Hyper-Targeting: a key component of Predictive Marketing Campaigns
In the previous blog, we discussed about an overview of Predictive Marketing Campaigns. In this post, let’s introduce the topic of Hyper-Targeting at a high level as it relates to Predictive Marketing Campaigns.
One of the key aspects as a Marketer, is to be able to target a specific group of individuals when running Promotions or Campaigns. Hyper-Targeting is a technique to identify or segment a set of individuals with specific interests to target.
Why do you need to segment?
Your Customer base must have tens of thousands or more often even running into millions of Customers also. The concept of segmenting your Customer base is not new in Marketing. You may have adopted custom criteria that is suitable to your business on top the basic RFM segmentation.
Segmentation is a technique to identify and make groups or subsets of Customer listings based on one or more criteria, to be able to pick and choose select group(s) out of millions, for running the Marketing Campaigns.
How accurately and precisely you segment, is what makes it an interesting challenge. Segmentation techniques can range from a basic, naive, seemingly common-sense criteria to more advanced statistical/scientific techniques. The basic, rudimentary techniques are not completely wrong but they simply are not complete and hence not the best method.
When you segment your Customer base based on certain set static, rigid rule based criteria, you are potentially missing two major issues in hindsight.
- Issue #1: By someone applying the rule to segment, you are inferring and assuming a lot about what would work best for the outcome (example: response rates)
- Issue #2: You are most likely not accounting for the entire historical knowledge, lessons learned in letting you drive the rules / algorithms to apply.
On the issue #1, you are taking control over the entire data and in some sense, acting as if you have got complete command of the full picture of your Customers on what would work. But, if you think about this, you will quickly realize that, without holistically mining for the data facts/figures, it is not logically sound to conclude that it is all fully figured out.
On the issue #2, it is very obvious that your rules/algorithms for doing the Segmentation is dependent on the past x weeks or months in question. But, in fact, your data is so dynamic that taking a narrow slice of recent past in segmenting for future campaigns, is the most innocent mistake that you can ever make. Perhaps, many people realize that, it is not sound but they do it anyway as there is no better alternative in sight.
Let’s lay out what type of solution would successfully address the above two issues. It maybe safe to restate a solution which is,
- A tool or technique that mines the entire Customer base and provides quantitative, aggregated statistics and also individual Customer level insights.
- A tool or technique that does not require manual intervention in feeding the rigid rules or criteria in discovering and segmenting the data.
In the next blog, let’s look into Personas and see how Customer personas complement Hyper-Targeting.
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