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©2016 MediaMath, Inc.
CASE STUDY
May 2016
MediaMath & Skylads
Promotional Campaigns
Maximize the Impact of an
Internationa...
mediamath.com
©2016 MediaMath, Inc.+
In order to keep
their customers
happy and
continue to build
brand loyalty,
a interna...
mediamath.com
©2016 MediaMath, Inc.+
CASE STUDY: MEDIAMATH & SKYLADS MAXIMIZE THE IMPACT OF AN INTERNATIONAL RESTAURANT CH...
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Skylads Case Study - International Restaurant Chain

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The use of Skylads' Artificial Intelligence (AI) optmization algorithms coupled with MediaMath Demand-Side Platform (DSP) allowed an international restaurant to maximize the impact of its real-time bidding (RTB) programmatic advertising campaigns.

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Skylads Case Study - International Restaurant Chain

  1. 1. ©2016 MediaMath, Inc. CASE STUDY May 2016 MediaMath & Skylads Promotional Campaigns Maximize the Impact of an International Restaurant Chain’s +
  2. 2. mediamath.com ©2016 MediaMath, Inc.+ In order to keep their customers happy and continue to build brand loyalty, a international restaurant chain executes promotional marketing campaigns that are catchy and resonate with consumers of all backgrounds and ages. They focus on massive audience reach through a large volume of multi-strategy campaigns. THE BACKGROUND In May 2016, Skylads and MediaMath joined forces to support an international restaurant chain’s digital marketing efforts and drive stronger performance for two promotional campaigns that were running across the US. The brand used MediaMath’s TerminalOne OS and internal Platform Solutions talent to create a large volume of multi-strategy campaigns for each of their promotional offers. Campaigns were set to run across 50 states, in English and Spanish, and aimed at a wide range of target groups (age, location, interests, etc.) and contextual targeting segments. CHALLENGES The brand defined digital marketing success based on massive audience reach in order to maximize the impact of its promotional campaigns, while aiming for a precise number of delivered impressions for each campaign at an ambitious CPM. To drive performance and precisely fulfill the brand’s marketing budget, MediaMath’s Platform Solutions had to diligently monitor and optimize an immense volume of highly targeted segments. MediaMath needed an automated solution to alleviate some of the complexities involved with scaling during the bidding process. SOLUTION MediaMath partnered with Skylads to power an engine that would effectively combat some of the bidding issues that Platform Solutions encountered. R.Skott. io™, a machine learning-powered campaign optimization engine, fine-tunes campaign performance by working with MediaMath’s bidding algorithm, The Brain. While The Brain works on the front-end and participates in the advertising auction process, R.Skott.io™ works at the ground level by analyzing the performance at both strategy and campaign level and modifying at every hour the bid, frequency and pacing to further power The Brain’s bidding process. MediaMath & Skylads Maximize the Impact of an International Restaurant Chain’s Promotional Campaigns CASE STUDY
  3. 3. mediamath.com ©2016 MediaMath, Inc.+ CASE STUDY: MEDIAMATH & SKYLADS MAXIMIZE THE IMPACT OF AN INTERNATIONAL RESTAURANT CHAIN’S PROMOTIONAL CAMPAIGNS RESULTS Skylads’ R. Skott.io™ dynamically shifted budgets between campaigns and strategies to find opportunities to buy at the best CPM possible while increasing the delivery and reach of all of the international restaurant chain’s campaigns. R. Skott.io™ also assisted The Brain in choosing the right input values (max bid, frequency cap and budget pacing amount). EXPLANATION OF THE RESULTS GRAPHS The graphs below visualize the results achieved by optimizing with R. Skott.io™ — meeting Target Budget Delivery and Target CPM Range — by showing the average distance (in %) to achieving the objectives over time. Each color represents a separate campaign. The y axis depicts the distance to achieving the objective per cents and the x axis indicates the time (DD/MM format). Relative Distance to Target Budget Delivery Relative Distance to Target CPM Range

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