Author: Chris Jones, Independent Multichannel Retail Consultant
Country-by-country guides to eCommerce, such as the IMRG / eCommerce Worldwide Passports, are great sources of high level data points, such as the total size of various retail categories in a country, or its eCommerce penetration. A key challenge for you as a retailer building the business case for taking your proposition into another country via eCommerce is to use such data points to answer the question: how much will we sell if we do so? The objective of this pair of articles is therefore to consider how to take those very useful high level statistics and use them to answer that much more specific question: what does this mean for us?
A succeeding article will consider an alternative approach: instead of using high level statistics in a top-down approach, trying to estimate the sales opportunity bottom-up. It’s highly recommended to adopt both approaches. If they roughly meet somewhere in the middle – they’ll never produce exactly the same figure of course, and you should probably be very suspicious if they do! – then your estimation process and reasoning is probably reasonably sound. Conversely if they produce wildly different estimates, then this is a good sign that you need to re-examine the way in which you arrived at your forecast.
So let’s take a look at how to arrive at a top-down estimate. This is going to be a two-step process, which we’ll consider in two successive articles.
You might be lucky and find country level statistics for eCommerce in your particular category. In which case, you can stop reading now, and head to the next article!
If you aren’t so lucky, or if you want to validate that fortunate data-point a bit (strongly recommended – category level eCommerce statistics in markets less mature online than the UK vary considerably in reliability), then here’s how to do it.
Step 1.1 is to find overall statistics for your retail category (i.e. overall retail, not just eCommerce) for that country. This is usually fairly easy. Moreover, in most countries overall retail doesn’t change that much year-on-year, so you can often find very reliable statistics from “slow” sources such as government data from a year or two ago and still use them as a realistic baseline. We’ll use the apparel category in Germany as an example: the total size in 2014 was about £51bn1, obviously with some allowance for exchange rate fluctuations.
Step 1.2 is to obtain the overall eCommerce penetration in your target country, from a high level guide such as the IMRG / eCommerce Worldwide Passports. In Germany it was 10% in 2014.2
Step 1.3 is to strip out the effects of grocery from the overall eCommerce retail penetration in that country, so that you can make a fair comparison with the UK. The UK, and France, are unusual in that there is a large online grocery sector included into overall eCommerce statistics. This is definitely not the case in most other countries. In the UK, online grocery sales are roughly £7bn3 in a total retail market of £320bn4, so they’re contributing about an extra 2% to the eCommerce penetration figure overall. In Germany, as a contrasting example, they’re pretty much zero. So although the headline eCommerce penetration in the UK in 2014 was 13.5% and in Germany only 10%, once you exclude food they’re rather closer together, at 11.5% and 10% respectively.
Step 1.4 is to discard general food retail altogether, to arrive at a true comparison of non-food eCommerce retail penetration. In the UK, food represents about 53% of total retail5, so overall eCommerce penetration into non-food is actually around 11.5% * 100%/(100%-53%) = 24.5%. If you can’t find this data-point for the country you are interested in, then a reasonable working assumption for developed countries is that food will be about 50% of total retail. So, having eliminated any distorting effects from online grocery, it’s a reasonably safe bet to just double the overall online penetration to get a baseline penetration for non-food.
Step 1.5 is to turn this into a direct comparison between the eCommerce maturity of the countries. We’ve seen that non-food eCommerce penetration in the UK is 24.5%, and we can estimate the figure for Germany as being 2 * 10% = 20%. So we can expect that, other things being equal, online penetration in Germany in a given category will be about 20/24.5-ths of what it is in the UK, or about 81% of the maturity of the UK.
Step 1.6 is to look at category level eCommerce penetration in the UK. You might well have very good data about your particular sub-categories. If not, here are some high-level baseline numbers for the UK for 20146:
|Health & Beauty||6.5%|
|Toys & Baby||20.2%|
Step 1.7 is to take the UK figures from step 1.6, and then apply the maturity percentage you calculated in step 1.5. So for clothing in Germany, we take the UK penetration figure of 26.1%, apply the maturity factor of 81% to that, at end up with an estimate of 26.1% * 81% = 21.1%.
Step 1.8 is optional, and is a bit of a fudge. If you are looking at a reasonably mature country such as Germany, its online categories are probably similar to the UK. If you are looking at a rather immature country, then it’s very likely that consumer electronics is already highly online, fashion catching up quickly, but other categories lagging behind. If you aren’t operating in one of these typically leading categories, you might just want to reduce your estimates a bit. We won’t need to do this for Germany.
Step 1.9 is to finally multiply the size of the category by your estimate for its eCommerce penetration. So for Germany we take £51bn * 21.1% = £10.7bn as our estimate for the size of online fashion (happily a bit of Googling for other sources of statistics suggests that this is a plausible estimate! This is easy to do for Germany, but rather harder for many other countries, so it’s comforting to validate the methodology a bit).
OK, so now you know the total size of the prize, we’ll take a look in the next article at how to top-down estimate your likely share of it if you were to open a localised version of your website in that country.
1 - Eurostat
2 - Eurostat
3 - BRC
4 - ONS
5 - ONS
6 - BRC