Who actually uses these products,
and what made them stay.

The Reluctant Salesforce User

An enterprise sales rep at a company with 200+ employees who did not choose Salesforce. It was there when they arrived. They've been trained on it twice. They use about 20% of its features and have found workarounds for everything else. They log activity because their manager checks. They update opportunities because forecasting requires it. They do not believe Salesforce makes them better at sales. They believe it makes their manager better at measuring sales.

“The shift was quiet.”

The Clay GTM Engineer

A GTM engineer, growth operations lead, or RevOps professional who uses Clay as their data enrichment and workflow engine. They build spreadsheet-like tables that pull from 50+ data providers — enriching companies with technographic data, finding decision-makers' emails, scoring leads based on signals, and triggering personalized outreach. They think in data transformations and API calls. They've replaced hours of manual prospect research with Clay workflows that run in minutes. They are the engineer of the sales pipeline's data layer.

“The shift was quiet.”

The Hex Collaborative Data Analyst

A data analyst or analytics engineer who uses Hex because it combines everything they used to do across 3–4 separate tools into one collaborative environment. They write SQL to pull data, Python to transform it, and build visualizations and dashboards — all in the same notebook. They share their work as interactive apps that stakeholders can explore without learning SQL. They've replaced Jupyter notebooks, Mode, and Google Sheets with Hex. They are the data person who makes data accessible to people who aren't data people.

“The marketing team asks: "Which campaigns drove the most pipeline last quarter?" The data analyst opens Hex, writes a SQL query to pull campaign data, joins it with pipeline data, and adds a Python cell to calculate attribution.”

The Segment Data Architect

A data engineer or analytics engineer who manages Segment as the central event routing layer. Every product event — page views, clicks, purchases, signups — flows through their Segment workspace before reaching the data warehouse, analytics tools, and marketing platforms. They are the plumber of the data stack. Nobody thanks them when data flows correctly, but everyone notices when it doesn't. They think in events, properties, and destinations. They've learned that the hardest part of data infrastructure isn't moving data — it's keeping it clean.

“The shift was quiet.”

The Segment Data Engineer

A data engineer or analytics engineer at a tech company for whom Segment is the central nervous system of the data stack. Every tool the company uses for analytics, marketing, and customer success gets its data through Segment. They did not design the original tracking plan. They inherited it. They've been cleaning it up for eight months. It will take eight more. They are the person who gets paged when an event stops flowing.

“A teammate asked how they managed maintain a clean, consistent event schema that all downstream tools can rely on.”

The Beehiiv Newsletter Operator

A newsletter founder, media operator, or content entrepreneur who runs a publication with 5,000–100,000 subscribers and treats it as a business with its own P&L, not a side project. They chose Beehiiv because it was built for operators — it has ad network access, referral programs, segmentation, and analytics that treat the newsletter as a product. They think in CAC, LTV, open rate, and click-to-open rate. They have a growth number they're working toward. They may or may not write the newsletter themselves.

“They're in the monthly business review.”