Diese Präsentation wurde erfolgreich gemeldet.
Die SlideShare-Präsentation wird heruntergeladen. ×

Driving Growth with Marketing Analytics

Anzeige
Anzeige
Anzeige
Anzeige
Anzeige
Anzeige
Anzeige
Anzeige
Anzeige
Anzeige
Anzeige
Anzeige

Hier ansehen

1 von 32 Anzeige

Weitere Verwandte Inhalte

Diashows für Sie (20)

Anzeige

Ähnlich wie Driving Growth with Marketing Analytics (20)

Anzeige

Aktuellste (20)

Driving Growth with Marketing Analytics

  1. 1. Driving Growth with Marketing Analytics Jill Enabnit U.S. Bank
  2. 2. “How can analytics influence customer satisfaction?”
  3. 3. “Which marketing programs ring the cash register – and how do we find more like that?”
  4. 4. “What are we doing about this Big Data thing?”
  5. 5. Questions and answers…… are becoming more
  6. 6. ProfitabiliyMatrix Retention RegulatoryImpacts OpenSource NetLiftModeling GeographicAssessments DesignofExperiments BigDataPlanning Triggers K-MeansFactor StructuredSemi-StructuredAndUnstructuredData IncrementalRevenue ProcessImprovements NextBestActionReactiveOpportunities NewDataSources RealTime SelfServiceReporting CFPB LogisticRegression Clickstream PathingAnalysis ClientAdvocacy DataGovernanceControls DataModeling LifeEvents Solutions Search&Display TransactionAnalysis ServiceToSales MarketingMixOptimization Segmentation CustomerExperienceFocus OmniChannelStrategy ReturnOnInvestment IncentivePlanning $$$ RiskTolerance Hadoop OrganicGrowth Behavioral Economics
  7. 7. Where to begin?
  8. 8. III. Is this the right choice for the enterprise? II. Have we provided incremental revenue? I. How does it impact our customers? Identify simple tenets
  9. 9. Single View of the Customer Life Events Channel Usage Credit Risk Segments Service Interactions Balance Drivers Marketing History Note: Sample data fields Clickstream Patterns Transaction Behaviors
  10. 10. veraging customer data for many u Retention Tactics Treatment Strategies Marketing Actions Measures & Metrics Capital Allocation Conversational Data Next product to market? Out of pattern transactions? Activate or deepen relationship? Approve this loan? Pay this overdraft? Authorize this transaction? Likely to attrite? Appropriate concessions? Meaningful potential? Marketing Analytics Data Expand or contract? Need a new branch? Channel investments? Increasing return? Champion or challenger? Met strategic objectives?
  11. 11. cs actively shape the U.S. Bank Customer Exp “Conversational Data” about customers’ financial objectives & existing relationships Prioritized offers and consistent treatment for each customer Behavioral Insights Mining up to 17 million transactions each day to identify out-of-pattern behaviors that may signal needs Predictive Analytics Evaluating customer value, purchase propensity and future potential for over 17 million customers Relationship Strategies Converting insights into decisions and guidance passed to customer facing employees & systems Teller Pops 24-Hour Banking ATMs Internet Banking Mobile Direct Mail Branches Specialized Sales Email
  12. 12. Blending marketing analytics with needs-based sales processes allows bankers to provide better solutions to customers The Andersons Model Score: 248 LiSA Segment: “Kids First” Need: Reduce Debt Service Mr. Anderson, I’d like to show you how we can use a home equity loan to reduce your monthly payments. “Conversational Data” allows us to tailor the product benefits and selling process Michael M. Model Score: 249 LiSA Segment: “Upscale Investor” Need: Smooth Cash Flow Michael, since nearly half of your income comes from bonuses, a home equity line could improve your cash flow. Banker
  13. 13. I. How does it impact our customers? II. Have we provided incremental revenue? III. Is this the right choice for the enterprise?
  14. 14. Or a resurgence?
  15. 15. nuous improvement to increase confid Deepen Defend Improve Build Create Hypothesis Design Tests Observe Behavior Measure Results Strategic Framework Champion/Challenger Test & Learn Performance Period Evaluation Branch Trade Area Profile MAIN STREET OFFICE Branch Manager: John Smith 101 Main St. NE Parent Market: Minneapolis-St. Paul-Bloomington, MN-WI Minneapolis, MN 55413 * Assume branch trade area radius of 1.50 miles Competitor Information & Market Share As of June 30, 2009 Top Competitors USB Market Share Rank Deposits ($M) Branches 1. Wells Fargo 2. U.S. Bank 3. Ameriprise 4. Marshall & Ilsley 5. TCF Financial All Other Total Trade Area Branch Type Avg. Deposits/Branch ($M) Deposit Growth/Yr. (2003-08) < Traditional < In-Store < Branch Trade Area  Overall Bank Institution < Branch Trade Area  Parent Market Market Demographics Age of Population Income Race/Ethnicity Per Capita & Household ($K) < Branch Trade Area  Parent Market < Per Capita < Household < Branch Trade Area  Parent Market Market Analytics & Performance Solutions Page 1 of 3 U.S. BANK CONFIDENTIAL - NOT FOR DISTRIBUTION Diversity Index (Baseline=100) Branch Trade Area Parent Market 115 81 Median Age (Years) Branch Trade Area Parent Market 31.2 35.8 Growth/Year (2008-13P) Branch Trade Area Parent Market 6.0% 3.7% 4 24 43 7 4 1 3$946 $437 $1,281 $19,467 $10,719 $4,704 $1,380 6 2 1 3 3 1 2 1 WF USB AMER M&I TCF $1,531 $1,176 $1,380 $315 $109 WF USB AMER M&I TCF 6.1% (1.3%) 0.0% 44.7% 81.2% WF USB AMER M&I TCF Deposits Branches 24% 8% Branch Trade Area Parent Market 9% 5% Branch Trade Area Parent Market 12.1% 21.1% 24.8% 14.5% 11.0% 7.5% 6.8% 2.2% 0-14 Yrs. 15-24 Yrs. 25-34 Yrs. 35-44 Yrs. 45-54 Yrs. 55-64 Yrs. 65-84 Yrs. 85+ Yrs. $31.4 $36.6$36.8 $73.7 Branch Trade Area Parent Market 50.0% 26.0% 12.0% 7.0% 0.1% 2.0% 6.1% 5.0% White Black Hispanic/Latino Asian Hawaiian/ Pacific Islander Indian/Alaskan Other 2+ Races Upgrade treatment strategy and create new hypotheses
  16. 16. Build the right competencies
  17. 17. - Response vs Net Lift - Triggers with models - New data sources (Big & Small) - Design of Experiments - Channel Optimization - Marketing Mix Be willing to test Not one „Holy Grail‟ answe
  18. 18. And now it's time to S.T.A.R.T. your journeySavings Today And Rewards Tomorrow ……and understand the enterprise impact
  19. 19. III. Is this the right choice for the enterprise? II. Have we provided incremental revenue? I. How does it impact our customers?
  20. 20. M A P S F E S T 2 0 1 2
  21. 21. M A P S F E S T 2 0 1 2
  22. 22. Value can differ significantly across campaigns $0 $20 $40 $60 $80 $100 $120 $140 $160 $180 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 Alerts Balance Product  $420 Campaigns by Number of Contacts and Average Value/Contact Logarithmic Scale Average Monthly Contacts AverageValueperContacts
  23. 23. A penny is a penny…..new or not
  24. 24. Is the juice worth the squeeze?
  25. 25. Building incremental revenue one bps a
  26. 26. Understanding the enterprise impact of
  27. 27. III. Is this the right choice for the enterprise? II. Have we provided incremental revenue? I. How does it impact our customers?

×