Find out how e-commerce Companies are using Location Data
Wednesday, February 20th, 2019

Find out how e-commerce Companies are using Location Data

Although at first, an E-commerce can sell and deliver their product almost unlimitedly, consumers location is the most important factor in order to increase their sales. This is the main conclusion of the study  published by MIT Sloan Management Review, “What Matters Most in Internet Retailing”.

What are the reasons?

1) Its potential depends on the different offline purchase options that each individual has. If a user has an option to buy the product near his home, the probability of buying online decreases and it decreases specially if the purchase causes an experience.

As it happens in China, target is very concentrated in large cities like Beijing and Shanghai, and also there exist a large supply of luxury stores. However, European luxury brands are selling more in such cities where they do not have their own stores.

We find another example in a vintage clothing online store with which I collaborate, LolaSpector. We have analysed the sales distribution of LolaSpector in different areas of Madrid. The conclusion is that sales are better distribuited in areas with lower concentration of target and stores than in areas where target is very concentrated but its demand is covered by a wide variety of physical stores.

2) Penetration is the key: once a company gets a few customers in an area, it will be easier to increase sales in the same area due to the word-of-mouth effect.

In the mentioned study it is showed the case of bonobos.com for whom those postal codes with many new customers tend to be close to areas with a high concentration of customers in previous periods.

3) The importance of expanding the business in similar areas in which you have been successful in terms of sociodemographic and socioeconomic data. In the digital world if you want to move up a level you need to grow and the best way to do so is to select those areas that are similar to the areas where your customers are concentrated.

In this way DataCentric can provide over 1.600 statistical indicators that include socioeconomic, sociodemographic and consumption data at census section level´s (the census section is the smallest unit of administration of which statistical information in Spain is obtained). Find here some examples:

  • Housing cadastral data: surface area, age, parking, swimming pool…
  • Socio-economic level
  • Default index
  • Socio-demographic data: household structure, professions, number of foreigners…
  • Family budget distribution: beverages, insurance…
  • Finance statistical information: stock market investment, wealth…
  • Living conditions statistical information: school fees, expenses related to heating, water, rent…
  • Statistical information on internet purchases

Mixing this data with customers behavioural data, the analytics team of DataCentric can make a potential scoring for each area, information that e-commerce companies use to make decisions.

4) Searching for “islands” or areas with different characteristics from those of our customers. What happens here is that in these areas we will find that our product is not represented by our competitors, and this provides an opportunity to the E-commerce.

For example, in some areas with young families, we usually find shops focused on babies. However, in areas with older population, there are always some young families but hardly any physical stores with an offers for them.

Generation of audiences in programmatic campaigns or in Google or Facebook allows us to identify potential clients by interest or intention in areas with lower competition. Here what we are applying is the old digital strategy, the “Long Tail”.

The most successful companies on the Internet are applying data-centric strategies and are managing their activity based on data, being Location one of the most important factors. In other words, the physical world determines the virtual world and vice versa, creating a single reality.

 

Gerardo Raído

Chief Digital Officer

DataCentric

http://www.linkedin.com/in/gerardoraido

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