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Data Quality is key to promoting customer loyalty

As per the old adage: “If you want loyalty, get a dog”. In the fourth industrial era, if you want customer loyalty, improve your data quality. For many organisations, when looking for ways to improve customer loyalty, data quality is probably not the first concept that springs to mind.

The Business to Me (B2Me) marketing approach, which looks at delivering hyper-personalised experiences through digital channels, may start to replace traditional Business to Consumer (B2C) and Business to Business (B2B) approaches. However, effective hyper-personalisation, a key component or driver of customer loyalty, is completely dependent upon quality data.

Connecting channels

Omni-channel is playing an important role in hyper-personalisation and is fast becoming the new normal, whereby consumers can interact with brands via their websites, customer portals, call centres, mobile apps, social media sites and physical stores.

Many customers expect an organisation to know who they are and what previous interactions they have shared in order to foster loyalty. Data quality solutions need to combine “traditional” data – like a customer’s name or account number – with additional data – such as an IP address or a device ID to build an accurate picture of each individual’s activities and preferences.

Enrich and extend

It is no longer enough to simply build this single customer view. Winning businesses are extending their customer understanding by adding additional context, such as location data and demographics that can help to build a better understanding of each individual. Some of this data may come from linking disparate internal data sets, while other data must be sourced externally and blended into the internal data set.

Enabling downstream value

Artificial Intelligence (AI) too is making its mark for retailers that want to understand their customers better and deliver an enhanced Customer Experience (CX), driving customer loyalty. It is increasingly deployed in mainstream retail applications – with recommendation engines, virtual assistants and personalisation engines being the top three areas of consideration.

For competing retailers deploying similar solutions, the differentiator is in the data, not the algorithm. The better our understanding of the individual, how they engage with an organisation, and what their interests are, the better an organisation’s AI recommendations will be.

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