Transforming the customer experience with analytics

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Tiffany Carpenter, head of customer intelligence at SAS UK & Ireland, looks at the benefits of real-time customer experience and offers a preview into how analytics is powering hyper-personalised customer journeys

In recent years, customer experience has become an important battleground for brands. Yet, in a hyper-connected, hyper-competitive environment where it is becoming increasingly difficult to compete on product or price alone, the concept of customer experience has grown in importance as organisations fight to remain relevant and deliver against customer expectations.

Customers expect the organisations they are interacting with to make it easy to business with them. They expect a seamless experience regardless of how they engage with you whether it be online, via an app, a call centre or in person; and they expect their personal information and data that they have made available, to be used appropriately by organisations to deliver relevant experiences.  To deliver against these expectations,  businesses must first fully understand the wants and needs of current and prospective customers. While this may sound simple enough in principle, most organisations are only using a limited amount of data to try to understand their customers. In fact, most UK organisations admit to using less than half of the valuable data available to them, and they will often analyse it using basic tools or spreadsheets that fail to provide a single view of the customer.

Achieving a segment of one

What’s needed is an approach that allows organisations to concentrate on delivering a superior customer experience by achieving relevancy at every touchpoint based on an understanding of each individual customer – a segment of one.

Today’s customers want the call centre to know when they have just been on the website. They want brands to adjust their marketing strategies if they’ve  made a complaint or negatively reviewed a product or service For businesses, this means having access to a ‘central brain’ that can analyse of all the data available in a timely manner with the ability to inject that insight into any customer interaction across any department and channel -  in real-time if necessary.

This means using data about what’s already happened as well as what’s happening now, to predict what’s going to happen in the future, what the best outcomes will be and make profitable and accurate decisions at each point of a customer interaction.

The central brain

In the race to digitalisation, the mistake many businesses make when trying to achieve a segment of one is placing too much emphasis and narrow focus on digital data. Each lifecycle stage, across each channel is important – from initial consideration, to active evaluation, to the moment of purchase and even the post-purchase experience. Key to successful customer intelligence strategies is tying together offline and online data to get a better understanding of the customer.

Rather than analysing data from a single digital transaction or following customers around in a digital world, It’s more important to understand what happens prior, during and after a digital interaction to create a full picture of behavioural insights. To truly understand customer behaviour and deliver the most value at each customer touch point non-digital data such as demographic, psychographic, transactional, risk and many others types of data - that sit both outside and inside the digital environment - needs to be analysed and mapped to specific stages in the customer lifecycle.

More importantly, once businesses gain these insights, they need to consider how they use this insight to make the right decisions that deliver value to the business. Where appropriate those decisions need to be made in real time and injected into the customer interaction channel at the point of engagement. Each stage of the customer journey needs to be viewed as an opportunity to improve the customer experience. And each stage is an opportunity to gain more insight that can be fed back into marketing processes to draw from the next time. Only then can you deliver the right message at the right time via the right channel.

A personalised experience in real-time

Shop Direct is a great example of a business embracing this approach. Its goal was to make it easier for customers to shop with them, thereby improving the customer experience whilst increasing customer spend. As a 40-year-old business that started as a catalogue company, it was sitting on a huge amount of data that had been captured over the years about its customers and they wanted to find a way to use that data to deliver a highly personalised customer experience.

At the time, a customer shopping for jeans on their Very.co.uk website could be presented with 50 pages of options to scroll through. By analysing the existing data Shop Direct is now able to predict which jeans a customer is most likely to be interested in and personalise the customer’s shopping experience. This is done via an individually personalised sort order in real time to show the products they are most interested in first. Harnessing data and advanced analytics to deliver unparalleled levels of personalistion has seen Shop Direct’s profits surge by 43%.

Group CEO at Shop Direct, Alex Baldock, has said that the company is "all about making it easier for our customers to shop. That's why we're passionate about personalisation. We want to tailor everything for our customer; the shop they visit and how we engage with them - before, during and after they’ve shopped."

The survival factor

In the future, developing a superior customer experience will rely on understanding the balance between delivering the right decision in real-time and giving yourself time to make the right decision. It’s crucial to remember that not every decision about the customer experience needs to be managed in real-time. Organisations have huge amounts of data at their fingertips that they can use to predict and plan to shape products, services and messages.

However, there will be moments when a decision needs to be  made in real-time as to what the right content, message, offer or recommendation for an individual customer might be. This decision should not just be based on what area of a website a customer clicked on, or whether they liked your facebook page. To make accurate and profitable decisions requires insight into offline and online historical data. This must be coupled with real time contextual data as well as a clear understanding of business goals and objectives, and clarity around the predicted outcome of each possible decision. To achieve this, businesses must move away from a channel-specific approach with fragmented systems and rules and embrace a centralised analytical decisioning capability. This would have access to all relevant data, a centralised set of logic and rules, and be able to automate complex analytical decisions at scale and push those out to any channel across any business unit at the right time.

This will need to be what underpins the entire business; the organisations that get this right, will be the ones that survive.

For more on how real-time insights can improve customer experience, read about maximising moments of truth.

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About Author

Tiffany Carpenter

Head of Customer Intelligence, SAS UK & Ireland

Tiffany has been helping organisations achieve bottom line results from their customer and marketing strategies for over 20 years. She specialises in helping companies gain deeper insight into their customers’ buying habits, preferences and lifestyles, social relationships and influences on purchase behaviour and loyalty - and using this insight to make smarter, data-driven decisions. Every customer journey is unique and every touch point is an opportunity to nurture customer relationships and deepen customer intimacy. Tiffany helps organisations get in sync with each customer's journey – no matter how fragmented for a clear competitive advantage and a bigger, better ROI.

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  1. Pingback: Build customer loyalty with the best Customer Experience - Hidden Insights

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