Methods: team is communicating the upcoming actions accordingly

Methods:

·     
Methods
that drive contextual insights are in early stages. Emerging methods such as sentiment
analysis, location analysis, and device usage analysis are in early stages of
development, but they have the potential to provide valuable context around
behavior and other customer analytics methods.

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·     
Methods
that drive personalization will enjoy significant success. Analytical methods that drive personalization,
such as next-best-offer analytics, will enjoy more success because they enable
the vision of executing insights in real-time and on a one-to-one basis.

·     
Established
methods fall into the Growth phase. More well-known analytics methods like behavioral customer
segmentation and customer churn and attrition analysis will gain more adoption
because of their potential to use enhanced customer data from Big Data sources
as well as leverage new data science approaches.

 

During merger:

1.) Migration support
levels and customer migration schedule

A specific migration
support system should be set up to provide support to the customers during the
process of merger. Each individual customer adds profit to the business so its
very important to retain them. Analytics help to identify the level of support
the customer should receive throughout the conversion through identifying
various factors such as  product and service
usage value, level of customer migration complexity and business demand.

Specifically, the customer segmentation modeling
helped to optimize several integration activities:   • Reporting—ensuring the highest migration
support levels are highlighted in a consistent manner for planning purposes and
the migration support team is communicating the upcoming actions accordingly to
the segmented customers.

 • Scheduling—segmented
customers should be scheduled for the specific events according to their locations
and functions so they feel they are important to the new company and stick to
it.

 • Support
model—creating dedicated support resource teams for each migration support
level that are trained in the unique features of their respective customer
groups.

The schedule allowed for effective pre-event migration
testing and post-event customer support. It also incorporated systematic
tracking of customer readiness based on the successful accomplishment of
pre-migration activities. Any customer or customer group deemed not yet ready
for a “standard migration event” was excluded and reassigned to future
conversion events.

2.) Customer impact
timelines and communications

Organizations can leverage analytics to create
customer impact timelines. Such timelines allow an organization to identify
customer groups that will undergo a high number of merger-related impacts
during any given period.

This timeline enabled the bank to clearly identify
particular customer groups that would, over the integration lifetime, undergo a
significant number or percentage of positive and negative impacts. It also identified
the phase when a customer would experience several consecutive negative impacts
(thereby increasing the likelihood of attrition). Based on an understanding of
negative impacts, the integration planning team proactively built mitigation
plans or “safety nets”—such as the careful timing of positive-impact
communications (e.g., bundled mailings) and promotions to strengthen customers’
experiences at key times. Identification of these customer impacts helps
companies, in turn, proactively plan and execute customer support models and
resource alignment to provide the appropriate level of support at the right
time.