CES is typically collected by asking a customer to rate agreement with a statement like the company made it easy for me to handle my issue, on a numeric scale, immediately after the interaction closes. Unlike CSAT, which asks how satisfied a customer felt, CES asks specifically about friction, whether they had to repeat themselves, switch channels, or wait for a response. Low effort scores tend to correlate with resolution happening in a single interaction rather than across several follow-ups.
For AI concierge deployments in MENA markets, effort is closely tied to whether a customer can complete a request in their preferred dialect and channel, typically WhatsApp, without being asked to repeat information already given or being redirected elsewhere. In regulated industries like banking or healthcare, where processes such as KYC or appointment booking can otherwise involve multiple steps and departments, an AI that lowers effort by handling the full workflow in one conversation has a direct effect on retention.
In Eshal: Eshal is designed around minimizing customer effort: context carried over from CRM records means customers are not asked to repeat information, and workflows such as returns, bookings, or KYC collection are handled within a single WhatsApp or web conversation rather than requiring channel switches. Effort reduction is tracked alongside CSAT and automated resolution rate as part of ongoing performance monitoring.