The Future of Loyalty Technology is Here
Standard predictive models within our loyalty solution technology use AI and machine learning scoring as part of the model training and operation. Models are built using structured and unstructured data housed in our loyalty platform database to optimize the predictive power of model scores. The output of the advanced models is a customer-centric model score and percentile ranking that can immediately be used by our segmentation engine.
Machine learning and AI allow us to capitalize on a wealth of collected customer data. This is done at scale, in a fraction of the time and with a greater accuracy than traditional rules-based modeling. These tools are used to create models for predictive churn, fraud prediction, customer journey classification and customer journey prediction.
SmartJourney® Prescriptive Diagnostics
AI and machine learning tools overlaid with data from global benchmarking data gives marketers deep insight into predicting customer behavior amongst key SmartJourney® milestones. This enables marketers to influence behavior to scale. It even uncovers hidden revenue streams and opportunities or gaps within the business for additional growth or efficiency.
Detecting and Predicting Fraud
Each business has to decide how they will manage potential fraud within their program. With predictive fraud modeling, algorithms score the likelihood of fraud in the program, while detecting anomalies, auditing and logging incidents and flagging inconsistencies within the system. This data gives your team the resources to decide how to approach and manage fraud.
Automated Triggered Communications
Scale with authenticity, with the help of AI and machine learning tools, to communicate to customers at the right time, in the right channel, with the right message
- Actionable insights in a fraction of the time and effort of rules-based analytics
- Intelligent optimization through the SmartJourney® methodology gives marketers the tools to develop the right strategy
- Predictive modeling tools allows marketers to analyze behavior and engage customers in ways that inspire them along their journey
- Continued test & learn capabilities are scalable with machine learning and AI tools
Executive teams that make extensive use of customer data analytics across all business decisions see a 126% profit improvement over companies that don’t.
The 4 Analytics Tools Marketers Need
Successful brands use data to direct business strategy, optimise customer journeys and craft relevant content to build long-term relationships.
How Big is Your Churn Problem?
Once you define your churn, before you set targets and compare to industry benchmarks, reflect on your core business KPIs and the maturity of your program
Predictive Churn Modeling: Improve ROI & Reduce Marketing Costs
Most business leaders know that new customer acquisition can be a challenge, with significant costs of acquisition during the process of marketing as well as the costs of effective onboarding.