Traditionally, non-profits have been viewed as “following the pack” when it comes to marketing innovation. Commercial marketers tend to have bigger budgets which allow for greater access to talent and resources, as well as a greater investment in new technologies. However, the lack of ready capital has lead some non-profit marketers to take a less traveled path.
The evolution of the digital age has brought about the accumulation of an infinite amount of data. While marketing databases and CRM programs spend a great deal of time managing data, significantly less time and energy is spent on obtaining valuable information from the data. Today, some non-profits marketers are bucking that trend. Some are taking a serious look at their accumulated data to uncover valuable insights about donations.
A recent article in Direct Marketing News highlighted the success of such an effort by the American Heart Association (AHA). Like many non-profit organizations, the American Heart Association saw a decline in donations from 15% in Q4 of 2007 to 6.6% in Q4 of 2009. The AHA decided to mine its database to understand what motivated people to donate. A program was implemented to “mind-type” the database. In simple terms, mind-typing defines the way that every person feels and views interactions with an organization. By showing participants various statements, each person was mind-typed and, based on their responses, were mind-typed into several different categories. Once completed, a direct marketing campaign was developed with messaging tailored to each mind-type.From May to September of 2009, 28% of donations were directly attributed to the campaign.The AHA’s results are difficult to ignore. They suggest that there may be great gains from investing in internal data-mining processes. The challenge is that it is often a less glamorous, more mundane discipline. Somehow it is easier to get excited about a new campaign than mining a database. However, with a process such as mind-typing, both non-profit and for-profit organizations may find that they can realize significant gains from the data they already have.