Optimize retail and eCommerce conversions with integrated advanced analytics.
At Blue Orange, we advise our clients on the best way to achieve integrated solutions. We've helped industry leaders in eCommerce and Retail shortening the effort to identify characteristics of the most profitable customers to empower marketing specialists to do what they do best: share your vision and gain devoted customers.
- Create a modern data warehouse that unifies customer data, website analytics, and enriched 3rd party consumer data.
- Apply data science algorithms to discover the predictive indicators that underlie customer behavior and optimal engagement processes.
- Integrate these insights in real-time to capitalize on predicted customer behavior.
- Dynamic Pricing and Price Optimization
- Real-time insights to engage on-site customers.
- Advanced Segmentation and Targeted Marketing
- Sell more with Recommend Products
- Acquire, re-engage, and retain devoted customers
- Predict supply and demand integrated with dynamic financial dashboards
- Integrate solutions with existing systems and supply chains
- Augment decisions with probabilistic inputs
Unified Customer Insights
Machine learning provides comprehensive predictions across the customer life cycle.
Influencing customer behavior is based on finding similarities
in different customer types. Identifying specific systematic
groups of customers can make marketing more precise.
Machine Learning is excellent at finding patterns in large sets
Behavioral Analysis is a system to help marketers better
understand how and why buyers act, as well as make more
accurate predictions based on that information. Analysis of
raw event data provides a more complete insight that
exposes opportunities to influence performance indicators.
A well trained chatbot can reduce operational costs
while increasing customer convenience and engagement. Conversational
marketing has been proven to increase conversion rates
while driving specific user behavior that is trackable. Chatbots
can be deployed at scale to engage customers in real-time.
Targeted and specific automated recommendations increase
cross-product conversion. A couple popular recommendation
models are derived from user-specific content-based data or
collaborative filtering, which identifies similarities between
groups of customers that made different purchases.