The right action at the right time for the right customer

Your customers see their relationship with you as one-to-one, and they expect that you do, too. As unique individuals, they don’t want to feel they’re getting blasted with marketing messages aimed at thousands or millions of other people. Obtaining continued loyalty requires doing exactly what’s right for each customer at each moment, be it making an offer, presenting useful content, or providing special customer service. Data science uses life-event patterns, buying behavior, social media interactions, and other insights to decide which actions should be taken for each customer increase loyalty, intensify interaction with your organization, and drive revenues.

Anticipate each customer’s needs

Use a holistic view of each customer and all available information to understand their present circumstances. Anticipate what each customer needs next to remain satisfied and loyal.

Increase conversions and purchases

When a marketing offer is the right next action, extend exactly the one most likely to be accepted – improving conversion rates and purchase volumes.

Create omni-channel experiences

Choose not just the right action and right time for each customer, but also the right channel through which to act. Avoid channel conflict and create a better customer experience.

Grow brand affinity

By ensuring every interaction is relevant, and includes more than just offers (service actions, content, etc.), you make customers feel they’re being served well by your brand.

Get started on your next best action project today!

View Other Use Cases

Churn Prevention

Identify customers likely to leave, take preventative action.

Customer Lifetime Value

Distinguish between customers based on business value.

Customer Segmentation

Create meaningful customer groups for more relevant interactions.

Demand Forecasting

Know what volumes to expect to improve planning.

Fraud Detection

Identify fraudulent activity quickly, and end it.

Predictive Maintenance

Predict equipment failure, plan cost-effective maintenance.

Price Optimization

Set prices that balance demand, profit, and risk.

Product Propensity

Predict what your customers will buy, before even they know it.

Quality Assurance

Resolve quality issues before they become a problem.

Risk Management

Understand risk to manage it.

Text Mining

Extract insight from unstructured content.

Up- and Cross-Selling

Convince customers to buy more.