Improve Your Marketing Campaign ROI with Predictive Analytics

Transcription

1 Improve Your Marketing Campaign ROI with Predictive Analytics Rajesh Shewani, Pre-Sales Leader India/SA IBM Business Analytics Cognos & SPSS

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3 Our world is becoming INSTRUMENTED Our world is becoming INTERCONNECTED Virtually all things, processes and ways of working are becoming INTELLIGENT 3

4 Transform Your Organization with Information Lack of Insight Volume of Digital Data 1 in 3 managers frequently make critical decisions without the information they need Inefficient Access Variety of Information 1 in 2 don t have access to the information across their organization needed to do their jobs Inability to Predict Velocity of Decision Making Source: IBM Institute for Business Value 3 in 4 business leaders say more predictive information would drive better decisions 4

5 IBM is uniquely equipped for Business Optimization In addition to driving continued innovation across SPSS s predictive analytics portfolio, we plan to leverage its strengths across many aspects of the broader IBM portfolio, increasing customer value We will be expanding expertise and capabilities for IBM s new Business Analytics and Optimization (BAO) service line 5

6 New ways of working to optimize decisions and actions Predict and act Volume Lack of Insight Velocity Inefficient Access Sense and respond Instinct and intuition Skilled analytics experts Real-time, fact-driven Everyone Inability to Predict Variety Back office Automated Point of impact Optimized 6

7 New ways of working to optimize decisions and actions Predict and act Volume Lack of Insight Velocity Inefficient Access Sense and respond Instinct and intuition Skilled analytics experts Real-time, fact-driven Everyone Inability to Predict Variety Back office Automated Point of impact Optimized

8 Imagine If Your Decision Makers Could predict and treat infection in premature newborns 24 hours earlier? adjust credit lines as transactions are occurring to account for risk fluctuations? determine who is most likely to buy if offered discounts at time of sale? apply inferred social relationships of customers to prevent churn? Physician Loan Officer Retail Sales Associate Telco Call Center Rep optimize every transaction, process and decision at the point of impact, based on the current situation, without requiring that everyone be an analytical expert 8

9 How How can can I I capture capture and and analyze analyze information about about how how my my customers, prospects or or employees are are feeling? feeling? How How can can I I predict predict behaviors and and preferences so so I I can can reduce reduce churn, churn, prevent prevent fraud, fraud, maximize campaign results results and and more? more? How How can can I I make make decisions in in real-time or or ahead ahead of of a potential issue, issue, instead instead of of making making decisions when when it it is is too too late? late?

10 Predictive Analytics offers Unique Insights to Answer those Tough Business Questions Predictive Analytics is a transformational technology that enables more proactive decision making, driving new forms of competitive advantage Analyses patterns found in historical and current transaction data as well as attitudinal survey data to predict potential future outcomes

11 Introducing SPSS, an IBM Company A leading provider of predictive analytic software, services and solutions Software data collection, text and data mining, advanced statistical analysis and deployment technologies Services implementation, training, consulting, and customization Solutions combine software and services to deliver high-value line-ofbusiness solutions; used for optimizing marketing campaigns, call center effectiveness, identification of fraudulent activity and more 40 years of experience and a broad customer base 250,000 customers: 100 countries, 50 states, 100% of top universities Enables decision makers to to predict future events and and proactively act act upon that that insight to to drive drive better business outcomes

12 Enabling the Predictive Analytics Process Capture Predict Act Data Collection delivers an accurate view of customer attitudes and opinions Predictive capabilities bring repeatability to ongoing decision making, and drive confidence in your results and decisions Unique deployment technologies and methodologies maximize the impact of analytics in your operation Text Mining Data Mining Statistics Data Collection Platform Deployment Technologies Pre-built Content Attract Up-sell Retain 12

13 Applying SPSS Portfolio to Accelerate Your Success Example: Customer Intimacy Reduces customer defection, increases uplift from cross-sell/up-sell targeting, and improves acquisition of the right customers, by enabling decision makers to: Understand unstructured data that is found in everything from s, call center notes, blogs, and open ended survey questions Identify drivers of customer behavior via survey analysis Identify key performance predictors (KPPs) including customer defection and outcome of particular customer interactions Prioritize customer programs as part of real-time decision processes View customer insights alongside key performance information through standard IBM reports, analyses and dashboards

14 Grow and Retain The power and ease of use of PASW Statistics enables the AMR Consumer Research department to perform more research than ever before and deliver timely reports while maintaining a small, dedicated staff. Success Stories: Customer Intimacy Grow With SPSS, HSBC Bank USA effectively mines an ever-growing file of customer data, creating predictive models to uncover cross-selling and roll over sales opportunities. Attract, Grow and Retain SPSS solutions add intelligence to our business ensuring efficiencies in pricing, marketing and reporting something no company can afford to ignore in today s business environment

15 Business Scenario Business scenario for Banking Campaign Insight and Optimization 15

16 Business Scenario: Cross-selling in Retail Banking Plenty of customers to contact, but what would be the best offer (if any) for each one?

17 Business Scenario: Cross-selling in Retail Banking Plenty of customers to contact, but what would be the best offer (if any) for each one? -Demographics -Channel Activity - Complaints -

18 Business Scenario: Cross-selling in Retail Banking Plenty of customers to contact, but what would be the best offer (if any) for each one? Predictive Models Likelihood to respond to each of the current marketing offers -Demographics -Channel Activity - Complaints

19 Business Scenario: Cross-selling in Retail Banking Next Best Action Best 3 offers recorded for every customer individually Customer ID A C F B G D H C Etcetera Plenty of customers to contact, but what would be the best offer (if any) for each one? Predictive Models Likelihood to respond to each of the current marketing offers -Demographics -Channel Activity - Complaints

20 Business Scenario: Cross-selling in Retail Banking Next Best Action Best 3 offers recorded for every customer individually Customer ID A C F B G D H C Etcetera Marketing offers are personalized based on Best Next Actions and mailed to customers Predictive Models Likelihood to respond to each of the current marketing offers -Demographics -Channel Activity - Complaints

21 Business Scenario: Cross-selling in Retail Banking Next Best Action Best 3 offers recorded for every customer individually Customer ID A C F B G D H C Etcetera Key Performance Predictors and Campaign Results Marketing offers are personalized based on Best Next Actions and mailed to customers Predictive Models Likelihood to respond to each of the current marketing offers -Demographics -Channel Activity - Complaints

22 Business Scenario: Cross-selling in Retail Banking Next Best Action Best 3 offers recorded for every customer individually Customer ID A C F B G D H C Etcetera Key Performance Predictors and Campaign Results Marketing offers are personalized based on Best Next Actions and mailed to customers Automated Updates To accommodate new offers and to apply customer contact rules Predictive Models Likelihood to respond to each of the current marketing offers -Demographics -Channel Activity - Complaints

23 Next Best Action Best 3 offers recorded for every customer individually Customer ID A C F B G D H C Etcetera Key Performance Predictors and Campaign Results Marketing offers are personalized based on Best Next Actions and mailed to customers Automated Updates To accommodate new offers and to apply customer contact rules Predictive Models Likelihood to respond to each of the current marketing offers -Demographics -Channel Activity - Complaints

24 Next Best Action Best 3 offers recorded for every customer individually Customer ID A C F B G D H C Etcetera Key Performance Predictors and Campaign Results Marketing offers are personalized based on Best Next Actions and mailed to customers Automated Updates To accommodate new offers and to apply customer contact rules Predictive Modeling Predictive Models Likelihood to respond to each of the current marketing offers -Demographics -Channel Activity - Complaints

25 Marketing offers are personalized based on Best Next Actions and mailed to customers Next Best Action Best 3 offers recorded for every customer individually Customer ID A C F B G D H C Etcetera Decision Optimization Automated Updates To accommodate new offers and to apply customer contact rules Key Performance Predictors and Campaign Results Predictive Models Likelihood to respond to each of the current marketing offers -Demographics -Channel Activity - Complaints

26 Next Best Action Best 3 offers recorded for every customer individually Customer ID A C F B G D H C Etcetera Key Performance Predictors and Campaign Results Marketing offers are personalized based on Best Next Actions and mailed to customers Integration with operational processes and systems Automated Updates To accommodate new offers and to apply customer contact rules Predictive Models Likelihood to respond to each of the current marketing offers -Demographics -Channel Activity - Complaints

27 Next Best Action Best 3 offers recorded for every customer individually Customer ID A C F B G D H C Etcetera Analysis, reporting and KPPs Key Performance Predictors and Campaign Results Marketing offers are personalized based on Best Next Actions and mailed to customers Automated Updates To accommodate new offers and to apply customer contact rules Predictive Models Likelihood to respond to each of the current marketing offers -Demographics -Channel Activity - Complaints

28 Next Best Action Best 3 offers recorded for every customer individually Customer ID A C F B G D H C Etcetera Key Performance Predictors and Campaign Results Marketing offers are personalized based on Best Next Actions and mailed to customers Analytical Asset & Process Management Automated Updates To accommodate new offers and to apply customer contact rules Predictive Models Likelihood to respond to each of the current marketing offers -Demographics -Channel Activity - Complaints

29 Grow customer value Next Best Action Best 3 offers recorded for every customer individually Customer ID A C F B G D H C Etcetera Key Performance Predictors and Campaign Results Marketing offers are personalized based on Best Next Actions and mailed to customers Automated Updates To accommodate new offers and to apply customer contact rules Predictive Models Likelihood to respond to each of the current marketing offers -Demographics -Channel Activity - Complaints

30 Market Next Best Action Best 3 offers recorded for every customer individually Customer ID A C F B G D H C Etcetera Key Performance Predictors and Campaign Results Marketing offers are personalized based on Best Next Actions and mailed to customers Automated Updates To accommodate new offers and to apply customer contact rules Predictive Models Likelihood to respond to each of the current marketing offers -Demographics -Channel Activity - Complaints

31 Campaign Data - Contact history - Response/purchases -Test campaigns - Demographics - Channel Activity -Complaints Capture Predict Act

32 Campaign Data - Contact history - Response/purchases -Test campaigns - Demographics - Channel Activity -Complaints Analyses Predict who is likely to respond, based on their customer profile when receiving the campaign Capture Predict Act

33 Campaign Data - Contact history - Response/purchases -Test campaigns - Demographics - Channel Activity -Complaints Analyses Predict who is likely to respond, based on their customer profile when receiving the campaign Scoring Capture Predict Act Marketing campaign process

34 Campaign Data - Contact history - Response/purchases -Test campaigns Key Performance Predictors and Campaign Results - Demographics - Channel Activity -Complaints Analyses Predict who is likely to respond, based on their customer profile when receiving the campaign Scoring Capture Predict Act Marketing campaign process

35 Campaign Data - Contact history - Response/purchases -Test campaigns Key Performance Predictors and Campaign Results - Demographics - Channel Activity -Complaints Analyses Predict who is likely to respond, based on their customer profile when receiving the campaign Scoring Capture Predict Act Marketing campaign process

36 Next Best Action Best 3 offers recorded for every customer individually Customer ID A C F B G D H C Etcetera Key Performance Predictors and Campaign Results Marketing offers are personalized based on Best Next Actions and mailed to customers Automated Updates To accommodate new offers and to apply customer contact rules Descriptive Predictive Models Likelihood to respond to each of the current marketing offers -Demographics -Channel Activity - Complaints

37 Next Best Action Best 3 offers recorded for every customer individually Customer ID A C F B G D H C Etcetera Key Performance Predictors and Campaign Results Marketing offers are personalized based on Best Next Actions and mailed to customers Automated Updates To accommodate new offers and to apply customer contact rules Behavior Predictive Models Likelihood to respond to each of the current marketing offers -Demographics -Channel Activity - Complaints

38 Next Best Action Best 3 offers recorded for every customer individually Customer ID A C F B G D H C Etcetera Key Performance Predictors and Campaign Results Marketing offers are personalized based on Best Next Actions and mailed to customers Automated Updates To accommodate new offers and to apply customer contact rules Interaction Predictive Models Likelihood to respond to each of the current marketing offers -Demographics -Channel Activity - Complaints

39 Before predictive analytics: Offer of the month sent to all customers Offer of the month sent to all customers

40 Predictive Model Likelihood to respond to offer of the month Offer of the month sent to all customers Step 1: Optimize offer of the month by not contacting customers not likely to respond - Demographics

41 Step 2: Establish feedback loop to measure the effect of subsequent improvements Key Performance Predictors and Campaign Results Predictive Model Likelihood to respond to offer of the month Offer of the month sent to all customers - Demographics

42 Key Performance Predictors and Campaign Results Offer of the month sent to all customers Step 3: Enrich the data Predictive Model Likelihood to respond to offer of the month -Demographics -Channel Activity - Complaints

43 Step 4: Optimize across multiple offers Next Best Action Best 3 offers recorded for every customer individually Customer ID A C F B G D H C Etcetera Key Performance Predictors and Campaign Results Marketing offers are personalized based on Best Next Actions and mailed to customers Predictive Models Likelihood to respond to each of the current marketing offers -Demographics -Channel Activity - Complaints

44 Next Best Action Best 3 offers recorded for every customer individually Customer ID A C F B G D H C Etcetera Key Performance Predictors and Campaign Results Marketing offers are personalized based on Best Next Actions and mailed to customers Step 5: Automate processes Automated Updates To accommodate new offers and to apply customer contact rules Predictive Models Likelihood to respond to each of the current marketing offers -Demographics -Channel Activity - Complaints

45 Marketing offers are personalized based on Best Next Actions and mailed to customers Future Steps: Next Best Action Best 3 offers recorded for every customer individually Roll out to other touch points Customer Service Center MyBanking website ATM Mobile banking Customer ID A C F B G D H C Etcetera Add retention offers Optimize across customers, offers, channels and time Introduce feedback strategies to uncover unmet needs for new product development Automated Updates To accommodate new offers and to apply customer contact rules Take risk predictions into account when making marketing offers Key Performance Predictors and Campaign Results Predictive Models Likelihood to respond to each of the current marketing offers -Demographics -Channel Activity - Complaints

46 Customers Experience a Measurable ROI 94% of customers achieved a positive ROI, average payback in 10.7 months Over 90% of users attributed an increase in productivity to SPSS 81% of projects were deployed on time, 75% on or under budget This is one of the highest ROI scores Nucleus has ever seen in its Real ROI series of research reports Rebecca Wettemann, VP of Research, Nucleus Research 46

47 A leading provider of predictive analytic software, services and solutions with 40 years of experience and a broad customer base Enables decision makers across the organization to predict future events and proactively act upon that insight to drive better business outcomes SPSS, an IBM Company Enables Next-Generation Decision Making From sense and respond to predict and act! 47

48 Thank You Copyright IBM Corporation 2008 All rights reserved. The information contained in these materials is provided for informational purposes only, and is provided AS IS without warranty of any kind, express or implied. IBM shall not be responsible for any damages arising out of the use of, or otherwise related to, these materials. Nothing contained in these materials is intended to, nor shall have the effect of, creating any warranties or representations from IBM or its suppliers or licensors, or altering the terms and conditions of the applicable license agreement governing the use of IBM software. References in these materials to IBM products, programs, or services do not imply that they will be available in all countries in which IBM operates. Product release dates and/or capabilities referenced in these materials may change at any time at IBM s sole discretion based on market opportunities or other factors, and are not intended to be a commitment to future product or feature availability in any way. IBM, the IBM logo, Cognos, the Cognos logo, and other IBM products and services are trademarks of the International Business Machines Corporation, in the United States, other countries or both. Other company, product, or service names may be trademarks or service marks of others