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8.5 min to readApplication Services

Enhancing customer loyalty with data insights and personalisation

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Wiktor ZdzienickiGlobal Practice Manager, Data and AI
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Knowing your customer is key for every business. With the right tools, you can leverage your existing data, as well as AI, to build better relationships and tailor your communications. Let’s explore a practical approach to gaining deeper customer insights, based on examples from the banking industry.

Understand your customer – it matters

We all know that the data we share is being used. But customers, especially young people, want that data to be used wisely. They really value a pro-consumer attitude.

Based on Wakefield research, only 41% of consumers may want to share personal information if they get more personalised offers in return.

This is very important, as currently customers have a lot of options to choose from. Brands have to be very careful and consistent in using the data well.

Irrelevant messaging worsens your customers’ experience

According to McKinsey, 65% of customers are frustrated by inconsistent experiences across channels. A situation when a person appearing in a digital web channel and the mobile channel is treated as two different people, still happens in today’s world. And consumers do not like it Companies should be able to connect this data and communicate with people by centralising all communication history from different channels.

What is more, 76% of customers are frustrated by the irrelevant content they are exposed to by their chosen brands. For example, bank customers wouldn’t want to get messages about travel insurance if they are not going anywhere anytime soon.

The challenge with data analytics

From the point of view of companies, we also know that managing customer data is not so easy. Data is continuously created, but the banks and financial organisations do not have full ability to use it properly. Only 20.6% of organisations managed to establish a -driven culture, as per the recent report by New Vantage Partners.

The biggest challenges they see are the inability to unify the data and the lack of means to extract it. We all hear that we live in the era of big data. The information is flowing, and we know we can use it, yet we don’t always have proper ways to collect, unify and leverage it in the best possible way. But there is a solution.

What is a customer 360 ?

Customer 360 overview is a unified view of customer data and use the right channels to engage with customers.

Consumers expect banks to provide comprehensive, personalised services and relevant communication. Further, communication itself gets less and less expensive.

The actual price, however, may be paid in customer loyalty. Whenever a customer receives something that is completely unrelated to them, they tend to get discouraged from using the service. That’s why we need to ensure that the messages we send are relevant and targeted.

Using data to personalise experiences

First, we want to gather all relevant data which, depending on the organisation, will be different. For a bank, the main source of data will be transactions.

This includes card payments, withdrawals and transfers between customers. We should also include demographics, behavioural data, and “less traditional” data, such as contacts with customer centre, responses to campaigns or social media data.

By analysing all this information, we can create a general view of our customer and get to know them better. In time, we’ll be able to go even further and predict their behaviour.

For example, if we have the transactional data, why not try to predict important life events? We may try to forecast whether a customer is going to buy a house soon, which would be an excellent opportunity to offer a loan.

As a result of these actions, we can create a very personal relationship. We can make use of the knowledge we have about our customers to create focused communication and offer them the most relevant products or services.

An essential tool for making this happen is a Customer Data Platform.

What is the Customer Data Platform?

The physical representation of the elements of a customer 360 overview is a so-called Customer Data Platform. It consists of 3 main pillars.

  1. Getting a complete view of customers – combining and enriching all your data in real time to be able to react to every change in a customer’s behaviour.
  2. Unlocking powerful insights – using machine learning and AI to predict customer intent.
  3. Driving meaningful actions – personalising engagement across channels and automating communications with the customer, keeping in mind that every relationship has to be individual and backed by data.

How to build and use Customer Data Platform with Dynamics 365 Customer Insights?

Dynamics 365 Customer Insights is a customer data platform from Microsoft, created to help its users drive customer-centric experiences. The solution is set up over 5 stages: ingestion, mapping and matching, conflation, enrichment, insights and action.


First, we need to ingest all the data we have – this means bringing customer and activity data from all sources. We can deal with structured data like traditional databases or unstructured like videos, images, etc..

Mapping and matching the data

The aim of this stage is to identify and understand customer data from different sources. We have some ready-made ways to achieve that. Customer Insights service also includes ways to unify the data efficiently.


What is very important at this point is data source lineage, i.e. the traceability of our information. If risk or compliance department asks us where the data comes from, we have to be able to quickly investigate that. This is especially important in terms of privacy and many risks associated with breaking it.


We have the data, we have connected and unified it. Now we should use AI to enrich it and generate new, unobserved knowledge through machine learning models.


Data and various models are only helpful if we generate appropriate business insights from them. Understanding the data and the models is challenging, which is why graphical representation is essential.


Finally, we need to take action through, for example, a personalised marketing campaign. Only then will our data and AI analytics bring real value.


The structure of Customer Insights

Now, let’s take a more detailed look at the elements that form our Customer Insights solution.


If we’re a bank, this will be mainly transactions, product usage, demographic data. But we can count on many different types of data, especially when it comes to external sources. If we are working with a partner, why not get this data to enrich our customer database?

We can also think about social media, e.g. interactions with our company profiles, as a huge source of behavioural analysis data. If we use a mobile app, why don’t we get the geographic data to show the true location of our customers and put them on the map? Customer Insights has the ability to automatically connect to many sources of data we might need.


This is where all the magic happens: ingesting, matching, conflating, and enriching. At this point, the customer 360 profile is being created, so we can use it later.


There are two main approaches to working with the data we are getting. We can either create a more traditional analysis in the form of dashboards or a general overview or use modern analytics. In our view, AI and machine learning is the way to go here.

We have so many possibilities to use computing power, e.g. with Microsoft Azure, and to create an action dedicated to each individual customer (even if we have millions of them!). It would be a shame to waste that.


Finally, we have the actions that we can take via different sample Microsoft’s services. Our main goal is to be able to transform the information on Customer Data Platform to engagement via mobile web, social media, or even bots – another piece of artificial intelligence at the very end of the process.


What are the applications of a customer 360 overview?

The possibilities are endless! But let’s explore some key ones.


We can create segments, but not in a “traditional”, a priori way. We no longer just categorise our population as “young” or “well-earning” customers. We are able to ask the algorithm to do that and to look for some previously unseen connections between our customers.

We can also use this data to score leads. If we introduce new products, we want to find the customers who are most likely to answer for the new offering.

Product recommendations

If we know that our customer is interested in traveling and has, say, two houses and drives three cars, this is excellent knowledge for us to decide what kinds of products they might need. We are able to treat them completely differently to the general group of customers.

Proactive support

Another application may be providing service and proactive support via different channels. We don’t really want to wait for our customers to ask for our service. We want to be there first! The goal is to introduce them to some new products or services and provide excellent care.

Improve your customer relationships with smart use of data

Using customer insights and data-driven strategies is imperative for today's businesses. With tools like customer 360 overview and Customer Data Platform, you can make messages personal, get better at connecting, and keep customers coming back.

The image below illustrates what we are essentially aiming for when creating a 360 customer overview. It’s a profile of each customer that includes dashboards and visual reports of various characteristics that may help us with personalising their interactions with us.

A screen shot of a dashboard in microsoft office.
An example dashboard in Customer Insights

We can use this information to engage and to develop an individual approach for every single customer, but it is very important that we use this data wisely. Our customers give us their data and they trust us, so we must engage with them in a smart and respectful way.

We cannot really approach a customer, saying “I know that you are going to buy a house in two days”. This is not the way to go. We have to be very careful how we approach customers, so we can build strong relationships and focus on actions that matter.

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A young man in a blue shirt is smiling.

Wiktor Zdzienicki
Global Practice Manager, Data and AI