ABI Role Call: Marketing
Reaching new and existing customers today is more important than ever. To do so, the Small Business Administration suggests companies should spend 7-8% of their gross revenues on marketing, although many reports put this number as high as 12%. Even at the bottom end of this range, marketing costs put a significant burden on a business’s bottom line. And to make matters worse, Commerce Signal estimates that 40% of all media spend is wasted.
So, figuring out where and how to spend your marketing dollars to maximize your investment efficiency can be a critical and daunting task. However, there’s good news!
If you’re collecting the most basic data on your customers and sales, then with the help of Analogyx BI’s Machine Learning capabilities, you already have the foundation to utilize one of the most powerful marketing tools available today: Customer and Market Segmentation.
Analogyx BI allows you to apply Prescriptive Analytics to learn a great deal about your customers and your product distribution so you can increase the effectiveness of your marketing dollars through Segmentation.
Today we’ll use Analogyx BI’s Customer Segmentation dashboard to define our high, mid and low level customers, as well as, their geographic location so we can maximize our marketing investment through targeted marketing.
First we’ll take a look at the About page to verify which methodology and/or calculations this dashboard is using. You can see this dashboard is utilizing the RFM Algorithm to segregate customers into High, Mid and Low value segments based on Frequency, Recency and Revenue.
As with all Analogyx Dashboards we can view our raw and calculated data that will both drive and be driven by our visualizations.
Next let’s look at our data visualization. This particular dashboard displays the numeric value of each Value Range so we can see those customers whose loyalty we need to maintain to focus on retention; those we may need to improve retention, Frequency and/or Recency; and those we need to make a decision to try to improve or discard to avoid being a burden on our resources.
We next see our complete list of Customers by Overall RCM Score with the ability to sort based on any number of parameters.
For geographical-based marketing purposes we can quickly see the average overall score by State and visually represented by color scale.
The next level of charts on this particular dashboard allows analysis of our customer value ranges in terms of Revenue vs Frequency, Revenue vs Recency, and Frequency vs Recency. In Revenue vs Frequency, our ideal customers would live in the upper right quadrant. In Revenue vs. Recency, we’d love to see every customer in the upper left quadrant, as would be the same for Frequency vs Recency.
Next, we can view our Customers within their respective value range.
As with all charts in Analogyx we can quickly change our view using our Edit Chart feature to change the number of visible records, as well as, increase & decrease the chart size for easier viewing.
This user also chose to view RFM results in terms of each bin versus the number of orders. One item of note that quickly stands out here is the large number of orders being processed for customers in the $0-200,000 sales range . . . perhaps a cause for possible concern regarding shop floor capacity for High Level Value Customer orders.
Now let’s use this dashboard to perform two Prescriptive Marketing Analytic exercises.
In the first scenario, our Marketing Department (who already has a tight budget) has been tasked with creating a campaign to effectively grow mid-value customers to high-value customers in the Southeast region.
Based on the cluster scores derived by the RFM algorithm, we can filter on the Mid-Value Segment and select the states on which we wish to focus, either by using the drop-down filter or simply clicking on the dynamic map.
We quickly have our segmented list based on customer value level and geographic location which can be exported, if desired, for use in external marketing tools or lists.
We could fine tune our marketing message even further through analysis of Segment comparison charts with the ability to export each chart’s filtered data.
For our second scenario, we’ve been tasked with determining why our 2nd highest revenue customer, Lane, Castillo, and Bullock, has an overall score of nine versus lower-revenue customers with higher overall scores and figuring out how we can move him up the ladder.
Let’s begin by comparing this customer, Lane, Castillo and Bullock, to our higher overall score customer, Smith, Holland, and Kane, by simply clicking on each customer in our table view.
We quickly see they’re in two different states that have very different average overall scores so could be a geographical issue at play here.
As we review our Segments chart we can see the largest delta exists in Frequency with Lane only having place 170 orders as compared to Smith’s 954 orders.
As a result of this analysis, our marketing department now knows they must craft their message to increase the number of orders Lane, Castillo and Bullock places with us. In conjunction with that State’s average overall score being on the low side, they may also want to increase the number of customer contacts by the territory salesperson.
These are just two examples of how your company can increase its competitive edge using Analogyx BI’s Prescriptive Analytics tools.
Targeted Marketing through Customer Segmentation. Isn’t it time you started to use your data to drive your company?
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Other videos in our ABI Role Call series: