Campaign Tracking
With all the effort put forth to execute the campaign, a key point of failure for campaign effectiveness lies with the tracking and analysis. Just getting the message out isn’t sufficient. How was that message received? What does the overall response to the message say for future campaigns?
Managing Your Results
For an email campaign, the last post talked briefly about using embedded codes in the response URL to aid in customer/response matching. Assuming this has been taken into account, the management of the results should be much easier. The responses will be tied to the customers and the results analysis will be much more robust. If however, the response data requires manual intervention, it is imperative that this data be collected and entered quickly in order to be able to provide campaign response analysis. Without this data, there will be no valid way to determine whether or not the campaign was worth the time, effort and expenditure and either future opportunities to repeat a successful campaign will be ignored or excessive costs will be squandered repeating unsuccessful campaigns.
Analyzing Your Results
Just counting the positive responses isn’t enough. Also including the negative responses is not sufficient either. Even the non-responders should be counted. For example, an email campaign is executed and 10,000 emails are sent. A control group of 1000 exist who were not sent the campaign message. The goal of the campaign was to generate an order. Of the 10,000 who were emailed, 700 ordered a product. 300 replied no thanks or just clicked through without ordering. And 9,000 did not respond. Of the 1000 control population, 50 ordered a product. 70% of those who responded did so positively. That’s good, yes? Yes, depending on the expected response rate. For an expected response rate of 5%, that’s quite good as the response rate was 10% and 7% of your responders were positive. What elements of this campaign worked well? Can these be replicated next time? If your expected response rate was 15%, then the results are not as good. The message was good for those who responded, but what needs to happen next time to drive the response rate? And consider an example where 300 responded positively, but 700 responded negatively of the 10,000 respondents. Careful analysis of how and why the message was received so negatively is in order.
Actions To Be Taken from the Results
Our learning and effectiveness comes from an iterative cycle. We learn from our successes and our mistakes. A good positive response, but low overall response rate means several things were done right – but the efforts for next time should focus on improving the response rate. Analysis of the expected response rate should be considered too. Was the original response rate too aggressive? Or was the expectation not aggressive enough? A poor positive response, coupled with a low overall response rate will require a re-focusing on the message as well as the methods in order to drive both positive response and overall response. A more detailed look into specific examples will be covered in future posts.
