Using Big Data to personalise the customer experience

Once you understand the significance of key stages of the customer lifecycle, it’s important to understand the individual journeys that customers take.

An enormous amount of data exists about customers – who they are, where they live, how they’ve transacted in the past, their preferences, likes/dislikes, service history (across every single customer touch-point), real-time online activities and a lot more besides.

The organisations that can most effectively analyse and proactively use this Big Data to aid real-time decision-making and improve customer experiences will increasingly be the ones that stand the best chance of commercial success. And a big part of improving the customer experience is in personalising it.

At a digital level, smart organisations are now tracking web site visitor behaviour in real time to find out how long customers have spent researching product choices online, what they’ve viewed etc. They are also analysing the content and context of live agent conversations with sophisticated speech and data analytics technologies.

By combining this information with past purchase history, customer feedback and data from knowledge bases, organisations can:

  • highlight related products/services
  • point to special offers
  • switch ‘public conversations’ (i.e. over social media) to one-to-one ‘private conversations’
  • offer immediate relevant support to create more personalised experiences
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