Due to the diversity of customer data today, one gets an ever better insight into the customer behavior. By means of the customer value or customer lifetime value (CLV), even an insight into the future is possible. This considers both the historical turnover and the customer potential, i.e. the anticipated sales. Thus, the CLV is the most potent figure among the KPIs in customer relationship management. By means of the CLV, it can be measured how "valuable" a customer is who is addressed via a certain sales channel. In addition, by means of the CLV, one recognizes how successful a measure such as e.g. a campaign is, and is thus able to control one's budget accordingly and implement process optimizations in customer service. Thus, the CLV is the key for more intelligent and long-term customer engagement and win-back. In addition, potentials for cross- and upselling can be recognized and customers who have a negative effect on the revenue, e.g. by means of regular returns, can be identified. Thus, the customer lifetime value is not merely a purely academic feature, but also an indispensable indicator in practice.
Increasing customer loyalty by means of the Customer Lifetime Value (CLV)
On 14. January 2016 from 11:00 am to 12:00 pm, you will have the possibility to learn from Dr. Michael Allgöwer, Head of the Competence Center Data Science with b.telligent how to optimize your customer loyalty by means of the CLV and, where applicable, win back lost customers. The presentation is designed to help you to evaluate the potential benefit of the CLV for your business, understand the differences of different variants of the indicator and give you an insight into how the CLV can be integrated into existing processes.
Practical examples by expert Dr. Michael Allgöwer
Dr. Michael Allgöwer has more than 15 years of experience in the area `data science` and `business intelligence` and has been managing the Competence Center Data Science of b.telligent, one of the leading management consultancies for business intelligence, customer relationship management, data warehousing and big data in the DACH area, for a number of years. The mathematics graduate is an expert for predictive analytics and forecasting and will accompany you through the webinar with practical tips and tricks.