As marketing budgets grow in size and influence, it’s increasingly important that companies use them wisely as they engage customers. Organizations with high-performing marketing teams are not strangers to data and the value it brings to their strategy. While descriptive analytics are helpful to some extent, marketing strategies can be further honed with data science.
Marketers face a lot of important decisions as they consider how, when, and to whom they market their products and services. Marketing dollars become ineffective quickly if marketing efforts miss the mark and fail to capture the attention of the desired audience.
This dashboard looks at data from a big box hardware store. The goods and services provided by this example company are as varied and diverse as the clientele they serve. As this company thinks about how to market to their customer base, there’s a lot to consider. How should the marketing approach shift based on customer profiles? Are customers contractors or ‘do it yourselfers’? Are they from large or small families? Do they have a high or low household income?
Customer characteristics matter because different marketing efforts will appeal to different groups. It’s also important to note that marketing efforts will be received differently throughout the year. Data science optimizes marketing initiatives by predicting when a given marketing effort will have the most impact and identifying customer groups that will most engage with that effort.
To help marketing teams understand this type of customer response, this dashboard sreveals the results of two data science models that segment customers into four groups and predicts the revenue of each group. This helps marketers understand what kind of marketing campaigns to run and when to run them for different customer groups.
Explanation of dashboard use
The donut charts illustrate the population density of three important characteristics for each group of segmented customers; presence of children, if they are a homeowner, if they are ‘do it yourselfers.’ This helps inform the make-up of each group and therefore what kinds of marketing campaigns to run.
These visualizations provide further detail around customer group characteristics bylooking at the distribution of family size, income, and spend. Like the donut charts above, these visuals lend increased insight into each customer group. They help inform marketing teams about themes and messaging that will best resonate with each group.
These trends illustrate spend fluctuations for the customer groups and predicts how these trends will continue. This insight helps marketing teams determine when to drive marketing campaigns to each group.
The trend filter helps dashboard users as they focus on specific time frames.