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Wednesday, July 17, 2013

Predictive Analytics in Action: Part 1 Demand Creation

By Bernie Lillis, Vice President of Strategic Solutions for Insurance Dialogue

Regulations and eligibility complexities can leave banking and insurance customers feeling lost when searching for products that fits their needs. Many businesses are incorporating predictive technology to deliver customers with the right message at the right time through their preferred channel of communication, providing customized messages, and anticipatory customer service.

To stay competitive, brands must take an analytical and predictive approach to better anticipate consumer behavior on an individual basis. Predictive analytics helps marketers to be dynamic and relevant by giving them the knowledge to present the right offer at the right time via the right channel, all based on what will best motivate the consumer to act. This allows companies to capture the attention of the audience quicker and reduce the total cost per acquisition. The predictive approach can be broken down into three parts that can work together to manage a fully engaged experience:
  • demand creation
  • demand activation
  • demand conversion
Demand creation stimulates a lead to take action by leveraging predictive algorithms that customize key marketing elements, such as web content, resulting in dramatic conversion lifts and an optimized cost per sale.

New technologies that analyze web behavior and predict the best way to engage are becoming the strategic differentiator of forward-thinking brands, often resulting in campaign ROIs that are as much as 75 percent higher than those not using predictive technology.

Demand creation through predictive engagement empowers a brand to turn online consumer behavior into customer intelligence that can be acted upon in real time. Predictive engagement web technologies maximize consumer engagement and conversion through predictive algorithms that optimize the cost per sale. This is done by dynamically customizing key marketing elements of web, mobile, and social media pages for every visitor, resulting in dramatic on-site conversion lifts. Visitors to your site(s) tell you a lot about themselves through every web interaction. Predictive engagement technologies utilize anonymous environmental, behavioral, social, and third-party data, learning what variables are the most engaging for specific individuals or segments of your audience. The learning is ongoing and delivers real-time optimized web experiences to provide the best content, products, and promotions to engage the user to become a buyer. Through a shopping cart analysis, a brand can even determine what a customer is most likely to buy next, allowing for effective cross-selling and upselling opportunities customized to each user.

To learn more on the benefits of predictive analytics, check back for part 2 & part 3 of this article and sign up for our August 15 Best Practices Panel presentation.