Customer Insight

How do you turn data into quality, actionable, customer insight? It’s a given that we now have the potential to gather more data on customers than ever before. But what to do with it? When it comes to capturing and analyzing customer data the past remains a reliable guide to the future, but increasingly – through revolutionary techniques like uplift modeling – you now have the potential to use your customer insight to focus on the road ahead, not just the rear view mirror…

• Data visualization (or Visual Data Mining) is about taking complex analytical models and comparing them through simple, intuitive graphic representations. You can change and experiment with different data models ‘on the fly’ – driving a more creative way of thinking about customers. Data becomes easy to understand, act upon and share – which means greater customer insight, faster decisions and less reliance on analysts. Read more »

• Predictive analytics takes customer insight a step further by focusing on the future rather than purely the past. Traditional business intelligence tools can manually slice and dice historical data to reveal patterns that inform future marketing decisions. But they only tell you what’s already happened (with interpretation left to the skill of an analyst). Predictive analytics provides a window on the future based on how we believe customers will respond to sales or service offerings. Read more »

• Uplift modeling is a progressive customer insight approach that takes predictive analytics a step further. While traditional response modeling can tell you who is likely to respond to your campaign it doesn’t go into the detail of who is most likely to be positively affected. Uplift modeling makes this important connection, empowering you to target only the customer segments that will react positively to offers and campaigns - thus optimizing your marketing spend. Read more »