Alexander Rausch

CERTA GmbH

CERTA ist ein führendes Unternehmen im Bereich der Immobilienbewertung in Deutschland, das sich durch innovative Ansätze und zertifizierte Expertise auszeichnet. Wir bieten eine umfassende Palette an Dienstleistungen, die von Verkehrswertgutachten bis hin zu Beleihungswertgutachten reicht, um den spezifischen Bedürfnissen unserer Kunden gerecht zu werden. Unser Fokus liegt auf der Nutzung modernster Technologien, um die Effizienz und Genauigkeit unserer Bewertungen zu maximieren. Wir sind stolz darauf, unabhängige und präzise Bewertungen für Eigentümer, Vermieter und Immobilieninvestoren anzubieten, die auf fundiertem Fachwissen und jahrelanger Erfahrung in der Branche basieren. Bei CERTA verpflichten wir uns, unseren Kunden erstklassige Dienstleistungen zu bieten, die sie bei ihren Immobilienentscheidungen unterstützen.

Gründer & Geschäftsführer

scaleup-mentor.com

Ich unterstütze Gründer + Führungskräfte bei ihrem Unternehmenswachstum auf EUR 150M+ Umsatz. Folge mir, um mehr über nachhaltige Skalierungsstrategien und den Umgang mit Wachstumsschmerzen zu erfahren

Start-Up and Scale-Up Mentor

talent360 GmbH

Die Software unterstützt Personaldienstleister dabei, Kandidaten zu finden, Bewerbungen zu verwalten, Nachrichten auszutauschen und Marketing-Kampagnen durchzuführen. Bei uns steht die Benutzerfreundlichkeit im Mittelpunkt: sofort einsatzbereit, bei minimalem Aufwand für die Systemintegration.

Business Angel & Growth Mentor

itravel Group

Interim-Manager

CHRONEXT

Managing Director

Joblift

Joblift – a job search platform providing candidates with the most intuitive and frictionless experience during the recruiting process. 

At Joblift I was responsible for 
- Performance Marketing: building key-word based bidding engines with millions of possible combinations
- Business Intelligence: creating a standard job taxonomy to classify job-titles, and job descriptions
- operational Processes: setting up a sales organization and introducing new markets
- recruiting: building a stellar organization and hiring top talent
- fundraising: raising 10M in Series A led by DN Capital

Chief Operating Officer

Amorelie / Sonoma Internet GmbH

- Initiated to sell private label products via Marketplaces (Amazon, Ebay, Rakuten, Otto)
- Managed Offline Sales Channel (Amorelie Toyparty) and grew business to 250+ Consultants
- Lead Finance & Accounting until Exit to P7
- Build up Operations & Customer Care from scratch: introduced third party logistics and self-service portal

Always-Party.com

- Built the biggest event community in Soest at the age of 16
- organized 1LIVE Chartsparty for the biggest radio station in NRW
- helped event organizers market their event with data driven approach
- sold community to competition

Founder

Warum Immobilieninvestoren an Cyber Monday jetzt hellhörig werden sollten 👇


Für alle vermieteten Bestandsimmobilien mit Baujahr vor 1990 kann ein Restnutzungsdauergutachten (RND) steuerlich und strategisch einen echten Unterschied machen. Wir realisieren teilweise Afa-Werte von bis zu 8,3% p.a. und haben bereits Tausende Gutachten realisiert.

Und genau deshalb gibt es jetzt bis zum 07.12.2025 ein starkes Angebot:

🔥 Exklusiv: 15 % Rabatt auf Dein Restnutzungsdauergutachten bei CERTA Immobiliengutachten

Unsere kostenlose Ersteinschätzung schafft Klarheit über die verbleibende  Nutzungsdauer Deiner Immobilie und damit über das Abschreibungspotenzial.

Wenn Du wissen willst, ob sich ein RND für Deine Immobilie wirklich lohnt:
👉 Kommentiere „RND“ oder schreibt mir eine DM. 

Ich melde mich dann direkt bei euch.

Unternehmer | WHU | KI | Immobilien | Growth & Business Automation – präzise, effizient, unabhängig

Glad to speak about our customer journey facilitated by artificial intelligence

Join us for the Germany AI Roadshow in Cologne, third stop of our six-city tour by Make and buildersklub.

​​These events are designed to deliver education, inspiration, and hands-on engagement for professionals already leveraging Make in their work. You’ll discover real solutions in action, get inspiration from genuine success stories, and connect with fellow builders, makers, and enthusiasts in your local community.

​​Agenda
​​18:00 – 18:30 - Welcome, networking, drinks & snacks
​​18:30 – 18:40 - Introduction by Buildersklub & Make
​​18:40 – 19:10 - Success Story: Alexander Rausch, Founder of CERTA Immobiliengutachten, will share how they leverage AI and Make to transform customer operations at scale. With 300+ Make scenarios running in production and 10 years of automation experience, he’ll walk us through how AI-powered sentiment analysis reduced bad reviews by 90% and how automation enables a 16-person team to serve 3,000+ customers annually in the highly analog German real estate appraisal industry.
​​19:10 – 19:40 - Live Demonstration: Roger P. of the 9x team builds a live AI agent with Make and guides participants to do the same on their own laptops.
​​19:40 – 20:10 - Q&A Session
​​20:10 – 21:00 - Closing remarks & informal networking

​​👉 Whether you’re deep into automation or just curious about how to scale AI in the real world, this evening will equip you with practical knowledge

​​✨ Reserve your spot today and be part of the growing Buildersklub & Make community shaping the future of AI and automation!

#MakeAIWorldTour #jointheklub

View event: AI Agents After Hours Cologne by buildersklub x Make - German AI Roadshow

AI Agents After Hours Cologne by buildersklub x Make - German AI Roadshow

Sebastian Hewing 🚀

Data Action Mentor

Building masterclasses and communities for data leaders and future data leaders who want to create outsized business impact with data & AI.

Sebastian Hewing Consulting

🚀 I build impactful, AI-first data infrastructure for VC/PE-backed consumer companies.

Previous clients include Zalando, Lazada, Global Fashion Group (Dafiti.com, Lamoda.ru, Jabong.com, TheIconic.com.au, Zalora.com), Linio, Jumia, Lieferando, eBay, Telefonica o2, HUK Coburg, Axel Springer, Lendico, OCC Assekuradeur, Creadi AG, Boerse Stuttgart, Bergfreunde.de / Backcountry.com, Sanity Group, Takeaway.com, Wasoko, Westwing, Beat81 and more

Owner

Locafox GmbH

Raised EUR 10+M from established Investors such as Holtzbrinck Ventures to digitize local retail and build Europe's largest omni-channel shopping marketplace

- Built up Business Intelligence and Analytics Team from Scratch
- Established a true Data Self Service Environment (Around 90% of Analytics Requests could be handled independently by Functional Departments)
- Managed and Led Market Entry to Spain
- Spain contributed 1/3 of the Total Revenues after 6 Months

Director Business Intelligence & International

Rocket Internet SE

Rocket Internet is the world's largest Internet incubator. Our team has been building online companies since 1999 and has created over 100 market leading companies in 50+ countries, dozens of which have been exited successfully. Examples: Zalando, Lazada, Delivery Hero, HelloFresh.

- Implemented and customised 7 Data Warehouses (DWHs) for Rocket Internet’s global portfolio
companies.
- Product Owner for Analytics Applications such as split-testing, catalogue
sorting algorithms, product recommendation algorithms, marketing attribution
modelling and predictive modelling.
- Built and led the global Data Team. Disciplinary lead for 10 central
employees and functional lead for 40+ employees in 7 Portfolio companies.
- Increased Revenue per Visitor of 3 Portfolio companies by 10-12% with the
help of a custom-built product recommendation algorithm.
- Management of the central Analytics Budget for 50+ Portfolio companies.

Head of Business Analytics

SHS VIVEON AG

One of Europe's leading boutique consulting firms for Data Analytics, Data Warehousing and Customer Management.

- Managed a variety of projects with focus on customer analytics; e.g. customer
segmentation, churn prevention and development of customer scorecards.
- Accountable for the development of the Multi-Channel Marketing practice area,
specializing in the field of Marketing-Performance-Monitoring and -Optimisation.
- Fast career progression, receiving semi-annual promotions.

Consultant

InsightAsia Research Group / DemandROMI (JV)

built up a pan-Asian consulting division focusing on Marketing & Sales Performance

Co-Founder

Accenture

conducted emprical study about success factors of Multi-Channel Management in Banking as part of final thesis

Business Analyst

Founder Data Action Mentor | Swiss Army Knife for Data & Analytics | Ex-Rocket Internet

I'm a mix of data engineer, entrepreneur, product manager and marketer. 🛠️🚀🧑‍💻🎯

I help tomorrow's data leaders create outsized business impact by building AI-first, 10X data teams.

-> Find out more at www.dataactionmentor.com

In the last 17+ years, I worked as a Data Practitioner and Data Leader for Startups, Corporates, and in Consulting across all continents. 

As Head of Business Analytics at Rocket Internet, the world's largest venture builder, I built and led Data & Analytics Teams and Infrastructure for 7 portfolio companies in 15 countries.

Rocket Internet scaled companies such as Zalando (Europe's leading online fashion platform), Delivery Hero (a leading food delivery platform), HelloFresh (the world's leading meal kit delivery company), Lazada (the Amazon.com of SouthEast Asia, exited to Alibaba) and Jumia (the first African company on the NYSE). 

As a consultant and advisor to Founders and CEOs, I built or re-built the first data team and data infrastructure for 50+ leading consumer companies.

P.S.: My biggest passion next to Data & AI is Traveling. I live on the beautiful island of Taiwan 🇹🇼 but I typically spend 5-6 months per year traveling to hang out with my awesome global clients. I have been to 100+ countries and territories.

Founder & Mentor

Solve all your Data- & Analytics Challenges and connect with experienced Data & AI Professionals for a price and time investment that every startup can afford

“Let’s define a data strategy.”

Translation: let’s argue about tools for 6 months.

Here’s the thing nobody wants to admit:

Most data strategies are just about data stacks.
Not actual strategy.

If you want a strategy that survives the next reorg, AI hype wave, or exec sponsor change - start here:

1. Problem: What are we solving?
2. Users: Who are you serving?
3. UVP: What's our data team's secret sauce?
4. Solution: What are we building and what are we NOT building?
5. Distribution: How will we get this in front of users without chasing them down?
6. Systems: What helps this scale without breaking us?
7. Outcomes: What will users actually do differently?
8. Costs: What’s the real investment? (Spoiler: it’s not just the software)
9. People: How will we grow a team that wants to stick around?
10. Vision: What guides our decisions when priorities clash?

Answer those 10?

You’ve got a data strategy.

Ignore them?

You’ve got a dashboard backlog and a stack no one uses.

♻️ Repost if you've ever watched a “data strategy session” turn into a Power BI vs Tableau debate.

👉 And join 3,000+ data leaders who read my free newsletter for weekly tips on building impactful data teams in the AI-era: https://lnkd.in/gt_2Gc4s

Sebastian Hewing

10x ROI with data & AI foundations for VC/PE-backed companies | Hands-on Data Strategist | Solopreneur & Travel Addict (100+ countries & territories) 🌏

We’re in the middle of a dashboard pandemic.

Symptoms include:

→ 173 dashboards across 3 tools
→ Nobody agrees on the numbers
→ “Can I get this in Excel?” - every day
→ Burned-out data teams trapped in JIRA tickets for minor tweaks

Diagnosis?

Chronic dashboard overproduction with decision fatigue.

Because somewhere along the way, we confused outputs with outcomes.

We thought: more dashboards = more insights = more value.

But here’s the thing:

-Dashboards don’t drive decisions
-Dashboards don’t change behavior
-Dashboards don’t fix broken processes

They visualize. That’s it.

Want to really move the needle instead of pumping out prettier charts?

Start with this:

→ What decision are we trying to support?
→ Who owns it?
→ What happens if we don’t build it?

It’s not easy.

But it’s the cure.

♻️ Repost if your dashboards are multiplying faster than decisions are being made

👉 And join 3,000+ data leaders who read my free newsletter for actionable tips on building impactful data teams in the AI-era:
https://lnkd.in/gMSUaAsx

Who gets rich when your data strategy starts with tools?

Not you.

Not your company.

But vendors? They’re popping champagne. 🍾

Snowflake, Databricks, Tableau, Fivetran, Power BI...

Every time you chase a new tool, someone at a SaaS company gets a bonus.

But when you start with your users and their problems?
→ You create products that stakeholders actually use.
→ You drive real business outcomes.
→ You build trust and influence.
→ You get promoted.

After 18 years, here’s what I’ve learned:

🚫 Picking tools is not a strategy.
✅ Solving problems for real humans is.

A proper data strategy has 9 parts:

1. Problem
2. Users (= Humans with a problem)
3. Unique value proposition
4. Solution
5. Distribution strategy
6. Systems strategy
7. Outcomes
8. Cost structure
9. People strategy

This isn’t a tech stack.

It’s a business model.

And when you treat your data team like a startup inside the company, you win. Not the vendor.

Build value, not vanity - Start with users, not tools.

♻️ Repost if your stack ever got shinier but your impact didn’t.

👉 And join 3,000+ data leaders who read my free weekly newsletter about building impactful data teams in the AI-age: https://lnkd.in/gQRrkUJ6

Putting together a bunch of tools is NOT a data strategy!

A data strategy is this: 👇 (refined over 18 years)

1. A problem to solve

Start by uncovering and deeply understanding stakeholder problems (not with tools and data stacks!)

2. A human who has the problem

Learn about the jobs-to-be-done your users are facing. Sit on their lap, if necessary.

3. A unique value proposition (UVP)

Clearly communicate why your users should drop Excel to use your services.

4. A solution

Craft solutions that solve your user’s problem(s) and take away their anxiety to try them (be accessible)

5. A distribution strategy

The best solution is worthless if your stakeholders don’t know about it. Let the world know why your data team rocks!

6. A systems strategy

The best data teams spend more time building systems than being a slave in a system. Don’t be a dashboard factory! Build a problem solving factory!

7. Outcomes

Most data teams only produce output - tickets solved, dashboards built yada yada. You need to produce dream outcomes for your stakeholders!

8. Cost Structure

A necessary puzzle piece, but a lot of data teams worry about it too much. Worry more about creating value than reducing cost!

9. People Strategy

Have a hiring and people management strategy that reflects your principles and values.

That’s all.

Easy peasy, lemon squeezy, right? 🍋

♻️ Repost if you’ve felt the pain of building dashboards while your stakeholders export to Excel.

👉 And join 3,000+ data leaders who read my free newsletter for actionable tips on building impactful data teams in the AI-era: https://lnkd.in/grgzCkUf

Building impactful data teams for the AI-age | Data Strategist & Engineer | Advisor to C-Level in VC/PE-backed companies | Solopreneur & Travel Addict (100+ countries & territories) 🌏

The biggest risk in data isn’t technical.

Most teams are optimizing the wrong thing:

→ The dashboards are pretty.
→ The pipelines are scalable.
→ The models are accurate.

But no one is using them.

Why? Because most data teams ignore the one question that matters:

Does anyone actually need this?

In tomorrow’s newsletter, I’ll break down:

- The two kinds of risk every data project faces
- A 3-step filter I use to decide if a pipeline is worth building
- Why governance, scalability & self-service can wait
- And how to shift your team from busy builders to impact drivers

If you’ve ever built something that never got used - this one’s for you.

Tomorrow, I’m sharing with 3,000+ data leaders how to build data products people actually want.

👉 Sign up for my FREE newsletter if you don’t want to miss it:
https://lnkd.in/gS8EqkDv

Everyone wants to use AI to reduce headcount.

But here’s the inconvenient truth no one wants to hear:

👉 The biggest driver of bloated data teams isn’t lack of AI tools - it’s lack of foundations.

→ If your single source of truth is chaos…
→ If definitions and metrics change depending on who you ask…
→ If data governance resembles a police checkpoint (or doesn’t exist…)

Then AI won’t make you lean.

You’ll just end up automating the mess and hiring more people to clean it up.
Let’s get specific.

Here's a realistic, right-sized setup for a late-stage scale-up, assuming solid foundations:

- 173 Users (consume data via dashboards & reports)
- 17 Super Users (can self-serve simple insights) → 10:1 ratio
- 6 Analysts / Data Scientists (handle complex questions) → 3:1
- 2 Analytics Engineers (curate data for analysis) → 3:1
- 1 Data Engineer (builds the technical platform) → 2:1
- 1–2 Product Owners / Data PMs (the glue across domains)

That’s 11 people in the data org, or 5.5% of employees.

Let’s recap:

🚫 AI won’t save you from foundational debt
✅ AI can amplify your impact - if your data isn’t broken
Otherwise?

You’ll be automating confusion and scaling chaos.

♻️ Repost if someone just told you AI will replace analysts and fix your data problems magically.

👉 And join 3,000+ data leaders who read my free newsletter for weekly tips on building impactful data teams in the AI-era: https://lnkd.in/gVEHHj_T

Most “data strategies” I've seen were just glorified shopping lists.

- Snowflake? Check.
- dbt? Obviously.
- Power BI and Looker? Why not both.
- Airflow, Fivetran, Monte Carlo… 🔥🔥🔥

Lots of tools.

Zero clarity.

Here’s the reality:

Your strategy isn’t defined by what you buy. It’s defined by what you prioritise.

And prioritisation doesn’t start in the data warehouse.

It starts in a conversation.

→ With the sales lead who’s buried in manual lead scoring.
→ With the ops manager guessing stock levels from gut feel.
→ With the marketing team who just wants to know which campaign is working.

Until you understand those problems intimately -
all the tooling in the world won’t make a difference.

You’ll just build shiny infrastructure to serve… nobody.

A working strategy looks more like:

- Let’s spend 80% of our time helping 1 team win big
- Let’s automate the 2 most annoying data asks that hit our inbox every week
- Let’s not migrate that legacy dashboard, because nobody uses it anyways

Data strategy isn’t shiny. But it is the difference between impact and noise.

♻️ Repost if you've ever “strategically” bought a tool you never fully implemented.

👉 And join 3,000+ data leaders who read my free newsletter for actionable tips on building impactful data teams in the AI-era: https://lnkd.in/gjhfn9Ed

For years, I thought this was the playbook:

Get data → Build tools → Deliver value

Spoiler: it never worked that way.

- I built beautiful dashboards that nobody used.
- I answered questions no one had asked.
- I fixed bugs in things that didn’t matter.

Eventually, it clicked:

→ Data doesn't create value. Action does.
→ Action doesn’t happen without buy-in.
→ Buy-in doesn’t happen without a story.
→ A good story only works if it speaks to a user problem.
→ And the only user problems that matter? Are the ones tied to business goals.

So now, I work like this:

1. Business Goal
2. User Problem
3. Data
4. Story
5. Buy-in
6. Action
7. Value

This isn’t semantics. It’s a mindset shift.

It’s how you move from “dashboard team” to business impact partner.
From “data request taker” to decision enabler.
From “data first” to outcome first.

Want to stop being a dashboard factory and start driving business outcomes?

👉 Join 3,000+ data leaders who read my free weekly newsletter: https://lnkd.in/gJJVgXcS

♻️ Repost if you’ve ever launched a dashboard and realized... everyone just exports to Excel

“We need one source of truth.”

Translation:

A giant dashboard with 37 KPIs, 12 filters, and 0 actual insight.

Too many data teams are building Metric Museums.

And most metrics in companies today are like fridge magnets:
They look pretty… but they’re not holding anything up.

You realize:

→ Your company tracks 2952 metrics - all important
→ 6 versions of “Revenue” exist
→ And nobody knows which metrics actually drive profits

Want KPIs that lead to action instead of analysis paralysis?

Then classify your metrics before building the next dashboard or data pipeline.

Here's the 5-Layer Framework I use:

1. Influenceability: Inputs (levers) vs. Outcomes (results)
2. Business Stage (AARRR): Know where you are before picking what to measure.
3. Time View: Is your KPI measured at the point of action or the point of impact?
4. Prioritization: Don’t confuse your North Star KPI (value delivered) with revenue (value captured).
5. Metrics vs. Measures: Measures are ingredients, Metrics are recipes

This isn’t just theory.

It’s the difference between data teams that advise, and those that get ignored.

Your company isn’t drowning in data.

It’s starving for clarity.

♻️ Repost if you've ever been asked to "just add that metric to the dashboard" with no idea why

👉 And join 3,000+ data leaders who read my free newsletter for weekly tips on building impactful data teams in the AI-era: https://lnkd.in/gjR_ihYP

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The Battle

Alexander Rausch

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Followers

Posts

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Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Alexander Rausch's LinkedIn Performance

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