What challenges did loveholidays face before AI implementation?

Customer service demand grew to as many as 3,000 contacts per day during peak periods. The existing on-premises approach made it difficult to scale booking and support workflows efficiently. The company needed to respond quickly to issues such as refunds, booking changes, and flight disruptions while maintaining a duty of care.

Source

GCPProductionEvidence: Medium50/100

loveholidays virtual assistants based on Dialogflow CX and Contact Center AI

Use case typeCustomer service automationUpdated Jun 13, 2026

loveholidays, a UK online travel agent, used Google Cloud Contact Center AI and Dialogflow CX to build virtual assistants for its customer service operation. The company needed to handle high contact volumes during peak travel periods, support sensitive travel issues quickly, and reduce the operational burden and cost of scaling human support.

Organization: loveholidays
Industry: Consumer & Food
Location: United Kingdom
Published: February 2024

Reported outcomes

Impact: Less than 50 seconds

Other quantified impact

Why do we believe this?Outcome claims, sources, and evidence checks

Normalized claim

Quantified impact: 10%

Google Cloud BlogFeb 21, 2024Blog postInferred claimMedium evidence strength

Within the first year, the virtual assistant handled 10% of customer service traffic.

Normalized claim

Quantified impact: 50%

Google Cloud BlogFeb 21, 2024Blog postInferred claimMedium evidence strength

The virtual assistants later handled about 50% of all traffic.

Normalized claim

Quantified impact: 50 seconds

Google Cloud BlogFeb 21, 2024Blog postInferred claimMedium evidence strength

Customers were connected to the virtual assistant in a fraction of a second, and chats were typically resolved in under 50 seconds.

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: loveholidays
Provider: GCP
Maturity: Production
Linked source: Google Cloud Blog

The company needed to handle high contact volumes during peak travel periods, support sensitive travel issues quickly, and reduce the operational burden and cost of scaling human support

Customer identity supportedSource describes one deploymentMaturity supported

Primary read

Use case focus

Showing 3 of 4

1Customer service automation
2Conversational AI
3Contact center modernization

loveholidays built a virtual assistant in Dialogflow CX on Google Cloud Contact Center AI to handle a portion of customer inquiries without human-agent involvement.
The team first used the assistant for simpler pandemic-era refund requests, then expanded intents as customer needs evolved.
The company later added more advanced Dialogflow CX capabilities, including short-term memory and visual flow maps, to manage more complex conversational journeys.
It also introduced a voice agent called Sandy to answer calls, identify caller intent, route calls, and automate some phone-based flows.
The organization uses interaction analytics to identify recurring customer issues and improve website content and API-driven information for travelers.

Technologies

Google Cloud Contact Center AI Dialogflow CX

The company reported saving £3 million to date.
Customers were connected to the virtual assistant in a fraction of a second, and chats were typically resolved in under 50 seconds.

Sources & evidence1

Evidence: Medium50/100Evidence strength