If you want loyalty, get a dog.
If you want customer loyalty, improve your data quality.
I must admit that data quality is probably not the first concept that springs to mind when brainstorming ideas to improve customer loyalty.
The “B2Me” marketing approach – delivering hyper-personalised experiences through digital channels – is replacing traditional B2C and B2B approaches. Hyper-personalisation is completely dependent upon quality data.
Omni-channel is the new normal. Consumers can interact with us via our website, our cusomer portal, our call centre, mobile apps, social media sites and our physical stores.
Many customers expect the organisation to know who they are and what previous interactions they have shared. Data quality solutions need to combine “traditional” data – like customer name or account number – with additional data – such as IP address or device IDs to build an accurate picture of each individuals 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. Other data must be sourced externally, and blended into the internal data set.
Enabling downstream value
Artificial intelligence is increasingly deployed in mainstream retail applications – with recommendation engines, virtual assistants and personalisation engines 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 our organization, and what their interests are, the better our AI recommendations will be.
For a more in depth look, read the Precisely eBook: Exceeding Expectations: Four Ways Data Quality Promotes Customer Loyalty