customer retention

Solutions

Approaching customers during the customer lifecycle

Customer Upsell / Cross-sell

When approaching customers during the customer lifecycle, the key consideration is customer value for the company. For high value customers it is worth spending more time and resources in servicing, marketing and support. The most valuable customers are the ones that are buying new products, actively using them and staying loyal to the organisation. Cross sell and upsell are ways to increase customer value.

The magic of successful cross sell is to make a relevant offer to the right customer at the right time and using the right communication channel. A solution to this problem is not easy and involves a lot of analytics. Models used in this context are mostly Propensity to Buy, Campaign Optimisers, Customer Segmentation, Customer Lifetime Value.

Propensity to buy

One of the basic approaches to cross sell and upsell is propensity to buy. Propensity to buy (PtB) is a statistical model predicting the purchase of a product or service in a predefined time horizon in the future. PtB models are useful in situations where you want to run a direct marketing campaign with limited resources and you need to select a subset of your customers, to whom you make an offer. PtB model allows you to select the customers with the highest chance for success, which helps you to optimise the ROI of your campaign (see the illustrative graph).

When you dive deeper into the campaign problem, you find out that you need to predict customer response in two different scenarios: 1) offer made, 2) offer not made (spontaneous purchase). For this, we develop more advanced Net Lift PtB models. To make matters even more complex, in reality you deal with multiple products to be offered, multiple channels and multiple time points that we can use to make the offer. In such scenarios you take PtB and Customer Lifetime Value models as inputs and solve complex mathematical optimisation problem to make your campaign most effective.

Propensity to buy

Cross Sell Campaign Optimisation

Deloitte’s campaign management offering focuses on direct marketing campaigns for existing customers and aims to maximise the expected gain of the direct marketing campaign in the complex scenario of multiple products to be offered, multiple channels and multiple time points which can be used to make the offer. The business value of this offering is the most efficient use of the limited marketing resources in order to target only the subjects with the highest propensity to buy and with the highest potential revenue. This also implies avoiding too frequent offers that are perceived negatively by customers, since the propensity to buy in this case is low (captured by the propensity model), and therefore the campaign optimiser does not include those customers in the next campaign.

Cross Sell Campaign Optimisation

Customer Segmentation

While the service needs of the customers remain individual, it is more and more difficult to approach customers individually through centralised operations. Customer segmentation identifies groups of customers that are similar such that when you apply different service approaches to limited number of customer segments; it is the optimum compromise between the benefits of the centralised operations with the individual approach to each customer.

Customer Segmentation

Customer Lifetime Value

Customer lifetime value (CLV) is the expected value of the future relationship with a given customer. The potential value of a group of customers or of the entire customer base is called customer equity. The calculation of customer lifetime value has four components: lifetime duration, cash in, cash out and the discount rate as illustrated below.

Based on the input data, we build customer micro-segmentation and customer profitability model using homogeneous Markov chains. The CLV model can be used together with a churn model in a matrix to identify the target group eligible for a marketing action, which is usually a contact with a special offer.

Customer Lifetime Value

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Jan Balatka

Jan Balatka

Director

Jan Balatka has extensive experience in Data Analytics, Forensic Analytics and Electronic Data Discovery. He has international experience from projects in Switzerland, Germany, the U.S., South Africa ... More