Automated Mail Marketing Platform

The Mail Marketing Platform was an automatic system created for niche digital-to-direct sphere operations.

GET FREE CONSULTATION

About the Client

PebblePost is a venture-backed company that pioneered in a niche business segment related to digital-to-direct mail. Their unique Programmatic Direct Mail technology enables the most efficient results for various marketing efforts. It currently boasts over 100 brand partners and a top space in ARF’s First Innovators A-List.

The company’s efforts have been recognized by a number of widely known business media, such as Forbes Magazine, Business Insider, Business Wire, etc. PebblePost has currently more than 50 employees and is headquartered in New York.

Technologies Used

Goal

The client needed to rebuild their existing platform entirely as the business grew rapidly and the company needed a more scalable solution. The current platform was developed as a proof of concept and wasn’t designed for huge loads. In addition, the client wanted to utilize Big Data technologies to the project to ensure high performance and scalability.

Work Description

The client’s original solution was based on Python which didn’t provide enough scalability for the rising demand. The client wanted to rebuild the platform completely and implement new web features. At first, Geomotiv ran deep technological analysis and provided a new architecture plan. Our team decided on Big Data technologies such as Scala, Spark, and GraphX for the solution. The client didn’t stop the original project, so we were supporting it and creating another one at the same time. Later on we performed full data migration from the primary solution to the new one and then the client stopped the original project. Our web technologies stack comprised Java and Spring for back-end and React for front-end. 

Our client had an agile (scrum) development approach and we were essentially an extension of the core team. The management process included three-week sprints, scrum meetings, backlog refinement, sprint planning, etc.

Work Stages

  1. New architecture design
  2. Back-/front-end development
  3. Data migration
  4. Quality Assurance
  5. Deployment
  6. Maintenance

Results

Having partnered with Geomotiv, the client was able to rebuild their entire system to the new business requirements. A specialized Big Data stack helped ensure scalability and fault tolerance of the delivered solution, which original Python-based platform couldn’t provide. With that system, the client managed to reduce the costs of additional support and provide their users with a greater scope of services.

RECOMMENDED CASES

Case Studies

media-buying-platform

Media Buying Platform

A technical solution designed to optimize and automate ad campaign deals, and to streamline “advertiser-account manager-publisher” communication.

View
clients-custom-solutions

Staff Augmentation for AdTech Company

A technical solution for ad campaign automation that was developed within the client’s integrated omnichannel DSP and DMP platforms.

View
big-data-chemistry

SSP and DSP Advertising Technology

A system to optimize the entire ad serving system that allowed for collecting, processing, and reporting on, billions of transactions every month.

View
custom-development-of-an-ad-management-system

White-Label Ad Management Solution

A flexible ad management system for large advertisers that brought industry recognition for MediaMath.

View
custom-scheduler-development

Custom Solution for Ad Campaign and Strategy Scheduling

Explore our user-friendly Scheduler system for ad campaigns and strategy scheduling integrated into the client’s DSP.

View
amazon-web-services-in-video-ad-network

Amazon Web Services in Online Video Ad Network

A perfect programmatic video-distribution platform for content owners that maximized monetization and personalization.

View
01
/
05

CONTACT

Let Us Contact You

Group 6 Created with Sketch.

Fill out the form below and we’ll get in touch within 24 hours

    Tell us about your project in your own words *

    I agree to  the  Privacy policy