Acquire new customers

Bring together customer and market data from new sources to target the best prospects. Tailor products to address emerging market opportunities and shifting customer tastes - both at the aggregate and individual levels. With Neo4j, an innovative e-commerce company engages customers with highly personalized, real-time product recommendations across all products and vendors in their store with analytics and recommendation algorithms examining individual customers and customers in various aggregates performing billions of calculations per millisecond to unearth the products that most closely match the taste of even a first time customer.

Grow existing relationships

Bring together fragmented data, isolated to different products and business units to better predict future purchases from your customers. Identify and close additional sales opportunities with existing customers. With Neo4j, one of the world's largest communications company overcame processing bottle necks when querying real-time on a rapidly changing, highly connected dataset with very high activity spikes to increase customer stickiness by enabling real-time interaction during live sporting events. This interactive and social offering paired with their existing product offering provided a new channel for reaching customers with information, promotions and ads.

Retain valuable customers

Consolidate existing data with new data types and deliver consistency across different analytic tools. Coordinate and enrich customer-facing activities across multiple touch points to improve the overall customer experience. With Neo4j, one of the world's largest professional networks company was able to improve customer responsiveness and ultimately retention by, moving away from pre-compute batch processing recommendations that took longer than a week to compute, which resulted in stale data being used to surface recommendations and state of connectedness between professionals. The Neo4j cluster implementation improved customer responsiveness by enabling real-time recommendations and connectedness data to be surfaced to customers immediately as the network changed.