(Part 2) The Ultimate Custom DTC Dashboard with Tyson Drake

In this episode, Tyson, an expert in dashboard integration and a fractional CMO, continues to shed light on how to align your dashboard data with your CFO's PNL for an accurate, real-time view of your net profit. He stresses the importance of transparency, real-time profitability decisions, and why traditional PNL cycles may not be up to the task.

We're getting into the nitty-gritty of dashboard details, including the significance of daily changes, gross sales funnels in Shopify, and the intricacies of cost of delivery data. Tyson shares valuable insights on including niche metrics like cash conversion cycles and the necessity of making data strategy central to your decision-making.

Get ready to understand how a well-crafted dashboard can enhance marketing decisions, from spend ratios to revenue mixes, and why Tyson believes aligning these metrics with your business goals is crucial. We'll also explore Tyson's journey from in-house brand work to being a fractional leader, and his reasons for focusing on eight to nine-figure brands.

Join us as we discuss the challenges of the CMO role, the importance of data integrity, and Tyson's tools of choice for data visualization. It's an episode packed with expertise for anyone looking to optimize their business performance through data-driven decisions.

00:00 Challenges with customer contribution margin calculation.

09:28 Align dashboard with CFO's standards for accuracy.

14:06 Calculate contribution margin from gross sales, minus costs.

17:30 CFOs' reliance on PNL creates execution issues.

24:55 Founder's goals determine company's growth strategy.

31:27 Analyze spending and make adjustments for optimization.

34:17 Teams use dashboard for business outcome context.

40:35 Working with brands, finance, calculating costs, reporting.

44:54 Toggle for understanding correlations and success metrics.

52:40 Assisting eight to nine figure brands with leadership.

55:01 Experienced with eight and nine figure brands.

01:02:31 Statista is valuable for industry data analysis.

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