Alexander Rausch

Ich baue und skaliere Unternehmen an der Schnittstelle von KI, Automation, Vertrieb und Marketing – mit Fokus auf klare Zahlen und Frameworks, saubere Prozesse und nachhaltiges Wachstum.

In den letzten Jahren habe ich als Unternehmer und Geschäftsführer Organisationen durch unterschiedliche Wachstumsphasen geführt: Von der Gründung über frühe Skalierungsphasen bis zu 9-stelligen Umsätzen.
Dabei lag mein Schwerpunkt immer auf zahlenbasierter Vertriebsorganisation, Performance Marketing und dem Aufbau skalierbarer operativer Strukturen.

Zuvor war ich u. a. COO bei Amorelie und Joblift, Geschäftsführer bei CHRONEXT.
Dort habe ich u. a. Performance-Marketing-Setups skaliert, datengetriebene Steuerungsmodelle aufgebaut, Vertriebs- und Operations-Teams strukturiert sowie Fundraising verantwortet.

Heute bin ich Gründer & Geschäftsführer von CERTA GmbH, einem unabhängigen Unternehmen für Immobilienbewertung in Deutschland. Wir wachsen profitabel durch klare Zahlenlogik, Automatisierung und saubere Verantwortlichkeiten und nicht durch Bauchgefühl.
Unser Anspruch: präzise Entscheidungen durch saubere Daten, unterstützt durch Technologie, Automation und klare Verantwortlichkeiten – für Banken, Investoren und Eigentümer.

Was mich antreibt:
Wachstum scheitert selten an fehlender Nachfrage, sondern an unstrukturiertem Vertrieb, ineffizientem Marketing und fehlender Transparenz in den Zahlen. Genau dort setze ich an.

Meine Schwerpunkte:
- Zahlenbasierte Vertriebsorganisation & Forecasting
- Performance Marketing & Marketingoptimierung
- KI & Automation in Sales-, Marketing- und Ops-Prozessen
- Skalierung von Geschäftsmodellen & Organisationen
- Immobilien, Bewertung & Investment-Logik

Dieser Account ist ideal für Gründer, Geschäftsführer und Führungskräfte, die Vertrieb, Marketing und Operations nicht isoliert, sondern als ein integriertes System denken wollen.

👉 Vernetze dich gern mit mir oder schreib mir, wenn du über skalierbaren Vertrieb, Marketingeffizienz oder den Einsatz von KI & Automation sprechen möchtest.

Start-Up and Scale-Up Mentor

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

Letzte Woche ist mir wieder bewusst geworden, warum ich genau das tue, was ich tue. 

Ein Raum voller Unternehmerinnen und Unternehmer, die sich ehrlich fragen: „Wie gehe ich dieses KI‑Thema richtig an? Ohne Chaos, ohne Risiko, aber mit echtem Nutzen?“
Genau solche Abende geben mir Energie. Gemeinsam mit Rene Käuper  durfte ich bei der J. Lehde GmbH in meiner Heimatstadt darüber sprechen, wie wir KI heute wirklich pragmatisch einsetzen können. Nicht als Hype, nicht als Spielerei, sondern als Werkzeug, das Prozesse vereinfacht, Menschen entlastet und Unternehmen stärkt.

Was mich besonders gefreut hat:
- Wie offen die Teilnehmenden über ihre Herausforderungen gesprochen haben.
- Wie viele Aha‑Momente im Raum spürbar waren.
- Wie groß der Wunsch ist, endlich Klarheit und Orientierung zu bekommen.

Denn viele stehen gerade an derselben Stelle:
- Wo fange ich eigentlich an?
- Wie mache ich das datenschutzkonform?
- Wie finde ich Lösungen, die nicht wieder Insellösungen sind?

Und genau daran möchte ich weiterarbeiten und mein Wissen teilen. Gemeinsam mit Unternehmen, die bereit sind, die nächsten Schritte zu gehen.
Ein herzliches Dankeschön an Johannes Lehde für die Einladung und die tolle Organisation. Es war nicht nur ein Vortrag, sondern ein echter Austausch auf Augenhöhe. Und ich freue mich schon jetzt auf alles, was aus diesen Gesprächen entsteht. 🚀

#KI #Mittelstand #Digitalisierung #Automatisierung #Innovation #Soest #Austausch #Unternehmertum

Wachstum ist kein Zufall, sondern ein System | KI & Automation | Immobilien | WHU

Gestern Abend durfte ich beim STARTPLATZ in Köln im Rahmen der buildersklub x Make AI Roadshow einen Vortrag zum Thema KI Agenten für Kundenzufriedenheit halten.

Meine Kernthese:
👉 Kundenzufriedenheit ist kein Ergebnis, sondern das Resultat eines Systems. 

Wer Happiness erst über NPS oder Reviews misst, der reagiert zu spät.
Wer Kommunikation, Tonalität und Muster während der Kundenreise analysiert, kann Zufriedenheit aktiv steuern bevor Frust überhaupt entsteht.

Vielen Dank an das gesamte Team und alle Teilnehmenden für den offenen Austausch. Es hat großen Spaß gemacht, dieses Thema mit euch zu diskutieren. Pierre-Yves

AI & Tech for business people 🧑‍💻 Co-Founder @ 9x

Customer happiness is not an outcome. It’s a system.

Last night in Cologne, for the buildersklub x Make Germany AI Roadshow, we explored how Alexander Rausch (Founder of Certa Immobiliengutachten) is rewriting the playbook for scaling tech-enabled businesses.

Alex isn't just an AI & automation enthusiast: he’s a seasoned entrepreneur. 

He shared his journey transitionong from 90% ProCode at AMORELIE (as COO), to 50% NoCode at CHRONEXT (Founder), to now running Certa Immobiliengutachten with 95% NoCode and 600+ active scenarios.

Here are my main takeaways from his masterclass on building a "Customer Happiness System"

1️⃣ Happiness is a leading indicator 
Most companies treat satisfaction as a lagging indicator (sending an NPS survey after the damage is done). Alex treats it as a leading indicator. By analyzing communication during the process, you can catch frustration before it becomes a bad review.

2️⃣ It’s not what they say, it’s HOW they say it
The AI agent doesn't read the text: it analyzes tone, repetition, and urgency. It aggregates emails, tickets, and calls to classify customers as Satisfied, Neutral, or Dissatisfied.

3️⃣ Humans don't scale, systems do 
The goal isn't to replace humans, but to use machines for what they are good at (pattern detection, continuous monitoring) so humans can do what they are good at (empathy, problem-solving).

4️⃣ The "Therapy Call" Strategy 
When the system flags a dissatisfied customer, the protocol is simple: Speed beats perfection. Alex picks up the phone immediately. As he puts it, "It's like therapy for them." They want to be heard.

5️⃣ The Result? A 90% reduction in negative reviews and almost 2 years without a single bad review.

And if I have to pick one quote from yesterday it would be: "The total cost of our AI & Automation Enterprise licenses is still less than of one single developer."

Thanks again Alex for sharing your journey.

Big shoot out to Roger from the 9x team who then walked our guests through building their first AI Agent on Make 🤖

And a big thank you to all the nice people who joined us yesterday in Cologne. 

We'll definitely come back!

Next stops: Stuttgart and Munich in 2 weeks.

#AI #Automation #MakeAIWorldTour #NoCode

Wir suchen für CERTA Immobiliengutachten eine Telefonassistenz! Du liebst es, mit Menschen zu sprechen, aber bitte nicht in einem Callcenter?

Als erste Stimme für unsere Interessent:innen sorgst du dafür, dass jede Anfrage professionell, freundlich und zuverlässig ankommt. Kein Skript, keine Kaltakquise! Nur echter, wertschätzender Kundenkontakt.

Was du bei uns machst:
- Anrufe annehmen, einordnen und Termine organisieren
- Interessent:innen aktiv nachfassen und offene Fragen klären
- Termine zwischen Kund:innen und Berater:innen koordinieren

Ist das etwas für Dich? Dann meld' Dich gerne direkt bei mir oder bewirb Dich über den Link in den Kommentaren!

𝐃𝐢𝐞 𝐈𝐦𝐦𝐨𝐛𝐢𝐥𝐢𝐞𝐧𝐩𝐫𝐞𝐢𝐬𝐞 𝐬𝐭𝐞𝐢𝐠𝐞𝐧 𝐮𝐧𝐝 𝐠𝐥𝐞𝐢𝐜𝐡𝐳𝐞𝐢𝐭𝐢𝐠 𝐝𝐞𝐛𝐚𝐭𝐭𝐢𝐞𝐫𝐭 𝐝𝐢𝐞 𝐒𝐏𝐃 𝐞𝐢𝐧𝐞 𝐬𝐜𝐡ä𝐫𝐟𝐞𝐫𝐞 𝐄𝐫𝐛𝐬𝐜𝐡𝐚𝐟𝐭𝐬𝐬𝐭𝐞𝐮𝐞𝐫.

Die aktuellen Marktberichte zeigen eine klare Trendwende: In vielen Städten steigen Immobilienpreise wieder spürbar.
Die stärksten Anstiege im Vgl. zum letzten Quartal laut Dr. Klein Privatkunden AG:
Köln: +1,31 % 
Frankfurt: +1,31 %
Hannover: +0,91 %
Deutschland gesamt: Wohnungen +0,33 %, Häuser +0,40 %

Auch im Jahresvergleich wird der Trend sichtbar:
Köln: +5 % bei Eigentumswohnungen laut immowelt

Gleichzeitig steigen die Mieten bei Neuverträgen deutlich:
+7,6 % in Köln, +4,1 % bundesweit (AdHoc News)

Diese Entwicklungen zeigen: Werte steigen und das schneller als viele erwarten.

Dann kommt die politische Komponente:
Die SPD-Bundestagsfraktion diskutiert aktuell eine Reform der Erbschaftssteuer. Steigende Immobilienpreise führen zu höheren Vermögenswerten. Das könnte bedeuten:
• strengere Bewertungsverfahren
• mögliche Mehrbelastung für Erben
• mehr Fälle, in denen Freibeträge überschritten werden

Für Eigentümer bedeutet das:
Steigende Werte sind erfreulich und können gleichzeitig steuerlich schnell teuer werden.
Deshalb wird eines immer wichtiger:
1. Den tatsächlichen Verkehrswert der eigenen Immobilie kennen.
2. Unabhängige Gutachten nutzen, um Überbewertungen durch das Finanzamt zu vermeiden.

Frühzeitig planen, bevor eine Reform Fakten schafft. Wie seht ihr die Entwicklung? 
#Immobilien #Erbschaft #Immobilienmarkt

Sebastian Hewing 🚀

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

Over the last 18 years I have built and led data teams across all continents - except Antarctica. ☃️

But my first data leadership job almost broke me:

It was 2010.

At 29 years old, I led the data team of the world’s largest venture builder (Rocket Internet).

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)
→ Jumia (the first African company on the NYSE).

I saw those companies and data teams grow from tiny startups into massive, global market leaders.

And even though we built data teams for 7 companies in 15 countries, I struggled...

... hard.

→ We were drowning in ad-hoc requests instead of shaping strategy.
→ We were shipping dashboards instead of outcomes.
→ And ultimately stakeholders didn’t trust what we built.
→ And my influence, impact and personal growth hit a ceiling. 

Over the following years, I became a trusted advisor to Founders and CEOs by building winning data teams for 50+ companies.

The one thing I realized over all those years after leaving Rocket Internet: 

I was lacking an operating system for building winning data teams.

So, I created it.

The Data Team Adjusted Lean Canvas Framework transforms how data teams create value based on best practices from:

- data engineering
- product management
- marketing 
- behavioral science
- and entrepreneurship.

In my Data Strategy Masterclass, I have helped hundreds of growth-oriented data experts from 40+ countries become more influential by applying my framework and by building impactful data teams in the age of AI.

Favorite testimonial: “I got more value from your $350 course than a $3,000 University of Berkeley executive education course.”

→ Find out more at http://www.dataactionmentor.com/masterclass-business-impact  ← 

P.S.: My biggest passion besides Data, AI & Entrepreneurship is traveling. After 2 years of "digital nomading", I now have a home-base in Taipei, but I typically spend 5-6 months per year traveling. 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

One boat has all the tools.

One lonely boat knows where it's going.

Guess which one delivers business value?

Every week I meet teams drowning in the “modern data stack”:

→ dbt models piling up
→ 15 Looker dashboards per stakeholder
→ Half-built AI POCs

And when things break, no one asks “what is the business trying to achieve?”

They ask: “should we migrate to another tool?”

Meanwhile, the high-performing teams?

→ They start with a problem.
→ They talk to real users.
→ They focus on impact over elegance.

Ship.
Learn.
Adjust.

No hype cycle. No data cult. Just progress.

Data strategy isn’t a shopping list.

It’s a decision-making framework.

And until that’s in place, no tool will save you.

♻️ Repost if you've ever inherited a stack with 12 tools and zero outcomes

👉 And join 3,000+ data experts who read my free newsletter for weekly tips on data strategy: https://lnkd.in/grEH8a3c

Sebastian Hewing

Pragmatic Data Strategist | Outcome-driven data strategy that earns your seat in leadership decisions

I used to design extremely complex data infrastructures.

Now I do the exact opposite.

When building data infrastructure, simplicity is king! 👑

This is true for high-growth startups AND large companies!

Here’s the exact approach for every new data infrastructure I build:

First, I talk to all stakeholders intensively.
↳ understand their use cases
↳ understand their challenges, struggles and desires
↳ understand how they are tackling these challenges today

This is typically about 25% of the WHOLE infrastructure project!

Second, I create a KPI/Dimension Map.

This is a cross-tab that captures all stakeholder challenges and use cases in an easy-to-read format.

Third, I evaluate a status quo for each KPI/Dimension combination (use case)
↳ where does the data come from?
↳ what is the data quality?
↳ are there manual processes involved in capturing the data?

Lastly, together with stakeholders, we define a data infrastructure MVP (minimum viable product).

The goal is to FULLY cover the first use cases in less than 4 weeks.

A lot of data people get the definition of a “data MVP” wrong.

A solution solving 10 use cases 50% is not an MVP.
A solution solving 1 use case 80% is.

♻️ Repost if you’ve ever built a pipeline only to find no one uses it

👉 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/gvTUPa5x

I will explain my approach in more detail in my coming newsletter this Sunday.

Pragmatic Data Strategist → From Dashboard Factory to Strategic Partner

“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/gpwGnGA2

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.

At some point, I realized:

→ Data doesn't create value. Action does.
→ And 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:
👉 Business Goal
👉 User Problem
👉 Data
👉 Story
👉 Buy-in
👉 Action
👉 Value

It’s not about moving from data to value.

It’s about moving from understanding to action.

With data as your ally, not your starting point.

This is how you shift from builder of dashboards to creator of business impact.

Want to transform your team from dashboard factory to strategic business partner?

👉 Join 3,000+ data leaders who read my free newsletter for weekly tips on building outcome-driven data strategies: https://lnkd.in/gzDsAYYR

♻️ Repost if you've ever shipped a dashboard that even you forgot existed.

You're drowning in ad-hoc requests instead of shaping strategy.

- “Can you pull this real quick?”
- “Can we get a dashboard by Friday?”
- “Can I export this to Excel?”

You’re busy and about to burn out.

I wrote 6 data strategy pieces to help data leaders break that cycle.

From busy-work to business impact:

1/ The End of the Data Analyst
→ What happens to the data analyst role in the age of AI?
🔗 https://lnkd.in/giCNfYXy

2/ Who should lead the data leader?
→ The reporting line that shapes your whole data strategy.
🔗 https://lnkd.in/gMHwnS8g

3/ Re-thinking the Single Source of Truth
→ When one truth isn’t enough for your company.
🔗 https://lnkd.in/gPTZBXHT

4/ The Hidden Structure of High-Performing Data Organizations
→ The quiet reason business and data teams clash.
🔗 https://lnkd.in/gkZX_5QU

5/ When the Intern beats your AI model
→ How overengineered data projects lose to scrappy, useful ones.
🔗 https://lnkd.in/ga-mYAex

6/ Pragmatic Data Governance that doesn’t kill the vibe
→ Stop building what people ask for. Start solving what they need.
🔗 https://lnkd.in/gxdPYcfJ

Inside these posts, you'll learn:

💡 Why the analyst role is evolving, not ending 
💡 Simple solutions that drive real business results 
💡 How to bridge the gap between business and data teams

Want to stop being a dashboard factory and start creating real value?

👉 Join 3,000+ data experts who read my free newsletter for weekly tips on building impactful data strategies in the AI-era: https://lnkd.in/gk9AXBAH

♻️ Repost if you’ve answered “just one quick thing” more than 3 times today

18 years in data. My 10 most powerful lessons.

(aka: how to avoid 5 years of pain, firefighting, and dashboard chaos)

No fluff. No hype.

Just hard-earned truths that changed how I build data teams:

1. Build data teams like a start-up
→ Don’t fall in love with your solution. Fall in love with the problem.

2. Embrace an 80/20 mindset
→ Ask: “What’s the smallest thing we can build to deliver 80% of the value?”

3. Don’t stop at dashboarding
→ Own experimentation. Feed data into ops tools. That’s where decisions happen.

4. Self-service is real
→ But it’s not “let everyone build dashboards.” It’s “help people answer the WHY on their own.”

5. Market Risk > Product Risk
→ You can build anything. The real risk? No one needs it.

6. Outcomes > Output
→ Dashboards don’t matter if they don’t change decisions. Measure business impact, not tickets closed.

7. Ad-hoc ≠ agility
→ Reactive teams burn out and lose trust.

8. Control before agility. Always.
→ Without trustworthy and understandable data, speed is just a faster way to crash.

9. Data teams are not service desks
→ Saying “yes” to every request keeps you busy. But it won’t move the business forward.

10. Business logic does NOT belong in dashboards
→ Keep logic in your data models. Or enjoy version wars, Excel exports, and endless confusion.

If I had followed these earlier, I would’ve saved my team months of pain.

Which one hits hardest for you?

♻️ Repost if you've ever shipped a dashboard that got zero views and one confused Slack message

👉 And join 3,000+ data leaders who read my free newsletter for actionable tips on data strategy: https://lnkd.in/gsjMX856

Your org chart is not a data strategy.

But it will make or break your data team’s impact.

Here’s what happens in most companies:

- The CTO says, “We need better data infra”
- The CFO says, “We need clean numbers”
- The CMO says, “We need attribution analytics”
- The CEO says, “We need a dashboard for the board”

And just like that... the data team reports to everyone and no one at the same time.

That’s how you end up with a “data strategy” that looks like:

- 791 dashboards
- 15 AI POCs
- 3 different metrics for ‘active user’
- 1 data team stuck doing requests with no real mandate

Let’s reframe the org chart conversation:

Instead of asking “Who should the data leader report to?”, ask:

→ Where is the pain greatest?
Data teams thrive when they solve high-impact problems. Attach them to the leader who needs them most.

→ Who understands what good data work looks like?
If the CxO treats the data team like a dashboard vending machine: wrong choice.

→ Who has room to lead?
Don't put your data org under someone who’s drowning in direct reports.

→ What business are you actually in?
Data should be aligned to the business engine - not to the loudest stakeholder.

Bad reporting lines don’t just hurt morale.

They kill momentum. Slowly. Silently.

And six months later, someone’s asking,
“Why is our data team not driving impact?”

Now you know why.

♻️ Repost if you've ever had to explain for the 5th time that data doesn’t belong under the CTO "because it’s tech stuff"

👉 And join 3,000+ data leaders who read my free newsletter for actionable tips on pragmatic, outcome-driven data strategies: https://lnkd.in/gxcJYSYQ

When the boss asks:

“What are your data team’s goals for next quarter?”

Many data leaders freeze.

Then default to:

→ ship 15 dashboards
→ reduce pipeline downtime
→ close more tickets

Sounds reasonable.

But it’s also how data teams quietly turn into dashboard factories.

The real problem:
Most data teams define success in outputs, not outcomes.

If you want to be seen as a strategic partner, your goals must ladder up to the business.

In practice, almost every meaningful data goal fits into one of 5 categories:

1️⃣ Increase revenue, growth, or market share
2️⃣ Decrease costs
3️⃣ Enhance reputation or brand
4️⃣ Strengthen relationships with critical stakeholders
5️⃣ Increase organizational knowledge & decision-making capability

Dashboards, pipelines, SLAs?

Those aren’t goals.
They’re internal activities.

If your quarterly goals don’t clearly map to one of the five categories above…
… then don’t be surprised when leadership struggles to see your impact.

Outputs keep you busy.

Outcomes keep you funded.

♻️ Repost if you’ve ever defined an OKR as “uh… we’ll close more tickets.”

👉 And join 3,000+ data leaders who read my free newsletter for actionable tips on data strategy: https://lnkd.in/g36_8cRq

“I was hired to migrate old reporting into a modern data stack.”

What a huge red flag! 🚩

Here’s the painful trap I didn’t see coming 11 years ago:

I used to think modern tooling = modern impact.

But all it does is ship the same old stuff… just faster and prettier.

It took me way too long to realize:

→ Stack migrations don’t build outcomes.
→ They build artifacts.
→ New stack, same old problems.

Here is how I shifted from shipping data stacks to shipping outcomes:

- We stopped accepting “build me this dashboard”
- We started unpacking decisions and friction
- We focused on solving real problems, not fulfilling tickets

That’s when people started trusting the numbers.
That’s when we got invited upstream.
That’s when we stopped being a dashboard factory.

So when someone says
“We’re modernizing our data stack,”

I always ask:
“Cool. Are you modernizing how you deliver value too?”

Because great tools don’t change anything.

✅ Want to build a data team that drives real outcomes?

👉 Join outcome-driven data leaders from 40+ countries in my data strategy masterclass: https://lnkd.in/gN7ZHYeH

taplio

The Battle

Alexander Rausch

Sebastian Hewing 🚀

Followers

Posts

Engagements

Likes

Performance ScoreAlexander Rausch's LinkedIn Performance

Performance ScoreSebastian Hewing 🚀's LinkedIn Performance

Ready to grow your LinkedIn presence?

taplio

The Battle

Alexander Rausch

Sebastian Hewing 🚀

Followers

Posts

Engagements

Likes

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

Performance ScoreSebastian Hewing 🚀's LinkedIn Performance

Ready to grow your LinkedIn presence?

Performance ScoreAlexander Rausch's LinkedIn Performance