CUSTOMER ANALYTICS
Modern marketing is about understanding customers at an individual level. This level of strategic segmentation is a prime use of Big Data technologies and one of the big drivers for data innovation.
CUSTOMER 360-DEGREE VIEW
Customer Journey – Understanding the different interactions a customer has with your brand and product over time and across channels can help you to improve conversions, cross across organizational silos, and upsell additional products and services.
Examples of customer journeys include:
- Opening a new account at a retail bank.
- Shopping for new music online.
- Monthly billing for an online service.
Every discrete interaction provides your organization an opportunity to understand your customer and better provide them with exactly what they need when they need it.
Customer Acquisition – Strategic, focused marketing and advertising efforts can be made more efficient with proper analytics, resulting in lower costs for identifying and wooing new customers.
Customer Churn – Conversely, every existing customer retained is worth a new customer earned. Modern analytics can help your organization predict customer churn and understand which customers are at risk of leaving and what preventative actions may help to retain those customers. Customer Journey touch points can be particularly valuable for spotting the signs of churn and for preventing it.
NEXT BEST ACTION
Customer insights become gold if the business can plot the Next Best Action (NBA) – the appropriate course of action that matches the customer’s individual needs. Data-driven decisions beat gut feelings when it comes to consistent results. Predictive analysis finds the best combination of timing and marketing levers that elicits the most optimal response from the buyer. Call center operators can work off a list of “most likely customer concerns” before picking up. Visiting representatives can arrive to meetings prepared with the most appealing agenda. Customer-support agents can proactively offer assistance or promotional material before frustration builds.
The model itself can be retrained at the appropriately set intervals to remain effective. Through PMML (Predictive Model Markup Language), personalized NBA can integrate directly into operational systems such as marketing automation systems, call center software, consultation scheduling systems – anywhere automated or manual processes take place.