What are Dynamic Audiences?

Dynamic Audiences let you build engagement queries, to surface patterns of customer behavior and create intent-based audiences you can use as the basis for delivering enhanced orchestrations. By asking the right questions, you get the actionable results you need to optimize the reach of those orchestrations.

Use dynamic audiences to define specific audiences using their journey traits and customer attributes to discover how the customer experiences you provide are performing and if they are meeting your customer’s needs.

Dynamic audiences is the starting point for:

  • Creating engagement queries. When you create engagement queries using MXO's Engagement Query Language (EQL) you are asking business questions about your customer behavior in relation to your products and services, so you can analyze how customers interact with your brand.
  • Viewing audience analytics. The Audience Analytics page provides you with an overview of the resulting audience data derived from your engagement query.
  • Viewing journey visualizations. Journey visualizations provide your organization with a real-time view of how and where the audience resulting from a specific query is interacting with your brand. It provides rich insight into the high and low-volume moments on the journey, along with details about the number of customers at each stage, forward and backward transitions, and drop offs. You can also see whether or not your orchestrations are influencing customer engagement and driving higher volumes of both sales and customer loyalty.
  • Sharing audience data. Sharing an audience is the last stage of using dynamic audiences. After defining your business use case and designing and executing an engagement query, you can analyze the customer analytics and results. If they meet your expectations, you can export the results to an audience destination. You can then use the data to produce individualized content to use in orchestrations for highly refined and filtered customer cohorts.

Dynamic Audiences Queries screen

Common Dynamic Audiences Terms

The table below lists common terms we use when talking about dynamic audiences.

TermContextDefinition
Engagement Query Language (EQL)Engagement queriesThe set of precision filters that produce statistics about customers and their journeys, allowing you to analyze and gain insight into their behavior and the success of your customer engagement strategy.
Action contextEngagement queriesThe unique features of an orchestration, defined in an engagement query, required to include a customer journey in the query results. Can include any combination of Channel, touchpoint, proposition, action, response, asset, optimization point, device OS, and device type.
Customer filterEngagement queriesThe set of filters, defined in an engagement query, that pre-filter the population of customers according to known demographic attributes (such as age, gender, marital status) or brand-related inquiries (such as submitting an email address). Customer filters perform their filtering on the full customer journey path.
Interaction contextEngagement queriesThe unique features of a customer interaction with your brand, defined in an engagement query, required to include a customer journey in the query results. Can include any combination of channel, touchpoint, lifecycle stage, activity type, proposition, date, device OS, and device type.
Journey filterEngagement queriesThe set of filters, defined in an engagement query and applied AFTER any customer filters, that split the full customer path into multiple journeys based on customers moving from one interaction to another with an objective such as completing a product application.
Active customerJourney visualizationA customer who last performed a tracked activity within 80% of the timeframe configured for a lifecycle stage.
Backward transitionJourney visualizationA flow that highlights customers moving backwards between two lifecycle stages.
ChannelJourney visualizationThe pre-defined category to which a touchpoint belongs. For example, web or mobile.
DropinJourney visualizationThe point at which a customer joins the journey.
DropoffJourney visualizationThe point at which a customer leaves the journey.
FlowJourney visualizationLine depicting the number of customers moving between two nodes on the journey.
Forward transitionJourney visualizationA flow that highlights customers moving forwards between two nodes on the journey.
High Value Moment (HVM)Journey visualizationNode identifying a positive moment on the journey that translates into customers being able to satisfy their goal.
Inactive customerJourney visualizationA customer who has not performed a tracked activity within 80% of the timeframe configured for a lifecycle stage.
Looping flowJourney visualizationA flow that highlights a customer moving from one channel to another, within the same lifecycle stage.
Low Value Moment (LVM)Journey visualizationNode identifying a negative moment on the journey that translates into customers being unable to satisfy their goal.
Most Dominant Path (MDP)Journey visualizationJourneys with identical start and end contexts, undertaken by the largest numbers of customers. Nodes in between the start and end contexts may differ.
NodeJourney visualizationA single Interaction or Action context on the customer journey.
Optimized customerJourney visualizationA customer who has received personalized content during the customer journey.
TimeframeJourney visualizationThe period of time that a customer can stay on a lifecycle stage before they are considered to have left the customer journey.
VolumeJourney visualizationThe total number of customers currently on a given node on the journey.