Your customer management is at a turning point
Companies are currently facing a turning point, particularly in sales, marketing, e-commerce and customer service: artificial intelligence can accelerate sales processes, personalise customer experiences and significantly reduce the workload on teams – provided it is implemented using the right approach.
Many of our clients are already achieving measurable business impact because they follow a central principle: use case before technology. This reflects our belief that AI only realises its full value within a specific business context.
Highly sought-after AI use cases in sales, customer service and e-commerce
Our AI solutions specifically address real-world business challenges and create measurable added value where processes, decisions and customer experiences can be optimised.
Here are five key areas where our AI solutions are making an immediate impact:
1) Sales & Revenue Growth
Focus: Boost revenue, empower the sales team, prioritise the pipeline.
Examples:
- Up- & Cross-Selling Agent
→ Systematically identifies hidden revenue potential and provides specific ‘next best actions’ for the sales team - Churn Prevention Agent
→ Identifies churn risks at an early stage and enables proactive customer retention - Smart Decision-Based Quoting
→ Prioritises quotation opportunities based on data and focuses resources on profitable deals - Apple CarPlay Sales Agent
→ Makes travel time productive through voice-controlled, data-driven visit preparation and documentation
2) Service Excellence & Automation
Focus: Efficiency, quality and scalability in customer service
Examples:
- Virtual Service Agent
→ Automates the entire ticketing process and significantly speeds up response times - Smart Triage Agent
→ Automatically prioritises and routes service enquiries so that critical cases are identified immediately - AI Service Agent
→ Responds to standard enquiries fully automatically and reduces the need for manual service work - Warranty Prediction Agent
→ Predicts warranty decisions and costs in order to quickly determine the appropriate service action
3) Field Service & Operations
Focus: Efficiency in operational processes and field service management
Examples:
- Smart Dispatching
→ Optimises resource planning, routes and resource utilisation in field service
4) Commerce & Customer Experience
Focus: Conversion, guided shopping and customer experience
Examples:
- Guided Buying im Webshop
→ Guides customers through complex purchasing decisions and increases conversion rates and basket quality
5) Data-Driven Sales & Planning
Focus: Transparency, management and data-driven decision-making
Examples:
- Distributor Demand Cockpit
→ Provides full transparency on demand, product range and distribution partner performance in a single dashboard - Smart Configuration / Quote Assistant
→ Speeds up complex product configurations through AI-powered suggestions and the codification of expert knowledge
How far have you got with your AI initiative?
Some companies are already leading the way with these and other use cases. However, reality also shows that many AI initiatives remain stuck in the experimental phase, without delivering any tangible business results.
The reason is rarely the technology itself.
Rather, it is the lack of focus on business value, use cases, data and architecture.
This is exactly where we come in with a special offering: Phaise 0.
In this series of workshops, we’ll work together over the course of just a few hours to develop a prioritised, actionable AI roadmap that provides clear answers to the following questions:
- Which use cases have the greatest business impact?
- What data and systems are required?
- What does the right architecture look like?
- What delivers quick wins, and what is strategically important?
- How do we achieve genuine buy-in across sales, marketing, commerce and service?
These are the four typical entry points for AI – and how Phaise 0 addresses them
Companies embark on an AI project from clearly distinct starting points. For each one, we offer a detailed step-by-step approach in Phaise 0. So that you can start from where you are today.
You already have specific AI ideas or planned projects – but no structured roadmap
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Case 1
Many companies today find themselves with a list of promising ideas: initial use cases, potential pilot projects, and suggestions from specialist departments or technology partners.
A typical challenge:
There is a lack of structured prioritisation: What delivers real business value?
What is feasible? What should be included in Phase 1 and what can be left until later?Phase 0 provides:
- Sorting and evaluating existing ideas
- Clear prioritisation based on business impact and feasibility
- Dependencies, data requirements, risks
- A workable roadmap rather than a loose collection of ideas
- Ideal if you already have a lot of material but haven’t yet decided on a direction.
You have a defined AI use case, but no implementation or architectural concept
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Case 2
A clear use case is on the table, often driven by a pain point in sales, service or commerce. However, the implementation is unclear:
- “What sort of architecture do we need for this?”
- “How do data, systems and processes interact?”
- “Which teams are involved?”
- “How do we minimise effort and risk?”
Phaise 0 provides:
- A concrete solution and architectural concept
- Data flow, interfaces, roles and responsibilities
- Technical roadmap and MVP path
- Clear success criteria and KPIs
- Ideal when a use case is urgent but the implementation strategy is lacking.
You would like to enhance existing systems with AI capabilities
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Case 3
Many companies want to enhance their existing systems – CRM, e-commerce, customer service, online shops, portals – with AI features, for example:
- Recommendation Engines
- AI Chatbots
- Agent Assist
- Lead Scoring
- Automation / Generative AI for content
Challenge:
How can AI services be integrated into the existing landscape in a modular, scalable and secure way?Phaise 0 provides:
- Architectural blueprints for AI extensibility
- Modular framework for integrating AI services
- Evaluation of tooling and system combinations
- Scaling and governance concept
- Ideal when AI is to be built on top of existing CX systems.
They already have AI technology, but no idea how it creates value
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Case 4
This scenario is becoming increasingly common:
Licences have been purchased and the tools are in place, but they are not being used and are failing to deliver added value.Common questions:
- “What is the best way to put this to good use?”
- “Which processes will really benefit?”
- “Where do we need to adapt data, roles or skills?”
Phaise 0 provides:
- Identifying suitable areas of application
- Maturity assessment for data, systems and teams
- Gap analysis and value prioritisation
- Roadmap for monetising existing technologies
- Ideal when AI is already in place but is not yet generating a return on investment.
AI in the context of customer service: Why now, of all times?
AI delivers its greatest ROI where hundreds of interactions take place every day: in direct contact with customers. AI-powered CX processes offer:
1. Significant, immediately visible business impact
Improvements have an immediate effect on conversion rates, the sales pipeline, average order value (AOV), time-to-resolution and customer loyalty.
2. A perfect data set
CX processes generate extensive user, interaction and transaction data – ideal for AI models.
3. Repeatable workflows = maximum ROI from automation
Lead scoring, product advice, routing, ticket handling, personalisation … AI learns from every cycle.
4. High variability = maximum benefit through pattern recognition
Every customer is different – AI can handle that.
5. Agents are relieved of some of their workload
Digital sales assistants, service bots and digital commerce advisors interact directly with your systems.
Why AI initiatives fail
Most AI projects fail not because of the technology, but because the fundamentals are missing.
1. Lots of ideas, no focus.
There are lists full of use cases, but no prioritisation based on value and feasibility. The result: no progress.
2. One use case, but no path forward.
The pain point is clear – yet data, architecture and responsibilities are missing. Proof-of-concepts (POCs) get stuck.
3. AI is meant to enhance systems, but the architecture cannot support it.
Without a modular framework, siloed solutions emerge that cannot scale.
4. AI tools are in place, but there’s no plan.
Technology is purchased but not utilised because clearly defined use cases are lacking.
The bottom line:
AI fails due to a lack of the big picture, not because of the algorithm.
Phaise 0 creates precisely this framework.
Our Phaise 0 approach: thinking about AI from a business perspective (rather than as a tool)
We combine business acumen, CX expertise, data know-how and architectural expertise. The result: a realistic, value-driven AI strategy that can be implemented immediately.
1. Identifying relevant use cases
We identify the processes that boost revenue, increase efficiency or improve the customer experience.
With clear success criteria: conversion? Costs? Time? Conversion rate?
2. Prioritise business impact and feasibility
Which use cases deliver quick results and secure sponsorship?
Which ones are strategically important? The result: a clear roadmap rather than AI hype.
3. Preparing data and architecture
Without a scalable foundation, there can be no sustainable use of AI. We analyse your data landscape, interfaces and CX systems and define a modular architectural model that seamlessly integrates AI.
4. Empowering people
Changes in customer management require user-centred enablement – to build trust, foster acceptance and deliver a return on investment.
What you’ll have at the end of Phaise 0
- Prioritised list of AI use cases
- KPIs & success criteria for each use case
- Data and architecture assessment
- Strategic vision for AI in CX
- Roadmap (90–180 days) with quick wins & architecture steps
- Governance and Enablement Framework
- Board-ready decision-making proposal
In short: everything you need to successfully implement AI. No risk, no ‘lighthouse’ projects, no technology hype.
FAQ – Frequently Asked Questions about Phase 0
What is Phaise 0?
Phaise 0 is a compact workshop-based approach in which you develop a prioritised, actionable AI roadmap for sales, marketing, commerce and service. We combine business impact, use-case prioritisation, data and architecture assessment, and clear next steps.
How long does Phaise 0 last?
The duration depends on the complexity of your organisation and the number of stakeholders. Typically, it takes 2–4 weeks.
The process comprises four structured workshop modules:
- Kick-off: 1–2 hours
- Workshop 1 – Use Cases: 4–6 hours
- Workshop 2 – Data: 4–6 hours
- Workshop 3 – Management & Technology: 4–6 hours
- Workshop 4 – Results & Final Concept: 1–2 weeks’ processing time (including analyses, architectural sketches, prioritisation & reviews)
All sessions can be held back-to-back, spread out or as a hybrid arrangement. The timeframe is deliberately compact so that you can quickly arrive at a decision-ready outcome suitable for presentation to the board.
When does Phaise 0 make sense for us?
Phaise 0 is suitable for companies looking to get started with AI, scale up their AI efforts or reorganise existing initiatives.
It is ideal if you:
- have lots of ideas but no clear priorities
- want to implement an urgent use case
- want to enhance existing systems with AI
- have AI technology but are not achieving a return on investment
We’ve already got a few AI ideas. Would Phaise 0 still work?
Yes. Phaise 0 is ideal if you have already gathered some initial use cases or project ideas but lack a structured framework.
We sort, prioritise and evaluate your ideas, and translate them into a clear, achievable roadmap that takes into account business value, architecture, data and effort.
What if we already have a specific use case but don’t know how to implement it?
Even then, Phaise 0 is the right place to start.
We clarify:
- What architecture is required
- Which data flows and systems are involved
- What the MVP path looks like
- What roles and responsibilities are needed
- Which KPIs define success
You’ll receive a comprehensive implementation and architecture concept tailored specifically to this use case — without over-engineering.
We would like to enhance existing systems with AI. Will Phaise 0 help us achieve this?
Absolutely.
If you wish to enhance your CRM, commerce or service systems with AI features (e.g. chatbots, recommendations, lead scoring, automation), Phaise 0 provides:
- a modular architecture framework
- integration and system recommendations
- prioritisation, feasibility and quick wins
- a scalable roadmap
This ensures that AI integrates seamlessly into your landscape — rather than building isolated solutions.
We have already purchased AI technology and licences. Is Phaise 0 still worthwhile?
Yes — in fact, particularly so.
Many companies already own AI software, but make very little use of it.
In Phaise 0, we define:
- where the technology really adds value
- which processes stand to benefit
- which data, processes or skills are missing
- how you can monetise your investment
Objective: to take AI off the shelf and translate it into real business results.
Which roles should be involved?
Typical examples include:
- Department leads (Sales, Marketing, Commerce, Service)
- Digital, data and IT managers
- Architecture teams
- Process managers
- Optional: Legal/Compliance (Trusted AI)
The broader the perspective, the more precise the roadmap becomes — but we deliberately limit the complexity.
What results do we obtain at the end of Phase 0?
You’ll receive a comprehensive package suitable for presentation to the board:
- A prioritised list of use cases, including KPIs
- Business impact and feasibility analysis
- Data and architecture assessment
- Vision for data and AI in CX
- A 90–180-day roadmap with quick wins
- Governance and enablement fundamentals
In short: everything you need to start implementation straight away.
Do we already need to have a data platform?
No.
Phaise 0 shows you where you stand, what gaps there are, and how you can gradually build up a database that is AI-ready — without any ‘big bang’ projects.
How much work will this involve for us internally?
Very manageable.
You’ll mainly be investing your time in the workshops and brief coordination sessions — we’ll take care of the bulk of the analysis, prioritisation and design.
How soon after that can we get started?
As a rule, work on the first steps of the roadmap can begin straight away.
Many customers launch their first MVP or quick win within 2–3 weeks of completing Phaise 0.
Does this depend on the vendor (CRM/Commerce/Service)?
No. We take a system-agnostic approach and integrate with your existing infrastructure (e.g. CRM, commerce, service, data platform). No. We take a system-agnostic approach and integrate with your existing infrastructure (e.g. CRM, commerce, service, data platform).
Discovery Call: Your strategic introduction to AI
During a free, no-obligation initial consultation, we will answer any questions you may have about our AI approach and discuss the process and timetable for a potential Phase 0.
Mail: sales@sybit.de
Tel.: +49 7732 9508-2000