In Pardot, every time a prospect engages in an action (i.e click on a link, open a web page, read an email), a score is awarded. Based on prospect's overall score and time needed to accumulate this score, we can draw the person's digital journey and estimate their level of engagement. This is one of many ways to segment our leads into different pools, from which we can further provide them with personalized email campaign, content, and promotional offers that meet their needs and interests.

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With the tools in hand, I first conducted an overview of the Pardot data to find the max, min, average, mean, and median of the dataset. To help us visualize the information, I created a histogram of the score distribution. Often time, the graphs are right-skewed, signifying the imbalance in our audience's level of digital engagement.

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With that information, I divided our dataset in to 4 different tiers (1,2,3,4) according to their engagement level. The higher tier (Tier 1) consists a small number of leads with high engagement, while the lower tier (Tier 4) consists the majority of people that came into our contact with minimal engagement (i.e Click to a link every once in a while, do not read email often).

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With the 4 tiers identified, we had a better understanding our our audience's web behavior, from which marketing strategy is developed accordingly. For example, Tier 1 will receive more exclusive promotional offers and marketing materials, while Tier 4 only get accessed to major updates and highlights at a later stage.