Why Marketing & Data is a love affair

It’s the one topic that Modern Marketers need to learn to love – data. But moving beyond basic profile data is a challenge for many organisations. Your inbox is bombarded with white papers, infographics and reports that tell you how to do it. So, what’s stopping you?

Our observations of what stops companies getting more from their data

There are many reasons why organisations find the data play a hard one. The most common difficulties we see relate to data silos. For example, you have data in the CRM, the ERP, perhaps your e-commerce platform and of course, the marketing automation platform. Modern Marketers need access to all data that relates to the Digital Body Language™ of their contacts.

The next step is to segment contacts based on their explicit and implicit data. e.g. Explicit data is typically their profile – name, address, job title etc. It can also include expressed preferences like “email me once a week” or “email information about your events”. These are all explicit and expressed data points.

Implied or implicit data is the data you capture about a person as they traverse your digital properties i.e. your website, social media properties and their behaviour when receiving your emails. Did they open? Did they click-through? Did they visit a landing page and download your offer?

While it’s a worthy goal to enrich your data and build it with an array of data sources, the best play to start is with the data you have today. Some key considerations for better quality data would be:

What is the source of truth?
Once you understand where the master data is stored or where it could potentially come from, you then need to ensure that data is available for your campaigns.

Ok, what if a prospect or customer updates their profile?
A marketing database is typically not the source of truth, this honour usually rests with the CRM or the ERP systems. But, what if a contact who you know as “Jonathan Blackburn” completes a form to register for an event and he edits his pre-populated form with his first name as “Jon”. Surely “Jon” knows who he is and it’s clear he’d prefer to be addressed as “Jon”, not “Jonathan.

You need to determine some rules and work out who wins.
Trying to explain a data model in this blog post is probably not easy. However, fundamentally Modern Marketers need to understand the relationship between their various data sources and how they connect and who wins from a synchronisation point of view. In the example above, you want to update your marketing database with “Jon”, but what about the CRM, ERP and other databases?

Quality data is a journey, not a destination.
You may have a small database of contacts, perhaps less than 50,000 contacts. However, the principles of data cleansing and integrity are much the same regardless of the size of your contact database. Granted, if you have millions of contacts you really need the help of either a full time data specialist (this person should reside in Marketing) or something like MDM (Master Data Management – another tech industry acronymn) .

An introduction to Master Data Management

In order to successfully manage the master data, support corporate governance, and augment SOA and BI systems, MDM applications must have the following characteristics:

  • A flexible, extensible and open data model to hold the master data and all needed attributes (both structured and unstructured). In addition, the data model must be application neutral, yet support OLTP workloads and directly connected applications.
  • A metadata management capability for items such as business entity matrixed relationships and hierarchies.
  • A source system management capability to fully cross-reference business objects and to satisfy seemingly conflicting data ownership requirements.
  • A data quality function that can find and eliminate duplicate data while insuring correct data attribute survivorship.
  • A data quality interface to assist with preventing new errors from entering the system even when data entry is outside the MDM application itself.
  • A continuing data cleansing function to keep the data up to date.
  • An internal triggering mechanism to create and deploy change information to all connected systems.
  • A comprehensive data security system to control and monitor data access, update rights, and maintain change history.
  • A user interface to support casual users and data stewards.
  • A data migration management capability to insure consistency as data moves across the real time enterprise.
  • A business intelligence structure to support profiling, compliance, and business performance indicators.
  • A single platform to manage all master data objects in order to prevent the proliferation of new silos of information on top of the existing fragmentation problem.
  • An analytical foundation for directly analyzing master data.
  •  A highly available and scalable platform for mission critical data access under heavy mixed workloads.

Oracle‘s market leading MDM solutions have all of these characteristics. With the broadest set of operational and analytical MDM applications in the industry, Oracle MDM is designed to support Governance, Risk mitigation, and Compliance (GRC) by eliminating inconsistencies in the core business data across applications, like Oracle Marketing Cloud and enabling strong process controls on a centrally managed master data store.


FP OMC Data Management Guide 200pxl WideAn easy to read guide for what many organisations find complex

Click through now to discover four important tips to support your activities and help your teams not fall victim to the traps of being daunted by data.

This guide would serve well as a discussion piece at your next Marketing team meeting.