I invited Yana G.Y. to a live conversation because she does something rare. She has a director title and a Substack generating between $5K and $10K a month on the side of her full-time banking job. And she runs it entirely on data.
Data-driven the way subscription businesses actually operate it. Numbers connected to decisions, decisions connected to outcomes.
Below are the ideas she shared. The full conversation is in the video above.
Stakeholders Make Emotional Decisions First (and They Have Good Reason To)
The standard data professional complaint is that stakeholders ignore data and run on gut. Yana flips that framing.
Her view:
Most people are wired to make emotional decisions first and look for data that confirms them second.
From her background in neurolinguistic programming, she puts the share of people who genuinely process the world through numbers at around 15%. Everyone else needs a different approach.
Showing up with a dashboard and expecting it to land is wishful thinking. Data needs a story around it. A number without context gets interpreted differently by every person in the room. One sees growth, another sees underperformance, a third questions whether the metric tracks the right thing at all.
Yana learned this early. Every conversation with engineering teams felt like friction. She was asking questions they thought she should already know. They were building things that missed what she actually needed. The gap cost both sides time.
What closed it was her decision to learn enough about how systems work to ask better questions. To stop being helpless in technical conversations.
The One Move That Ends Arguments in Any Meeting
Yana has one technique she uses across every organization. It works in telecom. It works in banking. She has a perfect record with it.
Before any contentious conversation, find the data that links your ask to what the organization actually cares about. Customers, revenue, profit. Those three. Then add competitive benchmarks if you can find them.
In her current bank, she came in and asked how many successful app registrations they were getting. She pulled the internal rate, found competitor data, and discovered some competitors were achieving double or triple the registration conversion rate. She put that in front of the team.
The conversation changed.
People stop defending their position when the data shows the position is costing them. Go into the meeting with the numbers already pulled. Link them to something the people in the room care about. Then let the data do the work.
This applies directly to data teams. When a project needs prioritization, funding, or unblocking, skip the technical justification. Show the business number it connects to, then show where a competitor is already ahead.
What Yana Actually Tracks on Substack
Substack’s native analytics fall short. Yana built her own spreadsheet and tracks the following every month:
Total subscribers
New subscribers
Total paid subscribers
New paid subscribers
Churned paid subscribers
New revenue
Average revenue per subscriber per month
Average revenue per subscriber per year
Free-to-paid conversion rate
Net Promoter Score
The benchmark Yana uses for revenue per subscriber is the email marketing industry average, ranging roughly from $1 to $12 per subscriber per year depending on niche. Above average means the business is healthy. Below average means something needs auditing.
The NPS tracking is the piece most Substackers skip. She uses Substack’s survey feature to ask paid subscribers one question: on a scale from 1 to 10, how likely are you to recommend this publication to someone you know. That one question, run through the standard NPS formula, tells her whether her paid tier delivers real value. Her target is above 70.
Yana’s reasoning:
NPS is the only reliable signal for whether paid subscribers are satisfied or are simply on their way out.
How She Runs a $10K/Month Business in the Hours Left Over From a Full-Time Job
Yana works five days a week, eight hours a day, in an office. She can answer Substack comments during lunch or late after work. That’s the window she operates in.
AI handles everything operational. Formatting, research, scheduling, the mechanical parts. For writing, she trained a system on her own content. She extracted all her published articles into a database, connected it to an MCP server, and built what she calls a second brain. She can query it for content gaps, understand what paid subscribers want more of, and run analysis on her own business data.
She writes in her voice, informed by her own data, with AI executing the work that requires no judgment.
Her warning about AI:
It pulls you into rabbit holes when you let it.
Every answer suggests the next step, and the next step, and an hour later you have built something with no clear business purpose. Use it to execute a decision. Know exactly what you want before you open it.
Yana also made the point that the 9-to-5 built the Substack. The telecom career gave her subscription business knowledge, customer journey expertise, conversion rate benchmarks, and an understanding of which metrics actually predict business health.
All of it went directly into how she runs the newsletter. The side business grew because of the day job.
Final Thoughts
Yana has 15 years of subscription business experience, a disciplined tracking system, and a clear rule: link your ask to numbers that matter, then find the benchmark that shows where you stand.
That’s the part worth sitting with. Data professionals spend time arguing that stakeholders ignore data. Yana learned enough about systems to have real conversations with engineers. She built her own analytics because the platform’s fell short. She tracks NPS because her industry background taught her it mattered.
The gap between business and data closes when people on both sides decide to move. Yana moved. The engineers still telling business people to figure it out on their own are the ones falling behind.
Interested into growing your Substack? Subscribe to Yana’s publication.
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