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CASE OVERVIEW / AI TICKET TRIAGE

Bulletproof: Using Automated Routing and Unified Views to Reduce Support Handling Time

Bulletproof used automated workflows, unified support views, and omnichannel service to keep pace with e-commerce growth, routing tickets before agents resolved them with full context.

Core changeA single path for every ticket became classification and routing first, followed by human handling for complex issues.
01 / INTAKE

Customers raise issues across channels

E-commerce customers submit delivery, order, product, or other support requests.

02 / CLASSIFICATION

The system identifies issue and priority

Automated workflows organize tickets according to their content and routing rules.

03 / ROUTING

Tickets reach the right team

The system sends each issue to agents with the relevant access and context.

04 / HUMAN RESOLUTION

Agents follow up in a unified view

Support staff review conversation and order information to resolve cases requiring human judgment.

Before & after
Before: One path for every ticket
After: Classification, routing, and human resolution

Before: Customer request → Shared queue → Human lookup and handling After: Customer request → Issue classification → Automated routing → Human resolution with full context

What makes this redesign work
  • Define stable ticket categories and routing rules first.
  • Bring conversation, order, and channel context into one view.
  • Track handling time and true resolution together.
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View process and full evidence

Nine sections covering context, ICP, positioning, channels, results, replicability, and next steps

Overview

Fact

Bulletproof needed its support operation to keep pace with e-commerce growth without sending every request through the same queue. Its published approach combined automated routing, unified views, and human resolution with order and conversation context.

Fact

Kustomer reports a 50% reduction in handling time and a 15% increase in first-contact resolution after the workflow was introduced.

Context

Fact

Bulletproof's Customer Care Advocates handled transactional issues, product-discovery conversations, and customer feedback. The operating challenge was to automate delivery and order work without removing the human attention needed for education and product insight.

Analysis

The workflow separated transactional resolution from higher-value conversations. A delivery problem could trigger an order lookup and text follow-up without an Advocate repeating the same steps.

Ideal customer

Analysis

The pattern is relevant to consumer brands whose support teams switch between order resolution, product education, and feedback conversations.

GTM problem

Analysis

The central problem was context switching: routine delivery work could consume the same Advocate attention needed for trust-building conversations.

Positioning

Fact

The implementation combined custom workflows, a unified conversation system, Kustomer's native Amazon Connect integration, and a mobile-focused path through text and voice. Bulletproof also planned to use Amazon Lex and Amazon Comprehend for language and sentiment analysis.

The operating model is: classify and route tickets first, then let agents resolve them with full context. For stable ticket categories, this preserves human judgment while removing avoidable assignment work.

Channels

Fact

Delivery prompts let customers reply with #BPDelivered or #BPCares, triggering feedback collection or an order lookup and troubleshooting flow. The support team also wanted Facebook and other conversations in one listening system.

Analysis

The channel choice was part of the operating model: push simple transactional work toward mobile automation, then keep Advocates available for conversations where trust and product knowledge matter.

Results & evidence

Fact

The official story reports a 15-point increase in customer perception of service quality over two months after launch and workflow optimization. The related Kustomer article reports a 50% handle-time reduction and a 15% FCR increase.

Analysis

These outcomes connect to a specific mechanism: automated delivery handling reduced transactional work, while shared channel data supported faster first-contact resolution.

Replicability

Replicability · Medium

Applicable when

  • Tickets can be classified by issue type, urgency, and team ownership.
  • Agents can view conversation and order context in one place.
  • The team has clear definitions for first-contact resolution and handling time.

Not transferable

  • The public material does not disclose ticket baselines, sample period, routing rules, or full configuration.
  • E-commerce delivery, returns, and product policies affect support complexity.

Risks

  • Incorrect classification can send a case to the wrong team.
  • Lower handling time does not necessarily mean that the customer's issue was solved.
  • The source does not isolate the contributions of routing, unified views, and other workflow changes.

Next steps

Define ticket categories, routing conditions, human escalation rules, and metric definitions before implementation. Codeleo can validate error rate, handoff time, true resolution, and agent load with a limited traffic segment before expanding automation.

Sources