Martech expert unpacks the true cost of messy Customer Data

Customer data is the primary need for today's businesses for product personalization. How can this data be structured to derive value? If you know your customers so well, then why do you keep treating them like strangers? It’s a conundrum marketers, brands and retailers face every day – and a challenge they are desperate to solve. In its simplest form, the issue stems from the cost of messy Customer Data or rather ‘dirty data’. This fragmented data is muddling their efforts to get a clear view of who their customers actually are.

Consider another incredibly common scenario: your brand just received a new online buyer called Victoria. You send her your welcome series. At the same time, another in-store customer called Vicky hasn’t purchased from you in four months, so you send her discounts persuading her to shop with you again. Here’s the kicker — Victoria and Vicky are the same person.

Data data everywhere, but where is the personalisation? - Customers provide businesses with a wealth of data — from loyalty programs, to transaction history and email  engagement. But the tricky part is making sense of it and then putting it into action. Quality data fuels consumer business and opens the path to delivering personalised marketing experiences. However, companies can’t personalise campaigns when they don’t know who their customers are.

Not knowing your customer costs more than you think - The cost of not knowing your customer is high. More so than annoying customers with promotional emails for products they already own, blasting them with ads for clothing they don’t like, or placing them on hold for 45 minutes as a customer service representative tracks down their details when they want to return a pair of shoes; this disconnected view of the customer is impacting the bottom line – to the tune of US$11 billion, in some cases.

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