Weekly product metrics

Every Monday morning I sit down and run the metrics for all of my products for the past week. I do this in order to make sense of what was happening with them, as well as to track their long term progress.

Why every week?

I found weekly metrics worked the best for me because it was a long enough timespan that I could see some results but short enough that I could get some feedback on them. I started with a month, thinking that since it was the standard cycle used in most businesses, it would be right for me. The problem with a month was that I’d be blind for weeks and would end up logging in to check on things every few days.

At the volume I’m at, daily metrics would waste too much time and not give me any additional information. All of my ebooks are a few years old right now so they are only getting a trickle of traffic each day.

My Metrics Process

The metrics I track are scattered across a few different services, so a large part of my process is to login to each service and run reports to get the numbers I need.

  1. I’d open my metrics spreadsheet. I use OpenOffice but Excel or Google Docs would work fine. There are a few formulas but the math is simple.

  2. Each product has its own tab and there is an ALL tab that summarizes the metrics for each product. Each row is a week, with a few calculation and title rows on the top.

  3. On a product’s tab there are several columns:

  4. Which week, which I have set to start on a Monday and end on a Sunday

    • Revenue
    • Total visits
    • Total sales (copies sold)
    • Mailing list subscriber count
    • Hours worked
  5. Then there are a few calculations that are done automatically for each week

    • Visit to sales conversion rate
    • Visit to sales delta, the change in the “Visit to sales conversion rate” since last week
    • Visitor to mailing list subscriber rate, which is the number of new subscribers from the visitors (e.g. 2 new subscribers on 100 visits = 2%)
    • Visitor to mailing list subscriber delta, the change in the “Visitor to mailing list subscriber rate” since last week
    • Revenue per hour
  6. Also on the top there are totals for each value and calculation. Those show me the metrics for the lifetime of the product.

  7. Then every week I go through each service and fill in the 5 values I need for each product.

  8. From DPD I enter the revenue and total sales.

  9. From Google Analytics I enter the total visits.

  10. Using a custom script I enter the mailing list subscribers. I previously used Mailchimp and have since switched to Aweber so I’d have to login to both places to find my subscriber count. I also have a few mailing lists per product so it was easier to write a script to automate the data extraction. (I have at least one prospect list and one customer list for each product. Some have additional launch lists or special lists).

  11. Using ChiliProject I run a report to show the number of hours I worked for each product. Recently this has been 0 or very little for my ebooks, since they are almost no-maintenance products at this point.

  12. After entering everything, I’ll review the metrics to see how the week went. The main ones I look at are the total visits (am I getting enough traffic?), the visit to sales conversion rate (am I still selling copies?), and all of the deltas (anything out of the ordinary?).

  13. Finally I look at the ALL tab which through the magic of spreadsheets and math, pulls the revenue data out of each tab and shows it in one place.

  14. On the ALL tab there are two calculations I really care about:

    • Total revenue from products for the week
    • % towards my goal of generating 100% of my revenue from products

Time commitment

After doing this for almost two years now, I’ve gotten this process down to about 10-15 minutes each week. I’ve tried to automate parts of it but I’ve run up against the problem of automating a semi-regular task that is fast. Basically, the time it would take to automate it would take years before it’s been paid back. Plus, some of the data sources have other metrics I like to glance at when I’m gathering my data. For example, in Google Analytics I like to check the referrers for traffic spikes.

Other products and services

I also collect weekly metrics for Chirk HR and my client services but those aren’t as standardized so they don’t fall into this process as easily. Quite frankly, I’ve also been slacking on collecting my client services metrics recently because I’ve been “busy enough” that I haven’t bothered. I might see if there is a way to adapt my client service metrics into this spreadsheet (or find a way to productize my client services more).

If you have any questions about my metrics, post a comment below or message me on Twitter (@edavis10).

[I won’t be able to share my metrics spreadsheet publicly, you could easily create one in the amount of time it would take to clean out my data.]