In part one, the beginnings, I traced the emergence of the Customer Engagement Platform (CEP). It’s an evolution from CRM as a system of record to a platform that still provides all the functional support but offers so much more. An effective CEP has the ability to orchestrate relevance dynamically throughout all customer interaction journeys. So what is under the CEP’s hood?
The 8 layers of the CEP
I’ve depicted the CEP along the lines of a Maslow hierarchy of needs pyramid. The apex represents the outcome, of a dynamically orchestrated and delivered experience throughout all customer interaction journeys. To achieve this desired state a customer engagement platform must be developed. The CEP consists of eight critical and integrated elements or technology layers, which together culminate in the desired customer experience outcome.
I’ll start at the base of the pyramid.
- Essential ‘plumbing.’
- Cloud infrastructure – from hyperscalers such as Amazon, Google, IBM, Microsoft, or the vendor’s own cloud infrastructure. This will also include cloud Platform-as-a-Service (PaaS) to enable enterprise developers to create their own extensions and provides the Software-as-a-Service (SaaS) enterprise applications from the vendor or vendors.
- Mobile communications capabilities enable remote or mobile working and enable in-app messaging.
- APIs to connect applications such as back-office ERP, financial and logistics systems.
- Microservices – reusable digital building blocks for ‘last mile’ application extensions or routines. They are also essential for rapid adaptations to meet changing circumstances, especially during the pandemic.
- Unified customer data management & dynamic profiling – ingestion and synthesis of customer-related data from all source systems. When synthesized in real-time, historical and live interaction data provide context that AI algorithms feed on to trigger the most relevant response. This can also be augmented with 3rd party data to enrich customer profiles and increase the likelihood of anticipating what customers need. Quality and trustability are essential, so this must include mechanisms and processes for data cleansing and quality control. Modern enterprise-CDPs (customer data platforms) can ingest a wide variety of customer-related data, including product, stock availability, location data, preferences, and behavioral data, in addition to basic demographic/firmographic and transaction data. They may contain a graph database to identify a complex array of relationships and their relative strengths between multiple attributes., revealing otherwise hidden relationships. The essential plumbing and data layers provide the foundation for a CEP.
- Security and compliance mechanisms – to protect data from cyber breaches and to meet regulatory requirements:
- general or regional such as – GDPR – EU’s General Data Protection Regulations, CCPA – California Consumer Privacy Act, LGPD – Brazil’s Lei Geral de Proteção de Dados, POPI – South Africa’s Protection of personal information.
- Industry-specific like – HIPAA – Health Insurance Portability and Accountability Act of 1996, for the US health sector covering patient records; PCI DSS – Payment Card Industry Data Security Standard in financial services.
- Irrespective of regulatory requirements, managing customer data is fundamental to a firm’s reputation and customer trust.
- Customer communications and content management/digital asset management – content comes in many forms, from simple documents to rich content types such as interactive-video. It forms an essential part of the customer experience. Modern CCM/DAM applications are evolving into digital experience platforms (DXM) and are a valuable subset of a CEP. It also provides a foundation for personalization.
- AI/analytics and Robotics Process Automation (RPA) – AI in the form of machine learning (ML) and natural language processing (NLP) provides event triggers and insights to generate a contextually relevant response.
- In the early days, just a few years ago, AI was often localized to support a specific application, such as marketing, sales, or service. The most advanced have AI embedded throughout the platform with a central ‘brain’ to make sense of all the millions of digital signals from customer interactions and external sources, such as social media platforms. The more advanced AI environments combine customer journey analytics and AI to surface behavioral patterns and provide recommendations to make the journey easier for each customer. AI is essential to trigger the most relevant response during the customer journey and identify behavioral patterns that would otherwise be hidden from view. It must, however, be used responsibly.
- RPA is often used to automate repetitive, time-consuming manual tasks. When end-to-end processes are optimized and automated, we expect RPA to be of less importance. Still, for now, it provides a good digital bandaid for imperfect processes and improves accuracy. Repetitive manual tasks, such as data entry are notoriously inaccurate. Robots are more reliable and don’t get bored.
- Industry-specific variants – different industries often have their own business rules, workflows and practices, and business taxonomies. The major vendors have different variants to support specific industries and sectors.
- Collaboration platform – to enable employees to collaborate across the enterprise, using enterprise social network without leaving the application they are currently using – messaging, email, phone, and video conferencing, as appropriate. The collaboration platform can also be used to engage with suppliers, partners, and customers.
- Functional support – The enterprise applications that enable the front office employees to perform their essential work. This may include marketing, sales, service automation, e-commerce, and subscription billing systems. These, together with the industry variations, and collaboration platform support employee engagement and provide the tools to respond appropriately to customers.
These eight integrated technology layers constitute the customer engagement platform that ultimately enable dynamic orchestration of the customer experience.
CEPs must be connected to operational systems
Unless CEP’s are connected to back-office operational systems and data sources, they will only provide very limited value. Customers expect a joined-up experience and find it irksome if they are passed between departments to resolve their queries. Omnichannel customer engagement depends on this level of connected data, intelligence, and automation.
Most businesses will already have some of the technologies contained within a CEP, often from multiple vendors. However, they will still face some tough choices. Do they consolidate on a single platform in which case what of their current technologies should they keep or retire? How well do those technologies integrate and to what extent might they support a unified CX environment? I shall explore this in part three.