Case

USING CUSTOMER DATA TO INTELLIGENTLY MANAGE CUSTOMER CONTACT WHILE BALANCING

POTENTIAL REVENUE WITH COSTS

Develop a mechanism to drive intelligent customer contact using customer data to balance

the sales and service strategies and the best interest of the customer to sustain a long-term

relationship

More intelligent customer contact

with customer profiles

A large financial institution had just completed a successful sales stimulation project in their cus-tomer contact center. Now the challenge was executing “smart” strategies in terms of how consumers were handled: selling when “next best sell” rec-ommendations were present, de-livering excellent service when retention issues were involved and handling the base customer as efficiently as possible when no opportunities or issues were pre-sent.

Approach Using existing customer profile data, a contact strategy concept was built incorporating key ele-ments of sales, service and effi-ciency:

Customers who had a “next best sell” assigned to their profile were treated as cross-selling leads

Customers who were high-value and seen as a retention risk or had not bought addi-tional products in longer than 3 years, were given a “service” treatment

Impact

Sales in the target segment for selling increased 175% in the test group versus the control

group

Talk time decreased by more than 20% in the target efficiency segment test group versus the

control group

study Turning

Thought Into Action

Critical Success Factors

Multi-disciplinary

team working to-

gether to develop a

workable model for

piloting

Pilots on different

business lines to de-

velop and refine

work instructions

A team of agents and

supervisors who

acted as advisors to

refine and revise the

work instructions

and the segmentation

model

“Personalized service in both sales and service”

The organization began to use the customer data that was

available to them and treat customers according to the

strategy assigned by Marketing

Customers who had no “next best sell” assigned and had been profiled as low potential were handled as efficiently as possi-ble, answering only the question that the customer asked and nothing more.

Segmentation and coding Business rules were defined to-gether with Marketing and Market-ing Intelligence in order to match the strategies to the customer pro-files. A code was implemented in each customer profile, giving agents instruction upfront as to which ap-proach they should use with the customer. This meant that the agent received a non-binding “hint” upfront as to the service approach, though they were free to respond to the customer as required in the con-versation. Pilot implementation Agents were trained to check this code when beginning a conversation with a customer. Agents were given relative freedom in how they ap-plied the strategy in the customer dialogue so long as they stayed true to the meaning of the strategy as defined upfront.

Pilots were conducted on one ser- vice line and one sales line, using a test and control group each time, to test the feasibility and the impact, and to develop and refine work in-structions to the larger agent popu-lation. The pilots used small groups of agents and supervisors to provide regular feedback and to help iden-tify successful tactics for each of the three customer approaches. Measurement and results Sales to customers who were identi-fied as sales targets increased 175% in the test group versus the control. In the efficiency group, talk time decrease more than 20% in the test group. Customer satisfaction was meas-ured also and this remained con-stant, indicating no negative effects of the piloted approach. Roll-out The approach was institutionalized across the customer contact center and the branch network.

EarlyBridge BV

Herengracht 518

1017 CC AMSTERDAM

The Netherlands

31 (0) 20 715 5918

info@earlybridge.com www.earlybridge.com