Understanding the Campaign Build Process inside Marketing Platforms
Marketing technologists need to be increasingly aware of the constraints that come in her/his away in staging successful email campaign. The delivery process hogs database resources and renders the system unavailable and / or too slow for other contenders like online subscriptions, data loads and reporting. Marketers need to manage the delivery process effectively as the key to ensure predictable campaign delivery, high availability to competing processes and in case of SaaS based platforms – direct Customer Satisfaction. This can be akin to the role an air traffic controller plays while trying to help land aircraft at a very crowded airport.
Let’s take a quick look at the four major phases of Email Marketing
- Creative: Creating & Editing Email Content and Link Up Pages
- Integration: Data Management, Cleansing and Import Functions
- Delivery: Campaigns, Segmentation, Personalization and Campaign Build Process
- Analytics: CED (Campaign Event Data), ROI, Link Tracking etc.
Enhancing the Campaign Build Process can be approached from three fundamental perspectives:
- Technical: Managing the Build Process external to the e-Marketing ecosystem
- Operational: Identification and Contention Management amongst competing processes
- Design: Database Design & Structural Rationalization
The Campaign Build Process and the Levers:
The high level process is a 3 step breakdown
a) Query the Customer database based on the Segmentation Rules
b) Execute Personalization rules set up by the Marketer
c) Merge Content ( Static & Dynamic) from the asset library / CMS
A detailed WORK FLOW of the campaign build process is depicted below
Performance of a campaign depends on a plethora of factors like
- No of active customers
- Concurrent Processes
- Data Model & Skew
- Segmenting Complexity
- Personalization levels
Some of the levers mentioned above can be tweaked to improve the overall performance and fall typically under three broad categories – Platform Architecture, Operational Process and Database design.