Focusing on the point of differentiation
Intelligence Cloud is an integral part of our direction as a company. It consists of the capabilities that are aimed to be the point of experience, or what we call: the point of differentiation. In this blog, I am focusing on three of the capabilities in Intelligence Cloud; Web Experimentation, Content Recommendations and Product Recommendations.
Within Intelligence Cloud, we have client-side experimentation (Optimizely Web Experimentation), as well as purpose-built content and product recommendation engines. The newly added Optimizely Data Platform (from Zaius) is also included in the Intelligence Cloud, which was addressed in my most recent blog.
1. Privacy (Web Experimentation)
Over the past 5 years, restrictions around user privacy on the internet have evolved rapidly. Browsers have started cracking down on cookies and other storage mechanisms to limit the potential for misuse. Also, governments have introduced regulations for how data is collected, used, and stored. At Optimizely, we are closely following all of these changes to make sure we provide our customers with modern, flexible solutions that comply with modern privacy standards while retaining the maximum functionality of their marketing stack.
We are releasing more flexible options to decide what user data is used and where it is stored. As a start, we are introducing the option to use an external user ID that already exists on your site for targeting and experimentation instead of requiring customers to create an Optimizely user ID. That gives you the flexibility to tie experimentation to existing user IDs and consent mechanisms without additional work. It also provides you with the opportunity to merge existing data sets with experimentation data in a much easier way without having to keep track of multiple user IDs. You can easily choose which user ID to use from the comfort of your Optimizely user interface.
2. Developer workflow (Web Experimentation)
Developers have always been some of the core users of our experimentation platform. While we offer a visual editor for quickly running simple experiments, many of our customers make use of our extensive developer tools within Intelligence Cloud to deliver and experiment on more complex digital experiences. We already provide a modern code editor that provides flexible utilities to make developing experiments easier. However, we acknowledge that most developers would like to work within their existing development environments. That is one of the reasons why we already have introduced IDE plugins and extensions for development tools such as Visual Studio Code. We have also released a Github integration that enables developers to push code to Optimizely experiments directly via Github actions, enabling versioning and avoiding the need to leave your existing development environment when delivering new experiences.
3. Performance Edge (Web Experimentation)
Optimizely Performance Edge allows customers to run blazing fast website experiments by moving key decisions to the edge. This means decisions can be made on the lightning-fast code delivered by the CDN instead of waiting for a server, and the solution is available today. We are now working to incorporate additional functionality into Performance Edge, including additional API support, Extensions, Custom Attributes, and Exclusion Groups. Most often used to integrate with analytics providers and to scale experimentation across a large organization, extensions offer customers the flexibility and ability to implement custom solutions with added scalability. Custom attributes will allow customers to segment their visitors and build audiences based on relevant characteristics. Lastly, exclusion groups allow customers to run mutually exclusive experiments, meaning, any visitor who sees Experiment A will not see Experiment B, and vice versa.
4. Cross-product metrics (Web Experimentation)
As more customers rely on both Web Experimentation and Full Stack together, they want to share a single consistent set of tracked events across the products. Currently, events set up in Web Experimentation and Full Stack can only be used in each of the products. Cross-product metrics will allow users to instrument an event once and use it across the platform, regardless of implementation, simplifying their workflow and unblocking more complex experimentation use cases.
5. Usability improvements (Web Experimentation)
6. 3rd generation Product Recommendations
The latest iteration of the Product Recommendations service is being tested and adopted across the customer base. These are new machine learning prediction models across several different areas. Updated B2C and B2B commerce customers on this service are seeing significant increases in performance across click through rates, average order sizes and more.
7. Enterprise SSO
Enterprise single sign on (SSO) will allow organizations to use their existing corporate and enterprise identity and authorisation services to allow access to our product and content recommendations services. This helps organizations meet their compliance obligations in easily managing and controlling who has access to manage and optimize these services and control this in accordance with their corporate processes.
8. Content analytics dashboards
Our new content analytics dashboards, called “Answers” within the platform, deliver a set of pre-built analytics across five key content performance areas, allowing users to drill into multiple reports in each dashboard. These provide a deep insight into content across the digital estates, the sources of visitors and their topics of interest, and high performing content leading to goal conversions. Based on all the aggregated data it provides actionable advice on what content to create next to move the needle on the business KPIs.