Consulting · Hamburg · 2026

Fromdata chaos
to
decision architecture.

A consultancy for the German Mittelstand that connects monetisation, process automation and analytics into one integrated architecture — with clearly defined deliverables.

Focus
Mid-market & startups
Model
Defined deliverable
Access
Senior · no overhead
Sources → Control Raw data CRM · GA4 · ad server MarTech · APIs Analytics KNIME · KPI model Ownership matrix Decision architecture Concept · blueprint · guidance Control. vendor-neutral · documented n8n · AI agents Workflow automation Power BI Dashboards · self-service BI
WorconIQ · Architecture stack Live
Market findings Why the German mid-market and startups need architecture now
6%
of companies have data of genuinely high quality.
Marketing Tech Monitor · 2026
33%
of the MarTech features they own are actually in operational use.
Marketing Tech Monitor · 2026
61%
make little or no use of the potential in their own data.
Bitkom · 2026
39%
can trace any bottom-line impact at all to their use of AI.
McKinsey · 2025
The problem · Act I

Tools without architecture.
Data without control.

“Mid-sized companies have data — but no control over it. The tool landscape keeps growing, the quality of decisions stands still.”

Christoph Worreschke · Founder, WorconIQ
01

Reporting stays manual.

KPIs are defined department by department — inconsistent, unconsolidated, impossible to steer by. Spreadsheet bridges between systems that should have been talking to each other for years.

02

Programmatic runs without yield control.

Floor prices set wrong, SSP hierarchies inefficient — quiet revenue losses over months that nobody notices, because nobody can see them.

03

AI pilots never leave the test stage.

Automation potential gets identified, presented, approved — and never turned into productive architecture. The showcase survives, the value does not.

04

No end-to-end provider for the mid-market.

Monetisation. Automation. Analytics. Three capabilities that belong together — but nobody connects them for the German Mittelstand. Until now.

The path · Act II

From a chaos of sources
to one architecture.

Before · status quo The data chaos.

CRMsalesforce.com
AdServergam-360
Excelmonthly_kpi_v8
GA4analytics
MarTechcloud-stack
PowerBIdraft_v3
  • Tools are bought, not connected
  • Data merged by hand
  • KPIs defined department by department
  • Decisions made on gut feeling

After · WorconIQ The architecture.

Layer 1 · SourcesCRM · MarTech · ad server · GA4
Layer 2 · ModelKPI framework · ownership
↓ Structuring ↓
Workflown8n · AI agents
VisualisationPower BI · self-service BI
↓ Integration ↓
Decision architecturecontrollable · documented · handover-ready
  • Three layers, one integrated architecture
  • A defined KPI model with clear ownership
  • Automated data flows · AI agents
  • Self-service dashboards for every team
Services · Act III

Three areas of expertise.
One architecture.

All services
Approach · Act IV

Three phases.
Three tangible results.

No open-ended scope, no counting hours — one defined deliverable at the end of each step.

01
Phase 01 · Entry

Getting to know each other, and first results

We start with a workshop or an analysis kick-off. Your team gets to know the method — no prior knowledge required.

Result A prototype or blueprint you can use straight away
02
Phase 02 · Build

Structure, data and dashboards

KPIs are defined, data sources connected, and the first dashboards go into production — fully documented.

Result A live dashboard with a KPI framework
03
Phase 03 · Automation

Automation and optimisation

Manual processes are turned into systems that run on their own. AI workflows take over the repetitive work.

Result A productive n8n architecture with AI agents
Fine-line illustration of the Hamburg skyline: city hall, St. Michael’s, TV tower, Elbphilharmonie, Köhlbrand Bridge, container cranes, Speicherstadt with bridge, and water in the foreground with a sailing boat and a harbour ferry.
Christoph Worreschke Architecture for
digital control
Hamburg
About · Act V

A specialist.
Not an agency.

Hands-on experience across digital marketing, AdTech and process automation — grown at exactly the intersection the German mid-market needs today. Responsibility for media budgets of more than €1 million.

Every project is handled by me directly — no junior team, no overhead, no chain of command through three layers of hierarchy.

Experience
10+ years in practice
Based in
Hamburg · DE
More about me
Insights

The latest insights.

All articles

Articles are published in German.

AdTech & Monetarisierung
3 min · August 2026

Buying Committees wachsen, Budgets wandern: Wie Agentic AI und Account-Based Marketing das Programmatic Advertising 2026 neu aufstellen

B2B-Marketing steht vor einer strukturellen Verschiebung: Die Entscheidung über ein Software-Abonnement oder eine Maschineninvestition liegt längst nicht mehr bei einer Person. Wer heute Programmatic Advertising für B2B-Zwecke plant, muss ein ganzes Netzwerk von Stakeholdern erreichen – und tut das mit Werkzeugen, die vor drei Jahren noch nicht existierten. Mehr Entscheider, weniger Kontrolle Buying Committees – also die Gruppe aller an einer Kaufentscheidung beteiligten Personen – sind in...

Marketing Analytics
6 min · August 2026

1 % Preiserhöhung, 8,7 % mehr Betriebsgewinn: Welche KPI-Architektur Ihr Analytics-Setup dafür jetzt braucht

Kein anderer Hebel im operativen Geschäft wirkt so schnell und so präzise wie der Preis. Ein Prozent mehr Marge auf den Listenpreis – ohne Volumenverlust – schlägt direkt auf den Betriebsgewinn durch, während jede Kostenreduktion zuerst durch Effizienzprogramme, Restrukturierungen und Umsetzungsreibung gefiltert wird. Der Effekt ist mathematisch robust und gilt branchenübergreifend. Das Problem: Die meisten Analytics-Setups im Mittelstand sind nicht gebaut, um diesen Hebel präzise zu...

AI / KI
5 min · Juli 2026

Warum die meisten KI-Initiativen im B2B scheitern – und welche End-to-End-Workflows den Durchbruch bringen

Die Zahl kursiert durch die Strategiepräsentationen vieler Berater, und sie ist ernüchternd: Nur ein Bruchteil aller Unternehmen, die KI-Initiativen starten, erreichen tatsächlich skalierbaren Geschäftsnutzen. Der Rest steckt in Proof-of-Concept-Schleifen, leidet unter Datensilos oder hat schlicht unterschätzt, was ein funktionierender AI-Workflow im B2B-Kontext wirklich braucht. Die Kernfrage ist nicht mehr, ob KI eingesetzt wird – 67 % der Unternehmen sagen bereits heute, dass Marketing...

First call

Ready for more control?

No standard pitch — a concrete conversation about your situation, your data, your architecture. Free, without obligation, and directly with me.

Direct
office@worconiq.de
A reply within 24 hours — from Christoph himself.
Model
Defined deliverable
Defined scope, defined outcome.