I’m excited to share a project that generated an additional $150K CAD in revenue for my team! 💰

The Challenge: Our sales team needed high-quality leads in construction and professional services, but manual prospecting was eating up 20+ hours per week.

The Solution: Built a Python/SQL automation system that: ✅ Generated 53,000 targeted contacts across key industries ✅ Enriched data with company size, revenue estimates, and decision-maker titles ✅ Automated list distribution to account managers ✅ Integrated directly with our CRM pipeline

The Results: 📊 $150K CAD in additional ARR after strategic redistribution ⏱️ Saved 200+ hours of manual prospecting work 🎯 Higher quality leads = better conversion rates

The Lesson: Tech skills aren’t just for developers. Sales professionals who can code have a serious competitive advantage.

What processes are you automating in your role?

#SalesAutomation #Python #AccountManagement #SalesOps #GrowthHacking

Hot take: Cold calling isn’t dead. You’re just doing it wrong. 📞

My Stats at TELUS (when I worked there): • 60 calls per day (consistently) • 2.4% conversion rate (industry average: 1-2%) • 350+ new SMB clients acquired in 13 months • $302K ARR generated • 95% client retention rate (industry average: 80%)

What’s working in 2025:

1. Research Before the Call I spend 2 minutes researching each prospect. Their website, recent news, pain points. The call is 30 seconds, but the prep wins the deal.

2. Value First, Pitch Second I lead with a specific problem I’ve solved for similar companies. No generic scripts.

3. Embrace the Rejection 97.6% of my calls don’t convert. That’s okay. The 2.4% pays the bills.

4. Tech Stack Advantage Python scripts help me prioritize highest-value prospects. I’m not just dialing randomly.

The Uncomfortable Truth: Most sales reps quit after 10 rejections. I get 10 rejections before my second coffee.

Cold calling works. But only if you show up every single day.

Who else is still crushing it with cold calls? Drop your best tip below. 👇

#ColdCalling #SalesLife #B2BSales #AccountManagement #SalesStrategy

Unpopular opinion: Product Owners should know how to code.

Not because they need to write production code. But because it changes how you think about product development.

My Experience at Datazentrik: • Managed 104 weekly sprints • Delivered 202 features • Designed and implemented the Pétrole Papillons website end-to-end (frontend, API integration, UX) • Automated SEO-optimized content creation using generative AI (LLMs, OpenAI)

What Coding Knowledge Gave Me:

1. Better User Stories I wasn’t writing vague requirements. I understood technical constraints and could write actionable acceptance criteria.

2. Realistic Estimations When devs said “this will take 3 sprints,” I could ask better questions and push back when needed.

3. Faster Prototyping Instead of waiting for devs to mock something up, I built quick prototypes myself. This saved us at least 2 weeks per major feature.

4. Credibility with Engineers They respected that I could jump into the code when needed. Less “product threw this over the wall” energy.

5. AI Integration Understanding When we automated content creation with LLMs, I wasn’t just reading docs. I was implementing and iterating.

The Stack I Used: HTML, CSS, JavaScript, Python, SQL, GCP, OpenAI API, LangChain, N8N

Bottom Line: You don’t need to be a senior engineer. But understanding the tech stack makes you a 10x better Product Owner.

What technical skills have made you better at your non-technical role?

#ProductManagement #Scrum #TechSkills #AI #WebDevelopment #ProductOwner

2018: Graduated from Le Wagon (Full-Stack Web Developer) 2021: Became a Wealth Manager at Manulife 2022: Pivoted to Product Owner at a tech startup 2024: Former Account Manager at TELUS (crushed quota)

People ask: “Why didn’t you just become a developer?”

Here’s the truth: I found my edge at the intersection of sales, product, and code.

What Wealth Management Taught Me: • Cold calling high-net-worth clients ($200k-$400k portfolios) • Simplifying complex concepts for non-technical audiences • Building trust through consultative selling • Portfolio management & risk analysis • Acquired $1.3M in AUM in 12 months

What Coding Taught Me: • Automation mindset • Data-driven decision making • Problem-solving frameworks • How to build (not just sell) products

The Superpower: Most salespeople can’t code. Most developers can’t sell. Most wealth managers can’t do either.

I can do all three.

Current Results: ✅ $300K+ ARR annually over the past 5 years ✅ 95% client retention rate (20% above industry average) ✅ Automated lead generation saving 200+ hours ✅ Canadian Securities Course (CSC) + Full-Stack Dev certified

My Advice: Don’t just pick one lane. Find the intersection where your unique skills create the most value.

That’s where you become irreplaceable.

What unique skill combination makes you stand out?

#CareerPath #Sales #TechSales #WealthManagement #FullStackDev #AccountManagement

During my 13 months at TELUS: $302K ARR. 20% above quota.

Here’s exactly what I did differently:

1. Volume + Quality (Not Volume OR Quality)

Most reps choose one. I refused.

• 60 calls/day (volume) • 2 minutes of research per call (quality) • Targeted industries where I had domain knowledge • Used Python to prioritize highest-value prospects

2. Upsells Start at “Hello”

I don’t wait 6 months to upsell. I identify expansion opportunities during the first conversation.

→ 95% retention rate because clients get more value over time, not less.

3. Automate Everything That Isn’t Selling

I built scripts to: • Generate lead lists • Update CRM records • Track follow-up sequences • Analyze conversion metrics

Result: I spend 80% of my time selling. Most reps spend 50%.

4. I Treat Rejection Like Data

Every “no” teaches me something: • Wrong timing? • Wrong pitch? • Wrong prospect?

I track patterns and adjust. Most reps just move on.

5. Bilingual = 2x Market

Being fluent in English and French literally doubled my addressable market in Canada.

The Uncomfortable Part:

I work harder than most people on my team. I don’t say that to brag. I say it because that’s the reality.

60 calls a day. Weekly pipeline reviews. Continuous learning. Automation after hours.

Exceeding quota isn’t a hack. It’s a system.

What’s one thing you do that most people in your role don’t?

#SalesQuota #AccountManagement #B2BSales #SalesPerformance #WorkEthic

The Project: Automate SEO-optimized content creation using generative AI

The Tools: OpenAI, Claude, Gemini, DeepSeek, Ollama, N8N, LangChain

The Goal: Create high-quality content at scale without sacrificing quality

What Actually Worked:

1. LLMs Aren’t Magic (But They’re Close)

You can’t just prompt “write me a blog post” and expect gold. You need: • Context about the brand voice • SEO keywords and search intent • Content structure/outline • Examples of high-performing content

2. The Workflow Matters More Than the Model

I built an N8N workflow that:

1. Scraped trending topics in target industries
2. Generated content briefs with keyword research
3. Created drafts with Claude/GPT-4
4. Optimized for SEO with custom Python scripts
5. Added a human review layer (critical!)

3. Human-in-the-Loop = Quality Control

AI writes the first draft. Humans: • Fact-check • Add unique insights • Refine tone • Optimize CTAs

We went from 1 article/week to 15 articles/week with the same team size.

4. Multi-Model Approach

Different models for different tasks: • GPT-4: Long-form content • Claude: Technical explanations • Gemini: Research summaries • DeepSeek: Cost-effective bulk generation • Ollama: Local testing/iteration

The Results:

✅ 10x increase in content output ✅ 67% reduction in content creation cost ✅ SEO rankings improved across 200+ keywords ✅ Automated 80% of the repetitive work

The Catch:

This isn’t “set it and forget it.” AI-generated content still needs: • Strategy (what to write) • Expertise (accurate information) • Creativity (unique angles) • Optimization (SEO, CTAs, etc.)

Bottom Line:

AI doesn’t replace content teams. It gives them superpowers.

What’s your experience with AI content creation? 👇

#AI #ContentMarketing #SEO #GenerativeAI #MarketingAutomation #LLM #ProductManagement

People are always surprised when I tell them I use Python, SQL, and cloud services as an Account Manager.

“Isn’t that for developers?”

Nope. It’s for anyone who wants an unfair advantage.

My Sales Tech Stack:

🐍 Python • Lead generation scripts • Data enrichment automation • CRM data cleaning • Pipeline analytics • Email sequence optimization

🗄️ SQL • Querying customer databases • Building custom reports • Analyzing conversion patterns • Segmenting prospects • Performance dashboards

☁️ Cloud (GCP, AWS, Azure) • Deploying automation scripts • Running scheduled jobs • Storing enriched lead data • API integrations • Cost-effective scaling

🤖 AI Tools • OpenAI/Claude for email personalization • N8N for workflow automation • LangChain for data processing • Custom GPT for sales research

📊 Data Tools • Excel (obviously) • Pandas for data analysis • Google Sheets + Apps Script • Power BI for visualizations

💼 Traditional Sales Stack • CRM (Salesforce/HubSpot) • LinkedIn Sales Navigator • Calendly • Loom • Slack

Why This Matters:

While other reps are manually: • Building lead lists (I script it) • Updating CRM fields (I automate it) • Analyzing pipeline health (I dashboard it) • Researching prospects (I enrich it)

I’m spending that time actually selling.

The ROI:

💰 $150K in additional revenue from automated lead gen ⏱️ 200+ hours saved per quarter 📈 20% above quota (consistently) 🎯 2.4% conversion rate (above industry average)

Real Talk:

You don’t need to be a software engineer. But learning to code as a sales professional is like learning to read as a business owner.

It’s not optional if you want to stay competitive.

Where to Start:

1. Learn Python basics (free resources everywhere)
2. Automate one manual task per week
3. Document what works
4. Share with your team
5. Scale the wins

What tools are you using to get an edge in your role?

#SalesTech #Python #Automation #SalesOps #TechStack #AccountManagement #DataDriven