Data that sells in online commerce
Data that sells in online commerce – Although a priori an Ecommerce can sell and deliver almost unlimitedly, the location of buyers is the most crucial factor when it comes to multiplying your sales. This is the main conclusion of the exciting study “What Matters Most in Internet Retailing”, published by the MIT Sloan Management Review.
Analyzing the online shopping data of major eCommerce companies, they found that their penetration is far from proportionally distributed: their sales are highly concentrated in specific neighbourhoods and postal codes. In contrast, they almost disappear in others with the same population.
What is the reason for this effect? The importance of localization is due to several reasons and provides us with the following lessons.
1. The potential depends radically on each individual’s various offline purchase options.
If a user has good options to buy what you offer close to her home, she is much less likely to buy online. This is so in the supply of products where offline shopping can be an experience and not a simple message.
Thus, in China, European luxury brands sell much more in cities where they do not have their stores than in large cities such as Beijing and Shanghai, where their public is very present, but a wide range of luxury stores are available. Luxury.
As a second example, in the online vintage clothing store LolaSpector, with which I collaborate. We have verified how sales are distributed in neighbourhoods of Madrid, where the supply of vintage stores is limited. At the same time, their success is reduced in the Centro district or Malasaña, where there is a significant public like-minded but already has its demand covered by a wide variety of physical stores.
Penetration is key.
Once you get a few customers in a neighbourhood, it is much easier for your sales to multiply in that same neighbourhood virally due to the word-of-mouth effect, which is still vital even though we are in the online environment. The case of bonobos.com is shown in the study above, for which zip codes with many new customers tend to be adjacent to areas with a high concentration of customers in previous periods.
The importance of seeking to expand into areas similar to others in which you have been successful in terms of sociodemographic data and the presence of offline competitors.
In digital commerce, if you want to move to the next level, you need to grow; the best way to expand to new geographic locations is to select neighbourhoods or census sections that are most similar to those where your current customers concentrated. At DataCentric, we have more than 1,600 statistical indicators that we can associate with each location in Spain, such as:
Cadastral data of the house: surface, age, garages or swimming pools, among others.
The socioeconomic level. A complete score that, using multiple data, summarizes a home’s income and economic capacity.
Geographical Index: A powerful indicator that identifies the risk of non-payment of an address.
Sociodemographic information: household structure, professions, number of foreigners, etc.
Distribution of the family budget by type of expense: drinks, insurance, etc.
Statistical information on finances: stock investment, wealth, etc.
Also, statistical information on living conditions: school fees, expenses related to heating, water, rent and others.
Statistical information on internet purchases can provide us with a lot of information about the potential for online purchases.
The strength of these variables achieved relating sociodemographic data with other data on the behaviour of our clients. It is not about using all the data but rather identifying which data cocktail most reliably characterizes our best customers compared to the average. With this, Data-centric analysts can score potential for each location in the territory.
Look for “islands” in not-so-favourable starting territories.
Another profitable strategy is to impact those potential individuals who are in areas where there is not a high density of potential from our target audience.
In these areas, the offer for these individuals will under represented in their local business, which gives the online seller an opportunity. For example, in neighbourhoods with young families, stores usually dedicated to the world of babies. However, in areas with an ageing population, there are always some young couples and hardly any physical stores with offers for them, which creates an opportunity.
The generation of audiences in programmatic campaigns or on Google or Facebook allows us to identify potential customers by interest or intention in areas with little competition. Here we are applying the old “Long Tail” digital strategy.
The most successful companies on the Internet have data-centric strategies and direct their activity based on data; location is one of the most important. In short, the physical world conditions the virtual world and vice versa, forming a single reality.
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