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Why Intelligent Applications Build Better Relationships With Customers

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

Photograph: Aedrian/Unsplash

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.

  1. 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.

  2. 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.

  3. 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.

The advantages of intelligent applications shouldn’t be ignored

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 is the key

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.

Good relationships are always about both parties

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.

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