Being overwhelmed by too many reports has the same outcome as having no reporting at all. Here are the reports I use to make decisions effectively.
This content was originally published in the No Best Practices newsletter on 01.29.2023.
In the last newsletter I talked about how I develop KPIs for paid media. This edition is going to talk about the reporting frameworks I use to manage those KPIs.
TL;DR: I think most brands should aim to be contribution margin profitable on their first purchase. That post is worth a read if you missed it. It includes a calculator you can use to develop CPA targets for your own brand.
I have to start off with a little rant about reporting. A lot of teams and organizations hide behind data. They’re terrified of making the wrong decisions, often because they don’t understand the business they’re trying to manage.
These are the folks who request dashboard after dashboard, then let those dashboards collect dust. They want some kind of plug and play analytics tool that not only spits out data, but tells them the right decisions to make with that data.
News flash: that is literally your job as a marketer. To make decisions, own the outcomes, and learn from them.
Rant over. When I think about what reporting to build (especially if resources are limited), I think of this flow chart. I’ll break this down into specific reports in the sections below.
Are We Hitting Our Daily Goals?
If I could only build one report to manage my digital marketing spend it would be this one (click here for a Google Doc you can copy and use yourself). Here is a breakdown:
Columns: There are a few major column groupings here:
- One column for each of your digital marketing channels. If a channel is purely used for remarketing to existing customers (rare), you can exclude it.
- A column to sum up your total daily spend across channels.
- Columns that break down your daily eCom demand (net of markdowns and promos, but not returns) by new v returning customers. This is easiest via Shopify.
- Columns that calculate new customer AOV, CAC, CAC:AOV ratio and MER (check out my template for the formulas).
- Columns that calculate the 7 day trailing average of the ratios above.
- You can also include your daily sales forecast if your forecast is that granular.
Rows: one row for each day of the year. As time goes on, you can build out a year-on-year view.
How I Build It:
The most straightforward (and free) way to do this is to grab a copy of my template and fill in the data manually. You would pull Day 1’s data on the morning of Day 2.
In fact, I know a few founders who refuse to automate this level of reporting because it forces them to think about the numbers as they’re logging them.
But if you do want to automate the reporting (I don’t blame you, I do!) there are a number of SaaS options for pulling Shopify and ads data into a Google sheet. Search something like “pull Facebook data into Google sheets” to see the major options.
How To Use It:
If you read the last newsletter, you should have a contribution margin-based all-in CAC target for the business. This dashboard tells you if you’re hitting that target each day.
If you’re not hitting the target, the 7 day trailing average lets you know if your miss is a blip or a trend. This is super important, because flying off the handle every time macro weirdness causes an off day is not conducive to growth.
You should have a list of things to review for each case: blip vs downward trend. The blip list will be smaller, and focus on catching things like a key page going down or a broken link.
What’s Wrong? / What Are Our Opportunities?
The focus of this section is not specific reports. Instead, it’s a framework borrowed from the world of operations that will save you countless hours and steady your mental state.
Have you ever heard someone say “he/she is out of control”? You may think this phrase was invented by concerned parents in the 1950’s, but it actually comes from the world of operations. You can do a deep dive on the topic here, or read this quote which is (IMO) pretty metal:
“Processes fall into one of four states: 1) the ideal, 2) the threshold, 3) the brink of chaos and 4) the state of chaos.”
How To Use This:
I like to take the daily metrics framework from the first section and apply it to key channel metrics and web metrics.
You track things like CPM, CPC and traffic on a daily basis and add the 7 day trailing average. But then you add in an upper and lower control limit (UCL and LCL), which is anywhere from one to three standard deviations from the average. You can do this with the STDEV formula in sheets or Excel.
Pick your number of standard deviations based on historical data. See which days fall outside UCL/LCL with each number of deviations. Compare that to what really happened–were those days true emergencies when you had to make a major pivot in channel strategy, or something broke?
I like to use UCL/LCL because channel-level metrics are really noisy. If you used the 7-day average, you’d have multiple fire drills per week, every week.
As for which metrics to track, pick whatever you feel is most critical to managing a given marketing channel. If you’re a smaller brand without much infrastructure to monitor site uptime, you can apply these views to your web metrics to determine if key parts of your site are having issues.
Was Our Plan Reasonable?
I have written a lot about forecasting, because a plan without grounding in historical data and a realistic understanding of causative factors is nothing but a dream.
I recommend that every brand selling in direct channels develop a customer forecast to go along with the financial forecast. At the end of each month, see how your actual customer behavior aligned with your assumptions. Does the team need to work harder/smarter? Or were your fundamental assumptions unreasonable? Both could be true.
You should be reviewing the following metrics within five business days of the close of each month:
- Actual sales vs planned sales vs LY sales
- The new v returning customers, revenue and AOV stats for each of the above
- Planned vs actual vs LY digital marketing spend and CAC
Then discuss the sales plan for the next three months within the context of these results. What must change at the KPI level for the brand to achieve its plan? What resources are required to make that work, and can the team activate those resources with its current bandwidth and budget?
Bonus: Are Short- And Long-Term Goals Aligned?
This is where we start digging into cohort performance i.e. how your customers behave after you acquire them.
For the vast majority of you reading this: you will never retain more than 35-38 of every 100 new customers you acquire. That’s just “the way it is” for mono-brand eCommerce businesses. And that’s why I encourage you to aim for customer acquisition that is contribution margin-positive on the first order.
That said, if none of your customers buy again, growing your brand will be an uphill battle. And you want to understand if various marketing activities are enhancing or diluting the quality of your customer pool.
This post on how I measure retention is a good 101 on this topic. I also like to look at monthly cohort performance–what percent of each monthly cohort comes back, and how much do they spend?
Another rule of thumb–the harder and faster you scale on Facebook, the more likely you are to acquire “one and done” customers. This isn’t necessarily bad, but you have to understand how it impacts the financial dynamics of your business and proceed accordingly.
You need to understand if acquisition is padding the top line or helping you build your customer file. If there is enough reader interest I’ll cover this topic in an upcoming newsletter.