Marketing executives have to effectively manage campaigns so that the cost of acquiring customers is optimized and the campaigns yield desired results.
We use predictive analytics to help you target those who have a higher chance of responding to your campaign. This type of predictive modeling can be performed using a combination of techniques. For example, binary choice modeling, where the outcome is either 1 = positive response or 0 = no response can be used to understand how several hundred demographic factors, such as age, income, household size, home value, household location, etc. can be used to predict the likelihood of response.
Marketers can use these predictive models to identify the customers that have a probability of responding higher than a threshold; say 15% or even >50%. Using this type of approach will optimize the cost of acquisition and ensure that a desired revenue outcome can be achieved in a given period.
More solutions that help retail companies acquire new customers include:
- Behavioral segmentation to determine the actual customer demand segments
- Segment analysis for insight into buying behavior for specific customer groups
- Guidance to build targeted marketing campaigns for specific segments and the most appropriate way to deliver the messaging including direct mail, email, print, TV and internet marketing for each segment.
Relationship Deepening with Existing Customers
Acquiring customers is expensive and time-consuming and often companies don’t have the tools to maintain and deepen their customer relationships.
These solutions help companies develop existing customer loyalty:
- Segmentation and prediction tools to determine next likely purchase for groups of customers
- Customer behavior analysis, including nearest neighbor models (similar to the Amazon recommendation engine) to predict the next product purchase
- Sophisticated loyalty program management solutions to build brand loyalty and deepen relationships.