Sizing the prize: Using a top-down approach - Step 2

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Chris Jones

Author: Chris Jones, Independent Multichannel Retail Consultant

 

Introduction

 

In a previous article (see ‘Sizing the prize: using a top-down approach - step 1’), we considered how to estimate the size of an eCommerce category in a country into which you might consider launching a localised website, based on only fairly easily available high level data, such as overall eCommerce penetration and overall retail category size; this can typically be found for example in the eCommerce Worldwide passports or government statistics.

 

Having found the size of the category however, you also need to be able to estimate your potential share of it. One way of doing so is to compare your share of the UK home market and then consider what might make that vary when applied to another country. The objective of this article is to suggest a model for doing this.

 

How to use such a model

 

Before plunging into the details, it’s probably worth briefly considering the purpose of consultants’ models such as this one. The first thing to say is that they are exactly that – models. The data-points in it, in this case weighting-factors, are proposals based on broad general experience that may or may not be valid in your specific case. Their purpose is not to define a magic formula, but rather to suggest a structure for slicing up the problem into chunks which are easy to think about, and then to provoke debate and thought processes which may be helpful in leading your team to a credible answer.

 

With that caveat in mind, let’s take a look at the model, and remember that if you don’t agree with any of the suggested weighting-factors, then change them!

 

Step 2 – the fair share model

 

Step 2.1 Step 2.1 is easy: you need to know your current, or anticipated, market share in your home country (which I will assume is the UK).

 

The next set of steps considers how this might vary in another country. In order to do so, we’ll use a simple model, based on the acronym P.R.I.C.E – Price, Range, Information, Convenience, Experience (for more information on P.R.I.C.E. see The Multichannel Retail Handbook 2016 Edition ISBN 978-1-326-47257-3).

 

Step 2.2 is therefore to consider your price positioning in the target country relative to your positioning in the UK. Compared to the local competition, will you be relatively more or less expensive than you are back home? If you’ll be more expensive, set a price weighting-factor of 40%; if less expensive, set the weighting-factor to 125%; if more-or-less the same to 100%.

 

Step 2.3 is then to consider your range. For your proposed product assortment, is there more or less local competition than there is back home? Is there, for example, a local category-killer (such as Zalando for shoes in Germany)? If you’ll face more competition, set a range weighting-factor to 50%; if less competition 150%; if about the same, 100%.

 

Step 2.4: we’ll hijack the information factor in the model to consider the uniqueness of your offer. Is your brand so desirable over there that there’s really no competition? Or are you selling such unique products that there isn’t much local competition anyway? If you’re selling generic products already available from local players, set an information / uniqueness weighting-factor of 25%; if you have something even more uniquely special than it is at home, set a factor of 125%; if you have something unique, such as sole distribution rights to a brand but which is in fact exactly the same USP as back home, then default to 100%.

 

Step 2.5 is to consider whether your proposition at home is based on partly convenience – for example very fast delivery times, click & collect, or premium delivery services – and ask whether you can replicate that abroad? Typically the answer is “no you can’t”. Take a look at likely local competitors and see what they are achieving in this area. If you can still beat them, set a convenience weighting-factor of 125%; if you can beat them, but only by charging a lot more than the local benchmark for delivery, then set a factor of 90%; if you’re going to be worse in some way, set a factor of 60%.

 

Step 2.6 is to consider the experience you intend to offer. The most important factor by far is whether or not you intend to localise your site. If you will fully localise, set a factor of 100%; if you’ll translate it but not otherwise localise it, set a factor of 75%; if you’re just going to use your existing site, then set a factor of 35%.

 

Step 2.7 is just arithmetic: you simply multiply your UK-market share by all these different weighting factors in turn.

 

So, for example, if you have a 30% market share in the UK, will be more expensive in the target country, face similar competition, don’t have anything very unique to sell, will be slower to deliver than the locals, but propose to translate your site, then your ‘fair share’ in the target country would be:

 

30% (UK share) * 40% (price) * 100% (range) * 25% (information / uniqueness) * 60% (convenience) * 75% (experience) = 1.35%

 

Step 2.8 is a brief pause to consider demographics. In many countries, eCommerce is more concentrated among the urban young than it is in the UK, where there are plenty of rural silver-surfers. Demographic information about eCommerce is often hard to find, but demographic information about internet use is typically much more accessible, and will be a reasonable proxy. If you’re selling clothing to rural pensioners, you might need to adjust your share down a bit, for example.

 

Step 2.9 is of course to apply that market share to the overall size of the category online in your target country, which we estimated in Step 1. The result is your total ‘fair share’ of sales in your target country.

 

Step 2.10 is to consider phasing. You won’t reach that market share overnight. How fast you can get there obviously depends on marketing spend in particular. As a default planning assumption, assuming marketing spend at a higher percentage of sales than at home but not ginormous, try a year 1 through year 5 assumption of 10%:20%:40%:70%:100% of the potential fair share you calculated in the previous step.

 

Step 2.11 is to re-validate all those weighting factors and other data assumptions and decide if they make sense in your particular context!

 

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