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What’s in your dashboard? Judah Phillips

PUBLISHED ON 9 JUNE, 2014

Our “What’s in your dashboard” series is back! After asking experts like Stéphane Hamel his top 3 KPIs for digital marketing and e-commerce management, and April Wilson her most valuable KPIs for content-based website optimization in previous posts, we are continuing the series today with another guest who speaks about his most valuable, practical, and inventive KPIs.

This time around we had the pleasure of asking analytics expert, Judah Phillips, to name his top 3 KPIs/charts for his ideal dashboard, tell us how he calculates them, explain where he would apply them, and why they are special to him.

Judah focuses on KPIs which he believes can best help you to increase business value. His top KPIs reflect revenues, costs and profit. Read on for his full explanation of which KPIs he finds most beneficial and influential for measuring business performance.

Judah’s answers:

Creating Key Performance Indicators (KPIs) against goals is one of many analytical approaches an analyst can take for understanding business performance.  It’s certainly a helpful approach, but KPIs are only a start, not an end, of analysis.  Lots has been written about KPIs over the years, and in my first book, “Building a Digital Analytics Organization” I outline my approach to the creation of KPIs. I explain that KPIs require data definitions that express goals to an audience who will use systems, reports, and dashboards to track KPI performance – and, most importantly, the audience will depend on you – the analyst – to communicate why they should care at all about KPIs.

KPIs can be easy to come up with – any analyst can do it – but real KPIs that are meaningful for measuring business performance can take more deliberation and thought to generate.  In fact, the best KPIs are business-specific; yet, some KPIs can be similar across industries.  For example, the ratio of quote starts and completes in the Insurance Industry is fairly domain-specific, but ROAS (return on advertising spend) can be generalized across marketing campaigns regardless of industry.

When Sweetspot asked me to name 3 KPIs I thought I would identify three generalized, business KPIs important for business analysis that the digital analyst should know and track.  As you can see below, as I emphasize in my business, on the teams I have managed, and in my books, analytics should focus on business value and tie to revenues, costs, and profit.  If your metrics don’t directly tie to real money, then your analytical efforts are more likely to be considered overhead – part of the L, not the P in P&L.

• Cost of Customer Acquisition.  How much money does your company spend to acquire a customer?  This potential complex calculus is beautiful in the way it can illuminate not only marketing spend but future business performance.  When does it make sense to spend money with Google to generate a lead or advertise in other ways?  CCOA can help answer that.

• Lifetime Value. The fabled LTV when understood against the cost of customer acquisition enables an understanding of customers and customer segments that would even make Philip Kotler blush. LTV is simply how much profit you can expect to make in your relationship with a customer.  LTV is a wonderfully power metric – and can even lead to fruitful data definitions about topics like “what is a customer and how do we use data to define them?”

• Net Profit Margin is the percentage of revenue remaining after deducting expenses.  Take for example, ecommerce campaigns which result in a conversion (a transaction).  Can you identify the cost and revenue on a campaign basis and do that math against the converted revenue?  What is your definition of expense?

As you can deduce, these metrics are closely related in that they not only tie to financial measures to marketing performance but also customer-specific measures that can be used for omnichannel analysis, which is a sweet analytical spot to be in.

Guest Bio:

Judah Phillips is well known for helping people create economic value using data, analytics, and research. He works with leading global companies whose executive and management teams are building, adapting, or reengineering their approach to digital analysis in order to increase profitable revenue, reduce cost, and boost profitability. He has authored and edited a number of books including Building a Digital Analytics Organization and Digital Analytics Primer.