Not long after publishing my latest e-book on human-first selling, I received a letter from a thoughtful reader. Her question was, I believe, the single most important question anyone can ask about the future of CRM, so I want to answer it publicly.
She wrote, in essence: Revenue, conversion rates, and engagement are easy for a CRM to optimize. But integrity, trust, the discovery of fair value, and the likelihood that a customer recommends a salesperson (the things your argument places at the heart of sales) are much harder to measure. So what exactly should the objective function of a human-centric CRM be? If the system learns primarily from closed revenue, it may reward short-term behaviors that undermine trust. But if the real goal is fair transactions and lasting relationships, how can the system learn from these human qualities without reducing them to another set of misleading metrics?
This is the alignment problem of sales technology, stated perfectly. Economists know it as Goodhart's Law: when a measure becomes a target, it ceases to be a good measure. A CRM whose intelligence learns only from closed revenue will reward exactly the behaviors that erode trust. And if we try to quantify trust directly, we risk turning it into one more metric to be gamed. Both horns of the dilemma are real. My answer is that a human-centric CRM must refuse the premise behind them, and here is how.
The objective function does not belong to the machine
In a human-centric CRM, the objective function stays with the human. The system is an instrument. It makes reality visible, and it amplifies judgment; it does not replace the salesperson's purpose with a number to maximize. The moment a CRM becomes an optimizer of human behavior, it is no longer human-centric, by definition.
This conviction is built into our name. Coevera stands for collaboration and evolution, a new era in which human and machine work as partners, not substitutes. The machine computes; the human decides. This is not a limitation of the technology. It is the design principle.
Change the timescale, and revenue stops lying
Here is the resolution to the apparent conflict between revenue and trust: they only diverge in the short term. Short-term transaction revenue rewards pressure, overpromising, and the quick close. But long-horizon relationship value and trust converge, because a fair transaction is precisely one that both parties would willingly repeat.
So a human-centric system learns from relationship-level outcomes, not transaction-level ones: retention, repeat purchase, expansion, referrals, lifetime value. Trust is not unmeasurable. It is measurable later. Win-win is empirically visible as the customer coming back.
Measure promise-keeping, not sentiment
The most honest observable proxy for integrity is not a survey score. It is this: did the customer realize the value that was promised at the moment of sale?
Value realization measured against commitments made. Regret churn distinguished from natural churn. Willingness to serve as a reference. These indicators are behavioral, hard to fake, and they directly encode what my reader called the discovery of fair value. A salesperson who consistently keeps promises builds a data trail no manipulation can imitate, because the customer's own behavior writes it.
Metrics as instruments, never as targets
Finally, the safeguard against Goodhart's Law itself: these indicators must remain a diagnostic dashboard that the human interprets, never a single score that the system, or the compensation plan, optimizes. The plurality is the point. The moment we collapse trust, retention, and referrals into one number to maximize, we have rebuilt the very machine we set out to replace.
The system informs. The human decides. Accountability stays with people.
In one sentence
The objective function of a human-centric CRM is repeated, verified fair exchange over time, with the machine measuring it and the human owning it.
That is what we are building at Coevera. Not a system that optimizes salespeople, but a system that makes it easier for salespeople to be what the best of them already are: trusted advisors whose customers come back, and bring others with them.
I am grateful to the reader whose letter prompted this article. Questions like hers are how the argument gets sharper. If this raises a question of your own, write to me. The conversation is the point.
