searchdiscovery.com

Market Basket Analysis (MBA) is a popular rule-based machine learning technique that can provide product recommendations to customers. Market Basket analysis shares a common DNA with recommender systems—systems that use machine learning to personalize recommendations for customers as scale (see below). That is, when someone views the item (or even if they have the items in the cart) from the left-hand side of a rule, we can apply machine learning to recommend the item on the right hand side on either a product detail page or at checkout. Market basket analysis can be a gateway to a recommender system, which can use real-time data to recommend complementary products to users live.

That’s because the sample gets recycled to study each factor independently without any increase in sample size. Take this scenario:To measure only main effects, you can plan your sample as if you were testing 1A vs. 1B because the sample gets recycled for 2A vs. 2B and 3A vs. 3B. In classic factorial experiments, researchers typically assume that complex interactions between many factors do not exist and that there are probably only main effects and a few low-order interactions. You can’t perform the same type of statistical test you use for A/B on MVT data and expect to get the level of insight you’ve

If you want to remove all of the current constraints of Adobe Analytics, you can send your digital website or mobile app data directly to AEP and then have AEP send the data to Adobe Analytics. Instead of manually updating Adobe Launch data elements and rules, Apollo can do it programmatically in a matter of seconds!Here is an example of the Apollo XDM Composer creating data elements:Here is an example of a new Adobe Launch rule using XDM:Here is an example of an Adobe Launch send event leveraging XDM: That may not be part of the standard XDM schema, so Apollo automatically creates a chat “mix-in” and defines the data that will be collected related to chats:Apollo will also create the required Edge Configuration needed and then automatically configure Adobe Launch to use the Adobe Edge:The preceding steps can take weeks or months to update if done manually, but Apollo provides a way to automate much of it and simplify your migration to XDM But the net result is that if your data layer is managed by Apollo, you can keep the same data layer you have been using and let Apollo automatically  translate it to XDM so that you can begin sending data directly to AEP.

An Introduction to Data Governance and Management for Marketers Data governance and data management are critical to the success of your business intelligence program and your entire organization. When starting a data governance/data management initiative, we typically introduce this hierarchy:This hierarchy helps differentiate between which tasks are owned by data governance and which are owned by data management. You cannot have effective data management and governance without data strategy as the critical output of your data governance. This group is aligned with data governance and data management tasks; however, their primary focus is to create a data strategy that the data management group can then execute.