{"id":2889,"date":"2026-03-01T03:02:32","date_gmt":"2026-03-01T06:02:32","guid":{"rendered":"https:\/\/suricata.la\/untitled-2\/"},"modified":"2026-03-01T03:02:34","modified_gmt":"2026-03-01T06:02:34","slug":"untitled-2","status":"publish","type":"post","link":"https:\/\/suricata.la\/en\/untitled-2\/","title":{"rendered":"Untitled"},"content":{"rendered":"<h2>Table of Contents<\/h2>\n<ul>\n<li><a href=\"#inestabilidad-en-conectividad-impulsa-cambio-de-proveedor\">1. Connectivity instability drives provider switching<\/a>\n<\/li>\n<li><a href=\"#contexto\">2. Context<\/a>\n<\/li>\n<li><a href=\"#impacto-de-la-inestabilidad-en-la-satisfaccion-del-cliente\">3. Impact of instability on customer satisfaction<\/a>\n<\/li>\n<li><a href=\"#intencion-de-cambio-de-proveedor-entre-los-clientes\">4. Intention to switch provider among customers<\/a>\n<ul>\n<li><a href=\"#porcentaje-de-clientes-en-riesgo\">4.1 Percentage of customers at risk<\/a><\/li>\n<li><a href=\"#ventanas-de-tiempo-para-el-cambio\">4.2 Time windows for switching<\/a><\/li>\n<\/ul>\n<\/li>\n<li><a href=\"#el-papel-del-connectivity-exposure-score-ces\">5. The role of the Connectivity Exposure Score (CES)<\/a>\n<\/li>\n<li><a href=\"#comportamiento-de-los-clientes-ante-la-inestabilidad\">6. Customer behavior in the face of instability<\/a>\n<ul>\n<li><a href=\"#adaptacion-en-lugar-de-escalacion\">6.1 Adaptation instead of escalation<\/a><\/li>\n<li><a href=\"#indice-de-compensacion-del-cliente-cci\">6.2 Customer Compensation Index (CCI)<\/a><\/li>\n<\/ul>\n<\/li>\n<li><a href=\"#estrategias-para-prevenir-el-cambio-de-proveedor\">7. Strategies to prevent switching providers<\/a>\n<\/li>\n<li><a href=\"#conclusiones\">8. Conclusions<\/a>\n<ul>\n<li><a href=\"#experiencia-del-cliente\">8.1 Customer experience<\/a><\/li>\n<li><a href=\"#prevencion-del-churn\">8.2 Churn prevention<\/a><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<div class=\"ai-article\">\n<h2 id=\"inestabilidad-en-conectividad-impulsa-cambio-de-proveedor\">Connectivity instability drives provider switching<\/h2>\n<ul>\n<li><strong>68% of households<\/strong> report <strong>recurring instability<\/strong> in whole-home connectivity, according to the <em>Home Connectivity Pulse<\/em> (February 2026).<\/li>\n<li>Churn intent is high: <strong>72%<\/strong> say they <strong>would switch providers<\/strong> if the problems persist.<\/li>\n<li>Among customers already \u201cat risk,\u201d <strong>26%<\/strong> would switch in <strong>three months<\/strong> and <strong>45%<\/strong> in <strong>six months<\/strong>, shortening the intervention window.<\/li>\n<li>The risk is often <strong>silent<\/strong>: many users <strong>adapt<\/strong> (reboots, moving the router) before complaining, so churn \u201cshows up\u201d late on dashboards.<\/li>\n<li>Metrics such as <strong>Connectivity Exposure Score (CES)<\/strong> and <strong>Customer Compensation Index (CCI)<\/strong> aim to detect the problem before it turns into a cancellation.<\/li>\n<\/ul>\n<div class=\"cc-table-wrap\" style=\"overflow-x:auto;max-width:100%;-webkit-overflow-scrolling:touch\">\n<table class=\"cc-table\" style=\"width:100% !important;max-width:100% !important;min-width:540px;table-layout:auto !important;white-space:normal !important;word-break:normal;overflow-wrap:anywhere;hyphens:auto\">\n<thead>\n<tr>\n<th>Benchmark signal (Home Connectivity Pulse, Feb-2026)<\/th>\n<th>What it indicates<\/th>\n<th>Why it matters for retention<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td><strong>CES (baseline): 68.1%<\/strong><\/td>\n<td>Share of customers exposed to unresolved \u201cwhole-home\u201d instability before opening a ticket<\/td>\n<td>Risk forms before support \u201csees\u201d it<\/td>\n<\/tr>\n<tr>\n<td><strong>Households with recurring instability: 68%<\/strong><\/td>\n<td>Friction is massive, not an isolated case<\/td>\n<td>The at-home experience shapes perception of the service<\/td>\n<\/tr>\n<tr>\n<td><strong>LCI (switching intent if it persists): 72.2%<\/strong><\/td>\n<td>Intent is triggered by sustained instability<\/td>\n<td>Churn is a measurable progression, not a sudden event<\/td>\n<\/tr>\n<tr>\n<td><strong>CAW: 25.8% in 3 months \/ 45.3% in 6 months<\/strong><\/td>\n<td>Typical time window for intent to turn into action<\/td>\n<td>Intervention must happen early (weeks\/months, not \u201cwhen they cancel\u201d)<\/td>\n<\/tr>\n<tr>\n<td><strong>CCI (concept)<\/strong><\/td>\n<td>Effort the customer takes on to \u201cmake it work\u201d<\/td>\n<td>Leading indicator of wear and loss of trust<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<h2 id=\"contexto\">Context<\/h2>\n<p>Home connectivity has become the real thermometer of service quality: it\u2019s not enough for the modem to be \u201conline\u201d if in specific rooms the WiFi drops, video freezes, or video calls stutter. In that arena\u2014the one of everyday use, by device and by room\u2014it is being<\/p>\n<\/div>\n<p>gestating a growing share of customer churn.<\/p>\n<p>The February 2026 <em>Home Connectivity Pulse<\/em> places the phenomenon at massive scale: The data suggests the problem is not marginal or episodic, but structural in many environments\u2014interference, device density, home layout, and coverage limitations that are not always reflected in diagnostics focused on the network up to the gateway.<\/p>\n<blockquote>\n<p><strong>Whole-home Wi\u2011Fi experience<\/strong><br \/>\n\u201cWhole-home\u201d doesn\u2019t just mean \u201cthe router has signal,\u201d but \u201cthe experience holds up where the customer actually uses the service.\u201d In practice, it usually includes:<br \/>\n&#8211; Variation by <strong>room<\/strong> (dead zones, walls, distance, height).<br \/>\n&#8211; Differences by <strong>device<\/strong> (mobile vs TV vs console vs laptop) and by Wi\u2011Fi standard.<br \/>\n&#8211; <strong>Interference<\/strong> (neighbors, microwaves, Bluetooth) and time-based congestion.<br \/>\n&#8211; <strong>Device density<\/strong> (streaming + video call + smart home) that stresses the local network.<br \/>\nThat\u2019s why churn can look \u201csudden\u201d in gateway-centric dashboards: the link may appear healthy while the real experience degrades inside the home.<\/p>\n<\/blockquote>\n<h2 id=\"impacto-de-la-inestabilidad-en-la-satisfaccion-del-cliente\">Impact of instability on customer satisfaction<\/h2>\n<p>Instability does not always translate immediately into a formal complaint. In fact, one of the benchmark\u2019s key findings is that dissatisfaction can build up without \u201cmaking noise\u201d in traditional indicators: the customer keeps paying, doesn\u2019t call support, and yet begins to lose trust.<\/p>\n<p>That erosion accelerates when the user perceives that the service doesn\u2019t 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 <strong>quality of experience (QoE)<\/strong> and support than on price: in an Airties survey (2025), a significant share of those who switched ISPs attributed it to <strong>poor QoE<\/strong> and, to a lesser extent, <strong>customer service<\/strong>, above offers or contractual terms.<\/p>\n<blockquote>\n<p><strong>Experience and support drive switching<\/strong><br \/>\nIn the Airties (2025) survey on reasons for switching ISPs, the results suggest the decision is explained more by experience and support than by price:<br \/>\n&#8211; Among those who switched in the last 12 months, <strong>47% (U.S.)<\/strong> cited <strong>poor QoE (36%)<\/strong> and <strong>insufficient support (11%)<\/strong> as the main reason.<br \/>\n&#8211; In the UK, <strong>49%<\/strong> cited <strong>poor QoE (41%)<\/strong> and <strong>support (8%)<\/strong>.<br \/>\n&#8211; By comparison, switching for a <strong>better price\/contract<\/strong> was lower: <strong>38% (U.S.)<\/strong> and <strong>35% (UK)<\/strong>.<br \/>\nOperational takeaway: when the<\/p>\n<\/blockquote>\n<p>instability becomes routine, \u201cprice matching\u201d rarely makes up for a QoE perceived as inconsistent.<\/p>\n<\/blockquote>\n<h2 id=\"intencion-de-cambio-de-proveedor-entre-los-clientes\">Intention to switch provider among customers<\/h2>\n<p>The most direct consequence of persistent instability is the activation of switching intent. The <em>Home Connectivity Pulse<\/em> quantifies that transition: respondents state that they <strong>would switch providers<\/strong> if the problems continue. In other words, churn is not a sudden event; it is a measurable progression that begins before cancellation.<\/p>\n<h3 id=\"porcentaje-de-clientes-en-riesgo\">Percentage of customers at risk<\/h3>\n<p>The report introduces the concept of the <strong>Latent Churn Index (LCI)<\/strong> as the proportion of customers who declare a likelihood of switching if the instability is not resolved. In the benchmark, that indicator stands at <strong>72.2%<\/strong> under conditions of sustained instability, a sign that risk is widely distributed and not limited to \u201cextreme cases.\u201d<\/p>\n<p>In addition, risk can concentrate in high-value segments: nearly <strong>49.9%<\/strong> 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 <strong>Monetized Frustration Rate (MFR)<\/strong>: <strong>95%<\/strong> of those who invested in \u201cbetter WiFi\u201d still showed unresolved instability or active intent to switch. This is the customer who has already demonstrated willingness to pay\u2014and who, if they don\u2019t see results, feels doubly let down.<\/p>\n<h3 id=\"ventanas-de-tiempo-para-el-cambio\">Time windows for switching<\/h3>\n<p>Intent doesn\u2019t remain theoretical. Among customers already considered \u201cat risk,\u201d the benchmark estimates a rapid activation window: <strong>25.8%<\/strong> would switch within <strong>three months<\/strong> and <strong>45.3%<\/strong> within <strong>six months<\/strong> if instability persists. This <strong>Churn Activation Window (CAW)<\/strong> reduces the room to react: when the user decides to \u201clook at alternatives,\u201d cancellation is usually a matter of weeks or a few months.<\/p>\n<blockquote>\n<p><strong>Actionable interpretation of LCI and CAW<\/strong><br \/>\nHow to read LCI and CAW without getting lost (and turn them into action):<br \/>\n&#8211; <strong>LCI (Latent Churn Index)<\/strong>: \u201cHow many say they\u2019ll leave if this continues as is?\u201d It\u2019s a signal of <strong>conditional intent<\/strong> (if instability persists).<br \/>\n&#8211; <strong>CAW (Churn Activation Window)<\/strong>: \u201cHow long until that intent materializes?\u201d It\u2019s a signal of <strong>urgency<\/strong> (how long the real intervention window lasts).<br \/>\n&#8211; Quick interpretation:<br \/>\n  &#8211; <strong>High LCI + short CAW<\/strong> = broad risk and limited time \u2192 prioritize early detection and guided resolution.<br \/>\n  &#8211; <strong>High LCI + long CAW<\/strong> = broad risk but with some leeway \u2192<\/p>\n<p>attack structural causes (coverage, interference, configuration).<br \/>\n  &#8211; <strong>Moderate LCI + short CAW<\/strong> = concentrated risk \u2192 segment (households with add-ons, high device density, remote work).<br \/>\n&#8211; Practical checkpoint: if the CAW shows <strong>3\u20136 months<\/strong>, the goal is not to \u201csave the downgrade,\u201d but <strong>to prevent the customer from getting to the point of comparing alternatives<\/strong>.<\/p>\n<\/blockquote>\n<h2 id=\"el-papel-del-connectivity-exposure-score-ces\">The role of the Connectivity Exposure Score (CES)<\/h2>\n<p>The <strong>Connectivity Exposure Score (CES)<\/strong> aims to measure something traditional systems often overlook: the <strong>proportion of customers exposed to unresolved whole-home instability<\/strong>, before there is a ticket or a call. In the benchmark, the CES stands at <strong>68.1%<\/strong> as the industry baseline.<\/p>\n<p>The implication is strategic: if the provider only \u201csees\u201d 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.<\/p>\n<blockquote>\n<p><strong>From CES to retention<\/strong><br \/>\nPractical use of CES (from metric to retention lever):<br \/>\n1) <strong>Define what counts as \u201cexposure\u201d<\/strong>: recurring instability in the \u201cwhole-home\u201d experience (by room\/device), not just link drops.<br \/>\n2) <strong>Measure and segment<\/strong>: observe CES by cohorts (households with WiFi add-ons, high device density, remote work, home size).<br \/>\n3) <strong>Read CES alongside behavioral signals<\/strong>: if customer effort increases (reboots, relocation, retries), risk is usually maturing even if there are no tickets.<br \/>\n4) <strong>Prioritize intervention<\/strong>: start with segments where the economic impact is greatest (e.g., customers who pay extra for WiFi) and where the CAW suggests urgency.<br \/>\n5) <strong>Quality checkpoint<\/strong>: after the intervention, validate that the experience improves in the problematic areas (not just that \u201cthe modem is online\u201d).<\/p>\n<\/blockquote>\n<h2 id=\"comportamiento-de-los-clientes-ante-la-inestabilidad\">Customer behavior in the face of instability<\/h2>\n<p>The classic churn narrative assumes a simple sequence: the service fails, the customer complains, the provider reacts. <em>Home Connectivity Pulse<\/em> describes a longer, quieter journey, with stages ranging from installation and the clash with the home\u2019s \u201creality\u201d to normalization, compensation, risk activation, and finally, the switching action.<\/p>\n<h3 id=\"adaptacion-en-lugar-de-escalacion\">Adaptation instead of escalation<\/h3>\n<p>Instead of escalating the problem to support, many users <strong>adapt<\/strong>: they reboot equipment, move the router, switch rooms, change usage habits, or \u201caccept\u201ddead zones. This normalization can keep certain satisfaction indicators stable in the short term, but it accumulates what the report calls \u201cexperience debt\u201d: the customer invests time and patience to make the service work as it should.<\/p>\n<p>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.<\/p>\n<h3 id=\"indice-de-compensacion-del-cliente-cci\">Customer Compensation Index (CCI)<\/h3>\n<p>To capture that pre-complaint phase, the report introduces the <strong>Customer Compensation Index (CCI)<\/strong>, which measures the extent to which the customer <strong>absorbs work<\/strong> 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\u2019re \u201cacting as the technician\u201d in their own home.<\/p>\n<blockquote>\n<p><strong>Stages of Customer Churn<\/strong><br \/>\nChurn formation sequence (6 stages) and what to watch in each:<br \/>\n1) <strong>Setup<\/strong>: expectations vs. the physical reality of the home (first no-coverage zones).<br \/>\n2) <strong>Experience Reality<\/strong>: instability shows up in routines (streaming, video calls, gaming) and across different devices.<br \/>\n3) <strong>Normalization<\/strong>: the customer adapts and \u201clives with\u201d the problem (here the risk grows without tickets).<br \/>\n4) <strong>Customer Compensation<\/strong>: effort increases (restarts, repositioning, retries); the CCI tends to rise.<br \/>\n5) <strong>Risk Activation<\/strong>: intent forms (\u201cif this keeps up, I\u2019m switching\u201d); the LCI captures this phase.<br \/>\n6) <strong>Churn Action<\/strong>: execution within a time window (CAW); winning the customer back is harder and more costly.<br \/>\nKey idea: the later you act (stages 5\u20136), the less room there is to rebuild trust.<\/p>\n<\/blockquote>\n<h2 id=\"estrategias-para-prevenir-el-cambio-de-proveedor\">Strategies to prevent switching providers<\/h2>\n<p>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:<\/p>\n<ul>\n<li><strong>Early detection<\/strong> of instability in the <em>setup<\/em> and <em>experience reality<\/em> stages, before the user normalizes the problem.<\/li>\n<li><strong>Whole-home visibility<\/strong>, not just the link to the gateway: performance by room, interference, device density, and usage patterns.<\/li>\n<li><strong>Prioritization by risk and value<\/strong>, especially for customers who pay for WiFi upgrades, where \u201cmonetized\u201d frustration concentrates potential losses.<\/li>\n<li><strong>Proactive interventions<\/strong> (optimization, recommendations, guided support) before the intent to switch is activated within thewindow of 3 to 6 months.<\/li>\n<\/ul>\n<blockquote>\n<p><strong>From Reaction to Proactive Prevention<\/strong><br \/>\nOperational checklist (to move from \u201creacting\u201d to \u201cpreventing\u201d):<br \/>\n&#8211; [ ] Identify households with <strong>recurring exposure<\/strong> (CES-type signals) even if there are no tickets.<br \/>\n&#8211; [ ] Detect <strong>compensation<\/strong> (CCI-type signals): frequent reboots, location changes, repeated retries.<br \/>\n&#8211; [ ] Segment by <strong>value and sensitivity<\/strong>: customers with WiFi add-ons, remote work, high device density.<br \/>\n&#8211; [ ] Act within the <strong>CAW (3\u20136 months)<\/strong>: proactive outreach, optimization guidance, configuration adjustment, coverage reinforcement.<br \/>\n&#8211; [ ] Validate \u201cwhole-home\u201d improvement: verify that the issue was resolved in the room\/device where it was experienced.<br \/>\n&#8211; [ ] Close the loop: if it doesn\u2019t improve, escalate to deeper intervention (equipment, visit, coverage redesign) before intent is triggered.<\/p>\n<\/blockquote>\n<h2 id=\"conclusiones\">Conclusions<\/h2>\n<h3 id=\"experiencia-del-cliente\">Customer experience<\/h3>\n<p>Connectivity is evaluated where it\u2019s used: in the living room, the home office, and the bedroom, with multiple devices competing for stability. With <strong>68%<\/strong> of households reporting recurring instability, the in-home experience stops being a \u201cdetail\u201d and becomes the core of service perception.<\/p>\n<h3 id=\"prevencion-del-churn\">Churn prevention<\/h3>\n<p>With <strong>72%<\/strong> willing to switch if problems persist and an activation window that can be <strong>three to six months<\/strong>, retention depends on anticipating. Metrics like <strong>CES<\/strong> and <strong>CCI<\/strong> point to one approach: identify exposure and compensation before the customer calls\u2014or leaves.<\/p>\n<h3 id=\"el-futuro-de-la-conectividad-y-la-retencion-de-clientes\">The Future of Connectivity and Customer Retention<\/h3>\n<p>In a market with lower net growth and price pressure, competitive advantage shifts toward <strong>perceived reliability<\/strong> and the ability to <strong>resolve invisible frictions<\/strong>. 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.<\/p>\n<h2 id=\"la-solucion-integral-de-suricata-cx-para-combatir-el-churn-en-telecomunicaciones\">Suricata Cx\u2019s Comprehensive Solution to Combat Churn in Telecommunications<\/h2>\n<h3 id=\"entendiendo-el-churn-latente-en-conectividad-hogarena\">Understanding Latent Churn in In-Home Connectivity<\/h3>\n<p>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.<\/p>\n<h3id=\"the-importance-of-customer-experience-in-retention\">The Importance of Customer Experience in Retention<\/h3>\n<p>The \u201cwhole-home\u201d 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 <strong>MFR<\/strong> in customers with WiFi add-ons.<\/p>\n<h3 id=\"how-suricata-cx-addresses-churn-challenges\">How Suricata Cx Addresses Churn Challenges<\/h3>\n<p>Under the report\u2019s logic, a comprehensive churn-oriented platform should focus on <strong>early visibility<\/strong>, reading <strong>behavioral signals<\/strong> (such as compensation), and the ability to <strong>intervene<\/strong> before risk is triggered, especially within the critical window of months.<\/p>\n<div class=\"cc-table-wrap\" style=\"overflow-x:auto;max-width:100%;-webkit-overflow-scrolling:touch\">\n<table class=\"cc-table\" style=\"width:100% !important;max-width:100% !important;min-width:540px;table-layout:auto !important;white-space:normal !important;word-break:normal;overflow-wrap:anywhere;hyphens:auto\">\n<thead>\n<tr>\n<th>Capability (oriented to latent churn)<\/th>\n<th>Expected benefit<\/th>\n<th>Trade-off to manage<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>\u201cWhole-home\u201d visibility (by room\/device)<\/td>\n<td>Reduces false \u201ceverything OK\u201d when the gateway is healthy but the experience isn\u2019t<\/td>\n<td>Requires instrumentation\/telemetry and a clear model of \u201cwhat is instability\u201d<\/td>\n<\/tr>\n<tr>\n<td>Early detection based on exposure (CES)<\/td>\n<td>Makes it possible to intervene before there is a ticket and before intent is activated<\/td>\n<td>Risk of excessive alerts if not segmented and prioritized<\/td>\n<\/tr>\n<tr>\n<td>Customer effort signals (CCI)<\/td>\n<td>Identifies relationship wear-and-tear (not just technical failures)<\/td>\n<td>May require integration with support\/usage data to be consistent<\/td>\n<\/tr>\n<tr>\n<td>Proactive intervention (recommendations\/optimization)<\/td>\n<td>Shortens resolution times and protects trust<\/td>\n<td>Balance between automation and human control to avoid inappropriate actions<\/td>\n<\/tr>\n<tr>\n<td>Value-based prioritization (e.g., customers with WiFi add-ons)<\/td>\n<td>Focuses resources where the economic impact is greatest<\/td>\n<td>May be perceived as unequal if a transparent service policy is not designed<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<h3 id=\"strategies-to-improve-customer-satisfaction\">Strategies to Improve Customer Satisfaction<\/h3>\n<p>The most effective levers align with the <em>Home Connectivity Pulse<\/em> 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 \u201cself-support\u201d and more guided, preventive resolution.<\/p>\n<h3id=\"conclusion-un-futuro-sostenible-en-telecomunicaciones\">Conclusion: A Sustainable Future in Telecommunications<\/h3>\n<p>The benchmark evidence points to an uncomfortable reality for providers: churn doesn\u2019t start with the cancellation call, but with small, repeated instabilities that the customer learns to tolerate\u2026 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.<\/p>\n<p>Instability in home connectivity and switching providers is not explained only by isolated outages, but by a \u201cwhole-home\u201d 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.<\/p>\n<p><em>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.<\/em><\/p>\n<\/div>\n<p><!--yoast-refresh--><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Table of contents 1. Connectivity instability drives provider switching 2. Context 3. Impact of instability on customer satisfaction 4. Provider switching intention 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 &#8230; <\/p>\n<div><a href=\"https:\/\/suricata.la\/untitled-2\/\" class=\"more-link\">Read More<\/a><\/div>\n","protected":false},"author":2,"featured_media":2866,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_yoast_wpseo_metadesc":"","content_central_editor_notes":"","yoast_description":"","footnotes":""},"categories":[48],"tags":[1217,1460,909,1461,1015],"class_list":["post-2889","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-noticias","tag-connectivity-issues","tag-customer-churn","tag-customer-satisfaction","tag-provider-switching","tag-service-quality"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Untitled - Suricata Cx<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/suricata.la\/en\/untitled-2\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Untitled - Suricata Cx\" \/>\n<meta property=\"og:description\" content=\"Table of contents 1. Connectivity instability drives provider switching 2. Context 3. Impact of instability on customer satisfaction 4. Provider switching intention 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. 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