Case Studies. 2 > © Teradata, 2008 Agenda Active Enterprise Intelligence 5 Call Center Areas for...
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Transcript of Case Studies. 2 > © Teradata, 2008 Agenda Active Enterprise Intelligence 5 Call Center Areas for...
Case Studies
2 > © Teradata, 2008
Agenda
• Active Enterprise Intelligence
• 5 Call Center Areas for Improvement With Analytics
• 5 Case Studies
• Taking Action
3 > © Teradata, 2008
Active Enterprise Intelligence
Helps You Make Better Decisions, Faster – Across the Enterprise
Strategic Intelligence:Great Insights about the Business
Align and Accelerate
Operational Intelligence:Operations People and Systems
Become Smarter and Faster
4 > © Teradata, 2008
Where Can Analytics Help the Call Center?
Screen PopACD
Monitor
ACD
Agent 3
Agent 2
Agent 1
Queue 1
Agent 3
Agent 2
Agent 1
Queue 2
OffShore
At Home
In-HouseAgent
Call
IVR
Can Analytics Help Here?And Here?And EvenHere?
5 > © Teradata, 2008
Credit
The ProblemCustomer Data Is In Silos … Everywhere
Business Unit A
WebChannel
Business Unit B
Call CenterChannel
Business Unit C
MailChannel
Business Unit D
SalesAgents
Marketing
Customer Profile
Website Call Center
Banking Sales
Planning and Retirement
Stocks FinanceAnnuities
Loans
Trades
Partner Info
6 > © Teradata, 2008
The SolutionOne Data Warehouse
STRATEGIC INTELLIGENCEOPERATIONAL INTELLIGENCE
MarketingFinanceProduct/
ServicesExecutive
MDM CRM OtherERP
Business IntelligenceTools and Applications
Workflow, Portals,and Applications
Web Kiosks SalesCall
Center
Data Warehouse
• Sales • Call Center• Finance• Marketing• Suppliers
• Customers• Channels• Products• Trades• Accounts
7 > © Teradata, 2008
Active Enterprise Intelligence Analytics
• Strategic Intelligence > Who calls?> Why? > Who eats up time?> What do they need? > What can we offer?
• Operational Intelligence > Consolidate customer
information for each channel> Single screen – all context> Smart dialogues> 2-4 next-best-offers> Call Center Agent and IVR
• Customer profile• Customer value• Churn probability• Segment
• Compelling offers• Products owned• Transactions• Buyer preference
• Contact history • Service records• Complaints• Emails
• Collateral• Sales kits• Scripts
Agent
8 > © Teradata, 2008
What Do Analytics Look Like?
Strategic Intelligence
ProductProfitability
RelationshipPricing
Propensityto Buy
Risk andProbability
of Fraud
CustomerResponses
NextBest
Activities
Strategic Insights
Operational Intelligence for The Call Center
How Profitable Has This Customer
Been?
At What Price
Will This Customer
Buy?
What WillThis
CustomerBuy Next?
What Is This
Customer’sProbabilityOf Fraud?
Will ThisCustomerReact on
This Channel?
Is This Customer Ready to
Buy?
Operational Insights
9 > © Teradata, 2008
How Can Analytics Be Used By The Call Center?
< >
<>
I see you made a large deposit 4/13/07. Do you have any plans for this? Can I suggest a high yield bond?
Did you know you are near your overdraft limit? Would you like to consolidate this into a term loan?
Personalized offers
Savings
Lending
Trigger X
Customer View
Cindy Bifano
1168 Barroilhet Dr.
Hillsborough, CA, 94010
555-954-5929
Customer Value score: 87
Attrition score: 32
Accounts
Household
Customer X
2181%6375
Hand offs
Sales$ TargetActualTarget
Offers Made
My Sales Targets & Scores X
Acct Age: 7 Last order: 01/15/07Last offer: B707
Renewals: 07/02/09 Affinities: e-Nest3Product links
04/21/07InboundCall Ctr
Customer History
04/18/07Outboundemail
03/02/07InboundCall Ctr
DateSummaryContact
X
!
!
708009838228
Joint account
Personalized Offers
10 > © Teradata, 2008
5 Areas Where Analytics Can Help
#1: Use Analytics to analyze what people are doing across all the channels
Move Simple Inquiries to Self Service (e.g., to the Web)
Simple Inquiries• Account balance• Frequent flier postings
Simple Transactions• Order flowers or a book• Make a stock trade • Book a flight
11 > © Teradata, 2008
5 Areas Where Analytics Can Help
#2: Use analytics to analyze what people want to do via the phone
Make the first options in the IVR the most relevant ones
• Match IVR selections to their purchases
• Match IVR selections to probable service needs
• Match IVR selections to marketing campaigns
12 > © Teradata, 2008
5 Areas Where Analytics Can Help
#3: Use analytics to drive queuing rules at the ACD
Deliver the best service to the best customers or high-potential prospects
• Faster queues• Educational or relevant
information while waiting • Connect to the best agents
13 > © Teradata, 2008
5 Areas Where Analytics Can Help
#4: Use data analytics to provide up-to-date status and analytical information to agents via dialogues
• Anticipate service problems, e.g., we “know” you had dropped calls this morning
• We “know” what kind of next best offer to provide, or service remedy
14 > © Teradata, 2008
5 Areas Where Analytics Can Help
#5: Use analytics to drive new management metrics: why people call, whether they are satisfied
Newer Metrics:• % first call solution … “One and
Done”• Holistic non-silo’d Caller Analytics
• Dialogue Refinement / Redesign> IVR and Call Script opt-out points –
where are we losing users?
Case Studies
16 > © Teradata, 2008
Situation
Increasing numbers of web banking customers. They sometimes need to call the Call Center with questions about transactions or help with how to use the Web Bank.
Problem
Call Center does fine under normal conditions, but surges of long calls cause queues, dropped calls, and customer dissatisfaction
Solution
Analyze and tier the customers (e.g., novices, experienced) and use that information to route calls to minimize long waits and maximize call center throughput. In the future, note where people are on the web before they call and use call waiting to dispatch to best available agent.
Impacts
• Faster call handling• Decreased churn of
high-value segments• Increased customer
satisfaction
Case Study #1: US BankAnalysis and Optimization of Pathways, ACD Queueing
17 > © Teradata, 2008Source: Gary Class, Wells Fargo, “Call Center Metrics: Who Calls and Why Do They Call?
Case Study: Smart Call Routing
Smart Call Routing
High propensity to buy caller
Arrivals
Lost calls• abandon• busy
Agent 3
Agent 2
Agent 1
Queue
Call sent to Agent
with sales skill set
18 > © Teradata, 2008
Case Study Impact
• Targeted campaigns: 3X more responsive than untargeted
• 90% lift in response to inbound marketing interactions
• 20% increase in activation from life-cycle messaging
• Phone bankers generate 4 times more revenue when routed high potential calls (plus training and incentive)
Senior VP, Customer Information and Analytics, Major US Bank – presentation at Partners 2007
19 > © Teradata, 2008
Situation
Need to speed calls through the call center, improve self-service in the IVR by increasing relevance.
Problem
System not connected to the CC. IVR programmed for one-size-fits-all.
Solution
Connected AEI to the IVR. Based on account data, program the IVR to only offer button push options that correspond to existing or potential product add-ons. If request is for an Agent, and all are busy, then play Next Best Offer audio while the customer is waiting.
Impact
• Better customer satisfaction (faster)
• Increased customer pre-conditioning on offers
• Increased sales
Case Study #2: European TelcoInbound IVR Call Speedups
20 > © Teradata, 2008
Case Study #3: Australian Bank Smart Outbound Personal Banker Calls
Situation
Opportunity to analyze customer banking activity to detect opportunities for personal banker to cross- and up-sell.
Problem
Information in transactional systems needed to be pulled together and analyzed.
Solution
All customer activity is loaded into the AEI Warehouse. 300 business rule queries scan the customer database every night to direct significant customer events to trigger out the best opportunities. Information is driven to banker desktops for outbound calls.
Impact
• Scan 2.7M daily customer events
• 3M annual opportunities• 500,000 relevant calls• >40% response rate
21 > © Teradata, 2008
Situation
Customers frustrated with CSRs who didn’t have accurate and up-to-date information about service activity and accounts.
Problem
Saw opportunity to do much better customer service if company could load information from front-ends into the AEI system within 5 minutes of any customer activity.
Solution
Needed to add Web service callouts from Call Center system to access customer history and proposals in real-time. Built the system in 3 months. Achieved all project goals.
Impacts
• Better informed CSRs and faster customer issue handling.
• <5 minute ETL latency on all customer activities
• 80,000 calls/day, 3000 agents
• SLAs: 95% < 1 sec, 99.9% < 4 sec
Case Study #4: North American TelcoImproved Customer Service with Real-Time Data
22 > © Teradata, 2008
SituationNeed for thousands of customers to get claim status via web and IVR. Need for 2500 internal business users to see up-to-date customer information.
ProblemDisjointed information systems. No single view of up-to-date data. IVR and Call Center not connected to the single view of the customer.
SolutionIntegrated daily information from 8 feeds (750M rows) on policy and claim valuations, providing daily forecasts to manage $12B of reserves.3 new kinds of web and IVR self-service queries, resulting in intelligent call center routing and claim status self-service for customers, and real-time visibility for underwriting at the broker portal.
Impact• Customer calls
handled within targets up from 60% to 95%
• Faster call routing let company re-assign 30 agents to higher value tasks
Case Study #5: Major USA InsurerBetter Daily Reserve Modeling, Customer and Broker Self-Service
23 > © Teradata, 2008
Situation
Volatility in the Balance Due for subscribers leads to customer confusion and dissatisfaction.
Problem
Subscribers are on tens of thousands of different rate plans. How do you recognize Balance Due volatility and then interact with the customer to manage satisfaction with this complexity?
Solution
Identify subscribers that are clearly on the wrong rate plan based on usage patterns as their billing data enters the warehouse, derive what rate plan is the right fit for the patterns and then proactively
reach out to the subscriber via phone or mail.
Impact
• Decreased bad debt
• Increased customer satisfaction
• Decreased customer churn
Bonus Case Study #6: Major USA Telecomm Managing Price and Plans for New Subscribers
24 > © Teradata, 2008
Active Enterprise Intelligence
Helps You Make Better Decisions, Faster – Across the Enterprise
Strategic Intelligence:Great Insights about the Business
Align and Accelerate
Operational Intelligence:Operations People and Systems
Become Smarter and Faster