Event-based marketing (EBM) & CEP use cases for CRM

Updated: February 3, 2020

Introduction – The Key Event Types

First, check out my latest article on this topic recently published: Shush – Listen for customer signals with event-based marketing & service —- Out of that article surfaced these distinct event categories:
Event Category Example
Account status Average bank account balance trending down (by X standard deviations)
Behavior-Account Roaming charges incurred or within x% of the limit
Behavior-Device Failure of device/machine
Behavior-Person Digital browsing – showing purchase interest/intent
Calendar Major shopping holiday approaching
Contract-Account Changes in the account/contract terms & conditions
Environmental Severe weather alert – hurricane warning
Forecast Model score updated – Churn/attrition score rises above a threshold
Inactivity No activity (of a certain type) in the last 30 days – e.g., no deposits
Law/regulation Change in the overall privacy policy
Milestone Birthday – Age changes (milestones such as 18, 55, 65, etc.)
Product/Service Replenish – consumable products, such as printer ink
Product-wide/Service-wide The interest rate on all accounts of type X increases by x%
Profile-Person Investable assets increase (or decrease) by x% (or crosses a threshold)
Transaction status Order status change (disruption in availability, timing)
Below you’ll find an inventory of event-based marketing (EBM) and complex event processing (CEP) use cases for customer experience management.  In each, the system senses behavior and alerts a user or another system to the unusual activities or conditions that warrant further investigation or action.

Vertical Complex Event Processing Use Cases

Fiserv: Consumer Banking and Credit Cards

  • Unusual account activity (e.g., large deposits/withdraws)
  • Unusual account activity trend (e.g., average daily balance down by two standard deviations)
  • Inactivity pattern (e.g., no transactions in last week)
  • Missed transaction (e.g., missed direct deposit)
  • Credit card spend activity use pattern (by spending category)
  • Insufficient funds pattern
  • Web or mobile click activity indicating an interest in a product

Insurance

  • Fraudulent claims activity

Operations

  • Predictive maintenance systems

Media and Communications

  • Dropped call pattern or degradation of signal/service
  • A customer has increased roaming (or other unusual account usages) behavior
  • Customer in route to a foreign country pattern
  • Popular programming based on a set-top box and social media insights
  • Prepaid consumption detection and stimulation
  • Churn detection

Healthcare

  • Claims fraud
  • Care interruption pattern
  • Fitness monitoring
  • Hygiene procedures pattern
  • Healthcare patient monitoring

Horizontal Complex Event Processing Use Cases

Customer Service Center / Retention Department / Loyalty

  • Customer struggling to get help pattern
  • Payment due
  • Strange returns activity
  • Customer likely wants to cancel service
  • Customer’s birthday
  • Customer’s service anniversary (e.g., been a customer for X years)

Marketing / Cross-sell & Up-sell

  • Customer online interest in a product or service
  • Customer in store interest in a product or service
  • Customer in the proximity of a store
  • Customer usage stimulation – Drop off in use of a product/service
  • Increase in use of a product/service
  • Loyalty Program – Monitoring points activity
  • Loyalty Program – Monitoring points expiration date
  • Monitoring social sentiment
  • Monitoring social influencer

Non-CX use cases

Here are some examples that are not for CX, but instead to improve business and operations efficiency:
  • Algorithmic stock trading such as if Stock A rises by X% and Stock B doesn’t automatically buy Stock B
  • Transportation security and fraud detection such as an id card used twice in a short time frame (e.g., piggybacking) or high volume transactions on a new account – and then automatically alerting the right parties
  • Detecting transportation congestion and incidents, and proactive notification of alternative routes
  • Inferred detections suggesting that a vehicle has crashed (and severity of crash), such as when an airbag has deployed
  • Communications security such as false alarms going off in a certain time window, not followed by other alarms that would be expected (false positive alarming)
  • Communications security such as network monitoring for detecting denial of service attacks, and alerting the right parties of this situation