SIFT ENGAGE

Real Time Contextual Action Engine

 

Design and automate complex multi-wave customer engagement programs (journeys)​

Customer Engagement Programs

  • Design and automate customer journeys with any number of engagement waves

  • A single engagement program can support:

    • Outbound engagement

    • Inbound engagement

    • or both

  • Segment based decision making

  • Next best offer based decision making

  • A/B testing

  • Deploy gamification strategies

  • Automate fulfillment within a customer journey

  • Multi-channel engagement

Next Best Offer / Action

Execute next best offer/action models either when engaging customers via push channels or within channels as customers are interacting.  ​
 

NBO decisions are made at the moment of interaction and based upon the customers real time profile ensuring a contextually relevant engagement at all times.
 

Marketers just need to manage their relevant offer calatlogues and data scientists the NBO model in either R, Pythin or PMML.

Gamification Offers

Improve customer engagement by employing game principles within campaigns.  Sift enables the design and deployment of engagement programs where long running individual challenges can be presented to a customer and monitored in real time.  

Customers can check their progress for each challenge as they go and see how far to go to claim bonuses or reach the next level of each customer engagement program.

  • Intelligent individual calculated challenges

  • Long running challenges

  • Multi-Level Challenges

Reminders

Maximize response rates through a flexible and contextual reminder framework.  
 

  • Scheduled Reminders: sent at pre-scheduled times until an offer is taken or expired.
     

  • Activity Reminders: sent when a defined activity takes place e.g. customer just turned their device back on, just reloaded, just made a call, just used a channel, etc.  
     

  • Partial Reminders: sent when a customer reaches a threshold within a conditional challenge e.g. sent when they reach 70% of that target.  

A/B Testing

Automatically split the offers that customers are presented with to test and learn which variations are the most effective.  

Marketing Product Catalog

Manage marketing rewards or bonuses whether it be core products/services, vouchers, coupons or loyalty points.

Products can be easily attached to Offers and automatically fulfilled according to defined conditions.

Omni-Channel Policy Control

Define and automate consistent real time contact policies across all channels.

At each contact decision moment determine whether an offer should be presented or suppressed.  This can be based on the last time the offer was presented, other active offers, whether an offer has been viewed, active or taken.

Contact policy management at three levels:

  • Global policy level

  • Channel policy level

  • Category policy level

Insights

  • Live reports: to ensure campaigns and offers are performing as expected, especially just after launch or after optimization changes, the performance can be monitored on live charts.  Live charts are particularly helpful for intra-day monitoring.
     

  • Historical reports: intuitive self-service reporting to get various views of campaign performance over time to assist with customer engagement strategy optimization and planning.

Component Architecture

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