What are marketing attribution and performance management platforms?

MAPM platforms help marketers demonstrate ROI and allocate future spending to bring it in line with business goals.

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One of marketing’s greatest challenges is proving its ROI. Marketing attribution and performance management (MAPM) platforms do this by using attribution functionality, statistical modeling and machine learning to evaluate the performance of a company’s marketing initiatives on bottom-line impact.

They can help marketers determine the success of their efforts so they may allocate future spending and bring it in line with business goals.

Terminology

There is no consensus on what to call these platforms. Some refer to them as “marketing performance measurement” or “marketing resource management.”

We use “marketing attribution and performance management” because it encapsulates both the attribution aspect (performance measurement) as well as the bigger-picture function of using data and technology to assess bottom-line results and make decisions about future spend (performance management).

Marketing Performance Management

Download the MarTech Intelligence Report: Enterprise Marketing Attribution & Performance Management: A Marketer’s Guide

Marketing attribution and performance management platform capabilities

Here’s a list of capabilities being offered on MAPM platforms.

Integrations and data gathering

  • Integrate with a variety of martech and adtech software, including CRM, marketing automation, customer service software, ad servers, demand-side platforms and the like.
  • Connect with other software the business uses to manage its operations, including enterprise resource planning (ERP) systems, business intelligence tools, inventory management systems and office suites.
  • Ingest data from multiple marketing and communication channels (radio, TV, connected TV, call centers, email, digital ads, website interactions, etc.) to capture information about customers’ and prospects’ interactions with a brand.
  • Relationships with Facebook, Google and other “walled gardens,” as well as data providers that allow for the augmentation of customer profiles and campaign metrics.
  • Gather information about conversions. This data most often comes from sales but may be generated by ecommerce, point of sale, CRM systems, or any location where transactions take place.

Analysis and reporting

  • Employ a variety of attribution models — single touch, fractional, algorithmic, proprietary, etc. — to tie the marketing interaction data to conversions. Insights gained from marketing mix modeling (MMM) may also be used to provide insights into how campaigns affect sales.
  • Allow users to choose from or tweak attribution models based on their own business categories and goals.
  • Incorporate custom models designed to make the most of first- and zero-party data to help marketers cope with the growing scarcity of third-party cookies.
  • Combine multiple different models and types of data into a unified whole that provides actionable insights.
  • Connect the marketing interactions to individual campaigns, including cost per thousand (CPM), cost per acquisition (CPA) or other relevant measures (internal resource expenditures) of the cost of that interaction to the brand.
  • Provide reports, including visualizations, that improve marketers’ understanding of data, including maps, charts, graphs, waterfalls and notifications. These reports help marketers understand which activities performed better than others. Reports can often be segmented by various dimensions, e.g. time, geography, product, channel or business unit.
  • Segment customer and prospect records to create audiences for targeting in marketing channels.
  • Analyze customers’ behavior throughout the purchase journey. This data is used to identify roadblocks in their path to conversion and reduce friction in the buying process.

Modeling and orchestration

  • Analyze historical or recently acquired data and proactively offer suggestions for future campaigns or for modifying ongoing campaigns in real time. This is facilitated by machine learning and AI technologies.
  • Planning functionality that lets marketers construct “what if” scenarios and generate likely outcomes, to aid in planning for future budget allocation.
  • Orchestration capabilities that enable marketers to act on their analyses by tweaking targeting, creative or other elements based on their conclusions.

Dig deeper: How marketing ops improves ROI through campaign performance and budget management

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About the author

Pamela Parker
Staff
Pamela Parker is Research Director at Third Door Media's Content Studio, where she produces MarTech Intelligence Reports and other in-depth content for digital marketers in conjunction with Search Engine Land and MarTech. Prior to taking on this role at TDM, she served as Content Manager, Senior Editor and Executive Features Editor. Parker is a well-respected authority on digital marketing, having reported and written on the subject since its beginning. She's a former managing editor of ClickZ and has also worked on the business side helping independent publishers monetize their sites at Federated Media Publishing. Parker earned a master's degree in journalism from Columbia University.

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