Customer Delight
In addition to existing dimensions such as reliability and responsiveness, in the Digital World Customer delight is augmented by the multi-channel interactions that take place for e.g., the customer first interacts with the brand on the website and their views of the brand are shaped by the ease of use, information access and knowledge. This is often followed by interactions that might take place through social media tools (experience shared by friends and family) and the broader network, influencers who shape the thinking of a brand. This is then followed by physical interaction at the store with the expectation that store personnel offer greater insights than what has already been gained by the Customer from the previous steps. It is expected that each of the above interactions drive exceeding expectations for the Customer to be delighted.
Technology is at an interesting inflection point where we are moving from a multi-channel experience to a possible immersive experience in the metaverse where real-life is mirrored in the metaverse.
The origins of the name “metaverse” is in the early 1990’s from a science fiction novel Snow Crash. It is a combination of “meta” and “universe”. metaverse creates an immersive and three-dimensional experience in the virtual world for Consumers by using advanced virtual reality technology (Sheridan et al., 2021).
As explained by Bloomberg Intelligence (Wheatley & Bakthavatchalam, n.d.) the metaverse revenue globally could grow to somewhere between $800B and more than a trillion dollars, making it the next big tech platform. Sensing this potential, all industry verticals are exploring metaverse and cryptocurrencies/NFTs with blockchain technology to make their mark in the virtual world. The metaverse is currently growing through the hype cycle of maturity as explained below in Figure 1; Evolution cycle of the metaverse:
Figure 1. Evolution cycle of the metaverse
Gartner report states that the metaverse is a virtual digital ecosystem that is immersive but siloed. There is ongoing development to create communication protocols that will make the siloed metaverses as interoperable. The metaverse is powered by content which can seamlessly intersect and co-exist with the physical world. The content is created in a collective, persistent, interoperable, and decentralized mode so that it can merge into the spatially indexed and organized content of the real world.
By 2026, approximately 25% of the consumers will spend approximately sixty minutes in a day in the metaverse for all their online activities related to retail purchasing, gaming, banking, social interactions, and entertainment. BCG, JPMorgan, and McKinsey estimate the market size for metaverse to be between $500bn to $1Tn+ by 2030. As per the study “For Meta or Worse” 66% of consumers are looking forward to the convergence of real and virtual world for their day-to-day interactions to enrich their lives as explained in the “Promise and perils of the metaverse”
Since metaverse is focused on the virtual world it often requires VR and AR headsets to engage. It is envisaged that in the foreseeable future metaverse becomes another channel in the omni channel experience route for the Customer. Several brands have already started engaging in the metaverse using NFTs, virtual events and selling and buying of virtual real estate.
This book chapter uses Grounded Theory and Framework Analysis Technique for verifying the impact of metaverse on Customer Experience and Delight. Grounded Theory helps to generate a theory from the qualitative data collected which has been analyzed systematically. As the name suggests, the theory is grounded in the data collected by the researcher. Grounded Theory can help to analyses the patterns of relationships hidden in the data and transcripts. Framework Analysis is a Qualitative Technique which is used to get feedback from the Users who implement the metaverse as well as use it. Framework Analysis provides a “Systematic Approach” for qualitative data analysis of Consumer experience in the metaverse. It scientifically helps to analyze interview transcripts to a easy and analyzable format as explained in Figure 2: Research Methodology