measure the solution’s impact. User feedback is continuously collected and integrated, driving targeted optimizations of both retrieval and generation components. Building on these insights, we develop a strategic roadmap to scale the RAG solution across additional departments and use cases. Ongoing maintenance and governance frameworks are established to ensure long-term reliability and continuous improvement.
Weeks: 4–6
Milestone 5
Commitment
What I value
I see my values as the foundation of my collaboration with clients. My actions are guided by a mission statement that is not only reflected in my consulting services, but also lived and practiced throughout every area of my services.
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Updated on 2 July 2025