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Customer Engagement for Retail & E-commerce

Customer Engagement for Retail & E-commerce

Use advanced analytics to get far more precise in everything you do.

FICO provides a seamless cloud-based or on-premises framework that helps retailers deploy analytic models and strategies as much as 90% faster, and develop decision management applications 70% faster. For retailers, this framework can help drive near-immediate improvements in fraud and risk execution.

Solution Details

Go beyond relevant, personalized offers to sense-and-respond interactions that inspire true customer loyalty and drive higher incremental revenue.

The retail industry showed the world how to use data-driven insights to increase consumer choice and personalization. But with today’s explosion of SKUs, product/service options, and ways to shop and take delivery, leaders know they need advanced analytics. What does your customer need now, and what do blended analyses of data from diverse sources and interactions — including the current one — tell you about what they value and how they buy?

What’s the best offer you can make at this point in time? And, because an offer may be just the beginning of a process, can you generate alternative offers or incentives on-the-fly based on customer responses and new information you’re picking up from the interaction?

FICO decision management solutions let you infuse insights from predictive, prescriptive and contextual analytics into customer engagements. We put the power of data science in the hands of your business users so they know exactly what to do next to build stronger revenue streams and customer relationships.

Use Cases

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Offers and Pricing

Understand what individual consumers value and their sensitivities to pricing and incentives.

Analytics can tell you if a customer is likely to buy a certain product within a specific time window — and how much a price change or discount would move the probability needle. They can generate POS offers on the fly from a combo of historical and real-time data. They can also generate alternative deals, including product/service/credit packages, for big-ticket items.

  • Predictive models (propensity, time-to-event, uplift)
  • Pricing optimization
  • Real-time offer generation from streaming data
  • Alternative deal optimization
  • Rapid design/deploy of analytics-driven digital applications
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Marketing

Allocate marketing budgets to where they will create the biggest lift.

Analytics and intelligent automation help you improve conversion rates, margins and customer retention with highly personalized omni-channel campaigns. Optimization can make hundreds of millions of SKU-level inventory decisions every day, and recommend the best space layout and shelf facings for particular stores based on their unique traffic, demographic and profit generation patterns.

  • Decision rules engine
  • Omni-channel digital marketing
  • Store space and shelf optimization
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Loyalty and Churn

Deliver spectacularly on the perennial customer question: “What have you done for me lately?”

The way to make loyalty programs stand out is by using analytics and optimization to constantly show members “We know who you are” and “We value your business.”

With analytics and optimization, you can deliver cost-saving and value-enhancing offers on products just at the moment when a member wants to buy them. That creates delight, wonder (“How did they know?!”) and loyalty (“Can’t wait to see what they’ll do for me next!”).

  • Predictive models (propensity, time-to-event, uplift)
  • Offer and pricing optimization
  • Contextual analytics
  • Attrition models
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E-commerce Risk

Do more business with less risk.

To combat the increasing levels of fraud being experienced by most online retailers and e-commerce exchanges, you need real-time transactional detection. These solutions spot third-party fraud, including identity theft. They also detect probable first-party fraud from legitimate consumers making purchases on credit without intending to pay, and can even be expanded to tell you about return risk.

  • E-commerce fraud and risk detection
  • Comprehensive fraud management
Case Study

Major Canadian Grocery Retailer

Learn how a major Canadian grocery retailer built relationship value by systematically learning what’s relevant to individual customers.

Case Study

Bluestem adds millions in revenue with segmentation strategies through advanced analytics

Being able to use multiple outcomes really helped us find opportunities in pockets of our membership database.

Case Study

Online Retailer

Automates Seller Onboarding and Reduces Fraud Losses.