Analytics

Analytics that are based on Customer Journey models or Process Interest Graphs (PIGs) can personalise any and all aspects of a relationship with any customer so that a product and its associated services become indispensable and unmissable. Then firms do not have to pay off customer with coupons and price reductions to get loyalty.

But this degree of analytical prowess requires data on many different aspects of each customer – which is a problem for most firms with fragmented databases and siloed departments. Even highly integrated firms with a single view of the customer need ways to access external data resources.

The good news is that firms are generating and sharing vast amounts of the data that customers generate by enquiring and buying products. The bad news is that the very scale and complexity of this data is a barrier to actually using it.

Firms that are using highly sophisticated analytical strategies, like PIGs, to analyse data as well as integrate it. The key to defining an actionable analytical strategy in the face of complex data resources and confusing commercial options is to look for connections between the two.

PIGs connect what individual customers are interested in, whether they know it or not, with the commercial objectives of a firm or a network of firms. This enables firms to actually use their vast hoards of data, and manage its use based on its value, as well as to create value from it.

Firms, and loose networks of firms, are starting to know much more about each of their customers than the customers, their family members or any other single human being. This huge leap forward in individually personalised, real-time insight for large sections of each customer’s life can be used to create new services as well as reduce costs.

But there are dangers associated with owning personal data.

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