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Retail Expansion in Asia

Every day retailers all over the world face the same problem – where to open a new trade point? How to attract customers and make the store profitable? Geomarketing science – the direction of marketing at the junction of geography and classical marketing research helps to solve this issue. Most the largest retailers have been using geomarketing researches in their work for a long time.

Geomarketing operates a huge set of various data – statistical and demographical indicators, pedestrian traffic data, mobile signals data, marketing information.  Instantly, with any data which have geo-referencing. The presence of geo-referencing is the most important point for this type of researches, because it is necessary to analyze the spatial distribution of a number of factors. These factors may be: permanent population density, active population density, transport accessibility, competitors’ presence (both internal and external), income level, points of interests. All these parameters can be analyzed with GIS technology.

However, entrepreneurs who wish to conduct a geomarketing analysis may face the following obstacles. GIS technology requires the knowledge of specialized professional software. This means searching and hiring an experienced GIS expert or a GIS company, who will do the research. Of course, this is an additional cost for business.

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How to get the key information remotely and quickly?

Meet Geomatrix – an online SaaS predictive analytics solution for the retail industry. Geomatrix will help you to open only profitable trade points, to increase and keep customer traffic in already existing shops. With Geomatrix you can perform online geomarketing analysis quickly, efficiently and independently, without the need of a GIS specialist, and this in 68 countries worldwide.

To this date Geomatrix covers 7  countries in Asia: Indonesia, Malaysia, Singapore, Thailand, the Philippines, Vietnam, India.

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1. Analysis of national statistics

Geomatrix uses only the latest official data from national statistical institutions. The main indicators are – population and average salaries at the lowest administrative level.  Population density are purchasing power on are calculated basing on the official statistical data.

As an example, take a look at this map of Tokyo:

[/av_textblock] [av_image src=’https://geomatrix-retail.com/wp-content/uploads/2018/10/joxi_screenshot_1539593110627-1030×541.png’ attachment=’14966′ attachment_size=’large’ align=’center’ styling=” hover=” link=” target=” caption=’yes’ font_size=’13’ appearance=’on-hover’ overlay_opacity=’0.4′ overlay_color=’#000000′ overlay_text_color=’#ffffff’ animation=’no-animation’ admin_preview_bg=”] Administrative division of Tokyo, Japan
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* The Tokyo Metropolis has complex structure of administrative division. In this example are shown only Tokyo’s 23 special wards (without Tama Area and Nishi-Tama District).

[/av_textblock] [/av_three_fifth] [av_two_fifth min_height=” vertical_alignment=” space=” custom_margin=” margin=’0px’ padding=’0px’ border=” border_color=” radius=’0px’ background_color=” src=” background_position=’top left’ background_repeat=’no-repeat’ animation=” mobile_display=”] [av_table purpose=’tabular’ pricing_table_design=’avia_pricing_minimal’ pricing_hidden_cells=” caption=’Population of Tokyo*:’ responsive_styling=’avia_responsive_table’] [av_row row_style=’avia-heading-row’][av_cell col_style=’avia-desc-col’]Special wards of Tokyo[/av_cell][av_cell col_style=”]Population, 2015[/av_cell][av_cell col_style=’avia-desc-col’]Special wards of Tokyo[/av_cell][av_cell col_style=”]Population, 2015[/av_cell][/av_row] [av_row row_style=”][av_cell col_style=’avia-desc-col’]Adachi[/av_cell][av_cell col_style=”]674111[/av_cell][av_cell col_style=’avia-desc-col’]Minato[/av_cell][av_cell col_style=”]240585[/av_cell][/av_row] [av_row row_style=”][av_cell col_style=’avia-desc-col’]Arakawa[/av_cell][av_cell col_style=”]209087[/av_cell][av_cell col_style=’avia-desc-col’]Nakano[/av_cell][av_cell col_style=”]316625[/av_cell][/av_row] [av_row row_style=”][av_cell col_style=’avia-desc-col’]Bunkyo[/av_cell][av_cell col_style=”]207413[/av_cell][av_cell col_style=’avia-desc-col’]Nerima[/av_cell][av_cell col_style=”]714656[/av_cell][/av_row] [av_row row_style=”][av_cell col_style=’avia-desc-col’]Chiyoda[/av_cell][av_cell col_style=”]56873[/av_cell][av_cell col_style=’avia-desc-col’]Ota[/av_cell][av_cell col_style=”]707455[/av_cell][/av_row] [av_row row_style=”][av_cell col_style=’avia-desc-col’]Chuo[/av_cell][av_cell col_style=”]138088[/av_cell][av_cell col_style=’avia-desc-col’]Setagaya[/av_cell][av_cell col_style=”]874332[/av_cell][/av_row] [av_row row_style=”][av_cell col_style=’avia-desc-col’]Edogawa[/av_cell][av_cell col_style=”]680262[/av_cell][av_cell col_style=’avia-desc-col’]Shibuya[/av_cell][av_cell col_style=”]217008[/av_cell][/av_row] [av_row row_style=”][av_cell col_style=’avia-desc-col’]Itabashi[/av_cell][av_cell col_style=”]544172[/av_cell][av_cell col_style=’avia-desc-col’]Shinagawa[/av_cell][av_cell col_style=”]372077[/av_cell][/av_row] [av_row row_style=”][av_cell col_style=’avia-desc-col’]Katsushika[/av_cell][av_cell col_style=”]449527[/av_cell][av_cell col_style=’avia-desc-col’]Shinjuku[/av_cell][av_cell col_style=”]327712[/av_cell][/av_row] [av_row row_style=”][av_cell col_style=’avia-desc-col’]Kita[/av_cell][av_cell col_style=”]338084[/av_cell][av_cell col_style=’avia-desc-col’]Suginami[/av_cell][av_cell col_style=”]547165[/av_cell][/av_row] [av_row row_style=”][av_cell col_style=’avia-desc-col’]Koto[/av_cell][av_cell col_style=”]493952[/av_cell][av_cell col_style=’avia-desc-col’]Sumida[/av_cell][av_cell col_style=”]258423[/av_cell][/av_row] [av_row row_style=”][av_cell col_style=’avia-desc-col’]Meguro[/av_cell][av_cell col_style=”]269689[/av_cell][av_cell col_style=’avia-desc-col’]Taito[/av_cell][av_cell col_style=”]189795[/av_cell][/av_row] [av_row row_style=”][av_cell col_style=’avia-desc-col’][/av_cell][av_cell col_style=”][/av_cell][av_cell col_style=’avia-desc-col’]Toshima[/av_cell][av_cell col_style=”]275507[/av_cell][/av_row] [/av_table] [/av_two_fifth] [av_hr class=’default’ height=’50’ shadow=’no-shadow’ position=’center’ custom_border=’av-border-thin’ custom_width=’50px’ custom_border_color=” custom_margin_top=’30px’ custom_margin_bottom=’30px’ icon_select=’yes’ custom_icon_color=” icon=’ue808′] [av_textblock size=” font_color=” color=” admin_preview_bg=”]

2. Analysis of Micro-Zones

For the analysis of potential locations, in some cities with a lage number of administrative areas (such as London or Paris) it is sufficient to use only national statistics, while in others (such as Ho Chi Minh with 19 districts) it is preferable to use a more detailed analysis. Therefore, Geomatrix also provides the analysis of micro-zones. Micro-zones are the squares of territory, 400×400 meters, which allow geomarketing research to be performed with much more precision and accuracy. Micro-zones show the distribution of permanent population, the density of mobile devices geo-signals, the concentration of people around POIs.

For example, in Ho Chi Minh, after analyzing 67784 residential blocks that were divided into 3128 microzones  with the average population by micro-zone of 2511 people, it is possible to identify the most populated micro-zones with a highest population 19119 people.

This analysis allows retailers to spot the best street retail locations within micro-zones in chosen cities.

[/av_textblock] [av_one_half first min_height=” vertical_alignment=” space=” custom_margin=” margin=’0px’ padding=’0px’ border=” border_color=” radius=’0px’ background_color=” src=” background_position=’top left’ background_repeat=’no-repeat’ animation=” mobile_display=”] [av_image src=’https://geomatrix-retail.com/wp-content/uploads/2018/10/joxi_screenshot_1539615272887-1030×540.png’ attachment=’15002′ attachment_size=’large’ align=’center’ styling=” hover=” link=” target=” caption=’yes’ font_size=’13’ appearance=’on-hover’ overlay_opacity=’0.4′ overlay_color=’#000000′ overlay_text_color=’#ffffff’ animation=’no-animation’ admin_preview_bg=”] Micro-zones of Ho Chi Minh City, Vietnam. Distribution by the density of geosignals from mobile devices.
[/av_image] [/av_one_half] [av_one_half min_height=” vertical_alignment=” space=” custom_margin=” margin=’0px’ padding=’0px’ border=” border_color=” radius=’0px’ background_color=” src=” background_position=’top left’ background_repeat=’no-repeat’ animation=” mobile_display=”] [av_image src=’https://geomatrix-retail.com/wp-content/uploads/2018/10/joxi_screenshot_1539615272887-1030×540.png’ attachment=’15002′ attachment_size=’large’ align=’center’ styling=” hover=” link=” target=” caption=’yes’ font_size=’13’ appearance=’on-hover’ overlay_opacity=’0.4′ overlay_color=’#000000′ overlay_text_color=’#ffffff’ animation=’no-animation’ admin_preview_bg=”] Micro-zones of Ho Chi Minh City, Vietnam. Distribution by the density of geosignals from mobile devices.
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3. The Accessibility Area analysis – a Market size analysis

The size of the accessibility area is the key indicator when choosing a location for a new store. The size of the area directly affects the number of customers who will visit your store. Moreover, the calculation of the accessibility area depends on the format of your future store. If we are talking about the format of a local store for daily needs, then it is necessary to analyze the pedestrian accessibility zone. If we consider the opening of a supermarket or hypermarket, then we should calculate the transport accessibility zone.

Compare these two accessibility zones through the Carrefour Singapore’s case (434 MacPherson Road, Singapore):

[/av_textblock] [av_one_half first min_height=’av-equal-height-column’ vertical_alignment=’av-align-middle’ space=” margin=’0px’ margin_sync=’true’ padding=’0px’ padding_sync=’true’ border=” border_color=” radius=’0px’ radius_sync=’true’ background_color=” src=” attachment=” attachment_size=” background_position=’top left’ background_repeat=’no-repeat’ animation=” mobile_display=”] [av_image src=’https://geomatrix-retail.com/wp-content/uploads/2018/10/joxi_screenshot_1539675212813.png’ attachment=’15032′ attachment_size=’full’ align=’center’ styling=” hover=” link=” target=” caption=’yes’ font_size=’13’ appearance=’on-hover’ overlay_opacity=’0.4′ overlay_color=’#000000′ overlay_text_color=’#ffffff’ animation=’no-animation’ admin_preview_bg=”] Accessibility area. 10 min by foot. Singapore.
[/av_image] [av_image src=’https://geomatrix-retail.com/wp-content/uploads/2018/10/joxi_screenshot_1539675240038.png’ attachment=’15035′ attachment_size=’full’ align=’center’ styling=” hover=” link=” target=” caption=” font_size=’13’ appearance=’on-hover’ overlay_opacity=’0.4′ overlay_color=’#000000′ overlay_text_color=’#ffffff’ animation=’no-animation’ admin_preview_bg=”] Accessibility area. 10 min by foot. Singapore. Report.
[/av_image] [/av_one_half] [av_one_half min_height=” vertical_alignment=” space=” custom_margin=” margin=’0px’ padding=’0px’ border=” border_color=” radius=’0px’ background_color=” src=” background_position=’top left’ background_repeat=’no-repeat’ animation=” mobile_display=”] [av_image src=’https://geomatrix-retail.com/wp-content/uploads/2018/10/joxi_screenshot_1539349014817-1030×483.png’ attachment=’15007′ attachment_size=’large’ align=’center’ styling=” hover=” link=” target=” caption=’yes’ font_size=’13’ appearance=’on-hover’ overlay_opacity=’0.4′ overlay_color=’#000000′ overlay_text_color=’#ffffff’ animation=’no-animation’ admin_preview_bg=”] Accessibility area. 10 minutes by car. Singapore.
[/av_image] [av_image src=’https://geomatrix-retail.com/wp-content/uploads/2018/10/joxi_screenshot_1539675099352.png’ attachment=’15041′ attachment_size=’full’ align=’center’ styling=” hover=” link=” target=” caption=” font_size=’13’ appearance=’on-hover’ overlay_opacity=’0.4′ overlay_color=’#000000′ overlay_text_color=’#ffffff’ animation=’no-animation’ admin_preview_bg=”] Accessibility area. 10 minutes by car. Singapore.
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It should be noted that one of the most common mistake in choosing a method of estimating a sales point is to estimate only one location. After all, the ultimate goal of all, even the most complex techniques, is to identify from several different proposals the best object, which has the maximum potential.

Accessibility area studies show very pertinent results in order to screen, rank, and select best options between several potential locations. Nevertheless, when arises the need to determinate the potential traffic and turnover of a retail outlet, more robust analytics should be used, such as catchment area analysis.

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4. The Catchment Area analysis – commercial conception efficiency analysis

Catchment area is the zone where live your potential clients. The calculation bases on 2 indicators – population and competitors’ presence.  Though, in real life the situation is usually more complicated. For example, within the 20 minutes by car accessibility area from your store there are your direct competitor’s shops. It means that a competitor has occupied a part of your catchment area, and probably some customers would prefer your competitor. The visualization of this situation in Geomatrix looks like this:

[/av_textblock] [/av_one_third] [av_two_third min_height=” vertical_alignment=” space=” custom_margin=” margin=’0px’ padding=’0px’ border=” border_color=” radius=’0px’ background_color=” src=” background_position=’top left’ background_repeat=’no-repeat’ animation=” mobile_display=”] [av_image src=’https://geomatrix-retail.com/wp-content/uploads/2018/10/joxi_screenshot_1538554167339-1.png’ attachment=’14460′ attachment_size=’full’ align=’center’ styling=” hover=” link=” target=” caption=” font_size=’13’ appearance=’on-hover’ overlay_opacity=’0.4′ overlay_color=’#000000′ overlay_text_color=’#ffffff’ animation=’no-animation’ admin_preview_bg=”] Accessibility area. 10 minutes by car. Singapore.
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Report for CC Project, at location: Vikas Marg, IG Indoor Stadium, ITO, Vikram Nagar, New Delhi, Delhi 110002, India

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Light-blue coloured zone is the accessibility area. Within this area are operating competitors – they are shown as purple dots. Squares of green and yellow shades are the catchment area, which lies within the accessibility area. The greener a square is, the more suitable the zone is for opening a new trade point (is in the accessibility area; no competitors).  Accordingly, the closer to competitor’s territory, the more yellow becomes the zone. If there are no squares, it means that this territory is occupied by other companies.

[/av_textblock] [av_two_third first min_height=” vertical_alignment=” space=” custom_margin=” margin=’0px’ padding=’0px’ border=” border_color=” radius=’0px’ background_color=” src=” background_position=’top left’ background_repeat=’no-repeat’ animation=” mobile_display=”] [av_image src=’https://geomatrix-retail.com/wp-content/uploads/2018/10/joxi_screenshot_1538556517452.png’ attachment=’14463′ attachment_size=’full’ align=’center’ styling=” hover=” link=” target=” caption=” font_size=’13’ appearance=’on-hover’ overlay_opacity=’0.4′ overlay_color=’#000000′ overlay_text_color=’#ffffff’ animation=’no-animation’ admin_preview_bg=”] Accessibility area. 10 minutes by car. Singapore.
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The system allows you to combine on one map data on the density of the permanent population with information about the location of shopping centers and their size. Even without creating additional reports, this makes it much easier to assess the location of objects.

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All trade points are divided into existing, under construction and projected objects. This allows us to see not only the current situation when assessing new objects, but also to predict the future. What’s more the system can be customized to your format and vision of the market.

Finally, the assessment of project’s potential with the help of gravitational model allows you to get an accurate estimate of the effectiveness of location in relation to competitors and the forecast of potential turnover and attendance of supermarkets, hypermarkets, shopping centers, etc.

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5. Discover the video

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