Why is it that even in a difficult job market, good salespeople usually have an easier time landing a new job? Because it is easy to become a salesperson, but hard to be a good one. A good salesperson has to combine qualities that may seem contradictory at first: having a thick skin while remaining empathetic, switching easily between tasks while being persistent enough to see deals through.
There are not many people who can combine all of these qualities. That is why companies compete for good salespeople and, once they hire them, invest in their training and development.
My name is Aleksei Prishchepo. At the beginning of 2026, I started building a tool that analyzed transcripts of customer phone calls to assess the quality of salespeople’s work and flag mistakes. Later I added a set of metrics, and the application began aggregating the data. The internal tool soon grew into a standalone product Sales Signals.
I know sales from the inside. I worked my way up from a direct sales representative to running a sales business that served many thousands of customers nationwide and operated successfully for over 15 years. I did the selling myself, hired and managed salespeople, worked on customer acquisition and retention, rolled out CRM systems, and mentored and trained staff.
Managing sales is genuinely difficult, even with a small team. Sales requires constant attention. A salesperson’s results are not immediately visible, and by the time a problem finally shows up in the numbers, it may already be too late. You can build a feedback system, set KPIs, hold regular meetings, and review reports — but a manager simply cannot be present in every conversation with a customer.
KPIs only solve part of the problem. This is where Goodhart’s law1 comes into play: once a measure becomes a target, people start optimizing for that measure itself, often at the expense of what actually matters. If revenue is the primary metric, discounts appear and profitability falls. If the target is margin, you can end up with the opposite problem: short-term profit starts to outweigh long-term customer relationships.
This does not mean KPIs are unnecessary. It means that looking only at the outcome is not enough. It is important to understand what happens along the way.
Not everything that can be automated should be handed over to a machine.
Sales is about relationships between people. Customers need someone who understands their situation, asks the right questions, works through their doubts, and takes responsibility for the decision. I do not believe in replacing a salesperson with a chatbot or voice bot simply because it is now technically possible.
People should talk to people, and machines should help people do it better.
That belief is what Sales Signals grew out of.
This is not yet another AI application looking for a use case in sales. The product is built on real experience in sales and on an understanding of how much valuable information gets lost in the ordinary sales process.
A machine can automatically analyze a customer conversation, fill in the CRM, spot a missed next step, help a manager see which salespeople need support, detect signs of risk for a specific customer, or reveal recurring questions and objections. But the decision and the action remain with the person.
That is why Sales Signals is not a system for monitoring employees. It is an intelligent assistance layer that works around the existing sales process: helping people remember what matters, turning conversations into data, data into action, and accumulated conversations into knowledge about customers, employees, and the market itself.
I want technology not to replace human connection where it truly matters, but to free people from work that machines do better.
This is how I see the role of technology in sales. It is what I am building Sales Signals to do. If this approach resonates with you, I’d be glad to show you how it works.
Footnotes
“When a measure becomes a target, it ceases to be a good measure.” The principle was formulated by British economist Charles Goodhart: once people are held accountable for a metric, they learn to improve the metric itself rather than what it is supposed to represent.↩︎