[DATA UNIVERSITY]: HOW TO FIGURE OUT IF YOUR ECOMMERCE BUSINESS IS GROWING

Business owners, managers, execs, and leaders all love talking about growth.

Is my e-commerce business growing? How can I make my e-commerce business grow faster? Is this year's growth better than last year's growth? The questions are endless.

When folks start talking about growth, one of the most important things to ask is, "What are you comparing it to?" The most common comparisons are day over day (D/D), week over week (W/W), month over month (M/M), and year over year (Y/Y). The period you choose to compare your growth is absolutely critical because choosing the wrong period to compare can give you an artificially inflated or deflated picture of your business' performance--so it might look like you're growing like gangbusters when you're actually not; or like things are gloomy in the growth department, when in fact they're not so bad.

We've developed a guide for choosing the optimal comparison period.

Let's start with a day/day comparison. Which period would you choose to compare today to (if today was 11/21/2011)?

1.) The period immediately before (11/20)*
2.) The period 1 week before (11/14)
3.) The period 1 month before (10/21)
4.) The period 1 year before (11/21/2010)

*Examples are given for Day/Day comparisons.

DAY OVER DAY COMPARISONS:

Number 1 doesn't work very well. Why? Because yesterday is not comparable to today.

Weekly seasonality in the e-commerce industry follows certain patterns as does internet traffic. In general, stores tend to have more traffic during the weekdays than the weekends. For most online businesses, Mondays are usually the strongest day and Sundays are usually the weakest in terms of sales. Comparing Monday to Sunday would show a massive uptick in revenue--not because your store is on an astronomical trajectory, but simply because Mondays are usually always better than Sundays.

Number 3 is the wrong choice, because simply choosing the same date from the month prior is unlikely to yield any useful information.

10/21 is not like 11/21. What if 10/21 was a holiday or 11/21 was a Friday and not a Monday? This may be consistent with monthly seasonality (e.g. commission based sites will often hit peak sales toward the end of the month to meet quotas or make bonus), however, the daily seasonality issue previously mentioned still makes this a far from optimal comparison.

Number 4 will likely yield the least helpful results of all the choices, based on all the possible variations between dates from the previous year.

Most likely, 11/21/2010 isn't at all like 11/21/2011. For starters, 11/21/2010 was a Sunday and 11/21/2011 was a Monday--there's the weekly seasonality issue that keeps coming up. Differences in holiday schedules, promotional campaigns, daily traffic and many other factors would also likely contribute to this comparison between the two years.

That leaves us with number 2, which is the correct answer in this case.

For day over day comparisons, looking at the same time period from the previous week will give you the most helpful data.

WEEK OVER WEEK COMPARISONS:

#1 and #2 are similar options here and either of them are correct. If the last 7 days rolling is taken into account, weekly seasonality is minimized. You do run into some snags if you're comparing a week with a holiday to a week without, but by and large this methodology is commonly accepted as the most accurate week over week comparison.

MONTH OVER MONTH COMPARISONS:

Since #1, #2, and #3 are the same option for monthly comparisons, we can only compare a month to a prior month or the same month a year ago. Comparing November 2011 to November 2010 or option #4 is actually the optimal choice since monthly seasonality like Thanksgiving and holiday shopping is accounted for. Comparing November to October will skew perceived growth since most e-commerce stores see an uptick during the holidays and a slump shortly after in January. Note that some folks call this a year over year comparison (comparing one month in a year to a month in the prior year).

YEAR OVER YEAR COMPARISONS:

The only option here is really #4. Ideally, we recommend performing a prior year to date versus current year to date (YTD) comparison. This takes care of the seasonality issue and prevents holiday bump at the end of each year from influencing the numbers early on in the calendar year.

Ok so that's a LOT of different ways of looking at your data from November 21st.

Here are the important takeaways:

a.) Comparing the correct periods of time with each other is crucial to ensuring that you're getting accurate information about the health of your e-commerce business.

b.) These sorts of comparisons are not an exact science as a variety of different factors can influence your results, however, they still provide a great way of staying on top of your revenue and monitoring your growth. 

c.) You should ALWAYS be staying on top of your data and monitoring your growth. Let your data work for you.

For some more reading on revenue growth, we enjoyed this post on GetElastic: Uncovering The Hidden Profit Treasures of Your Company.