Consultancy Projects
Engage with CSA - Pilot/Consultancy Projects
1. AI Platform to Track, Flag and Predict your At-Risk Customers- In Real Time
Lead - Mohamed Zaki
2. Multimodal AI to predict your customer engagement in digital platforms
Lead - Mohamed Zaki
3. Service Business Model: A Capability Assessment
Lead - Andy Neely
4. Enterprise-level KPI for complex Services
Lead - Andy Neely
5. Turn Customer Experience Management (CXM) into a Competitive Advantage
Lead - Gautam Jha
Projects in the Past
What is the service business model capability assessment?
The DT BM assessment is a diagnostic tool designed to help you and the rest of your management team identify whether you have the right capabilities in place to innovate your digital twins’ business model. The assessment covers 50 sub-capabilities that are clustered under four main headings: (i) Value proposition, (ii) Value Capture, (iii) Value Network, (iv) Value Architecture, (v) Barriers.
What value does the Digital twins business model assessment deliver?
The assessment helps you to identify which capabilities and business model configurations are suitable for your digital twins business model. Our research shows that there are five main types of business models for Digital twins: i) Mission Asurers, (ii) Uptime Assurer, (iii) maintenance optimisers; (iv) strategic partners, and (v) Broker/orchestrators. Through this assessment, your team can identify your current position (be it laggard, adopter, or innovator) and help selecting the most fitting business model for your firm.
How long will it take to complete the assessment?
The DT assessment involves three phases: (i) an initial briefing to explain to those completing the assessment the background and the assessment materials; (ii) self-assessments: typically between 6-12 people are asked to complete their own assessment of the digital twins’ capabilities; (iii) group discussion and facilitated workshop. At the workshop, we review individual assessments, explore the reasons for differences of opinion and create a consensus assessment. This consensus assessment is then used as the input to an action planning discussion.
Lead Name: Erika Parn
What is conversational customer service analytics?
Our conversational customer service analytics tool is an AI-driven approach designed to help you identify personalised conversation styles which have a profound positive impact on the customer churn, loyalty and overall experience. The tool helps to identify customer profiles and recommends the use of conversation styles, which in particular addresses the customer’s emotions and therefore improve their emotional loyalty, affective experience and reduce churn.
What value does the conversational customer service analytics deliver?
Customer service interactions are often perceived to lack a personal touch and caretaking. In particular in text-based interactions such as live-chats or chatbots customers are frustrated because of impersonal, scripted and poor replies. Our tool builds on three-year long research and recent advancements in the field of natural language processing to help you to move away from frustrated customers and being able to provide a personal touch through the right choice of conversational style. The method has shown to enhance KPIs such as purchase intention, customer loyalty, reduced customer churn and customer experience.
How long will it take to complete the analysis?
Applying the conversational customer service analytics tool involves three phases: (i) relevant textual conversational data from the customer service context needs to be shared; (ii) we apply our framework and state-of-the-art natural language processing (NLP) techniques to analyse the textual data; (iii) we provide and explain in a meeting the outcomes of our analysis in form of a report. The overall project duration is between 12-16 weeks depending on the availability of the data.
Lead Name: Jan Blümel