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MediaMath to help marketers understand customers, real time

6 MIN READ

Independent programmatic company for marketers, MediaMath, has announced an enhancement to its management platform with the launch of Adaptive Segments. The latest addition to the management platform claims to help agencies and marketers to create, reach and understand their customers, in real time.

How will it help?

MediaMath states that client data is complex and fragmented, coming from multiple sources across platforms, making it difficult for marketers to understand their target audience. Adaptive Segments helps marketers to define granular audiences in real time, understand how they perform, optimize them quickly and activate them immediately across the internet. The audience segmentation ensures that marketers have a unified view of their customers to deliver personalized offers across channels and over time. Adaptive Segments has been designed to integrate with MediaMath’s DSP (Digital Signal Processor) to maximize performance and insights. Clients can also push audiences outside of the MediaMath platform to gain true customer-centric marketing capabilities.

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Keith Hawley, VP, Audience Platforms, MediaMath said, “Adaptive Segments enables marketers to transform their raw data into immediate actionable marketing tactics that enable actual one-to-one conversations with their best customers.”

“It’s no surprise that MediaMath’s largest brands and agencies are already actively using Adaptive Segments to personalize messaging at every stage of the customer journey and across their campaign budgets to serve the right message at the right time.”

How does it work?

According to the company, its DMP (Data Management Platform) connects data management directly with media execution and decision solutions, creating a single system of record across the life cycle of the consumer to drive the best outcomes to maximize marketing ROI. In addition to this new enhancement, additional components of its DMP include pixel and CRM onboarding tools, a cross-device and cookie-less identity solution, advanced analytics and insights tools, proprietary transaction-level data and predictive insights and third-party audience data available through the company’s network of data partners.

 

 

Rahul Vasudev, Managing Director, Asia Pacific, MediaMath stated, “One of the biggest issues facing the more advanced programmatic marketers today is the inherent latency that arises from trying to stitch together an ad tech stack with multiple parties.”

“There is a meaningful amount of data lost in transit. At the same time, marketers are losing their most important customers, the ones who have just put a product in their shopping cart in the past hour or so. While MediaMath has always had data management capabilities, Adaptive Segments heralds the beginning of a new era of data management technology that is already delivering performance improvements in orders of magnitude.”

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Key features:

  • Instant segmentation: According to the company, the audience size can be determined in seconds, enabling smart planning and budget allocation. Segments can be redefined and iterated over time without having to start from scratch. Spend starts instantly and segment membership is always accurate.
  • Granular testing and reporting: Adaptive Segments allows users to conduct “what if” scenarios without spending a cent of budget to test new segments to understand how they would have performed in past campaigns. Then maximize their ROAS (Return on Ad Spend) by targeting only the segments shown to have the best performance, and don’t waste spend on segments unlikely to perform.
  • Direct integration into MediaMath’s DSP: By native integration with MediaMath’s omnichannel DSP claims to enable instant-on audiences for maximum scale and reach. Standalone audience creation tools create a problem for marketers—whenever data is pushed into the buying platform, a large amount of addressable audience is lost. Using an integrated solution, marketers can reach 100% of their audience, and do it more simply, in one system.
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