Mix Modeler use cases

Last update: 2024-07-10
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Mix Modeler enables the following key use cases.

Understand omnichannel incremental performance

This use case helps you to measure the impact of marketing across all paid, earned, and owned channels.

 Details

Challenges

The challenges these use case addresses are:

  • Difficult to measure incremental performance from siloed customer journey data, signal loss, and walled gardens.
  • Inconsistency in insights from separated MMM and MTA methodologies, reducing confidence in results.
  • Limited understanding of what marketing channels and tactics drive success.

Approach

The step-based approach for this use case is:

Step Details
Ingest Identify and ingest data sources under common schemas.
Apply existing investments in Adobe Analytics or Customer Journey Analytics to fast-track deployment.
Configure Configure flexible models using an AI-as-a-Service framework for your specific business objectives
Automatically ensure consistency between touchpoint & summary-level with bidirectional transfer learning.
Analyze Clearly understand the ROI of overall marketing and individual channels / subchannels.
Clearly understand which touchpoints best drive incremental conversions.

Impact

Successful implementation of this use can have the following impact:

  • Incorporate aggregate data, touchpoint data, and exogenous variables to get the richest view of measurement.
  • Use an AI-as-a-Service solution to quickly create models for driving success with access to model transparency for level of confidence.
  • Increase confidence in strategic and tactical decision-making through alignment in summary-level and touchpoint-level results.

Build marketing plans that optimize ROI

This use case uses user-friendly, AI-enabled optimization & scenario planning tools to maximize ROI.

 Details

Challenges

The challenges these use case addresses are:

  • Create data-driven marketing investment plans based on efficiency curves, not relying on gut feel.
  • Maximize outcomes across multiple geographies, lines of business, and channels simultaneously.
  • Long iteration cycles to create and compare multiple budget scenarios with high manual effort required.

Approach

The step-based approach for this use case is:

Step Details
Configure Easily customize measurement models to your business objectives.
Define parameters in a few clicks, no coding required: for example channels, geographies, sales cycles, lags, internal & external business factors, and more.
Train Train configured AI/ML models on to learn the best fit on input data, providing the most accurate results.
Optimize Get automated optimized budget allocations based on model forecasts.
Develop and compare multiple budget scenarios in a few clicks using an intuitive UI.

Impact

Successful implementation of this use can have the following impact:

  • Create marketing investment plans that maximize ROI across multiple goals and priorities.
  • Use incremental ROI curves to identify opportunities to shift budget.
  • Get monthly or weekly forecasts quickly using self-serve, democratized tools.

Activate tactical insights across Adobe applications

This use case helps you to gain strategic incremental insights on customer segments and journeys by accessing touchpoint scores.

 Details

Challenges

The challenges these use case addresses are:

  • Top-down solutions alone may miss on identifying granular key optimization opportunities.
  • The outputs of measurement models are overwhelming, overly descriptive, and do not easily lead to insights or actions.
  • Cannot conduct ad-hoc analyses to gain insights because models are not transparent and granular scores are not available.

Approach

The step-based approach for this use case is:

Step Details
Model Configure and train an AI/ML model to obtain consistent MTA touchpoint scores and MMM aggregate results.
Analyze Export incremental touchpoint scores into Customer Journey Analytics or external BI tools.
Perform granular analysis and build advanced dashboards using touchpoint scores.
Action Create and activate lookalikes to top consumer segments using Real-Time Customer Data Platform.
Develop data-driven marketing strategies by customer segments for future campaigns.

Impact

Successful implementation of this use can have the following impact:

  • Develop an understanding of incremental customer behavior and marketing tactics to inform strategic priorities for marketing and across the organization.
  • Maximize ROI by quickly detect trends impacting customers and your business to develop strategic responses.

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