Ask any retailer and they’ll tell you that an enhanced customer experience is at the top of their ‘must do’ list. Improving customer experience is the key to winning new customers, keeping existing ones happy and bumping up revenue and profit.

  • iVend Reporting & Analytics

Data and customer experience go hand in hand.

iVend helps retailers analyse data for an enhanced customer experience.

There are many ways to improve customer experience, but there is one thing that underpins all of them – and that is data. Data is at the heart of all strategically sound business decisions, including those that a retailer takes in order to improve customer experience.

As a recent Forbes article highlighted*: ‘Meeting the high expectations of consumers is the dream of any company, but it is an achievable goal only for those organizations who are committed to managing data for its application in intelligent decision making.’

So let’s take a look at how to use data to improve customer experience – here’s our top seven tips:

  • Loyalty – customers want to engage with brands and feel connected. Over 80%** of consumers use a loyalty program, a further 8% have used one in the past and 7% think they will use one in the future. Loyalty programs pack a massive punch when it comes to data – they are a rich source of information. Every interaction that a loyalty customer has with you is a data point, which gives you greater insight into their behaviours and preferences. This information can then be used to provide an enhanced customer experience, with a loyalty program that rewards them for their ongoing engagement with your brand.
  • Personalisation – we know that today’s shoppers want to feel that they are recognised, valued and important to the retailers they buy from. Personalisation is a major factor in improving customer experience, and 88%+ of shoppers will return to an online store that makes them feel like an individual. Data analytics for customer experience provides the insights into customer behaviour which enable retailers to offer personalisation.
  • Forecasting – the best retail experience happens when a retailer is one step ahead of what shoppers want, and ready to serve them. Customer experience data analytics will help you predict future trends, essential for planning your purchasing and campaigns. A survey of retailers who are running data analytics for customer experience shows that 86%++ of them saw a positive ROI.

  • Operational efficiency – shoppers will always have an enhanced customer experience in a well-run, store – one with the right goods on the shelves, sufficient staff, speedy checkouts. Running an efficient store is only possible if you have data to show you where any bottlenecks and inefficiencies lie. Efficiency depends on being able to capture and aggregate data from every point in your organisation, and analyse it for tactical insights and longer term strategic planning.

  • Motivated staff – ‘There’s a direct link between employee satisfaction and customer satisfaction. Happy employees equal happy customers. Unhappy employees lead to unhappy customers.’ The retail customer experience is directly influenced by the morale, motivation and engagement of retail associates. Customer experience data analytics enables you to understand the behaviours of your team and reward the behaviours that improve customer experience.

  • Mobile enabled staff –the best customer experience depends on staff who are not only willing, but equipped, to help. 61% of global retailers are equipping staff with mobile POS, so that they can offer better retail customer service. This strategy means you have to give associates the data that will help them improve customer experience – for example, being able to see a shopper’s previous orders or browsing history, data about stock levels and locations, data about their loyalty points or promotions. Making this data available to staff is a big step towards a smooth and seamless customer shopping experience.

  • Inventory planning – a significant determinant of enhanced customer experience is shoppers being able to buy the goods they want. Out-of-stocks are a big frustration. Data about inventory – whether it’s in the store, or a distribution centre or warehouse – is crucial to help retailers ensure that they have the right goods in the right place, at the right time, allowing them to sell more and deliver the best retail experience.

An enhanced customer experience depends on many factors in the retail ecosystem – and they all start with data and analysis. Data and customer experience truly do go hand in hand.

What is data analytics?

Data analytics means analysing ‘raw’ data to find patterns and trends, and to draw conclusions. It often involves combining, or aggregating, data from multiple sources, which, when viewed together, can uncover insights that would otherwise have remained unnoticed. Data analytics often uses automation and algorithms so it can handle vast amounts of data, far more than could ever be processed by the human brain.

What is the value of data analytics?

The value of analytics is that, essentially, it turns data into information. The process of analysis uncovers insights that help a business to optimise operational performance, streamline formerly inefficient processes and gain a deep understanding of customer behaviour, so that retailers can align their processes to the way that shoppers want to interact.

References:-
*https://www.forbes.com/sites/forbesbusinesscouncil/2022/11/23/in-data-driven-customer-experience-we-trust/?sh=1c6ed06d68bc
**https://www.softwareadvice.co.uk/blog/3272/how-many-customers-use-loyalty-programs
+ https://www.retailcustomerexperience.com/news/personalization-influencing-most-online-shoppers/
++ https://www.brandpoint.com/blog/using-big-data-to-predict-consumer-behavior-and-improve-roi/

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