Customer Retention and Personalisation of the Shopper Experience

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I was chatting with a few of my digital channels, analytics and social experts about retention strategies and how personalisation might work. Here’s what we discussed one evening in the Vivat Bachus, a nice watering hole in Holborn.   1) Traditional retention strategies are flawed, in two ways – firstly marketing and comms campaigns are […]

I was chatting with a few of my digital channels, analytics and social experts about retention strategies and how personalisation might work. Here’s what we discussed one evening in the Vivat Bachus, a nice watering hole in Holborn.
 
1) Traditional retention strategies are flawed, in two ways – firstly
marketing and comms campaigns are too generic in between purchases,
when customers demand personalisation. And secondly, especially for
industries with long periods between purchases (e.g. high end
electronics, holidays, white goods), it is hard to figure out the
moment a customer moves from a passive mode to actively looking for to purchase again.
 
2) Personalisation depends not just on knowing the customer when
they’re added to your database, but also continuously refreshing that
view as the customer’s life evolves. The couple who used to order a
case of wine every fortnight for dinner parties is now buying diapers and baby food.
Like your products, customer data has a sell-by date.
 
3) Dynamically picking up triggers from the customer – are they
exploring other brands? Have they started actively looking to purchase?
Has their sentiment towards your own brand dipped? Were they fervent
fans interacting with your brand online, but suddenly stopped?
Companies track NPS scores across all their customers – could they track it individually?
A constant relationship with the customer based on trust is required,
where the customer is happy to share a constant stream of information
about themselves, for example through twitter or facebook.
 
4) A retention algorithm that based on signals generated from (2) and
(3), is able to identify what stage of the retention process a customer
is in, and send targeted and personalised content and marketing. Of course at some point a customer may become an advocate – but you still need to concentrate hard on how to retain that advocacy.
 
Like an excellent butler, a retention algorithm should always know everything
about the customer, from their likes to dislikes, their favourite
topics of conversation, and anticipates their needs even before they know it.
 
I think the “butler” bit appeared quiet late into the evening! If you’re interested in discussing retention and advocacy and our point of view and solutions don’t hesitate to contact me, sherif.choudhry@capgemini.com.

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