Experience Optimization Platform (EOP)
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An Experience Optimization Platform (EOP) is a IT platform for creating experience optimization systems.
- See: Amazon Personalize, Adobe Target.
References
2018b
- ((McCormick et al., 2018) ⇒ James McCormick, Emily Miller, Gene Leganza, and Robert Perdoni. (2018). “The Forrester Wave™: Experience Optimization Platforms, Q2 2018 - Continuous Improvement: The Digital Intelligence Playbook." Forrester Research, June 20, 2018
- QUOTE: In our 24-criteria evaluation of experience optimization platform (EOP) providers, we identified the eight most significant ones — Adobe, Dynamic Yield, Evergage, Monetate, Optimizely, Oracle, SAS, and SiteSpect — and researched, analyzed, and scored them. This report shows how each provider measures up and helps customer insights (CI) professionals make the right choice. ...
- At the crux of continuous optimization are three capabilities that are central to this EOP evaluation:
- Online testing. These techniques compare how variations of customer interactions perform against a control group to determine the best treatment. Online testing allows organizations to create, deploy, measure, and manage A/B, multivariate, and other statistical experimentation types to compare multiple versions of an online experience. These tests provide objective, data-informed guidance to help optimize matching the right visitor segments with the right digital experience. Firms commonly use online testing to enhance marketing and product engagements. (see endnote 4)
- Behavioral targeting. These techniques enable a firm to serve tailored experiences to digital visitors based on events, business rules, and the context, characteristics, behavior, and interactions of customers. (see endnote 5) Behavioral targeting tools allow users to deliver personalized experiences (like relevant discounts, promotions, or special functionality) to particular customer segments using rules or predictive algorithms.
- Recommendations. Recommendations processes are enabled by analytical engines that serve recommended experiences to digital visitors, such as those using websites or mobile apps. Recommendations can include suggestions for related content based on business rules, machine learning algorithms, or a combination of both. Recommendations are traditionally associated with eCommerce merchandising — showing visitors complementary or similar products with the goal of encouraging cross-sell conversions. However, today other industries, such as media and financial services, commonly apply recommendations (e.g., new movie suggestions on Netflix "because you watched The Blind Side ").