4 days brought three calls from a GCC retail-bank customer about one disputed charge on a savings account. During call three, the customer asked to close the account. A survey sent after call two returned 4 out of 5. Standard reporting showed no churn risk until the customer said so directly on call three.
This pattern appears often in Arabic-speaking contact centers and exposes the limits of using CSAT as the only service measure. CSAT records immediate satisfaction with the agent interaction. It does not record the accumulated work that came before it or the frustration of calling again about an unresolved matter. In this case, the customer was satisfied with individual agents on two calls and still churned.
What Customer Effort Score measures and why it matters
Customer Effort Score, or CES, was created to cover this missing dimension. Its premise is straightforward: the effort required to resolve an issue strongly predicts loyalty or churn. Customers tend to stay after low-effort interactions and leave after high-effort ones, even when the issue is eventually resolved.
English-language markets commonly use CES surveys beside or instead of CSAT, often asking, "How easy was it to resolve your issue today?" on a 7-point scale. Service-quality research has repeatedly indicated that high effort predicts churn more strongly than low satisfaction predicts loyalty. Preventing a poor experience matters more than producing a good one.
Across MENA contact centers, CES infrastructure is less developed for Arabic-speaking customers. Arabic post-call surveys also tend to receive fewer responses, while borrowed English question formats may fail to express effort clearly within Arabic conversational norms.
The survey gap and what it leaves unmeasured
In our pilot partner data, Arabic-speaking Gulf customers were less likely than English-speaking customers in the same organization to complete post-call surveys. This is not a cultural reluctance to give feedback. Survey mechanisms such as IVR press-1-for-yes prompts and Arabic SMS links have often offered poor MENA UX, and customers who had a difficult experience are less likely to answer a follow-up survey about it.
That creates a systematic omission of high-effort experiences from CSAT and CES data. Customers facing three transfers, two hold periods, and an unresolved issue are least likely to finish the survey. Those receiving a smooth one-call resolution are more likely to respond. In a contact center with high Arabic call volume, survey results therefore lean toward better-than-average experiences and conceal the effort issue.
This occurs beyond Arabic-speaking markets, but the effect is sharper where survey infrastructure is less mature and other measurement options are less developed.
Inferring effort from call data
When surveys do not represent the full effort distribution, the calls themselves can provide a more dependable source. Several recording-based signals consistently relate to customer effort and can be measured without requiring a post-call response.
Repeat contact is the clearest signal. Calling again about the same topic within a short period indicates high effort by definition. Finding these contacts requires linking calls with customer identifiers and topic labels, which call recordings can provide when paired with CRM data. In our pilot work, 20 to 30 percent of high-churn-risk calls in Arabic banking contact centers came from customers who had raised the same issue within the previous 14 days, a pattern absent from CSAT reports.
Transfer count offers a second signal. Moving between teams or agents makes the customer repeat the issue, authenticate again, and often wait again. Arabic call transcripts explicitly reveal these events. Customers may say, "this is the second time I have been transferred," or, "the person I spoke to yesterday told me to call this number." Disposition codes do not always record such references, although transcripts show them consistently.
Repeated explanation during one call is a third signal. Restating the same issue usually indicates that the customer feels misunderstood. In Arabic, the customer may repeat the core problem with different wording or add emphasis markers. Detecting this requires dialectal Arabic text because these phrasing conventions differ from MSA.
Arabic-specific linguistic markers of frustration
Arabic uses expressive patterns for frustration that differ from English equivalents and can indicate high effort in transcripts. In Gulf Arabic, some diminutives and intensifiers carry resignation or exasperation without a direct English equivalent. A shift from informal dialect to formal register can also show that the customer is stressing the seriousness of the issue after feeling unheard.
Arabic complaint language is distributed differently as well. Gulf conversational norms often place contextual framing before a direct complaint. A customer who spends the first minute in apparent small talk may be setting up a substantial complaint. Systems based on English-derived sentiment scoring may label that opening neutral and miss frustration embedded in the conversation's structure.
These patterns can be detected, but the system must be trained on dialectal Arabic call data rather than adapted from an English sentiment model.
What intella tracks for effort estimation
intella's churn-signal analysis combines indicators that approximate effort without depending on survey responses. These include repeat-contact frequency, transfer references during calls, topic repetition, call duration compared with topic complexity, and linguistic patterns associated with frustration in Gulf and Levantine Arabic.
This is not to suggest surveys are useless. Call analysis complements them. Engaged respondents provide information that transcript analysis cannot reproduce. But in Arabic-speaking contact centers where high-effort customers respond at systematically lower rates, call-derived signals represent the actual effort distribution better than surveys alone. Where possible, using both provides the fullest view.
What better effort measurement changes
For a MENA bank or telco replacing CSAT-only reporting with an effort-sensitive contact-center view, team priorities change in several ways.
Process problems become visible that satisfaction scores may miss. A process requiring repeated transfers appears as a high-effort pattern even when agents manage each call well. The remedy is a process change, not agent coaching.
The at-risk population also looks different. Customers can report high CSAT, experience high effort, and still churn. Finding them requires measuring effort alongside satisfaction. For Arabic-speaking customers, whose survey responses are less dependable, call-based signals fill an important gap in the at-risk view.
Product and policy problems surface sooner. Repeated calls about one issue category at scale indicate a product signal as well as a service signal. Three weeks showing repeat contacts around one account feature can warn that the feature is causing confusion. Teams should therefore monitor repeat-contact and transfer signals by topic, then route confirmed patterns to process or product owners.