Customer Profiling and Direct Mail Execution Techniques to Maximize ROI on Direct Mail

Project Description

Overview

We are a marketing technology company printing and mailing a lot of direct mail for our SMB customers. As such, we are collecting a lot of data otherwise not typically aggregated in one platform, including unique response data tied to each direct mail piece.

We have a data-set with over 1,000 direct mail orders, perhaps millions of recipients. We have response data (call-tracking data) for each order monitoring unique calls. We also have a number of attributes on each order - i.e. the creative used, the offer available, the day it dropped, the geographic area it dropped to, the demographic make-up of the ZIP Codes, the type of mail, etc. We also may be able to access lists of actual customers.

2 Problems to Solve

Problem #1

We would like to build specific data models around core product offerings and promotions that we know will optimize targeting and list purchase techniques for direct mail and therefore maximize ROI on each campaign. 

Problem #2

Other than the list targeting component of direct mail, there are many other factors that affect ROI. We'd like to figure out all the factors that influence outcomes to make recommendations to our clients on how to decide on creative, offers and other mailing techniques based on the audience being targeted to maximize ROI.

Expertise Required

We are seeing someone authorized to work in the United States who has had a track-record and significant experience in the above. And if this pans out, is open to the idea of longer-term relationship.

Data Sources at Our Disposal / Current Technology Stack

We have a host of database developers that can assist with getting you what we need, either from outside sources to augment the data or of course, inside sources based on the data we are generating.

Our technology stack relevant to this project is: 

Postgres, Apache Tomcat, LogiAnalytics Java engine

What are we looking for?

Someone to:

- Pointing to a successful track record of similar projects and referrals, help us save time and effort by giving us key instructions on how to set this project up for success.

- Analyze the data we have.

- Suggest additional data we should be capturing or third-party sourcing

- Find patterns and unlock value in the data beyond the obvious, helping us report back on key findings.

- Build predictive models as a result of key learnings that can help us purchase mailing list aquisition data to maximize ROI.

- Supply our technical team with models to build into our product and deploy to our Private Cloud-Based Application. NOTE WE ARE NOT EXPECTING THE CONSULTANT TO DO THIS WORK, just provide us the specifications to help build this into our platform.

Samples data files and fields will be provided upon execution of an NDA after initial proposals are submitted. For all intents and purposes, assume we have all the data necessary to derive value out of this project.