Align your product offers on the website and in e-mails with the customer profile and increase sales based on data mining
Benhauer provides an analysis of customer behavior on presale stage and analysis of transactions in order to identify patterns of customer behavior and to build product recommendations with the highest conversion rate. We perform customer segmentation based on statistically significant data on their profile and create mechanisms to adapt product recommendations best suited to a specific customer profile.
Transaction analytics and design of predictive next best offer mechanisms includes:
- analysis of historical data about interest in specific products
- analysis of historical data on transactions made by existing customers
- information about the impact of demographic and behavioral factors on purchases
- continuous optimization of mechanisms applied on the basis of changes in consumer behavior
Analytical methods for the service:
- cluster analysis – isolation of compatible groups within the customer base with similar characteristics (age, gender, product categories, expenses) for the purpose of segmentation and differentiation of the subsequent communication
- basket analysis – an indication of hidden, recurring relationships between products that are being bought and determination of the probability degree of purchase of product A in the case of purchase of the product B
- sequential rules – indication of the buying behavior based on the sequence of historical events such as visiting a website, or previous purchases in order to enhance the effectiveness of up and cross-selling
The result of the transactions analysis is a report containing information about significant in terms of sales, customers segmentation and their key regularities of buying behavior. The data collected in the report can be used to map out a strategy of communication with different groups of customers.
Based on the data collected we build predictive next best offer mechanisms, which continuously analyze customer behavior and modify the way the selection of products in the recommendations for use on the Web page and e-mail communication.