Why churn is like divorce
To understand the forces at play in churn and retention dynamics, it’s useful to think of your relationship with customers as a marriage, and churn as divorce. Not because the metaphor is poetic, but because mathematics backs it up.
Economist José-Manuel Rey, in his paper A Mathematical Model of Sentimental Dynamics Accounting for Marital Dissolution, proposes that marital relationships follow a second law of thermodynamics: they naturally erode over time unless sustained by a constant influx of effort.
This same dynamic applies to business‑customer relationships across banking, telecommunications, and retail. Left unattended, the emotional bond that keeps customers loyal decays, until one day the relationship ends in a quiet, predictable ‘divorce’: churn.
Balancing feeling and effort
Rey treats relationships as dynamic systems with two core variables:
- Feeling — how partners feel about the relationship
- Effort — the energy invested to sustain it
His model aims to achieve sentimental equilibrium, a theoretical state in which a relationship is maintained at a constant level of both feeling and effort.
For businesses, this maps neatly onto customer experience: feeling corresponds to loyalty, trust, and satisfaction; effort corresponds to the investments you make in service, pricing, personalization, and support.
The effort gap
In banking, telecommunications, retail — everywhere — the default state of any relationship is entropy. If you are not actively strengthening relationships with your customers, they are weakening.
To counter this trajectory, effort is required. A key finding of Rey’s model is that the effort level required to maintain equilibrium is always higher than the effort level that partners would naturally prefer or find most comfortable. This difference is called the effort gap, implying that a lasting relationship requires a permanent exertion of extra effort.
In banking, telco, retail — everywhere — the default state of any relationship is entropy. If you are not actively strengthening the relationship, it is weakening.
There is also a point where too much effort becomes counterproductive. Rey’s theory of effort utility acknowledges that making a small amount of effort — such as planning an enjoyable activity with your partner — can be pleasant and emotionally rewarding. However, once the required effort surpasses this optimal threshold, additional effort begins to decrease utility and becomes emotionally costly. As effort continues to increase beyond this point, dissatisfaction rises without bound.
In business-customer relationships, this mirrors the balance between cost and return on investment: you want to ensure the effort (monetary and operational investment) makes a positive enough impact to outweigh the cost.
Stability in an unstable system
Because external forces are unstable, partners must continuously monitor their effort levels. Any change that causes a drop in effort must be corrected quickly. If partners are not alert to these changes, the relationship will drift onto a trajectory of deterioration.
The same applies to business-customer relationships. Factors outside your control affect customers’ lives daily, influencing their mood and decision-making. To maintain a good relationship, businesses need a way to gather signals about emotional change.
Leading indicators of emotional change include:
- Reduced usage velocity
- Delayed renewals
- Drop in engagement depth
- Lower response to outreach
- Increased support friction
Detecting change is one thing. Responding in a way that prevents churn is another. In digital environments, detection and response are driven by algorithms. If algorithms cannot detect behavioral signals, businesses will inevitably miss opportunities to prevent churn.
This is why ecosystem.Ai’s customer interaction solutions are driven by behavioral algorithms including Sentimental Equilibrium, Loss Aversion, Prospect Theory, and Risk Aversion. By detecting behavioral signals, these systems can identify emotional shifts, incorporate real-time and historical context, and respond with the right amount of effort at the right time and in the right way.
From reactive churn to proactive equilibrium
Churn is rarely a sudden event; it is the visible outcome of gradual entropy. Like any relationship, customer loyalty decays when effort is misjudged, mistimed, or misdirected.
The challenge is not simply to act, but to calibrate action: to detect subtle behavioral shifts, interpret them correctly, and respond with the right amount of effort before dissatisfaction compounds.
Behavioral intelligence makes this possible. By identifying early emotional signals and dynamically adjusting engagement, businesses can close the effort gap without overspending or overwhelming the customer. In doing so, they replace reactive retention tactics with proactive equilibrium — turning potential divorces into durable, long-term partnerships.