What Value is Hidden in your Customer Data?
As the adoption of CRM and marketing automation matures, it’s no surprise that companies with these technologies are sitting on a wealth of data. Leading organizations often hook in internal usage and external social data to empower sales & marketing staff in their decision making, using AI in customer data and cost adjustments according to each campaign ROI. Unfortunately there is only so much data a human can process and interpret. This is where machine learning comes into its own.
According to Forrester 89% of Sales and Marketing Departments now have predictive on their roadmap to improve their customer cycle and adjust in real time their business proposal, what about you?
“The Data-Sphere Value to accelerate growth” gives you the keys to fully exploit the potential of your customer data using AI:
- What value is hidden in your customer data?
- 4 steps to predictive Sales & Marketing
- How does Artificial Intelligence work?
- The value of the Data-Sphere
CRM, back-office interface and digital marketing tools are just examples of the data sources companies now have to manage. This information are highly valuable to analyze purchasing tendencies, understand customer experience and make cost adjustments according to each campaign ROI to anticipate launches and limit risks.
Digital is considerably changing companies’ knowledge of their customers and the associated value. To develop their revenue, companies put the customer at the heart of their strategy and use artificial intelligence on Big Data to understand and target the market better, find hidden information and predict tendencies.
How Does Artificial Intelligence Work?
Marketing Departments traditionally estimate the future value of a client through numerical average based on the results of the past year, current economic index and estimations from the coming year’s strategy.
Machine Learning algorithms exploit internal and external data to identify new prospects, scored by similarity with the ideal customer profile and according to their purchase likelihood. By analyzing the constantly evolving scores of prospects and customers, companies can adapt their communication, following the interest level and the detected priority. Artificial intelligence provides new levers to decision-makers and empowers them to focus on operational tasks and grow business.