As they strive to implement commerce everywhere models, retailers are adapting their offerings to drive real-time contextual customer experiences
To provide an empathetic level of customer experience, companies need to have the ability to deliver empathy at scale
Retail commerce platform, and analytics foundations driven by artificial intelligence and machine learning will be central to executing empathy at scale
"Commerce Everywhere" Business Models Rely on Real-time Contextual Experiences
Customer experience personalization isn't just about the consumer making a purchase — consumers expect individualized support throughout the entire customer journey, from initial engagement to customer service. Organizations are therefore facing increasingly complex challenges as they look to meet customers where they want, when they want and how they want. Leading organizations now recognize that customer experience is a key differentiator.
In the retail industry, 90 percent of organizations globally feel the pressure to evolve to experience-based business models. Retailers are going beyond "segment of one" through real-time contextual experiences. According to IDC's 2019 Global Retail Innovation Survey, 20 percent of retail companies adopted a real-time contextual customer journey model in 2019, compared to 2 percent in 2017 and 5 percent in 2018.
Businesses are striving to implement commerce everywhere business models that meet increasingly demanding customer expectations. They are also adapting their offerings to facilitate real-time contextual customer experiences, integrating them into the extended retail value chain.
The engagement and experience continuum goes from the lowest level of indifferent (experience) to impersonal, targeted and personalized (experience), and finally to empathetic experience. To reach the empathetic level, retailers have to deliver what IDC calls empathy at scale. This embraces and addresses the so-called "three Cs" of empathy at scale — consent, conversations and customer journeys :
Consent : focusing on data privacy and regulatory compliance, and how these impact marketing operations and personalization to treat customers more sensitively and avoid withdrawal of consent
Conversations : moving interactions with consumers from a transactional focus to one that can create contextually relevant engagements
Customer journeys : implementing personalized and automated customer experiences leveraging end-to-end process convergence-based system integration
The "future of the customer" requires a fundamental shift in how organizations view the process and nature of engagement with customers — recognizing the unique aspects of each customer and the elastic nature of the relationships with them.
Executing an empathy at scale approach is a long-term and resource-demanding effort. Achieving the highest level of customer experience personalization is a huge challenge for retailers. The major constraints include improving innovative customer loyalty programs and defining new key performance indicators to measure customer experience. The retailers continue to face the need to select useful data and integrate data silos (cited by 30 percent of respondents in IDC's 2019 Global Retail Innovation Survey).
Nowadays, companies can dynamically collect data from a number of consumer interfaces, aggregating and transforming it, and delivering real-time contextual experiences. By having more customer data (both historical and contextual) and a higher technology level to appropriately employ this data, retailers can meet and predict customer needs more effectively. Contextual and highly personalized interactions can transform customer engagement, driving overall satisfaction and increasing trust.
Executing this approach requires retailers to allocate adequate investments to customer experience-oriented Artificial Intelligence (AI) / Machine Learning (ML) analytics capabilities. Importantly, they should frame these investments within the broader implementation of what IDC calls a retail commerce platform. This platform comprises four core capabilities — customer experience services, commerce services, order fulfillment services and content optimization services — along with embedded AI / ML analytics foundations. At the same time, end-to-end security services and open application program interface–based development and integration services encompass the entire set of platform services.
Being a foundational component of customer experience and commerce platforms, AI / ML analytics should be leveraged across marketing, service, commerce, and product and service innovation. It is therefore important for retailers that they aim to achieve customer experience personalization at scale to better select, collect, and manage customers' consolidated records and real-time contextual data streams by:
Breaking down internal data silos among existing departments and functions in the retail organization
Integrating and enabling the platform capabilities by leveraging a solid ecosystem of strategic partners, such as information technology vendors, business process management providers, systems integrators, consumer packaged goods companies and even other retailers open to co-innovation
To learn more about the importance of executing an empathy at scale approach through a retail commerce platform, read the IDC Vendor Spotlight, titled The Path Toward Empathy at Scale
Click here to understand how business process management providers can support your organization in executing an empathy at scale approach.
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Retail; WNS Triange
08 November 2022
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