Top 3 Customer Experience Personalisation Challenges for Retailers - Part 1

Leveraging Customer Data

In this 3-part series, we will explore the biggest challenges facing retailers in 2019 and beyond. Our focus will be on the challenges commonly associated with digital transformation and delivering value through customer experience, personalisation and data because we believe that seamless and personalised retail experiences are going to be crucial in order for retailers to innovate and standout in a crowded marketplace.

In part 1, we discuss the importance of data because, from our experience within the retail sector, getting your data right is the most fundamental issue that retailers are facing when they first start approaching a digital transformation project.

The cost of poor data management

While retailers are starting to understand and appreciate the importance of unifying the customer experience across all channels, many are failing at the first hurdle and experiencing fundamental technological challenges as a result of poor data management.

Customer databases are built up of valuable customer records that, with a data management system, can be used to build up detailed customer profiles that can be used for predictive analytics and personalised marketing campaigns with relevant and timely messages that increase individual customer value.

However, many customer databases suffer from duplicated data entries, which show a single customer as multiple customers because of slightly different information such as a change of address or surname. These databases usually contain a large amount of dark data – data that is collected, processed and stored through regular business activity but is not used for a profitable purpose.

In fact, around 6% of businesses’ annual revenue is being lost through poor quality data, according to the Royal Mail. But it isn’t just your revenue that is suffering, there are costs associated to your resources and labour costs. 50% of a data worker’s time is spent finding and correcting errors across systems. If your team is working at only half of its true capacity, can you imagine the impact this is having across your department?

A lack of technology means that these valuable customer insights go dark and the data becomes disorganised and so valueless.

Exploring data in the retail space

To highlight the importance of data, let’s take a look at an example of the importance of data in the context of retail. A customer database for ‘ABC Retailer’ contains records on ‘John Smith’, a middle-aged business executive who purchases a new female, red, stripy bag every year in October – his wife’s birthday.

‘ABC’ gathers this information from the customer’s purchase history but currently, this data is stored in separate data silos across its various disconnected systems making it near impossible to harmonise its data because there is no data management system in place to connect to the various data sources and to unify the data.

Now let’s say we have a data management system, ‘ABC’ can start to recommend secondary purchases that complement ‘John’s’ buying habits  such as a matching pair of shoes or a dress, around the time that John usually makes this yearly purchase with a personalised message: ‘Hi John, we noticed that your wife’s birthday is around the corner – have you considered these recommended items that we’re sure she’d love?’.

‘John’ receives an instant, relevant message that appeals on a personal level and is more likely to lead to a sale compared with a generic ‘sale’ (or, more accurately, spam) message that will be ignored or, worse, lead to a disappointed customer when the message isn’t relevant or desired. Without a level of personalisation beyond ‘Hi John’, sales messages like these are more likely to drive your customers to your competition than convert to a sale because customer expectations have changed.

Personalised experiences make customers like John feel more in touch with your brand and valued because you are taking the time to get to know his specific needs and offer complimentary products that he may not have been aware of or hadn’t considered before. Our example retailer, ‘ABC’, has also benefited from the timely and relevant marketing messages that led to the additional sale that, in the past, would have been lost.

This is a simple example, but it highlights the value of quality data as the vital starting point for creating a personalised customer experience as part of your digital transformation strategy. Personalised customer interactions are key to delivering the level of service that will differentiate the offerings between retailers.

Applying data insights to improve business and marketing performance

Clean data is the foundation block for success and should be the focus for retailers. Data informs every business and marketing decision as well as providing insight into key trends such as top-selling product lines and individual customer records. Poor quality data can cause misinformed or under-informed business decisions which can cause marketing initiatives to fail through inaccurate metrics and figures.

A data management system connects to your existing data sources and unifies the data using intelligent algorithms. These insights are used to create detailed customer profiles, so you can understand the what’s, where’s, when’s and why’s of your customers to deliver personalised customer experiences and accurate marketing campaigns.

In part 2, we discuss the next challenge for retailers once data management is implemented: KPIs and reporting capabilities.

Data Clarity co-founders, Kevin Carrick and Pana Lepeniotis

Co-Written by Kevin Carrick and Pana Lepeniotis

Connect with Kevin and Pana on LinkedIn to discuss your data strategy.


Want to find out more? Contact our data experts to have a chat about your current data challenges and how Data Clarity can help you achieve a greater ROI and improve your customer experience.

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