Customers’ relationships with brands are changing, becoming an ongoing conversation with multiple and continuous interactions. Customers now expect personalisation at every brand touch point, whether that’s in store or online.
Customers demand personalisation, especially in an age where we are exposed to thousands of marketing messages each day. Achieving this level of personalisation requires having a ‘joined up picture’ of each individual customer. However, customer data is usually spread across many databases, and is uninformative until unified in one place.
We unify a variety of customer data sets, such as transactional, marketing and online behavioural data to provide a holistic view of your data. This allows us to gain valuable insights about your customers by summarising a wide range of characteristics, such as buying behaviours and preferences. This information also feeds into our machine learning models to add further value by predicting attributes for every customer.
THE TECHIE BIT
The Peak AI System ingests all of the data you have about your customers, unifies it into one place, and performs automated intelligent transformations. We use supervised and unsupervised machine learning techniques, including tree-based models, generalised linear models and ensemble methods, in order to predict attributes such as time until next purchase and next year spend. These algorithms establish which factors are the best predictors of customer behaviours, where predictors can be factors relating to value metrics, online behaviour, preferences and engagement with marketing communications.
Our AI System identifies particular characteristics of customers (e.g. those who are likely to buy in the next week) and suggests the optimal way to contact them such as through email or social media. Alternatively, you can query the AI System with a list of attributes (e.g. those who have bought item X in the last month) if you’d like to find the best audience for a particular campaign. This gives you the ability to optimise communication strategies for each individual customer by showing them the content they want to see, when they want to see it, leading to improvements in purchase frequency and revenue.