DIGI117

A cloud-based microservice application with AI-enabled data analytics and processing to manage, track and optimize mobile advertising campaigns for CPA strategies.

This system allowed a US-based marketing agency to run ad campaigns and monetize ad inventory with various types of publishers such as websites, mobile apps, ad networks, and affiliates.

Key system components:

• Complex server-to-server logic for setting up and tracking mobile ad buying between customers (advertisers) and vendors (publishers)
• Campaign management functionality to create, target and measure ad campaigns
• Contact management functionality that syncs advertiser and publisher data with existing CRM
• Detailed real-time reporting and analytics, including spreadsheets, graphs, and downloadable CSV/PDF files
• AI-powered ad optimization that uses machine learning and predictive analytics to analyze ongoing ad performance and optimize it for campaign KPIs
• Billing module that records finance data per campaign and creates respective invoice to be uploaded to existing finance software via API

To deliver the MVP of this application, DIGI117’s team used Node.js-based framework and NGINX web server, empowering JavaScript’s natural performance and scalability for high-load systems.

To organize campaign statistics and data storage, our developers leveraged MongoDB and ClickHouse database technologies and implemented flexible Redis data caching. Google AI was integrated as part of the campaign management module to optimize ad performance and target KPIs.

The system was designed as a cloud-based microservice backend architecture deployed with AWS. It utilized default progressive page-load together with server-side rendering that improved UX.

A special emphasis was made on the fast processing of big data for real-time campaign analytics and reporting.

This project included custom MVP development with product design and prototyping, AI machine learning for analyzing fraud patterns and anomalies, and high-performance database management for large datasets.

DIGI117’s team provided the client with a detailed project estimate to specify the resources needed to create an MVP tailored to their needs, covering desired features and components for ad fraud protection.

Key steps in the development process:

1. Making hypotheses and predictions about the must-have features
2. Building a product backlog that reflects the client's technical and business requirements and shapes the project vision
3. Creating graphic design and sketches, including product branding, HTML slicing, custom themes
4. Developing core features and functionalities, including user management, traffic tracking, fraud analytics, database management system
5. Delivering additional features, including artificial neural network module, API integration, file export, UI theme customization
6. Sharing interactive prototypes with user groups to demonstrate new features and optimize UX

DIGI117’s team included a project manager, data analyst, four developers, graphic designer, and two QA specialists. The team followed the two-week sprint process throughout the project course to build the requested feature set, collect regular user feedback, and customize MVP according to the client’s needs.

The system identifies most types of mobile ad fraud and anomalies, including:

• Botnets, device farms, device emulation, VPNs & proxies
• Click spamming, click injection
• App SDK spoofing and install hijacking
• Incentivization, duplicates, invasive ads
• Mobile attribution anomalies such as CTIT anomaly, wrong app versioning, abnormal device distribution

This Android app had to be as simple as possible, the special emphasis was made on the lack of excessive functionality that could otherwise complicate the UX and diminish the idea of hassle-free daily task management.

As a result of the scoping session, we were able to offer a variety of essential suggestions, such as:

• Using "Plan versus Actual" method, also known as a deviation analysis in project management, to organize tasks, dates, and categories, making it easy for users to track open and completed to-do items in the app.
• Dynamically syncing tasks and schedules with cloud services such as Google Calendar and MS Outlook.
• Implementing an automatic AI-driven smart priority system. App's AI would use machine learning to analyze task history (priorities, completion dates, task statuses, etc.) and suggest priorities for next tasks that feature similar attributes.

DIGI117’s team has successfully implemented a variety of features in the app’s MVP, for instance:

• AI engine to analyze tasks and suggest priorities
• Pie Chart, Bar Graph and tabular reports to track personal productivity by "Planned vs. Actual" stats
• "Offline" mode to create and manage tasks, to-do lists, calendars, and categories when there is no Internet connection
• Specify Status, Priority, Due Date, To-do List, Reminder, Notes, and Attachments for tasks
• Sync tasks and calendars with MS Outlook and Google Calendar
• Push, sound, email and SMS notifications
• Sound, email and SMS notifications
• Google location services to assign "Location" to tasks
• Task export and backup

The MVP version of the app has been delivered to the client within 10 weeks following the project kick-off and subsequently released to Google Play Store.