I caught up with the folks from Conductrics to learn about their 3.0 release (I have blogged about Conductrics before). Conductrics has been in the decision optimization business for many years now. At its core Conductrics is about assigning customers to experiences. They recently released 3.0 with some new features.
Conductrics Express is a point-and-click tool to help set up tests and personalized experiences for web sites. It’s a browser extension with lots of control. Historically Conductrics has been more API-centric. Some audiences really like a “headless” and API based platform but others want something more UI-based. In addition, quick tests or temporary projects are common and the new visual setup lets them quickly set something up. For instance, figuring out which customers get which experience sometimes requires some quick A/B testing or experimentation and there is no time to work with IT etc. Conductrics Express sits on top of the API so can be evolved and integrated with other API based projects.
To make it easier to use machine learning, the new version supports explicit induced rules. This gives you an interpretable AI as it converts complex optimization logic into easily digestible, human readable decision rules. Users can use it for audience discovery and can either have it drive the experience or just “listen” to see what it would have recommended. This engine does trial and error or A/B testing and as you collect data it builds a decision tree for audience segmentation.
One of the nice features of the engine it that it predicts likelihood of success for offers but also predicts how likely an option is the best one. This enables you to identify both those experiences that are clearly better than alternatives despite having a low chance of success as well as those that seem significantly better but where there is a high degree of uncertainty. This reflects the reality that additional targeting is lower value for some (sometimes there’s just not much difference between best and worst). This lets you see the marginal benefit of targeting (v picking A or B) etc. and allows you to see poorly served audiences.
The current version allows Inline creation of options, easy specification of goals and has a Javascript API that allows packaging of logic into a file that is locally available e.g. on mobile app. You can also group agents into a multivariate agent for reporting and create mutually exclusive agents to make for more sophisticated analyses. Users can also add rules to constrain or force experiences, use predictive analytics in assignment or randomly assign people to learn from experiments. A single recommendation can be the objective or a list of recommendations can be. All this can be tied together using flowlets that specify logic to tie agents together using adaptive or random logic. This allows for more complex decisions where making one implies another.
Finally, there is a new faster JavaScript API to the existing web service API and a variety of deployment options from hosted to on-premise.
You can get more information on Conductrics here.
