Customer Retention Optimization
Retain your customers with machine learning,
with an added human touch
With the help of modern machine learning solutions, we provide real-time personalization of your offerings, content, and messaging to your customers, giving them a cohesive experience across all channels and devices, to improve your customer retention and lifetime value.
Businesses often place so much focus on finding new customers, that they neglect to cater to the needs of their existing client base. This can become a never-ending tug of war, where the exodus of existing clients threatens to outpace the influx of new ones.
Obtaining a new customer can cost your company up to five times more than retaining an existing one. It is fairly easy to lose an existing client after just one or two bad experiences.
Businesses that choose to ignore opportunities enabled by recent advances in machine learning risk falling by the wayside as their customers flock to the competition.
Knowing in advance which customers are most likely to churn and applying preemptive measures can protect your revenue in the short run, and ensure customer loyalty in the long run.
Enhancing Customer Journey
A comprehensive review of the customer journey, and the data associated with it allows for a better understanding of the value proposition, and the role of customer personas including their pain points, needs, and behavioral patterns – a prerequisite for building an effective Customer Retention Optimization solution.
ML Powered with Human Touch and Common Sense
While machines are best at recognizing patterns and insights, humans alone are capable of interpreting and understanding them.
With the abundance of data available on each stage of the buyer’s journey, we are capable of building ML-driven solutions for personalization, precise targeting, and context-relevant engagement activities. Combined with behavioral science and meaningful UX-design, these solutions ensure high customer retention rates.
Provectus is a one-stop-shop solution, possessing key competencies essential to solving a problem of customer retention:
Driving Customer Lifetime Value Through Technology
Marketing, Product, Customer Relations Team
“Next Best Action”
Understand — Predict — Personalize
Eight out of ten consumers who leave one company for another say they would not have switched if the primary company had done something differently to entice them to stay.
You must personalize to stay relevant and therefore make your customers happier. Our ML system is able to suggest the “Next Best Action” for each customer at critical points of their journey with your product. Personalizing the customer experience alone will noticeably boost customer retention, right away.
Go beyond personalization with predictive analytics, to know in advance which customers are about to churn. Finding indicators of decreasing customer satisfaction with ML algorithms enables us to identify “risky” customers early on, and target them with personalized re-engagement measures.
Key Benefits of Customer Retention Optimization
Predict customer churn
and increase customer
of products/services inventory
You Cannot Improve What You Cannot Measure
Customer retention optimization impacts the following key business metrics:
It is crucial to empower non-technical teams who will use the solution by giving them insight into new personalized customer experiences. Tracking customer behavior helps determine the best ways to offer personalized recommendations to your customers, and it allows to measure the effectiveness of personalized experiences.
Amplitude is a product intelligence tool that handles behavior analytical tasks, saving engineers valuable time. Amplitude provides product teams and marketers with real-time, easily customizable dashboards, to quickly understand where personalization is effective and applicable. It helps make appropriate changes as user behavior changes, without relying on guesswork and delayed performance metrics.
In most cases, integration of behavioral analytics is straightforward and does not affect your current corporate data architecture.
Fast Proof of Value
We conduct a workshop and proceed with fast Proof-of-Value development. You will be able to see the first proof of value in just 4 weeks after the workshop. The paperwork usually takes longer.
POC in a Box Framework
Provectus runs several assessment sessions with customer stakeholders to define goals and success criteria, check your organization’s data readiness.
Provectus explores potential use cases, builds initial models, and evaluates the metrics. All active models are evaluated to outline the path to production.
Provectus runs the model to test how it interacts with real-world data from your application. The model is fine tuned to improve performance.
Provectus evaluates A/B test results against initially defined goals and success criteria. The next steps required to move POC to production are provided.
ML Infrastructure for Personalized Video Recommendation
FireworkTV reduces infrastructure costs and improves performance of its video recommendation system