Automated Recommendations Increase Revenue per Email by over 2,500% for StubHub

Recommendations—Promote Relevant Choices

Description

Omniture Recommendations™ enables businesses to easily promote products and content online. Through flexible data and behavioral driven algorithms, businesses can increase conversions by ensuring relevant choices are automatically presented to the right customers at the right time—on-site or through email campaigns. Omniture Recommendations is part of the Omniture Online Marketing Suite of business optimization applications.

Business Challenges

Marketers and merchandisers are looking for ways to easily promote compelling product or content choices for maximum cross-sell and up-sell impact. Businesses are wary of black-box solutions that do not offer the flexibility required to meet their unique business goals. Many do not have the resources to manually build and manage online recommendations effectively. Businesses that sell products and services or derive advertising revenue through their online channel require maximum control over recommendations effectiveness and presentation.

Solution

Omniture Recommendations allows marketers and merchandisers to define recommendations that promote relevant choices to visitors and increases cross sell and up sell revenues.

  • Automate Recommendations

    Eliminate the need for expensive, time-intensive manual approaches.

  • Marketer Managed Algorithms

    Select from several algorithms and configure parameters to manage results.

  • Any Marketing Channel

    Provide recommendations via Web, email, mobile or other marketing channels.

  • Built-In Testing

    Enable marketers to test recommendations performance in real time.

  • Enriched by Online Analytics

    Eliminate ‘cold start’ by using existing analytics data.

Relevant Product or Content Recommendations

Easily create, test and manage automated recommendations for online promotions such as cross-sell or up-sell
  • Visitor data drives recommendations; no server-side or offline integration required
  • Interacts directly with your site’s presentation layer
  • Automatically “learns” about content catalog from online visits—no API or catalog integration required
  • Includes products and content to support recommendations for articles or blog posts
  • Recommendations can be started, stopped and modified by marketers, no IT support required
  • Run different recommendation types on different pages: show top sellers on your homepage and cross-sells on a product page, for example

Configurable Algorithms and Presentation Templates

Marketers and merchandisers have a high level of control over recommendations algorithms, with ability to tweak settings and modify layout.
  • Choose from a variety of popularity and affinity algorithms to suit your business needs based on viewing, searching and buying activity of previous visitors or shoppers
  • Algorithms include: ‘Most Viewed,’ ‘Top Sellers,’ ‘People who bought or viewed this also bought that,’ Omniture’s Site Affinity algorithm and recommendations based on SiteSearch queries
  • Use metrics from SiteCatalyst and DataWarehouse to power recommendations
  • Change the algorithms to include only visitor data from the last day, week, month or longer
  • Import algorithms to third-party applications to show recommendations beyond your Web site

Integrated with the Omniture Online Marketing Suite

Extend the value of online recommendations by using them in conjunction with other Omniture products, and leverage across marketing channels using integration services from Omniture Consulting Services.
  • Integrate with Test&Target; to run sophisticated tests on your recommendations and target them to different visitor groups
  • Integrate with SiteSearch to run the “Omniture SiteSearch Recommendation” on your search results pages
  • Omniture Genesis enables integration with 3rd party vendors—such as email application providers to deliver recommendations via email

Built-in Testing and Reporting

Ensure that you are getting the most out of your recommendations by continually optimizing them by changing the algorithm controls and template design.
  • Test recommendations against default content or products to monitor conversion performance metrics
  • Built-in reporting interface shows visits, clicks and purchases with conversion lift data
  • Analyze reports to change business rules or to determine winning promotions