Tag: personalisation
-
Why do customers rate your personalisation worse than you do?
You think you personalise well. Customers do not agree. You grade effort, they grade outcome. Close the gap by measuring the customer side.
-
How do you personalise without crossing the creepiness line?
Personalisation feels creepy when you use data the customer did not expect. The fix is a rule of use, not less data, and a value exchange the customer can see.
-
Why does identity resolution fail, and how do you fix it?
Identity resolution is the layer every other data project stands on, and the one most teams skip. Below 60% coverage your personalisation and attribution are guesses. Build the spine deterministically.
-
How does poor data quality undermine AI, and how do you fix it?
Feed a model bad data and it scales your errors instead of your revenue. Poor data quality costs the average company 12.9 million dollars a year. The fix is a habit, not a one-off cleanup.
-
How do you handle consent and privacy without killing personalisation?
Privacy rules feel like they block personalisation because consent lives apart from the profile it governs. Treat consent as a first-class data type: captured once, enforced everywhere. Then it stops fighting revenue.
-
How do you keep messaging consistent across every channel a buyer uses?
Every channel keeps its own copy of the message, so they drift apart. Fix it by unifying content at the source, backing the self-service buyers prefer, and adding a channel only when it reaches someone new.
-
Customer Data Maxxing
Use your teams energy to maximise your customer data. Everyone’s “data-driven” now. Sure they are. And yet most mid-sized businesses are sitting on years of customer data and using a fraction of it. It’s the gym membership of business assets — paid for, rarely touched, vaguely guilt-inducing. Here’s the maths that should annoy you. You’ve…