The most underrated revenue function in most organisations.
Built for leaders
who need results.
Whether you are a startup scaling fast, a mid-market firm navigating complexity, or a PE-backed company on a tight timeline, Preconsultify's Customer Experience experts have been where you are.
High-Volume Consumer Businesses
Fintech, e-commerce, and telecom: companies handling 10K+ contacts per month.
SaaS Companies
Building scalable support operations as the customer base grows.
Companies Deploying AI CX
A chatbot strategy that actually works, not just checks a box.
Beyond the core, deeper expertise.
Service Design
Mapping and redesigning the end-to-end service experience across all channels.
Agent Enablement
Training, tools, and workflows that make agents more effective and less burned out.
Customer Lifecycle Programmes
Onboarding, retention, and win-back journeys that measurably shift LTV.
Work with verified top-tier experts.
Engagement Manager
Principal

Associate Partner
Project Leader
Customer Experience expertise across industries.
Problems solved. Outcomes delivered.
Tiered Service Architecture for a Consumer Fintech
The customer service team was handling 43,000 contacts a month and the breakdown was maddening: 61% of them were balance inquiries, transaction status checks, limit-reset requests, things that required looking up a number in a system, not human judgement. Agents were spending most of their day on tasks that anyone with access to the right database could handle. First-contact resolution was 69%. Agent satisfaction was poor. The irony was that the customers who actually needed help, disputes, account issues, fraud flags, were getting the most distracted version of the team.
A tiered service architecture: Tier 1 routes routine inquiries to an AI chatbot integrated with the core banking API. Tier 2 routes complex cases to agents with the full contact history already surfaced, no more asking the customer to repeat themselves. The chatbot was trained on 3,200 anonymised historical conversation transcripts, then tuned over eight weeks in parallel with human handling. A containment rate target of 45% was set for month 3 as a deliberately conservative milestone, so the team wouldn't be chasing an optimistic number in the early months.
Month 3 chatbot containment: 52%, above the target. Month 5: 58% of routine contacts fully resolved without agent involvement. Human contact volume fell 34%, not the projected 38%; the gap was account-linking queries that turned out to need a product fix, not a CX fix. FCR for human-handled cases rose from 69% to 81%.
NPS Recovery Programme for a Regional Life Insurer
This reflects the type of challenge our consultants are built to solve, drawn from real industry experience. The company's NPS was -11 and had been declining for three straight measurement periods. The management team knew it was bad. What they didn't know was which of the hundred things that could be wrong were the two or three actually causing it. Customers were complaining about renewal confusion and claims friction, but those are symptoms, not root causes. Agents were fielding 58% of renewal calls that the policy design intended to be self-service, which meant the agents were also frustrated. Four claim types required a branch visit, for customers who could sometimes be hours away from one.
Full journey mapping across five customer archetypes, not to produce a diagram, but to identify the 14 friction points that were in the insurer's direct control without regulatory changes. A WhatsApp renewal reminder and self-confirmation flow was built over 6 weeks with the IT team. Four claim types were digitised for remote intimation. Front-line staff at 14 branches were trained on a revised conversation guide for renewal-related complaints, because the call wasn't going away immediately, but the experience of the call could improve.
NPS moved from -11 to +6 across three measurement cycles over 9 months. The WhatsApp flow handled 4,300 renewals in its first 90 days; 68% needed no follow-up call or branch visit. Branch walk-ins for claims fell 31% on the four digitised claim types. One claim type planned for digitisation was delayed by a regulatory clarification issue and remains on manual. Nobody pretended otherwise.
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