Tech is everywhere. It has become a ubiquitous part of modern life, with smartphones acting as digital Swiss Army knives that serve as communication devices, internet browsers, and banking platforms, etc., all rolled into one.
Meanwhile, smart assistants like Google Home and Amazon Alexa are helping to redefine standards for convenience in the home, enabling users to control the level of lighting in their living room, set their burglar alarm when heading out, or add items to their shopping list, simply with the power of their voice.
With all this technology constantly changing how we see and interact with the world, people are understandably eager for other digital devices and services to provide experiences that are personalised to their individual needs.
After all, according to a McKinsey report titled: ‘The value of getting personalisation right’, 71% of consumers expect companies to deliver personalised interactions, while a further 76% say they get frustrated when this doesn’t happen. It seems, therefore, that personalisation is no longer just a ‘nice to have’, but something that customers demand, and if businesses are not able to provide these experiences, they will simply look elsewhere. This trend of greater personalisation has led to the birth of the ‘experience economy’, which has seen businesses placing increased focus on using digital technology to offer more unique and personalised experiences, not only for the benefit of customers, but for employees also. After all, tailoring the technology that workers use on a daily basis allows them to carry out their roles more effectively and efficiently than ever before.
Given the rise of the experience economy, those companies that take the time to fine tune the personalised experiences that they provide will likely reap the rewards of their efforts and, as such, organisations must make the trend a central part of their digital transformation strategy.
Conversational AI
As mentioned above, the experience economy is not a phenomenon that is limited only to providing personalised experiences to individual consumers. Businesses are also keen for the technology used to power their key processes to become more tailor made to their needs, thereby giving employees the tools needed to carry out their roles more efficiently.
There is a wealth of technologies now available to businesses who want to improve digital experiences, both for their workers and customers. Artificial Intelligence [AI], for example, is enabling companies to enhance their customer support, through advancements like conversational AI.
This is giving organisations the ability to automate low-value/high-volume customer queries that they receive, alleviating the burden on human agents and providing customers with 24/7 support, meaning their query can be answered more quickly. Not only does this lead to increased customer engagement, being that customers are more likely to return if they had a positive experience, but also greater satisfaction with the service. On top of this, human agents who are often forced to spend much of their time manually responding to queries can be freed up to work on other areas of the business where their input has greater value.
Furthermore, virtual agents also have the ability to automatically pull a customer’s data, such as their name, location, IP address, etc to suggest new products and services that they might be interested in based on previous preferences, or even to engage with the customer in their native language. This ties in with a recent industry survey which found that 91% of consumers are likely to go with a brand that recognises, remembers, and provides them with relevant offers and recommendations.
These are just some of the simple ways that AI can help to enrich the user experience, and for businesses to demonstrate their ongoing commitment to improving products and services.
Machine Learning
Machine learning is another prime technology within the experience economy that is helping businesses to personalise customer journeys. In essence, machine learning uses AI systems to automatically learn from customer experiences without the intervention of human agents. This means that the technology can look back across a customer’s entire conversation history with the organisation to gain an understanding of their situation, as well as what can be done to assist them.
Again, this is an effective way to relieve the burden of manual response, given that businesses can have confidence that virtual agents have the knowledge to accurately address ongoing customer issues. In addition to this, machine learning can help to improve customers’ opinion of the brand by demonstrating an awareness of who they are, and how they have communicated with the company to date. After all, customers do not want to have to explain their situation every time they get in touch with the organisation. They want to be able to understand progress of an ongoing issue or pick up where they left off as seamlessly as possible. Machine learning makes this possible.
By analysing patterns in customer data, organisations can get even more value out of their investment in machine learning technology. With a broader picture of the types of issues that customers are facing, as well as what solutions they are looking for, organisations can make more informed decisions when it comes to marketing and service delivery that are not only beneficial to themselves, but are also genuinely effective at helping customers. In delivering the more personalised experiences that come with this, businesses can increase brand loyalty and, as such, truly stand out from their competitors.
Experience is king
In today’s business landscape, organisations must constantly seek new ways to enhance the technology that is at their disposal to streamline processes and provide better services to customers. When undergoing a digital transformation, firms must keep the importance of the experience economy at the forefront of their minds, given how crucial it is when it comes to keeping customers on their side amid a market competing for the best consumer experiences.
By working with Software as a Service [SaaS] providers, companies can use enterprise-wide platforms driven by technologies like AI and machine learning to create personalised work experiences through digital workflows, pulling in data from multiple front and back office systems, as well as external third party systems, where necessary. It is understandable that many businesses will want to focus on what they do best and leave the experts to it. By hiring a consultancy, organisations can do exactly that, with peace of mind that they are making positive steps towards enhancing experiences.
In doing so, businesses can form a hybrid Cloud structure that allows them to maximise opportunities, personalise customer and employee experiences, and ensure that data integrity is not compromised.
Not only can investing in customer and employee experiences lead to increased revenue from the delivery of more efficient products and services, but can also lead to greater employee satisfaction, which translates to greater retention of staff. All in all, making such an investment can be hugely positive, and genuinely transformative for company performance and brand reputation.
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