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Belgium 20-10-2026 Squad Only Virtual English

Deciding What Runs Where: Cloud, Edge, On-Prem, or Hybrid; How to place workloads based on performance, cost, sovereignty, resilience, and AI requirements.

Cloud decisions are becoming more selective. The challenge is deciding where each workload should run based on cost, performance, control, resilience, sovereignty, and business need. Three pressure points usually drive the decision. - Cost visibility becomes harder when usage grows across cloud services, data platforms, and AI workloads. - Performance and latency matter more when systems need fast access to data or support operational processes. - Sovereignty and resilience become critical when data location, continuity, vendor dependency, and exit options enter the discussion. The working question is simple: how do we place workloads where they create the most value while keeping the hybrid landscape manageable? If these trade-offs are on your agenda, let’s compare how others are handling similar choices.

Belgium 10-11-2026 Squad Only Virtual English

Choosing the Right Data Platform Without Creating New Silos; How to balance speed, flexibility, semantics, governance, and long-term maintainability.

Data platforms are meant to simplify access and support better use of data. The challenge is choosing and governing the platform landscape in a way that creates consistency, reuse, and long-term value. Three pressure points usually appear. - Platform choice becomes difficult when teams have different needs for speed, flexibility, cost, and control. - Business meaning needs protection: customer, revenue, product, risk, and FTE need shared definitions across tools. - Ownership and governance need to be clear, so platforms grow with accountability and discipline. The working question is simple: how do we give teams the data capabilities they need while keeping the platform landscape understandable, governed, and reusable? If these questions are familiar, let’s compare approaches with others facing the same data landscape.

Belgium 13-11-2026 Squad Only Physical English

Building the Business Case for New IT Capabilities; How to justify investment when value is strategic, shared, or only visible over time.

Many IT capabilities are essential and difficult to fund through a simple project ROI. The challenge is showing why architecture, governance, resilience, cybersecurity maturity, data foundations, and AI readiness deserve investment before the gap becomes expensive. Three pressure points make the case harder. - Shared value means the benefit often sits across several teams, while the budget sits in one place. - Timing creates friction because the cost is immediate while the value appears over time. - Risk translation is needed so business and finance leaders understand the consequence of delaying the investment. The working question is simple: how do we turn foundational IT capabilities into credible investment cases that link cost, risk, business value, and future flexibility? If you are building these cases internally, let’s compare how others are positioning value, risk, and timing.

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How ticket automation helped Lush reach a 60% first contact resolution rate

Global handmade cosmetics brand Lush was hesitant about automating their support — but needed to clear their inbox of FAQs and give agents more time to connect with customers. Here’s how they went from support automation skeptics to AI enthusiasts.

Lush at a glance

The customer

Lush is a global cosmetics brand offering fresh, handmade beauty products.

The market

HQ’ed in the UK, they have branches in 21 countries — and stores operate in additional regions under franchise.

The support team

170 agents provide support in 15 languages to Lush customers around the world.

The channels

Customer care is available 7 days a week via phone, SMS, and email.

The situation

Lush needed to scale their support to meet growing demand — without growing their customer service team.

The solution

Ultimate’s ticket automation solution and a seamless integration with their existing CRM: Zendesk.

Getting started with Ultimate

Customer-centricity is at the heart of how Lush operates. That’s why they started out as support automation skeptics. “We’ve always resisted too much automation because we never wanted to replace personal interactions,” says Naomi. But once they saw the substantial effort ticket automation would save them — giving agents more time to engage in meaningful conversations with customers — the support team soon became AI enthusiasts.

It took just 16 days for Lush to go live with ticket automation, and on his first day Marvin (as the team named their bot) answered 37% of tickets. But Lush’s support department doesn’t measure success by traditional efficiency measures. Instead, they focus on what customers are saying. In the week after launching, despite higher numbers of complaints over Black Friday and delivery disruption due to UK Royal Mail strikes, CSAT was at 93%.

Get started with automation

“With the pandemic and now a global recession, we’re not in a position to make our Customer Care team bigger and bigger. So we needed to make agents’ jobs easier by taking away the repetitive questions.”

Naomi Rankin
Global Customer Care Manager, Lush

First contact resolution rate: 60%

Minutes saved per ticket: 5

CSAT score: 93%

AI use case spotlight: freeing their inbox of FAQs

The support team in UK and Ireland was already using Zendesk macros (prepared responses) to answer FAQs, but agents were still swimming in repeat requests.
Lush went live with 4 intents to cover their most repetitive queries: sales and discounts, donations, order dissatisfaction, and discontinued products.
With Marvin taking care of common customer questions, the team reached a 60% first contact resolution (FCR) rate — giving agents more time to work on complex cases that require their skills.

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AI use case spotlight: scaling support without scaling the team

Lush’s support department was struggling to keep pace with rising volumes as the company continued to expand, but hiring additional agents wasn’t an option.
As well as deflecting FAQs, Marvin can request customer information upfront and add tags and labels to incoming tickets, giving agents the context they need to solve issues faster.
These efficiency gains save Lush roughly 5 minutes per ticket and 360 agent hours each month — savings that free up their support team to dedicate more energy to meaningful customer interactions.

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The success story

Seamless Zendesk integration

Our ticket solution fits right inside Lush’s existing tech stack, so personalization isn’t lost with automation and there’s no risk of data silos.

Multilingual

For a global business like Lush, multilingual support is a must — luckily, our industry-leading conversational AI can speak 109 languages.

Intelligent triage

Automatic ticket tagging and pre-filling makes agents’ jobs easier and removes the possibility of human error: meaning accurate data and reporting.

Easy to train and maintain

It took just 16 days for Lush to go live with ticket automation and the team can continually iterate to improve the bot’s performance.

Next on their automation journey

Building on the success of their English-language bot, the team is aiming to launch ticket automation in German next. After that, Lush plans to localize their automated ticket support in other English-speaking regions such as Australia. Eventually, Naomi wants to have bot managers taking care of ticket automation in every region Lush operates in.

Technologies

Ultimate: Ticket Automation Zendesk: A CRM Platform

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