For a publisher in the Netherlands, HUMAI’s solution was used to drive more value from their existing customers, whilst saving cost. The publisher’s team had the need to identify and deliver a relevant message & offer to the right individual, at the right time and in the right place. Additionally, the marketing budget was under pressure, which made it challenging to achieve their sales goals.
REACH RELEVANT CUSTOMERS
An important source of revenue is generated by customers that have a magazine subscription. Whilst the number of new customers that get a first subscription is high, the number of people that cancel their subscription (churn) is high as well. An important insight is that customers who have two or more magazines tend to keep their subscriptions for a longer period of time. Therefore, several lifecycle campaigns are in place to persuade customers to get a second subscription. However, due to several cost savings, the team was forced to find smarter ways to run their cross-sell campaigns in order to meet their sales targets.
HUMAI’s software centralised and harmonised all relevant customer data from various disparate systems. Pre-developed algorithms created a profile based on historic activity and scored the potential of every individual customer. In this automated process drivers, or attributes, were identified that influence customers’ purchase behaviour. This was then used to produce a ranking based on the likelihood of customers to convert to a second subscription at a certain point in time. To establish a cut-off point for which customers to contact, the below insight was produced. It shows that contacting 42% of the customer base, instead of 100%, which was done by default, results in approximately 60% of the total expected up-sell transactions. The graph also shows that using HUMAI’s customer segmentation module led to customers converting to a second subscription at almost twice the rate as randomly targeting the full customer database.
In addition, these results suggest there is also a potential to gain value from customers that are less likely to convert. Several options could be explored: 1) contact this customer segment through other marketing channels, 2) orchestrate messages through multiple channels, 3) identify the most optimal time-of-contact or 4) determine price sensitivity and adjust the offer accordingly.
The use case showed that marketing effectiveness can be dramatically improved at a lower cost. Up to 60% of cost savings were realised by ranking customers on the likeliness of converting to a second subscription for the next few weeks.
By using algorithms to determine potential for up- and cross-sell on an individual level it becomes possible for businesses to create a distributed omni-channel strategy to engage customers, drive value and lower costs. It also enables a segmented approach in campaigns based on customer ranking by not engaging customers that are not ready. But instead reach them with different marketing strategies and – campaigns to increase the potential before selling.