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Table of Contents

• 1. Connectivity instability drives provider switching
• 2. Context
• 3. Impact of instability on customer satisfaction
• 4. Intention to switch provider among customers
  • 4.1 Percentage of customers at risk
  • 4.2 Time windows for switching
• 5. The role of the Connectivity Exposure Score (CES)
• 6. Customer behavior in the face of instability
  • 6.1 Adaptation instead of escalation
  • 6.2 Customer Compensation Index (CCI)
• 7. Strategies to prevent switching providers
• 8. Conclusions
  • 8.1 Customer experience
  • 8.2 Churn prevention

gestating a growing share of customer churn.

The February 2026 Home Connectivity Pulse places the phenomenon at massive scale: The data suggests the problem is not marginal or episodic, but structural in many environments—interference, device density, home layout, and coverage limitations that are not always reflected in diagnostics focused on the network up to the gateway.

Whole-home Wi‑Fi experience
“Whole-home” doesn’t just mean “the router has signal,” but “the experience holds up where the customer actually uses the service.” In practice, it usually includes:
– Variation by room (dead zones, walls, distance, height).
– Differences by device (mobile vs TV vs console vs laptop) and by Wi‑Fi standard.
– Interference (neighbors, microwaves, Bluetooth) and time-based congestion.
– Device density (streaming + video call + smart home) that stresses the local network.
That’s why churn can look “sudden” in gateway-centric dashboards: the link may appear healthy while the real experience degrades inside the home.

Impact of instability on customer satisfaction

Instability does not always translate immediately into a formal complaint. In fact, one of the benchmark’s key findings is that dissatisfaction can build up without “making noise” in traditional indicators: the customer keeps paying, doesn’t call support, and yet begins to lose trust.

That erosion accelerates when the user perceives that the service doesn’t deliver what was promised in their real context (remote work, streaming, gaming, smart home). Market studies cited in recent research indicate that switching reasons are more concentrated on quality of experience (QoE) and support than on price: in an Airties survey (2025), a significant share of those who switched ISPs attributed it to poor QoE and, to a lesser extent, customer service, above offers or contractual terms.

Experience and support drive switching
In the Airties (2025) survey on reasons for switching ISPs, the results suggest the decision is explained more by experience and support than by price:
– Among those who switched in the last 12 months, 47% (U.S.) cited poor QoE (36%) and insufficient support (11%) as the main reason.
– In the UK, 49% cited poor QoE (41%) and support (8%).
– By comparison, switching for a better price/contract was lower: 38% (U.S.) and 35% (UK).
Operational takeaway: when the

instability becomes routine, “price matching” rarely makes up for a QoE perceived as inconsistent.

Intention to switch provider among customers

The most direct consequence of persistent instability is the activation of switching intent. The Home Connectivity Pulse quantifies that transition: respondents state that they would switch providers if the problems continue. In other words, churn is not a sudden event; it is a measurable progression that begins before cancellation.

Percentage of customers at risk

The report introduces the concept of the Latent Churn Index (LCI) as the proportion of customers who declare a likelihood of switching if the instability is not resolved. In the benchmark, that indicator stands at 72.2% under conditions of sustained instability, a sign that risk is widely distributed and not limited to “extreme cases.”

In addition, risk can concentrate in high-value segments: nearly 49.9% of households say they have paid extra for upgrades or WiFi add-ons. In that group, the report observes a disproportionate concentration of exposure and switching intent, summarized in the Monetized Frustration Rate (MFR): 95% of those who invested in “better WiFi” still showed unresolved instability or active intent to switch. This is the customer who has already demonstrated willingness to pay—and who, if they don’t see results, feels doubly let down.

Time windows for switching

Intent doesn’t remain theoretical. Among customers already considered “at risk,” the benchmark estimates a rapid activation window: 25.8% would switch within three months and 45.3% within six months if instability persists. This Churn Activation Window (CAW) reduces the room to react: when the user decides to “look at alternatives,” cancellation is usually a matter of weeks or a few months.

Actionable interpretation of LCI and CAW
How to read LCI and CAW without getting lost (and turn them into action):
– LCI (Latent Churn Index): “How many say they’ll leave if this continues as is?” It’s a signal of conditional intent (if instability persists).
– CAW (Churn Activation Window): “How long until that intent materializes?” It’s a signal of urgency (how long the real intervention window lasts).
– Quick interpretation:
– High LCI + short CAW = broad risk and limited time → prioritize early detection and guided resolution.
– High LCI + long CAW = broad risk but with some leeway →

attack structural causes (coverage, interference, configuration).
– Moderate LCI + short CAW = concentrated risk → segment (households with add-ons, high device density, remote work).
– Practical checkpoint: if the CAW shows 3–6 months, the goal is not to “save the downgrade,” but to prevent the customer from getting to the point of comparing alternatives.

The role of the Connectivity Exposure Score (CES)

The Connectivity Exposure Score (CES) aims to measure something traditional systems often overlook: the proportion of customers exposed to unresolved whole-home instability, before there is a ticket or a call. In the benchmark, the CES stands at 68.1% as the industry baseline.

The implication is strategic: if the provider only “sees” the problem when the customer contacts them, it arrives late. The report argues that visibility must shift from the network perimeter (gateway) to the real in-home experience, where perceptions of quality are formed and, with them, the risk of churn.

From CES to retention
Practical use of CES (from metric to retention lever):
1) Define what counts as “exposure”: recurring instability in the “whole-home” experience (by room/device), not just link drops.
2) Measure and segment: observe CES by cohorts (households with WiFi add-ons, high device density, remote work, home size).
3) Read CES alongside behavioral signals: if customer effort increases (reboots, relocation, retries), risk is usually maturing even if there are no tickets.
4) Prioritize intervention: start with segments where the economic impact is greatest (e.g., customers who pay extra for WiFi) and where the CAW suggests urgency.
5) Quality checkpoint: after the intervention, validate that the experience improves in the problematic areas (not just that “the modem is online”).

Customer behavior in the face of instability

The classic churn narrative assumes a simple sequence: the service fails, the customer complains, the provider reacts. Home Connectivity Pulse describes a longer, quieter journey, with stages ranging from installation and the clash with the home’s “reality” to normalization, compensation, risk activation, and finally, the switching action.

Adaptation instead of escalation

Instead of escalating the problem to support, many users adapt: they reboot equipment, move the router, switch rooms, change usage habits, or “accept”dead zones. This normalization can keep certain satisfaction indicators stable in the short term, but it accumulates what the report calls “experience debt”: the customer invests time and patience to make the service work as it should.

That pattern explains why churn can seem sudden on dashboards: the decision is simmering for weeks or months without explicit signals, and when the call or cancellation comes, the recovery window has already been used up.

Customer Compensation Index (CCI)

To capture that pre-complaint phase, the report introduces the Customer Compensation Index (CCI), which measures the extent to which the customer absorbs work to compensate for unresolved issues. A high CCI works as a leading indicator: it reflects not only a technical failure, but a relationship that wears down because the user feels they’re “acting as the technician” in their own home.

Stages of Customer Churn
Churn formation sequence (6 stages) and what to watch in each:
1) Setup: expectations vs. the physical reality of the home (first no-coverage zones).
2) Experience Reality: instability shows up in routines (streaming, video calls, gaming) and across different devices.
3) Normalization: the customer adapts and “lives with” the problem (here the risk grows without tickets).
4) Customer Compensation: effort increases (restarts, repositioning, retries); the CCI tends to rise.
5) Risk Activation: intent forms (“if this keeps up, I’m switching”); the LCI captures this phase.
6) Churn Action: execution within a time window (CAW); winning the customer back is harder and more costly.
Key idea: the later you act (stages 5–6), the less room there is to rebuild trust.

Strategies to prevent switching providers

The shift the benchmark proposes is moving from reactive churn management (when the customer cancels) to prevention based on exposure and behavior. In practice, that implies:

• Early detection of instability in the setup and experience reality stages, before the user normalizes the problem.
• Whole-home visibility, not just the link to the gateway: performance by room, interference, device density, and usage patterns.
• Prioritization by risk and value, especially for customers who pay for WiFi upgrades, where “monetized” frustration concentrates potential losses.
• Proactive interventions (optimization, recommendations, guided support) before the intent to switch is activated within thewindow of 3 to 6 months.

From Reaction to Proactive Prevention
Operational checklist (to move from “reacting” to “preventing”):
– [ ] Identify households with recurring exposure (CES-type signals) even if there are no tickets.
– [ ] Detect compensation (CCI-type signals): frequent reboots, location changes, repeated retries.
– [ ] Segment by value and sensitivity: customers with WiFi add-ons, remote work, high device density.
– [ ] Act within the CAW (3–6 months): proactive outreach, optimization guidance, configuration adjustment, coverage reinforcement.
– [ ] Validate “whole-home” improvement: verify that the issue was resolved in the room/device where it was experienced.
– [ ] Close the loop: if it doesn’t improve, escalate to deeper intervention (equipment, visit, coverage redesign) before intent is triggered.

Conclusions

Customer experience

Connectivity is evaluated where it’s used: in the living room, the home office, and the bedroom, with multiple devices competing for stability. With 68% of households reporting recurring instability, the in-home experience stops being a “detail” and becomes the core of service perception.

Churn prevention

With 72% willing to switch if problems persist and an activation window that can be three to six months, retention depends on anticipating. Metrics like CES and CCI point to one approach: identify exposure and compensation before the customer calls—or leaves.

The Future of Connectivity and Customer Retention

In a market with lower net growth and price pressure, competitive advantage shifts toward perceived reliability and the ability to resolve invisible frictions. The churn of the future, the report suggests, will not be understood only as a recorded cancellation, but as the predictable result of in-home instability that was allowed to mature in silence.

Suricata Cx’s Comprehensive Solution to Combat Churn in Telecommunications

Understanding Latent Churn in In-Home Connectivity

The benchmark describes churn that forms before the complaint: exposure to instability, normalization, and customer compensation until switching intent is activated. In that context, any retention-oriented solution needs to detect risk before it becomes visible in traditional channels.

The Importance of Customer Experience in Retention

The “whole-home” experience becomes the real product. When the user pays for upgrades and still suffers outages or poor coverage, frustration intensifies and risk concentrates, as reflected by the MFR in customers with WiFi add-ons.

How Suricata Cx Addresses Churn Challenges

Under the report’s logic, a comprehensive churn-oriented platform should focus on early visibility, reading behavioral signals (such as compensation), and the ability to intervene before risk is triggered, especially within the critical window of months.

Capability (oriented to latent churn)	Expected benefit	Trade-off to manage
“Whole-home” visibility (by room/device)	Reduces false “everything OK” when the gateway is healthy but the experience isn’t	Requires instrumentation/telemetry and a clear model of “what is instability”
Early detection based on exposure (CES)	Makes it possible to intervene before there is a ticket and before intent is activated	Risk of excessive alerts if not segmented and prioritized
Customer effort signals (CCI)	Identifies relationship wear-and-tear (not just technical failures)	May require integration with support/usage data to be consistent
Proactive intervention (recommendations/optimization)	Shortens resolution times and protects trust	Balance between automation and human control to avoid inappropriate actions
Value-based prioritization (e.g., customers with WiFi add-ons)	Focuses resources where the economic impact is greatest	May be perceived as unequal if a transparent service policy is not designed

Strategies to Improve Customer Satisfaction

The most effective levers align with the Home Connectivity Pulse diagnosis: reduce exposure (CES), decrease the effort the customer takes on (CCI), and act before the intention to switch solidifies. In operational terms, that translates into less frustrating “self-support” and more guided, preventive resolution.

Conclusion: A Sustainable Future in Telecommunications

The benchmark evidence points to an uncomfortable reality for providers: churn doesn’t start with the cancellation call, but with small, repeated instabilities that the customer learns to tolerate… until they no longer do. In that context, business sustainability depends on making the invisible visible and intervening while there is still trust left to save.

Instability in home connectivity and switching providers is not explained only by isolated outages, but by a “whole-home” experience that silently degrades until it triggers churn. From Suricata Cx, this type of risk is addressed by making that instability visible before the complaint arrives, with automation and human-controlled workflows that speed up resolution and protect customer trust.

The figures cited are based on publicly available information as of the time of writing, such as benchmarks and surveys mentioned in the text. The percentages are aggregated and may vary by country, network type, household size, and usage profile. In home connectivity, minor changes in devices, interference, or home layout can significantly alter the experience, so these data may be updated with new information.