Customer support · Production

Smalls scales personalized CX with Kustomer unified timeline and Forethought AI automation

The problem

As Smalls grew, subscription and order data flowed through multiple systems, leaving agents without a full picture of each customer's journey. Without a unified view, personalization took extra effort and manual triage slowed response times.

Workflow diagram · grounded in source

AI handles repetitive inquiries

ai_action

“Forethought provides scoped automation for high-volume, repetitive inquiries”

Route to right agent

routing

“Response times have dropped as conversations route directly to the right agents”

BPO handles Tier 1 and 2

human_review

“A BPO partner handles Tier 1 and most Tier 2 inquiries, keeping volume manageable”

In-house handles high-sensitivity

human_review

“while Smalls' in-house team focuses on high-sensitivity conversations—illness reports, legal concerns, VIPs, and brand reputation moments”

Issue detail logging

output

“Smalls makes extensive use of custom attributes to capture the full context of each issue. If a customer reports damaged packs, for example, agents log not just the issue but also the specific SKUs and quantities.”

Operational feedback loop

feedback_loop

“That detail is then passed back to operations to address problems at the fulfillment center”

Reported outcome

Response times dropped as conversations routed directly to the right agents, productivity improved through macros and unified data, and visibility expanded dramatically so managers could identify operational issues and agents received real-time accountability feedback.

Reported metrics

Response timeshave dropped

Agent productivityhas improved

Operational visibilityhas expanded dramatically

Reported stack

KustomerForethoughtAircallAgorapulseShopifyRechargeStripe

Source

https://www.kustomer.com/customers/smalls/

Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Response times dropped as conversations routed directly to the right agents, productivity improved through macros and unified data, and visibility expanded dramatically so managers could identify operational issues an…

What tools did this team use?

Kustomer, Forethought, Aircall, Agorapulse, Shopify, Recharge, Stripe.

What results were reported?

Response times: have dropped; Agent productivity: has improved; Operational visibility: has expanded dramatically (source-reported, not independently verified).

How is this customer support AI workflow structured?

AI handles repetitive inquiries → Route to right agent → BPO handles Tier 1 and 2 → In-house handles high-sensitivity → Issue detail logging → Operational feedback loop.