Decisions Driven by Data — Passive Income Superstars
Free Guide — Passive Income Superstars

Decisions
Driven by Data

The online business owner's guide to knowing your numbers and actually using them - plus a monthly review checklist to keep you on track.

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From Leanne Chapman at passiveincomesuperstars.com

Most online business owners care about their numbers. They just don't always know which ones matter, where to find them, or what to do when they do find them.

So decisions get made on gut feeling. Memory. A rough sense that something's working - or isn't. And that's fine for a while, until you realise you've been pushing an offer that peaked 18 months ago, or putting money into a lead strategy that's bringing in people who never actually buy anything.

This guide walks you through 5 decisions every online business owner has to make - and the exact data behind each one. For each one, you'll see what to measure, what changes when you know it, and what the difference could mean for your income. There's also a monthly review checklist at the end so you can make this a proper habit.

Let's get into it.

1
Which offers should I prioritise - and which ones actually move the needle?
The question every time-poor business owner needs a real answer to
Metrics to track
Year-on-year sales trend per offer  ·  % of total revenue per offer  ·  Funnel income vs launch income split  ·  Refund rate per offer

When you're short on time - which is most of the time - you can't give equal energy to everything. But without data, the answer to "what should I push this month?" often ends up being whatever's newest, or whatever you feel most excited about that week.

Year-on-year sales trend tells you which offers are growing and which are quietly declining. An offer trending down two years in a row probably isn't the one to anchor your next launch around, no matter how much you love it. Meanwhile something ticking up in the background might deserve a proper push.

The funnel income vs launch income split matters too, because funnel income is your non-negotiable base - the offers earning without you actively promoting them. Knowing which offers pull their weight on autopilot vs which only earn when you're shouting about them changes how you plan your whole calendar. You lead with the anchors, then fill the gaps on purpose rather than randomly.

What changes
Your promo calendar stops being a guessing game. You lead with what reliably converts and make deliberate choices about everything else.
Bottom line impact
Putting a launch behind a rising offer instead of a declining one can mean thousands of dollars difference - same amount of effort, very different result.
How to find this manually
Export your transaction data from your checkout platform. Group sales by product and year in a spreadsheet and calculate totals and year-on-year changes. Then do the same separately for funnel vs non-funnel transactions.
2
Is this list growth strategy actually worth what I'm putting into it?
Because cheap leads who never buy aren't actually cheap
Metrics to track
Revenue per subscriber at 30, 90 and 180 days - by source  ·  Cost per lead by strategy  ·  ROAS for paid ads  ·  ROI at each time window

Not all subscribers are equal, and open rates won't show you that. Two list growth strategies can bring in similar numbers of leads at a similar cost, and one cohort converts to buyers at three times the rate of the other. Without tracking revenue by source, you'd never know.

Revenue per subscriber over time - at 30, 90, and 180 days after joining - is the number that cuts through all of it. It answers the actual question: are the people joining my list via this strategy buying things?

Some strategies take time to pay off. A bundle subscriber might take 90 days to trust you enough to buy. A summit lead might convert faster. Knowing the pattern means you're not pulling the plug on something with a slow burn, or scaling something that looks great at 30 days but drops off completely by month three.

What changes
You cut lead sources that bring browsers not buyers, and put your energy and budget into the ones that actually convert.
Bottom line impact
Cutting one underperforming $300/month ad campaign saves $3,600/year. Scaling a high-converting strategy by 20% could add significantly more on top.
How to find this manually
Export your subscriber list filtered by a specific tag or sign-up date range. Export your transaction data. Cross-reference email addresses across both lists via VLOOKUP in a spreadsheet, then calculate average spend per subscriber at 30, 90 and 180 days. Repeat for each strategy you want to compare.
3
Which emails are actually making me money?
Open rates are flattering. Revenue is honest.
Metrics to track
Same-day revenue per email  ·  Open rate by email type  ·  Click-to-open rate by email type  ·  Revenue by subject line style and send day

Open rates tell you who found the subject line interesting enough to click. They don't tell you who bought. A flash sale email with a 28% open rate might generate twice the revenue of one with a 45% open rate - because the high-open one was a nurture email, and the other was a direct offer to a warm, ready-to-buy segment.

When you know which email types drive real revenue, you stop writing entirely from scratch every launch. You spot patterns in subject lines and send days that are worth repeating - not because they feel right, but because the numbers back it up.

A few launches in, this gets really useful. You can look at which day of your launch sequence historically converts best and time your strongest email to land then. That's not luck. That's your own data working for you.

What changes
You repurpose what works instead of starting from scratch every time. Less guessing, stronger results, and time back in your week.
Bottom line impact
Better-performing emails from day one of a launch, plus real time savings across multiple launches a year - both add up quickly.
How to find this manually
Pull your broadcast stats from your email platform. Export transaction data from your checkout platform. Cross-reference by date to find sales made on the same day each email went out. Track email type, send day, open rate, click rate and same-day revenue for each broadcast in a spreadsheet.
4
Are my payment plans a revenue risk - or am I fine?
The quiet revenue leak most business owners don't spot until it's too late to chase
Metrics to track
Overdue instalments by plan  ·  Projected vs actual split pay income  ·  % loss rate from defaults  ·  At-risk revenue (plans currently behind)

Payment plans are great for conversions. They're also really easy to lose track of - especially when you're running multiple offers with different plan structures at once. A customer missing their second instalment doesn't usually announce it. They just go quiet.

Most people only chase defaults when they happen to notice them. Which is often late, and sometimes never. The gap between what you expected in split pay income and what actually lands in your account is a number worth knowing.

The forward planning piece matters too. If you know there's $2,400 in split payments due over the next 90 days, that changes how urgently you need to generate new income elsewhere this quarter. It's a real number, not a rough estimate.

What changes
You spot defaults while they're still recoverable and plan cash flow with actual numbers rather than guesswork.
Bottom line impact
Even recovering 2 missed plans at $297 each puts $594 back in your pocket. Across a year with payment plans running regularly, it adds up to a lot more.
How to find this manually
Cross-reference every payment plan transaction against the expected instalment schedule. Flag any plan where the rebills received don't match the number expected by now. Calculate projected income by multiplying outstanding instalments by the rebill value for each active plan.
5
How healthy is my business, really?
Because income coming in doesn't always mean things are heading in the right direction
Metrics to track
Email list churn (unsubscribes + cold/unengaged subscribers)  ·  Net subscriber growth  ·  Offer or membership churn rate  ·  Average months in membership before cancelling  ·  MRR trend over time

Sales coming in is a good sign. But it's possible to have a solid revenue month while your list is quietly shrinking, your membership churn is climbing, and your longest-standing members are the ones most likely to leave next. By the time you feel it in the numbers, it's usually already been happening for a while.

Email list health is more nuanced than just unsubscribes. A lot of people stop engaging long before they ever click that button - they go cold. Open rates dropping month on month, click rates declining, revenue per email flattening out - these are all signs worth paying attention to, even if the total subscriber count looks fine on paper. A list adding 200 new people but losing 180 to unsubscribes plus another chunk who've simply stopped opening anything isn't really growing. It's treading water, and quietly getting less engaged.

For membership and retainer owners, average time before cancellation is one of the most useful numbers you can have. If most members leave after month three, you know exactly where to focus your retention efforts - not at month six when it's already too late, but in month two when it still makes a difference.

What changes
You catch slow leaks early enough to do something about them - before a churn problem or a disengaging list becomes a revenue problem.
Bottom line impact
Keeping one member for an extra 3 months at $97/month is nearly $300 per person. Across 10 members that's close to $3,000/year - from better timing, not more selling.
How to find this manually
Pull monthly subscriber counts and open and click rate trends from your email platform and track them month by month. For membership churn, cross-reference join dates and cancel dates from your transaction data and calculate the average time between them. Churn rate requires knowing both how many active members you started the month with and how many left during it.
Monthly Review Checklist

10 questions to ask yourself every single month

Work through these once a month after you've updated your data. If you can't answer something quickly, that tells you something useful in itself. Click to check them off as you go.

Which 2-3 offers generated the most revenue this month - and is that consistent with the last few months?
Metric: Revenue per offer, month on month
Are any offers trending down two months in a row? Do I need to rethink how I'm promoting them?
Metric: Year-on-year and month-on-month sales trend per offer
What's my net subscriber growth this month - and are open and click rates moving in the right direction?
Metric: New subscribers minus unsubscribes, plus engagement trends
Of the subscribers who joined 90 days ago, how many have bought something - and where did they come from?
Metric: Revenue per subscriber at 90 days by source
Which email sent this month had the highest same-day revenue - and what was different about it?
Metric: Same-day revenue per broadcast
Do I have any overdue payment plan instalments that need chasing right now?
Metric: Overdue instalments by plan
How much split pay income am I projecting over the next 90 days - and does that match what I need?
Metric: Projected split pay income by month
If I have a membership or retainer - how many people cancelled this month, and how long had they been a member?
Metric: Churn count and average time before cancellation
What's my refund rate this month - and is it higher than usual for any specific offer?
Metric: Refund rate per offer
Looking at all of the above - what's the one thing I'm going to do differently next month?
This one's on you. The data points the way. You make the call.