Lotte Shopping's turnaround math is operating leverage — profit growth squeezed from flat-to-falling sales — and service operations spread across department stores, marts, e-commerce and home shopping are exactly where duplicated cost hides; a single agentic frontline that handles orders, deliveries, memberships and returns across every format converts scattered service desks into one measured, shrinking cost line.
Lotte Shopping operates department stores, Lotte Mart, e-commerce (Lotte ON), home shopping and cinema businesses, and has spent recent years restructuring — closing underperforming stores and cutting costs to restore profitability.
Public factLotte Shopping's 2025 results showed operating profit rising double-digits on slightly falling sales, with e-commerce losses narrowing sharply — a turnaround driven by cost discipline rather than growth.
Public factKorean retail is squeezed between Coupang's logistics dominance and Naver's commerce platform, forcing incumbents to compete on curation and omnichannel service rather than delivery speed alone.
Public factService volume spans formats — department-store memberships, mart delivery slots, Lotte ON orders, returns across all of them — likely handled by separate teams with separate systems.
Reasoned inferenceL.POINT/L.PAY membership questions cut across every format, making cross-format context the recurring service failure.
Reasoned inferenceSeasonal gift-set peaks (Chuseok, Lunar New Year) likely multiply contact volume against fixed staffing.
Seller hypothesis — validateValidate with the account team before outreach: Actual service volumes and desk structures by format · Lotte Group AI initiatives (Lotte Innovate) and any group-platform mandates · OMS and logistics-system integration readiness across formats · Seasonal-peak volume multiples and surge-staffing costs
Limited internal ability or appetite to build the core platform — strong candidate for the packaged solution
Evidence: Lotte Shopping is a restructuring retailer whose technology runs through group IT affiliates without any public conversational-AI platform program; a turnaround P&L funds proven cost-out tools, not infrastructure builds — this is a clean governed buy with group-IT integration partnership.
Why they won't build the full stack: A retailer cutting its way back to profitability cannot fund a multi-year AI-platform build against Coupang's scale; every quarter of internal development is a quarter of duplicated format-level service costs the turnaround math cannot afford — buying proven capability converts service cost to usage pricing now.
Lotte Shopping's 2025 results showed operating profit up double-digits to the mid-500-billion-won range on slightly declining sales, with e-commerce losses narrowing more than 60% — a cost-discipline turnaround the market has begun rewarding.
GTM implication: Pitch service consolidation as the next line item in a cost story that is visibly working — operating leverage the group already knows how to celebrate.
Lotte Shopping continues restructuring underperforming domestic formats while growing overseas (notably Vietnam) operations.
GTM implication: A consolidated service layer scales down with domestic rationalization and extends to overseas formats — matching both directions of the strategy.
| Workflow | Why it matters here | Value | Complexity | Speed | Channels |
|---|---|---|---|---|---|
Order and delivery service desk Status, reschedules and returns resolved in-conversation with live OMS data; contacts per order fall measurably. | Delivery-exception and order-status contacts are e-commerce's structural volume, and Lotte ON's loss-narrowing depends on cost per order falling. Friction today: Status questions span Lotte ON, mart fulfillment and third-party sellers; reschedules need logistics handoffs; peaks melt queues. | KakaoTalkApp chatVoice | |||
Membership and L.POINT service line Membership servicing resolved once with cross-format context; the loyalty program feels like one company. | The loyalty stack spans every format; membership friction erodes the cross-format shopping the group's strategy depends on. Friction today: Point balances, tier questions and pay issues route differently per format; context is lost between them. | App chatKakaoTalkVoice | |||
Seasonal-peak surge desk Elastic absorption of seasonal peaks at consistent quality, without surge-hire economics. | Gift-set seasons compress a quarter's contact volume into weeks; surge hiring costs peak exactly when margin matters. Friction today: Chuseok and Lunar New Year peaks force temporary staffing that degrades quality when volume is highest. | VoiceKakaoTalkApp chat |
Voice & channel orchestration, telephony, conversational execution, session/state, routing, integration build. Capability coverage validated during implementation.
API access to these systems is the critical-path dependency.
Identity-bound sessions, policy-bounded actions, 100% audit logging, human approvals at defined points, in-tenant intelligence.
All figures are modelling estimates from the labeled inputs above — nothing here is customer-provided yet. The pilot's first job is replacing these assumptions with Lotte Shopping's measured baseline. Package price covers implementation only; recurring usage billed separately.
Why this package for Lotte Shopping: Order/delivery service plus membership servicing span the group's formats over shared OMS and CRM integrations — Scale scope with clear consolidation economics for a restructuring retailer.
Packages cover implementation and integration only. Recurring costs are billed separately: Tilicho Labs platform usage (~$0.15/call-min indicative, usage only), Google Cloud consumption, telephony/carrier charges, managed operations, and support & optimization. No package includes unlimited usage.
“The turnaround is a cost-discipline story; consolidating five formats' service operations into one measured frontline is the next restructuring chapter — visible in the operating-profit line the market is finally rewarding again.”
“One governed agent layer above OMS, loyalty and logistics systems serves every format — replacing scattered format-level service stacks with an architecture the group can actually consolidate on.”
“Seasonal peaks and format-duplicated desks are your structural inefficiencies; elastic cross-format capacity removes both without another round of headcount surgery.”
“Loss-narrowing lives on cost per order; cutting contacts per order and resolving the rest automatically is the service-side contribution to the breakeven path.”
“PIPA-aligned handling with full logging across formats — customer-data governance actually improves when five service stacks become one governed layer.”
“The pilot measures contacts per order and cost per contact against your own baselines by format; consolidation savings compound as each format migrates.”
Written from this account's own research — the strategic signal, the capability gap, the entry workflow, and the modelled economics — not a mail-merge template. Pick the moment and the persona, edit anything, then copy or open in your mail client.
Customer-safe by construction: drafts are composed only from customer-facing fields. Account tier, build-vs-buy classification, priority score, internal routing, and partner-commercial detail are not inputs to the composer, so they cannot appear in a draft. Money figures are always framed as modelled from the customer's own volumes. Read before sending — you own what goes out.
Korea's retail conglomerate is mid-turnaround — profitability restored through restructuring while sales still shrink — running department stores, discount marts and the loss-narrowing Lotte ON e-commerce arm, with service volume spread across formats and a P&L that rewards every removed cost.
Cross-format service audit with group CX leadership: map current desks and volumes by format, then pilot the order-and-delivery workflow on Lotte ON ahead of the next seasonal peak.
Entry: Order and delivery service desk (Lotte ON and mart fulfillment) · Scale package · 10–14 weeks to production across priority workflows. Human fallback throughout; success thresholds agreed before build.
Start the pursuitResearch-based priority-account universe assembled from public information, market scale, communication volume, and solution fit. This is NOT an authoritative list of top Google Cloud customers; existing Google Cloud relationships are noted only where publicly reported. Validate every account with the account team before outreach.