the practical, profitable magic of prescriptive analytics

The Practical, Profitable Magic of Prescriptive AnalyticsTransform Big Data and Insights into Action

©2014 Fair Isaac Corporation. All rights reserved. 2

As consumers, we’re all having more experiences that seem almost magical

You’re in a mall, and your smartphone beeps. It’s an offer for 20% off a pair of shoes you’ve been looking at online—from the store you just walked past!



You found the right car, but the standard financing terms are all wrong.So you talk with the dealer a bit, who taps some info into his tablet, and voila: 3 new deal structures that meet your needs, all pre-approved by the lender. Your choice.



You’re home from work, with time to take care of personal business.Here’s a text from a creditor gently reminding you of an unpaid bill. You tap a button, and it’s taken care of. Just in time to make dinner.


As business people, we know it’s not magic, but rather analytics powering these outstanding customer experiences.Still, the way analytics cut through massively complex data and a mind-boggling number of possible decisions to point us to the best action at the right moment does work magic in daily operations. And on the bottom line.


Let’s look at the business side of the experience:

Targeting and timing personalized offers Analytics can tell you which customers are likely to buy a particular product within a specific timeframe, such as the next two weeks. Also how much is a 20% discount going to increase the likelihood of a purchase—and would a 15% discount be just as effective?

Generating optimized alternative deals in real timeBy using optimization analytics, you can give customers more choice by generating an array of alternative deals at the point of sale. Every deal meets not only the customer’s needs but also the company’s business objectives, constraints and regulatory requirements.

Contacting customers in the way most likely to succeedWith the right analytics, you can know which actions have the best chance of influencing a particular customer’s behavior—and the most effective channels and timing for reaching that customer.


Analytics (algorithms and engines) have evolved to the point where they answer an expanding range of useful questions:

What happened? Descriptive Analytics

Why did it happen? Diagnostic Analytics

What is likely to happen next? Predictive Analytics

What is the best action to take? Prescriptive Analytics


Understanding the roles of analytics with what and why customers are buying...

Descriptive Analytics: typically used in Business Intelligence (BI) products u What are my customers buying more of this month? (sandals, high-

top sneakers, trainers, etc.?)

u Who is buying trainers? (demographics and other customer characteristics)

Diagnostic Analytics: also used in some BI suites u What caused the jump in trainer sales last quarter?

u Was it e-coupons, a price drop, a cool new model that was featured in a movie or a combination?


Analytics can tell you what could happen if you take certain actions.

Predictive Analytics: u Is Tom likely to buy a pair of trainers in the next six weeks?

u Is he likely to buy in the next two weeks if offered a 20% coupon?

Prescriptive Analytics: u What action should we take now to increase the probability of that

purchase? For example, offer Tom a cash-back reward toward his next shoe purchase.

u What is the optimal action for maximizing profitability while meeting all of our other business objectives? 15% or 20% off coupon—and which brand of trainer?


Predictive analytics estimate the probability of future behavior

Patterns in historical data that have proven to be predictive of specific customer behaviors are used to build predictive models. When those patterns recur in today’s data, the models estimate the probability of an individual customer exhibiting that behavior in the future.

There are many types of predictive models. A propensity model, for instance, can determine that a customer is likely to respond to a discount on a particular product because while she’s not concerned with brand names, she is price sensitive.

Brand

48” FlatScreen TV

20% O�SALETODAY!


BusinessObjectives

Outputs from predictive analytics are key inputs to prescriptive analytics

These predictions perform an essential function by estimating the values of unknown data variables. For example, unlike known variables such as a customer’s address, a customer’s likelihood to become delinquent in the future is a variable with an unknown value.

Prescriptive analyticsBased on these data-driven insights, we can estimate and compare the likely outcomes of any number of actions, and choose the very best action to advance business objectives.

Predictive analyticsProbability of purchase

Probability of delinquency

Probability of attrition

Probable revenue

Probable relationship profit

Etc.


Optimization is at the heart of prescriptive analytics

While in casual usage, optimize often just means “to make something better,” in analytics we mean a precise mathematical process that identifies the best way to use your resources given all your business objectives and constraints.

Variablese.g., cost per unit,

profit per item,attrition risk,throughputper hour...

KNOWNvariable valuesdiscovered bydescriptive &

diagnosticanalytics

UNKNOWNvariable values

forcasted bypredictiveanalytics

Constraintse.g., HR policies,

campaignexclusions,

regulations...

Objectivese.g., minimize cost,

maximize profit, minimize

downtime...

Capturedin business

rules createdand edited by

businessexperts

OptimizeFind best solutions

(variable values)that maximize the

objective whilehonoring theconstraints.

RecommendedAction


Decision management is the process of operationalizing predictive and prescriptive analytics for timely action—including real-time

By embedding analytic models into rules-driven applications, you can make smarter, more timely decisions. And by deploying models via decision engines, you can call on those same insights from any number of service-oriented applications.

AnalyzeResults

TakeAction

Variablese.g., cost per unit,

profit per item,attrition risk,throughputper hour...

Constraintse.g., HR policies,

campaignexclusions,

regulations...

OptimizeFind best solutions

(variable values)that maximize the

objective whilehonoring theconstraints.

RecommendedAction

Objectivese.g., minimize cost,

maximize profit, minimize

downtime...


And now, with Big Data, the ability to go from insight to immediate action is more important than everBig Data comes from conversations consumers have with customer service agents. From web pages they visit, products they review and blogs they comment on. From purchases they make with credit cards and social media posts telling friends about what they just bought.

This vast field of data is full of insights that can help companies understand how to serve customers better. But it also accumulates and ages quickly. You have to be able to act on analytic insights before they get too old and opportunities melt away.


Companies use predictive and prescriptive analytics with decision management to drive actions literally calculated for success

Financial Services:A European Bank with global operations increased profit per customer by $120 with no increase in losses, achieving a 6:1 return on investment in 12 months.

Retail:A mid-size specialty retailer generated an additional $250,000 in revenue per campaign and increased retention, using an analytics-based marketing solution to target customers and find the right marketing mix.

Insurance:A large Brazilian insurer grew net profits by 130% using predictive analytics in its underwriting to reduce risk and grow revenue from profitable customers.

Health Care:A major commercial payer saw more than $20 million in annual savings using an analytics-based fraud solution to detect provider fraud and abuse, overpayment, and policy and system errors.


The FICO® Decision Management Suite

u FICO® Decision Management Platform

u FICO® Decision Studio

u FICO® Application Studio

u FICO® Visual Insights Studio

Delivered on-premises or through the FICO® Analytic Cloud, FICO Decision Management Suite helps you rapidly create and deploy powerful analytic decision solutions.

Today you can incorporate more of these advanced analytics into your business with less time and expense

90% or more faster model deployment

70% or more faster application development

60% or more lower maintenance costs

Up to 50% better decision performance

Up to 50% better action optimization

Up to 40% better model performance

Ready to bring more magic to your customers and operations?Learn more:Download our white papers:

Insights #74: Cloud Democratizes Access to Big Data Analytics

Insights #81: Big Data: Overhyped or Underexploited?

Find out about the FICO® Analytic Cloud:

www.ficoanalyticcloud.com

Check out our blog:

FICO Blog

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the practical, profitable magic of prescriptive analytics

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