Customer Behaviour Models
Customer Behaviour Models crucially empower businesses to accurately predict customer behaviour. Here are some of the key benefits:
forecasting of customer lifetime value
predicting customer propensity to churn
predicting customer product preferences
forecasting the profitability of marketing campaigns
sending highly-specialised campaigns to target audiences
and much more
It is essential to a robust and cost-effective CRM strategy.
How we can help
We specialise in data scientific models within retention and upsell - most notably AI-powered machine learning models. Our vast experience in this field has resulted in numerous successful results for businesses (examples found here). We offer various Customer Behaviour models, here are a few of our popular solutions:
Customer Lifetime Value Model
Customer Lifetime Value (LTV) is a forecast of a customer’s lifetime spend with a business. With advanced AI and machine learning techniques, we are able to accurately and precisely predict the lifetime value of a customer . We use all the data available about your customers - including spending patterns, demographics, acquisition channel and product preferences - and from there, determine which variables are the strongest barometers of Customer Lifetime Value.
Having an accurate & robust forecast of the lifetime value for each and every one of your customers is a powerful tool in determining which customers should be targeted for spend-stretch or reactivation campaigns. It is also extremely powerful in determining the success and effectiveness of acquisition spend as it allows our clients to determine whether they are onboarding genuinely valuable customers.
Product Preference Model
Product Preference is a forecast of a customer’s preferences towards the various products a business sells. Using AI, we provide a scoring breakdown across all the products a client sells. This sets the foundation for an analytical approach to product cross-sell campaigns and product risk diversification.
Product Preference is also hugely important in a customer’s welcome journey. In order to maintain engagement and build brand loyalty, it is important that a business markets a product that the customer will actually like.
Propensity to Churn Model
Predictive to Churn is a forecast of a customer’s propensity to churn. Using AI, we provide a score denoting the likelihood that a customer will churn/lapse in the next 30 days (or relevant timeframe for the business in question). This is a tremendously powerful tool in keeping customers engaged. Our clients use the Propensity to Churn model to also build a comprehensive picture of spend frequency.
Customer Segmentation Model
A one-size fits all marketing strategy often produces mixed results. CRM campaigns work for some customers and don’t for others. In order to maximise the efficiency and effectiveness of CRM campaigns, businesses use Customer Segmentation.
Customer Segmentation is the powerful strategy of dividing customers into smaller groups that share similar characteristics. Once these groups have been created, businesses can start employing analytical, customer-centric and ROI-driven CRM campaigns.
It is vitally important to have a robust and data-driven process when segmenting customers into groups. If customers are not split into groups appropriately or effectively, the impact of Customer Segmentation on the effectiveness of CRM campaigns will be limited or negligible.
We offer a Customer Segmentation model that uses advanced AI to group customers based on their lifetime value and various statistically significant customer characteristics. We usually use the statistical technique of clustering. Customer segmentation is one of the key fields we specialise in within marketing strategy. Our data-driven approach has produced impressive ROI results for our clients (results can be found here).
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