Effective Data management for Affiliate marketing

This multi-part blog post recommends a framework for Advertisers to effectively manage data sharing with their partners and affiliates and boost their returns from various channels. Let’s begin by taking a look at some of the complexities involved with data sharing and a brief introduction to the Vizury framework. In subsequent posts, we will dive deeper into the framework with the help of specific examples and understand how some 3rd party players are advancing the evolution of this aspect of the ad-tech ecosystem.

Partners, affiliates and data

Channel partners or affiliates need data to engage users and lead them to transact on an advertiser’s website. A price comparison site like Junglee, Coneco or eTao might need product (catalog) data only. Sophisticated channels like retargeting need both user-intent and product data. As Advertisers begin to work with a motley group of affiliates, managing their individual data needs often starts turning nightmarish. It’s just data, why do we need a framework/process to manage it, you say? Well, here is what could go wrong:

  • Data security: Safe-guarding personally identifiable information (PII) or other sensitive data needs to be a part of the organization’s DNA. Like disaster recovery solutions, everyone knows it’s important but rarely is anything done till it’s too late.
  • User experience: If not done right, how you distribute data can impact other systems which may hamper users’ experience with your brand/website. For e.g. badly engineered affiliate tags could bring website page loads to a crawl.
  • Consistent and correct messaging: Imagine the after-taste when a user sees and clicks on an ad for a discount offer that actually expired days ago! Not great, right? Messaging is important and advertisers should moderate what affiliates say to potential customers like orchestra conductors.
  • Sub-optimal ROI: If affiliates aren’t enabled with the right data, advertisers are actually getting in the way of their delivering the best results they are capable of.

As an organization that works with hundreds of clients, we are no strangers to the aforementioned challenges. Catering to different verticals and advertisers requires us to deal with disparate data sets, each with a mind of its own! To make our lives easier, we have come up with what we believe is a handy framework to effectively visualize, monitor and enhance our data input setup. And, we would like to share this with everybody.

The Vizury Data Management framework

The following are the fundamental tenets of the framework:

  • Segregate data sources: Identify the different sources of sharable data across systems and segregate them based on the source type. E.g. Catalog data may be extracted from inventory management systems; User interaction data needs to be sourced from content management systems/website and so on.
  • Build a data dictionary: Enumerate the different data fields and define each field in detail. Definition could include attributes like purpose, format, nature of aggregation, temporal sensitivity etc.

Data Dictionary
data dictionary

  • Map data sources/fields to affiliates & share effectively: Understand who needs what data and whether the best practices for ingesting a particular data source are being adhered to or not.

Segregation and Mapping
Data Segregation and Mapping

In the next blogs in this series, we will dig deeper into each stage of the framework and go through detailed examples of sharing catalog and user intent data. I hope you will find this method useful. Keep watching this space for more!

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