Operational Approach to Tweaking the Campaign Build Process

  • 18 May 2015
  • Posted by Anand Sambasivam
  • 0 Comments

Marketers need to comprehend that a cloud based marketing platform is enticing but SHARED across other customers of the ESP / MSP.  If their campaigns have a performance problem, you can bet your boots that your holiday / week end campaign gets hit as well.

The challenge of course, is in getting this context – MSPs may not share this information and degree of “Infrastructure Sharedness” too freely. After all, as a marketer, you subscribe to SLAs around the infrastructure not to a “labeled” marketing server itself.

Getting a little technical here, since the context is important in understanding the overall challenges in managing first a marketing database and second on infrastructure like cloud based systems.

Managing a fully functional Marketing database is a challenge primarily due to the usage patterns that it needs to cater to. Some of the Use cases an email marketing database needs to exhibit are listed below.

  • Online Transaction Processing - for opt-in Management, preferences and Transactional Messaging.
  • Data Warehouse
  1. Extract, Load and manage millions of demographic, transactional and behavioral  data
  2. Manage and Effectively Utilize Event Data for segmentation and reporting.
  3. Merge and Query Massive data sets for Effective Targeting.
  • Reporting 
  1. Data exports on campaign efficiencies and ROI.
  2. Campaign Trends & Response Variance Analytics.

A primary area where the use cases seem contra indicatory are Data Load Jobs and Campaign Launches. Both are business critical; time sensitive and contra indicatory–one being a bulk data import and the other a data crunching background process.  Scheduling Campaign Launches and Load Jobs appropriately is critical since both processes tend to use the same database resources / objects and can quickly tie each other down creating dead lock scenarios depending on the underlying technology.

It is important to correlate these adjunct activities from  frequency, intensity and duration depicts the perspectives in order to predict and manage system load. The following days in life

 

                                        Figure 1: Launch & Load Jobs Scheduling

chart contention that a typical Email Marketing database goes through.

This chart (Fig 1) depicts the Data Load / Campaign launch identifier on the X axis and the scheduled   time of the day on the Y dimension. The Red colored dots indicate the times of the day when concurrent jobs and campaigns could potentially come into conflict. This information by itself is only an indicator since intensity or the load on these jobs / campaigns is still not evident.  .

The following graph Fig 2 is a more analytical report which combines the schedule with the average time consumed for the launch or load job.  The X axis indicates the Job / Campaign identifiers and the Y axis the schedule. The intensity is of the process is indicated by the length of the execution process as the average duration of the load or campaign process over the last 30 days.

 

                               Figure 2: Campaign & Data Load  Intensity Perspective 

This kind of “Contention Analysis” is highly useful tool in deciding operational strategy, System Housekeeping, maintenance requirements and ultimately managing campaign performance.

So, the key to operational control is the track and ensure proper scheduling of campaigns and parallel jobs in such a way as to reduce stress on a common infrastructure. Remember, spread it thin and keep it simple.