"Create bespoke media plans at speed"
We look forward to further using Neuton to provide high quality forecasting products to
Wavemaker clients. We are positive that it will stimulate customer satisfaction rate and
revenue growth by applying more effective and efficient marketing campaigns.
Wavemaker Media Agency Leverages Neuton AutoML to Optimize Media Planning
Customer
Wavemaker is a media agency with recognizable expertise in analyzing the consumer purchase
journey, thereby requiring the processing of a huge amount of data and global billings of over
$38 billion US Dollars and is part of GroupM and WPP plc.
Wavemaker Russia is a branch of the second largest media agency network in the world, with clients such as Johnson & Johnson, Beiersdorf, Huawei, IKEA, Colgate-Palmolive and many others.
Wavemaker Russia is a branch of the second largest media agency network in the world, with clients such as Johnson & Johnson, Beiersdorf, Huawei, IKEA, Colgate-Palmolive and many others.
Challenges
Nowadays, in the process of media planning, econometric models are often used to allow
forecasting of the values of various indicators in the future: clicks, purchases, Internet
traffic, website visitors, and much more. These models also help establish a marketing budget
intelligently split across channels, products, customer segments and regions.
The creation of econometric models typically requires the efforts of highly qualified software and data specialists and, which makes difficult both to launch the models quickly, and to use them widely. Wavemaker Russia, however, sought to develop a solution that would allow their business users with no coding skills to apply similar models in the media-planning process efficiently.
The creation of econometric models typically requires the efforts of highly qualified software and data specialists and, which makes difficult both to launch the models quickly, and to use them widely. Wavemaker Russia, however, sought to develop a solution that would allow their business users with no coding skills to apply similar models in the media-planning process efficiently.
Solution
Using the “no-coding-required” Neuton AutoML platform, Wavemaker Russia’s tech hub was able to
build out the desired econometric model quickly and with high accuracy (see Fig. 1).
The whole process from idea and data gathering to creating a working predictive model, including data preparation and feature engineering, took less than a week.
The ease and efficiency of utilizing Neuton Auto ML, without need for coding skills, provided Wavemaker Russia with an instrument for creating highly accurate econometric models for media planning efforts, while also freeing up the time of their most highly skilled software and data specialists so that it can be redirected toward more complex or challenging projects.
The whole process from idea and data gathering to creating a working predictive model, including data preparation and feature engineering, took less than a week.
The ease and efficiency of utilizing Neuton Auto ML, without need for coding skills, provided Wavemaker Russia with an instrument for creating highly accurate econometric models for media planning efforts, while also freeing up the time of their most highly skilled software and data specialists so that it can be redirected toward more complex or challenging projects.
Figure 1. Model quality index for Wavemaker Russia’s econometric model.
Results
During Wavemaker Russia’s initial exploration of the Neuton Machine Learning solution proved
itself to be a highly efficient automated platform which can simultaneously:
“We are looking forward to further integration with Neuton API to provide high quality
forecasting products to Wavemaker clients. It will stimulate customer satisfaction rate and
revenue growth by applying more effective and efficient marketing campaigns.” – Anton
Kolesnikov.
be used by business users with no coding skills for everyday forecasting routines;
enable companies to reduce time to market and improve overall model and process reach &
efficiency;
minimize the need (and associated cost) for tech specialists, and/or allow these key
resources to focus on other areas, where they can better serve the company.
