Third Party Data

Here is what differentiates first-party, second-party, and third-party data:

• First-party data: Data a company collects from its own users (apps, CRM, website). 

• Second-party data: Another company’s first-party data shared through partnerships. 

• Third-party data: Aggregated, privacy-compliant data from multiple ecosystems (devices, apps, ad-tech, mobility, marketplace signals), providing additional context about the consumer and enriching decision-making at scale. 

Third-party data comes from consent-driven sources such as mobile app ecosystems, publishers, ad-tech networks, device sensor signals, app metadata, and location/mobility insights. Providers like Mobilewalla collect, clean, and aggregate these into stable datasets or productized signals. 

Yes. Providers like Mobilewalla only work with anonymized and pseudonymized identifiers, not PII. This ensures strong privacy protection. 

Yes, third-party data is legal to use when sourced and processed under user consent frameworks, and if it is compliant with local privacy regulations. Mobilewalla data as well as their LendBetter, and Market Flow solutions operate under GDPR, PDPB, CCPA, and region-specific guidelines. 

Mobilewalla, as a highly trusted industry source for third-party data, works only with partners in the ecosystem who capture consent transparently. All data we capture globally is non-PII.

Mobilewalla maintains compliance through anonymization, opt-out mechanisms, strict data vendor vetting, and audit procedures across all markets we operate in. Mobilewalla data products and services, including but not limited to LendBetter, Market Flow, and our Data Enrichment solutions, operate under GDPR, PDPB, CCPA, and region-specific guidelines. 

Data aggregation in context of third-party data implies grouping of signals (e.g., device behaviour, mobility flows) at a segment or location level, ensuring no individual can be identified, essential in products like Mobilewalla Market Flow that provides broadband providers with granular market and customer insights for operational planning and strategic decisioning.

First-party data shows “what customers did in the context of their relationship with you.” Third-party data from Mobilewalla provides context on: 

• What similar users are doing outside of your ecosystem 

• Competitor exposure 

• Device behavior patterns 

• Risk or fraud markers (via LendBetter) 

• Telco market movement (via Market Flow) 

This creates a more complete user profile for achieving better outcomes in use cases such as campaign optimization, boosting free-to-paid conversions, optimizing default risk in lending to thin-file and new-to-credit, preventing fraud, etc. 

Third-party data, from reputed and trusted providers such as Mobilewalla, enriches decision-making with signals that reveal intent, risk, fraud patterns, competitor influence, mobility, and multi-app behaviors, and thus helping digital first businesses build more complete profiles of their users and prospective customers.

Yes. Third-party data artifacts such as Mobilewalla’s set of predictive consumer features can consistently add 10–25% predictive lift across models involving risk scoring, churn prediction, segmentation, and offer propensity. 

Third-party data, when sourced from a reputed and reliable source like Mobilewalla, provides rich market-level consumer/context data even before a business builds first-party datasets in a new region. It can be a great strategy to explore third-party data for pushing initial use cases in a new market, as first-party data is limited in such scenarios.

Third-party data use cases span a wide spectrum of functions across marketing, lending, fraud, risk, product, operations, network planning, and customer analytics. Data providers such as Mobilewalla are adept at understanding the needs of each of these domains and providing the right solutions that lead to optimal predictive performance lift consistently.

• That third-party data always contains personal or sensitive data (it does not). 

• That it is unreliable (quality depends on provider maturity — Mobilewalla is an enterprise-grade provider). 

• Privacy laws prohibit third-party data (they regulate it, not prohibit it).

Mobilewalla provides a wide range of third-party data based predictive customers features that power machine learning use cases across functions like risk, marketing, fraud, network planning etc. Some of the foundational ones are as follows:   

• Device and behavioral metadata 

• App usage and affinity intelligence 

• Mobility and location-derived household insights 

• Fraud, risk, and stability indicators (LendBetter) 

• Market share and subscriber flow analytics (Market Flow) 

• Consumer segments and enriched user attributes 

While evaluating and choosing a third-party data provider, make sure to test for the following during the POC, and/or during discussions: 

• High quality 

• Breadth, depth and scale 

• Privacy and consent compliant

MAIDs are anonymized device identifiers used for ad attribution and analytics, set at an operating system level and unique to every smartphone. Mobilewalla uses MAIDs as a privacy-safe backbone for device-level enrichment.

Data enrichment is the process of adding new variables from third-party data providers such as Mobilewalla to a business’s first-party user records to create a richer customer dataset.

Some of the most compelling use-cases for a digital-first business to acquire third-party data from providers like Mobilewalla include: 

• Location-based marketing 

• Footfall attribution 

• Customer acquisition or retention 

• High value customer identification 

• Look-a-like audiences 

• Credit scoring (LendBetter) 

• Fraud detection 

• User segmentation & audience building 

• Market share intelligence (Market Flow) 

Mobilewalla works with leading global businesses across Fintech, Telco, e-commerce, gaming, QSR, OTT, travel, and marketplaces. 

Mobilewalla ensures data accuracy using multi-source validation, machine learning checks, anomaly detection, and long-term behavioral consistency scoring. We validate our data through statistical benchmarking, external reference checks,and use of truth-sets periodically. Truth-set validations are used to assign confidence scores to certain predicted demographic features like Gender and Age.

The key things that differentiate Mobilewalla’s data solutions from other third-party data providers are scale, multi-year consistency, multi-region coverage, highly predictive features across a variety of business use cases, and strict supplier auditing.

Coverage refers to % of devices, households, or users represented. Higher coverage results in more representative intelligence, especially solutions like LendBetter or Market Flow. Mobilewalla has device-level coverage across APAC, MENA, and global markets, powering both lending and telco use cases.

Mobilewalla adopts enterprise-grade encryption, secure transfer protocols, region-specific hosting, and SOC2-aligned practices. We build our data platform and analytics solutions on AWS infrastructure, enabling a reliable, scalable, and secure environment for managing vast datasets. While Mobilewalla applies our own privacy and governance policies, the underlying AWS platform provides secure compute, storage, and networking.

A trusted and reputable third-party data provider like Mobilewalla will always provide data science support, model guidance, feature selection help, and post-integration tuning.