With skilful use of technology and data, businesses today can create intelligent customer experiences that outclass anything that was previously possible. Intelligent applications – those that use AI and predictive analytics to provide personalised, actionable outcomes – cannot be overlooked for those wanting to get (or stay) ahead.
01 February 2022 • 4 min read
Every company wants to improve their customer experience. In 2022, the most effective way to do this is with technology.
Intelligent applications learn from existing interactions and optimise for future ones. For enterprise organisations, this is creating intelligent customer experiences that outclass anything that was previously possible. But it’s not easy to make clear decisions about which technologies to adopt and which should be given top priority, considering the multitude of new innovations in recent years. It can be helpful to think of intelligent applications in three categories.
The first type to be developed was robotic process automation. This type of application allows businesses to automate steps in their workflows. For example, opening PDFs, supplying products, processing invoices, inputting data, or transferring data into other systems. Or it can combine these steps into an entire automated workflow, for example, sending triggered emails.
Later, we started to see technology that replaced some human activities. For example, Alexa, Jarvis or chatbots that work with structured text and data, such as emails, job adverts or product descriptions. These applications don’t replace all cognitive tasks, but they partially replace some actions. They’re useful because they collect a lot of input data and can help humans improve their performance in an area.
Finally, we have the most evolved category: apps that create new products and experiences based on artificial intelligence. This includes things like self-driving automobiles, which create the need and market for completely new vehicles. They create business models and services that would not be possible without machine learning technologies. They replace human activities and often even whole processes.
Intelligent applications are action oriented. They’re not waiting for the end users to make every move. They study our behaviour and actions, and then use artificial intelligence and predictive analytics to provide personalised, actionable outcomes.
They’re also a rich source of data. These technologies enable you to have a more analytical deep dive than a traditional data model. You can collect information in real time through websites, mobile apps and so on. The possibilities for data analysis, and increased competitive advantage, are huge. This data can inform actions to take to improve retention, reduce pain points and attract new customers.
With intelligent applications, customers only receive the information that is valuable to them.
Intelligent applications provide a switch from traditional marketing to contextual marketing: intelligent applications can easily distinguish between data that is specific and appropriate for a customer, and data that isn’t. Does the customer want to see clothing for men or women? Are they interested in football or kayaking? Do they have a car? When’s their birthday? With intelligent applications, customers only receive the information that is valuable to them.
And perhaps one of the most important benefits of intelligent applications is that they’re omnichannel. You have to build a superior, end-to-end experience for the customer, no matter what channel they’re using. According to Trusted Shops, companies with a strong omnichannel strategy retain an average of 89% of customers, compared to an average customer retention rate of only 39%. Building with omnichannel in mind can save organisations a huge amount of time and money.
Customer experience data reflects every interaction between a business and its customers – even if it’s only brief and doesn’t result in a sale. It’s about the feelings of the customer towards your business. By collecting specific, relevant data about your customer, you can help ensure a long-term relationship with them. This is the most important trigger to continue your existence as a company.
I saw business people with years of expertise in their industries who chose not to use intelligent applications, because they felt they knew the customers better than the data. But it wasn’t enough.
This was my experience when I worked in sales. I saw business people with years of expertise in their industries who chose not to use intelligent applications, because they felt they knew the customers better than the data. But it wasn’t enough. Even though the competition didn’t have the same level of expertise they still performed better, because they had access to prospects’ interests, their current situation, deeper insights into their pain points and more.
In the early days of automation, businesses were extremely focused on improving their own operations and collecting data. But businesses found that even with all the operational data collected, every process automated and all systems working together seamlessly – it wasn’t enough. Operational data only reflects one half of the relationship with your customers.
You might have rich data on the operations of your business. Perhaps you have an invoice in your workflow and you know where it is at every moment, but this doesn’t help very much with the relationship with the customer. For this, you have to collect the data from the customer’s side.
Even if it’s a brief interaction that doesn’t end up with a purchase, experience data is coming from these interactions and it tells you what you need to change to do better.
Customer experience data shows you how the customer feels about your products, business, and most importantly, their interaction with your company. Even if it’s a brief interaction that doesn’t end up with a purchase, experience data is coming from these interactions and it tells you what you need to change to do better. Intelligent applications are predictive. If your customer doesn’t like something about your product or your relationship, intelligent applications can take action to prevent them from leaving.
There are two halves to every good relationship. You can’t only focus on yourself, nor can you only focus on the other party. For businesses, this means splitting their focus between operational processes and the customer experience. It’s about finding the right mix between operational and customer data. In 2022, the only way to do this competitively is with intelligent applications.
Discover more inArtificial intelligence
AI is maturing. One of its newest uses can help advertising match the most relevant content to the viewer, touching gaming, TV. Here’s how.
01 February 2022 • 2min read
What safeguards do organisations have against the constant tide of disruption? Those that are smart are taking full advantage of technologies like cloud, AI and big data analytics – and doing so with one focus in mind: giving their people what they need to leverage the full power of their collective intelligence.
01 February 2022 • 6min read
Trust is an imperative value in human interaction and behavior. In the business world, this is no different. AI has also become a key tool in unifying the business world with human elements to help automate processes and manage complex data. The pressure is on for organizations to keep up with the times and adopt using AI, but why are some companies hesitant to do so? Can AI be trusted?
20 June 2022 • 1min read
Education is not just a fundamental right for everyone: it’s also a pathway to a better quality of life, playing an instrumental role in attaining many of the UN’s Sustainable Development Goals. Through sharing skills such as cybersecurity, businesses can spread knowledge and help to shape more resilient, informed future global citizens.
01 September 2021 • 4min read
Obtaining data can open up a whole wealth of business opportunities, as long as the data is valid and trustworthy. However, having incorrect, outdated or inaccurately sampled data can be damaging and costly. In such turbulent times, how can we secure data integrity for the best outcomes for businesses?
13 June 2022 • 6min read
Businesses strive to create new technologies, products and services that reshape or even disrupt their markets. Yet businesses also need to understand they must innovate sustainably and ethically. With pressure to innovate quickly - bias, ethics and discrimination can easily be forgotten.
01 February 2021 • 5min read
If the past two years have taught organizations anything, it’s that empathy is an essential part of customer service and engagement. This is the right time for organizations to focus on building a culture of empathy by developing processes that promote empathetic customer experiences and engagements through tailored interactions and smart technology.
19 July 2022 • 4min read
Could it be possible to make your organisation twice as agile? When businesses behave intelligently, they use data science to facilitate a culture of continual, democratised decision-making, which can cut response times in half.
01 February 2022 • 5min read
As businesses continue to evolve their use of automation, what does this mean for leadership? AI and machine learning promise massive efficiency gains, but at what cost? Effective leadership in today's agile businesses means connecting on an emotional level with each employee. An algorithm will never replace an empathetic leader.
01 October 2020 • 4min read
If the modern firm is an organism living through rapid and complex changes in its ecosystem, then data insight provides its sensory information. Using data to drive decision-making, as has long been the case for telecoms companies, holds the key to continual adaptation and improvement.
01 June 2021 • 4min read
Innovation in technology has great potential in helping to provide accessible, tailored learning for every child. Through our AIDA project, we created a unique system that could give caregivers and educators the information they need by bringing together elements from design, AI, IoT and VR.
01 September 2021 • 4min read
Bias in technology is real, and as we design and build increasingly powerful systems, our obligations to those using the technology increase in step. Two experts share what they’ve learned for building diverse and efficient teams and ethical AI frameworks.
25 October 2022 • 3min read
It’s the next big thing in understanding and engaging customers: building a virtual replica of the business ecosystem, and leveraging ontologies as enabling technology. This exciting branch of AI can help businesses to generate very targeted insights into their customers’ expectations and needs.
16 June 2022 • 4min read
Continuous innovation used to be enough to drive growth. However, today’s organisations also must innovate at speed and scale. Indeed, a frequent question we hear from CEOs around the world is: “How can my organisation adapt and move faster?”
01 February 2022 • 2min read
The world is changing beyond recognition. Society is increasingly demanding that companies address sustainability as part of their transformation to a post-pandemic world. Sustainability is now firmly on the C-Suite agenda and it’s at the heart of NTT DATA’s vision for the future.
01 September 2021 • 1min read
New norms are emerging. Social movements, such as Black Lives Matter or Fridays for Future, urge companies to position themselves politically; and new legal frameworks and standards such as GDPR push companies to rethink the ways they develop products and services. As the responsibilities of companies grow and change, making sure that ethics, diversity and inclusion, and sustainability are built into every process is essential for both consumer and company.
01 February 2021 • 1min read
Manufacturers are dealing with fundamental changes in every part of their operations, with a growing demand for higher product customisation, making traditional manufacturing processes no longer fit for purpose. It’s time for manufacturing to undergo a new stage in its transformation: Hyper Automation.
01 February 2022 • 1min read
Algorithms may be perceived as being an objective way to instill diversity, equity and inclusion in an organization, but AI is by no means exempt from the unconscious biases that human beings exhibit, and we must guard against thinking of AI as a silver bullet. We know that greater diversity leads to greater innovation, but diversity of thought and cultural background is also crucial in driving out biases from AI design.
23 November 2022 • 4min read
From picking up on our tendencies toward exclusion to offensively grouping characteristics, AI is learning (and scaling) our worst habits. Luckily, awareness and a desire to take action is growing across many organisations. It’s not too late to resolve this problem. So, what do businesses need to know and do to prevent it?
01 February 2022 • 5min read