Mobilewalla FAQ  

Your Most Asked Questions - Answered 

Fast answers to frequently asked questions about Mobilewalla, our data repository, methodology, privacy, and data accuracy. Have a question not listed here? Our data experts are happy to help – connect with us today. 


What does Mobilewalla do? What is data enrichment?

Mobilewalla provides innovative data solutions that help marketing professionals, line-of-business leaders, and data scientists better understand their customers and prospects, enabling them to better analyze and predict consumer behavior to make more informed decisions and drive business results. 

Our proprietary solutions provide rich insights into consumer behavior, like location and mobility data at scale, that aren’t available through first-party data collection alone. These insights and attributes help organizations better understand, acquire, and retain their most valuable customers. In artificial intelligence applications, these attributes and features optimize and improve machine learning and predictive modeling outcomes to make more accurate predictions about consumer behavior. 

Mobilewalla offers a unique combination of the industry’s most robust data set and deep artificial intelligence expertise. We empower our customers through three key services:

  • DATA ENRICHMENT We enrich first-party data to help brands build a more complete picture of their customers. This unparalleled understanding of consumer behavior patterns positions brands to better attract new customers and retain and grow their existing business.
  • PREDICTIVE MODELING We provide Feature Mart a library of sophisticated highly predictive features that improve modeling accuracy and results while decreasing the cost and time associated with the feature engineering process.
  • AUDIENCE SEGMENTS With thousands of buyer data points modeled into any number of campaign-specific audiences, we help organizations effectively identify and reach their most valuable customers and prospects while maximizing their advertising ROI. 


How is Mobilewalla unique? How can consumer data help me?

Mobilewalla has the most comprehensive repository of consumer data in the industry, collecting 75 billion signals a day for more than 2.2 billion unique mobile devices in over 40 different countries. Our differentiators include:

  • SCALE Mobilewalla has the most comprehensive repository of high-quality, privacy-compliant global consumer information in the industry, with over seven years of historical data. The breadth and depth of our data allow us to build a more accurate understanding of consumer behavior and our historical data allows us to better detect these trends over time. 
  • INSIGHT Through deep data science and AI expertise, Mobilewalla delivers insights that enable brands to better understand their customers and prospects to drive growth. We offer 300 different attributes to help you get a comprehensive view of your customers and prospects and better understand and predict their behavior. 
  • IDENTITY Mobilewalla creates a comprehensive cross-channel view of the customer using the mobile ID as a persistent key to connect online and offline behavior and understand household relationships. Mobilewalla data is not cookie-derived and our extensive number of diverse data sources has helped us to main supply during the changes affecting the data ecosystem.
  • QUALITY Mobilewalla incorporates fraud prevention and cleansing measures to provide the highest quality data at scale, for accurate consumer intelligence, precision targeting, and high-performing predictive models.


Where does third-party data come from?

Mobilewalla acquires data from various third parties in the digital ecosystem, including publishers, demand-side platforms (DSP), data management platforms (DMP), and data aggregators. 

After consolidating the data from multiple sources, Mobilewalla applies data cleansing techniques, fraud detection measures, and various methodologies, using a combination of deterministic, artificial intelligence, and machine learning techniques to discard bad data and leave only highly accurate data which can be used to make predictions, create profiles, or perform data analysis. 

The depth and breadth of this data, collected over an extended period, allows Mobilewalla to build a profile around each device ID. These profiles include the data received directly from the data source as well as insights into broader consumer behavior that have been derived using various artificial intelligence techniques.


What does it mean when data is privacy compliant?

Mobilewalla takes consumer privacy and consent seriously and as a steward of this data is compliant with all local, national, and international regulations (such as CCPA and GDPR).

Each Mobilewalla data partner must meet rigorous criteria and are required to represent and warrant qualifications such as:

  • They have a consent and privacy framework and associated processes for active compliance.
  • The data provided to us has been obtained lawfully and in compliance with the local regulations where the data was sourced.
  • They have the legal right to sell and transfer the data to us.
  • They will electronically provide us with any requests from users that have communicated to them any of the following: opt-out, data deletion, information requests, do not track (DNT), do not sell, consent withdrawals, and any other similar user requests.
  • The partner clearly discloses in their privacy policy how the user’s data will be processed, including that third parties will/may process their data, and that a user has a clear and easy way to communicate their consent and privacy requests to the partner both electronically or by written means.

We take the following additional steps:

  • Our customers complete a data usage form as part of the contract process that outlines the use cases for the data they are sourcing from Mobilewalla to ensure data is being used appropriately.
  • We process opt-outs received through our data partners, the Digital Advertising Association, opt-out request proxy companies as well as through direct submissions at multiple points in our processing to ensure that data is used in compliance with regulations.
  • Our privacy policy is accessible from multiple places on our website, as are links to our opt-out pages. We also accept opt-out requests by email and mail.


Do privacy updates decrease the available data collected from users?

One of the hallmarks of our input data is its high degree of source diversification. As a result, our data repository is insulated from severe impacts caused by privacy changes. We get data from many apps representing the entire spectrum of categories. All our other data items are meta-data that either arrive in a signal directly or that we have derived. 

We have built massive redundancies across app-to-user linkages, and no app has a significant percentage of our user population.


How do you validate audience segments for accuracy?

Mobilewalla uses predictive modeling to understand patterns around a device and then to group devices into specific consumer segments. We have created over 300 syndicated Audience Segments that satisfy a specific consumer targeting criterion. 

To validate segment accuracy, we have compared our Audience Segments to credible ground-truth data. In tests, Mobilewalla audience segments have shown consistently higher accuracy than similar segments from Facebook. Here is a summary of our testing methodology:

  • Reliable ground-truth data exists for the two most widely consumed audience segments — age and gender. Accuracy benchmarks are typically provided based on a metric called On Target Percentage (OTP).
  • To compute the OTP value for each high-confidence segment outlined, we pulled random devices from segments and ran campaigns against them on Facebook. We pulled approximately 1 million devices for each segment. This means we are providing a lift 3.5 times that of a nontargeted segment.
  • We then ran the corresponding campaigns for an average of five days. To compute our uplift, we looked at the number of devices that Facebook reached through the campaign. Out of 100,000 devices the campaign reached in the 35-44 age group, our OTP for that group was 69%, while the Facebook country average for the age group was 20%
  • This means we are providing a lift 3.5 times that of a nontargeted segment.

Learn more about our test methods and results in our Demographic Data Accuracy technology brief. In this document, we report on a comparison of the OTP of Mobilewalla audience segments to the Facebook country averages for those specific segments.


How do you detect and remove fraudulent data?

Mobilewalla applies data cleansing techniques, fraud detection measures, and various methodologies, using a combination of manual and third-party validation, as well as deterministic artificial intelligence and machine learning techniques to discard bad data. 

This leaves only highly accurate data, which can be used to make predictions, create profiles, or perform data analysis. Read our technology brief on Anomaly Detection to learn more about what makes our data trustworthy.


How do I map third-party data to my first-party data?

Mobilewalla has created a set of techniques to match an organization’s first-party data with the vast amount of information available through our consumer intelligence platform. To enrich your existing data with Mobilewalla, we must find a common "key" that can match across both data sets. 

Mobilewalla data is keyed on the mobile advertiser ID (MAID) and can match several first-party consumer data such as MAID, IP Address, Physical Address, and Hashed Email (HEM). 

Data sets can be purchased together or separately depending on your business needs. They are available in various forms to easily integrate with existing internal systems via system-to-system transfers.

We support leading cloud platforms: 

  • Amazon Web Services 
  • Microsoft Azure 
  • Google Cloud 

Our data can also be accessed through various demand-side and data management platforms at a frequency that makes the most sense for your business. 

Or, contact us to ask specific questions about our mapping methodology or see how data enrichment can work with your MarTech stack.


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