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Bayview Technologies modernised a fragmented, chat-dominated contact centre by adopting Avaya Experience Platform as a unified cloud-based foundation for channels, routing and operational insight. The company’s reported results show why the project was about customer experience and self-service—not simply replacing telephony: chat represented 75% of contacts, its bots handled about 16,000 conversations a day in five languages, and those chatbot services achieved 75% first-contact resolution as of October 2022.
Why Bayview had to change its contact centre
Bayview is an IT-enabled business-process outsourcer serving global companies with customer support, back-office and IT services. It operates from Hong Kong, Taiwan and Gibraltar, with a wider presence across Asia and Europe. Some work involves processing payment requests across territories and languages, so a delayed or misrouted contact can affect a customer’s transaction directly.
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Rapid growth left Bayview with separate tools for email, voice and SIP, and web contacts. That fragmentation made it difficult to see queue conditions and contact flows as they changed. Contact-centre strategic lead Nigel Mansfield described the starting objective as gaining “a real-time understanding of what’s happening in the contact centre” while reducing operating cost without adding headcount.
The channel mix made the problem unusual. Bayview reported that 75% of contacts were chat-based, creating a requirement for an enterprise-grade chat engine rather than a voice-first system with chat added as an afterthought.
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What Bayview selected
Following an evaluation, Bayview selected Avaya Experience Platform. The case study says the platform met the required functions and anticipated contact volumes. Its value was the combination of channel handling, routing and operational visibility in one environment.
Unified channels and blended skills
Agents could blend voice, chat and email skills instead of being confined to a single channel or separate queue. That allows staffing to follow demand: chat capacity can be increased during a digital spike, while voice-skilled agents remain available for contacts that need a conversation.
Real-time operational insight
Avaya’s omnichannel view showed how customers moved between channels during demand spikes. Managers could see queue and flow changes while they were occurring, rather than reconstructing them later from disconnected reports.
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- Enables high speed call handling through support of up to three 12 or 24 button Expansion Modules.
- Delivers high definition audio that can increase productivity by reducing fatigue and provides easier to understand multiparty calls through the wideband audio codec in the handset and headset.
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- Simplifies call control on the display using softkeys for everyday functions such as transfer conference and forwarding
Integration for chat analysis and AI
Bayview used APIs to analyse chat topics and sub-topics and began adding its own AI suite. This approach treats the platform as an orchestration layer: conversation data can inform routing, automation and service improvement without requiring every capability to come from one vendor.
How the customer experience changed
More issues resolved without an agent
As of October 2022, Bayview said its chatbot services handled about 16,000 conversations per day in five languages and achieved 75% first-contact resolution. “First-contact resolution” here refers to those chatbot services, not to every contact across Bayview’s operation.
Shorter effort for routine requests
Bayview calculated that customer conversations took one-third of the time an agent would need for the same task. That benefit comes from automating repetitive interactions, not from asking agents to work faster on complex cases.
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Agents focused on complex work
Mansfield said the aim was to remove pointless tasks until people handled mainly complex cases. Because that strategy intentionally leaves agents with harder work, Bayview did not use average handling time as its primary success target.
Reported outcomes and what they mean
| Measure | Bayview’s reported figure | Qualification |
|---|---|---|
| Chat share of contacts | 75% | Described by Nigel Mansfield in a 2023 Computer Weekly case study; reflects the operation at the time of the interview. |
| Chatbot conversations | About 16,000 per day | Bayview figure as of October 2022, across five languages. |
| Chatbot first-contact resolution | 75% | Applies to those chatbot services as of October 2022, not necessarily the whole contact centre. |
| Time for a customer conversation | One-third of an agent’s equivalent time | Bayview calculation reported by Computer Weekly; the methodology is not independently audited in the case study. |
| Total cost | Halved over three years | Claim attributed to Mansfield; it is not presented as an independent audit. |
The cost claim should therefore be read as Bayview’s own assessment of its omnichannel route, not as a universal return-on-investment benchmark. Results will vary with language coverage, automation quality, contact complexity, labour costs and integration effort.
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Why contextual omnichannel routing matters
In a conventional setup, a customer who starts in chat and later calls may be treated as a new case. Contextual routing aims to carry the interaction history and intent into the next step, directing the contact to an appropriately skilled agent or automated flow.
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For customers
- Less repetition when moving from a bot or chat to voice.
- Faster access to an agent familiar with the issue, language and required process.
- More consistent service when demand shifts between channels.
For agents
- Conversation history and topic data can be available at hand-off.
- Skills can be blended across voice, chat and email instead of managed as isolated silos.
- Suggested text and fulfilment routines can reduce routine composition and lookup work.
For operations teams
- Real-time queue and flow information supports staffing decisions during spikes.
- Topic and sub-topic analysis identifies where self-service or process changes will have the greatest effect.
- Routing rules can be refined using observed customer journeys rather than assumptions about channel preference.
Bayview’s planned next steps included contextual routing, suggested text, fulfilment routines, further cloud migration and video. The case study describes these as plans; it does not establish that every item was subsequently delivered.
What other chat-heavy BPOs can learn
Start with visibility, not a feature checklist
Bayview’s transformation began with fragmented tooling and limited real-time understanding. A similar operation should first map queues, transfers, repeat contacts, channel switches, language demand and the work agents perform after a bot hand-off.
Design around the dominant channel
When chat is the majority channel, the platform must support concurrency, bot escalation, transcript context, language handling and reliable integrations. A voice-led design with a basic chat widget will not address the operational bottleneck.
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Measure resolution and effort alongside speed
Average handling time can reward premature transfers or rushed interactions. Bayview instead emphasised removing pointless work, self-service and the ability to reserve agents for complex cases. Useful measures include first-contact resolution by channel, containment with successful completion, repeat-contact rate, transfer rate, customer effort and agent time spent on non-value-adding tasks.
Use APIs and internal AI where they add control
API access lets a BPO connect topic analysis, knowledge, fulfilment and its own AI services to the contact-centre workflow. Governance still matters: organisations need language-level quality checks, escalation rules, transcript controls and monitoring for incorrect automation.
Plan for spikes and regional variation
Bayview serves customers across Asia and Europe and handles multilingual, territory-specific work. Capacity planning should test sudden volume increases, language queues, payment-process dependencies and the hand-off from automation to human support.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.A practical decision framework for replacing a contact-centre platform
For a similar evaluation, compare candidates on the capabilities that shaped Bayview’s decision:
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- Real-time visibility into queues, contacts and cross-channel journeys.
- Enterprise-grade chat, bot escalation and omnichannel context.
- Contextual and skills-based routing.
- Self-service orchestration and first-contact-resolution measurement.
- APIs for analytics, fulfilment and internal AI.
- Blended workforce management for voice, chat and email.
- Scalability during demand spikes and across languages.
- Cloud migration options, security and integration with existing voice or SIP services.
- Total operating cost, including implementation, automation maintenance and training.
The central test is not whether a platform has the longest feature list. It is whether supervisors can understand demand in real time, customers can move between channels without losing context, and agents spend their time on work that genuinely needs human judgement.
Bottom line
Bayview’s case shows a contact-centre modernisation driven by experience and operational control. Avaya Experience Platform unified channels, routing and insight for an operation in which chat made up three-quarters of contacts. The company’s October 2022 figures—about 16,000 multilingual chatbot conversations a day and 75% first-contact resolution for those services—illustrate the potential of automation when it is connected to the wider customer journey. The transferable lesson is to build visibility, context and self-service around the real channel mix, then judge success by resolved customer needs and reduced pointless work rather than handling-time reduction alone.
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