Geomarketing for offline retail and services for urban residents

Choosing a place to launch a sales outlet (FMCG, DIY, pharmacies, cosmetics, etc.).

Step 1. Know our TA portrait and correlate it with the portrait located on the territory

Before opening a sales outlet, it’s important to understand who your target audience is. The more accurate its portrait is, the better.

Knowing your target audience will make it easier to correlate it with the local audience. You need to carefully analyze the age of the population, its purchasing power and consumer habits. It will be useful to calculate the share of working and living population in the area and determine who can become a potential customer.

Step 2. Determine the infrastructure density

Explore the area where you’re planning to locate your new outlet. Study the transport and trade infrastructure, the number of places of employment, the number of catering facilities, etc.

You should use the service radius of the sales outlet as a determining factor in the trade infrastructure. The service radius (pedestrian accessibility) is the area of operation of a sales outlet determined by the distance covered by the customers from their place of residence to this sales outlet.

On the map, we plotted a radius of 450 meters or a 5 minute walk.

This way you can plot the service radii of all of your competitors' outlets and understand where the radii intersect. The same can be done with transport accessibility, which implies that your potential customer moves, for example, by car.

The map below shows what distance a potential customer will cover from a given sales outlet in 5 minutes.

You can simulate the target audience by infrastructure objects. Look at the density of universities and the density of catering facilities in the city, pay attention to the density of banks and boutiques in the same city, and you will see that there are interesting differences related to the system of preferences of students and that of active business people with incomes above the average.

Step 3. Customer flow

The next step is to analyze the outlet for how many people will walk in its immediate vicinity.

Based on a local analysis — for example, cellular data (big data) — you can determine the number of people that passes through your trading area at different times of the day on weekdays and weekends.

The flows in the area of Chistye Prudy are distributed as follows.

Step 4. Competitive environment

The competitive environment in many cases is a threat.

For small stores, you should look for “your own” niches. For a large grocery retail company, there is always the option of opening a store in a place with the least number of competitors — let’s assume that large retail outlets are your competitors.

Step 5. Calculate the future profit: how much money will come from this location

In large companies, turnover formulas have been created empirically for years. In Western companies, they are often documented, strictly regulated, are a know-how and are not disclosed as trade secrets. The basis of the turnover formula is precisely geomarketing factors that affect the number of people that will visit your outlet and buy goods in a certain location.

Basically, this formula includes all we have described above.

2) Choosing a place for a private clinic

A place for opening a clinic: how geomarketing works

In order to understand where to find a place for a medical clinic, finding “customer flow” commercial premises is not enough — you need to study the environment: the population density, the age and sex structure, population incomes, transport and pedestrian access to the facility, the direct and indirect competitors.

A comprehensive geomarketing analysis and selection of a clinic location requires a methodology, data, and a geo-information or geomarketing system. They can be both professional and designed for users without specialized skills. If you have no resources, you can try to do without a geo-information system, but you will have to go “into the field” or look for information about the clinic location in open sources, where there is often little or insufficient information.

How to find a place for opening a medical clinic using multi-factor analysis

1.Define the goals and objectives of the geomarketing research.

2.Study the city by district or use a multi-factor analysis model.

3.Execute local analysis.

Determine the demand of the population

To study the city and understand what place is suitable for opening a clinic, you can assess the availability of medical services in each district of the city — calculate the number of hospitals or specific services per population.

Find the target audience on the city map

The data from mobile operators indicate mass crowds at different times of the day. This data is not a substitute for local measurement of pedestrian traffic but is suitable for macroanalysis.

Profiling mobile application users

Each geotag (mobile device position coordinates) is assigned a user's interest depending on the environment of the geotag. If the geotag is located near a place where a medical clinic is located, we consider this person to be interested in the medical clinic. The more often this user is interested in the object, the more we assume that the interest is steady. You can profile mobile application users in different categories: pharmacies, grocery stores, restaurants, etc.

Map of the target audience with interest in medical facilities.

Multi-factor target audience search model

Depending on the portrait of the target audience and the specifics of the business, we build hypotheses about the factors of spatial efficiency (high population density, high traffic flow, proximity to the metro, etc.) and TA attraction factors (places of work, places of leisure, etc.). Each factor is assigned a weight, and the values of these factors are added or multiplied. As a result, the user sees the places most suitable for opening a clinic on the map.

The best areas for opening a clinic

An alternative to the multi-factor model is comparative analysis.

Step 1. Determine the service area and calculate the number of people living around the future location of the clinic.

The number of houses and apartments in the service area. The number of residents, the ratio of children to parents. Population density: the number of residents per square kilometer.

Step 2. Count the people passing by.

Step 3. Evaluate the competitors.

When choosing a location for medical clinics, it is important to understand how much of the potential audience the medical clinics are fighting for among themselves. To do this, the user crosses the service areas on the map with a special GIS tool and considers the share of the population in the crossing zone.

First step: crossing the service areas of the two multidisciplinary medical centers.

Second step: calculating the population in the crossing zone of the two centers. There are 7,748 people living in the crossing zone.

Step 4. Assess the places of attraction of the audience. In addition to the population and pedestrians, it is always useful to assess what places of audience attraction are in the environment. These places can provide nice traffic.

To determine which commercial premises is better, record the indicators in a table and compare them with each other.

Geomarketing for retail delivery analysis

When consumer behavior shifts to online, when quarantine gives a strong impetus to people using the delivery of goods, food, and even services, these are the conditions when location analysis (geomarketing) with regards to deliveries is of even greater interest. Let's figure out what examples there are to study for different industries.

1) Geoanalysis for PUPs (pick-up points)

Here, zoning approaches are paramount. There are several types of zones: pedestrian, transport, radius with and without obstacles, arbitrary. As a rule, people tend to use radii. However, if you use estimated zones (which include transport and pedestrian ones), you’ll make more optimal and accurate calculations of delivery zones. In our experience, you can reduce the number of couriers, delivery time, and delivery budgets by about 25–35%, if you resort to more accurate calculations. Pedestrian zones are “suitable” for pedestrian delivery analysis. Transport zones are naturally fit for car delivery.

Pedestrian zones and delivery points

Transport zones 10 and 15 minutes away from the PUP in Geointellect and actual hand-drawn zones (red). Non-optimal matches are visible (in blue)

If, for example, you build such zones from all PUPs and overlay them, you can calculate the extent to which the city is covered time-wise. Are there uncovered places, how many of them are there?

The uncovered location (blue) in the city made it possible to count the uncovered population by house.

Later, you can calculate the market capacity in these uncovered places and decide whether to open a new PUP there or not. This is done on the basis of data on the population in houses, income, and demographic data. In professional systems, this analysis usually takes no more than 1 day.

When examining the zone closer, it turned out that there was a large percentage of post-crisis buildings, which is an indirect factor of certain families living here.

Naturally, such an analysis should be done with regards to competition. Of course, we cannot know the actual targeted delivery of the competitors. However, logistically, everyone will service the nearest locations first one way or another. It is necessary to take account of delivery by foot couriers or by car (you can find this out from open sources) to a certain extent and make a zoning similar to the one above, only not from your own points, but from competitors' points.

Next, by overlaying the delivery zones from our own network with the delivery zones from your competitors and taking into account that there are certain types of houses, people in them, and other geomarketing metrics, we end up with those locations that are not adequately supplied with PUPs in the city and will definitely be in demand.

If the market in the city is crowded, such locations may not exist. This is also a result. In this case, at this stage, you “dig” even deeper, including fighting for delivery time compared to competitors, services for the population, etc.

Since setting the optimal delivery system is a technological process in many respects, Geointellect offers a zone API or a geodata API for your existing systems — for example, in your CRM, BI, and other systems.

Another interesting case for visualizing any metrics, both external and internal, is the ZIP-Code index zone. Having such contours on the map with an index code in a table cell, delivery companies can quickly visualize their own geodata on the map without giving them to us. Because the zone data will be accessible through the API.

Index zones are covered not only in cities, but throughout the country. You can take them into account, analyze and compare their metrics:

In addition, for remote territories, the number of people traveling to the country is often taken into account for the analysis of deliveries and the deployment of additional PUPs. Especially for agglomerations, the market may have 30-km adjusting seasonal coefficients ranging from large regional centers that generate “to the country cottage” traffic during a certain season:

The 30-minute transport zone on the way from Moscow and the calculation of cottages. A store opened here can service about 3 thousand households.

2) A restaurant with the delivery of a certain cuisine. Geomarketing analysis method

The task is to open or redesign a restaurant with the delivery of certain cuisines in a large city.

How to solve such a task. Let’s apply the geomarketing approach, which will help us figure out what affects the performance of a restaurant with delivery services. There is a target audience group of factors and a competition group of factors.

A) Derive the index of the target audience

The consumption is affected by the following factors that can be described by geodata:

• the population living in the houses
• gender and age
• working population
• income level
• other indicators — for example, according to our observations, more goods are delivered to a certain type of houses and less to others. This is due to the type of people living in these houses. The same goes for the working population.

Next, we make a “convolution” of spatial factors and display it in the form of a heat map of the TA Index. It shows locations with regards to the weights of various factors that model the target audience (the higher (green) the index value, the more attractive the usefulness zones from the target audience’s perspective):

B) However, this map does not take account of the number of our orders that can be lost to our “competitors”. To do this, resort to factoring the competitors in. This can be done in different ways: for example, by taking account of the distribution of all food services in the city, by looking at which ones provide delivery services (because a person or a family always has an alternative to go to a restaurant in the city or near the house instead of ordering a delivery).

Having put thousands of objects on the map, you can see their density and also, with the help of an additional study of delivery aggregators from open sources, understand which cuisines are in priority for delivery by certain players. This additional capacious analysis bears fruit, and we end up with the following cartograms:

Using the cartogram data, one can easily see that Pizza and Sushi are approximately equally provided with delivery, but Georgian and Ossetian cuisine have potential.

A “convolution” of factors and the final competition index with regards to offline restaurants of various cuisines are made and shown the same way:

C) If we convolute the two indexes, we get the resulting heat map, with which the decision maker or the marketer can choose the zones and conduct a comparative analysis:

How to build a comparison table on the right? You need to select a location (for example, it can be a free commercial premises in the green zone) and build transport zones or several zones from it, after which, based on them, calculate the metrics: income, demography, market capacity, competition. Then you will get a lot of charts and comparisons, which will inspire thoughts on the priority of opening a restaurant with the delivery of a certain cuisine in the city.

Indicator	Transport zone
	20 minutos	40 minutos
General assessment of the market capacity in the location by the end of 2018, rubles/month	84,516,002	191,442,207
Assessment of market capacity by residents, rubles/month	71.422.388	150.502.493
Population, people	518.082	11.098.379
IThe income of the resident population in the zone, rubles/month (assessment)	53.044	52.722
Assessment of market capacity by working population, rubles/month	1.227.471	14.061.009
The number of employees in business centers, people	9.738	121.423
The average salary of workers, rubles/month	48.500	44.557

Geoanalytics for small business franchises

For a novice entrepreneur, buying a franchise is often a guarantee of success. A well-known brand, a ready-made brand book, a well-thought-out business model, training and support really make the thorny path of an entrepreneur easier, but they do not give an absolute guarantee that the business will succeed. One of the possible causes of failure is the wrong choice of a trading spot.

Global geomarketing analysis — for the franchisor, local — for the franchisee

Ideally, the franchisor should assess the market potential in the city in order to offer real growth opportunities when selling the franchise and leave the local assessment to the franchisee by giving him the search algorithm.

Global analysis

Knowledge of the market and consumers is the task of the franchisor. Based on this, you need to remember the following indicators:

The market share in the segment with regards to both the market leader in the segment and the closest competitors.

The provision of service or consumer goods: how many restaurant outlets fall on the target audience — for example, women and men aged from 18 to 60 both in the city as a whole and in districts or administrative districts.

The distribution of the target audience by district or administrative district.

For franchises operating exclusively in shopping centers, it is important to estimate the attendance of shopping centers. One of the estimation methods is the Huff gravitational model. This model is based on the principles of attractiveness of a shopping facility to the consumer. Most often, the basis of attractiveness is the area and remoteness from the target audience. The closer the facility is located and the larger its area, the more attractive it is for the consumer. The model determines the relative proportions in which consumers are distributed between trading areas.

Analysis of a potential trading area

The local analysis, in turn, is the work of the franchisee. His task is to find a highly profitable place by having studied the local market, competitors, and consumers. What does this require?

You can determine a potential trading zone expertly. If your target audience walks on foot, use pedestrian accessibility zones; if it travels by car or public transport — zones of transport accessibility. Compare your shopping zones with your competitors’ zones. In fig. 1, we compared the five-minute walking areas of two competing sites. Yellow color indicates the crossing zone. This means that people living in this zone are equally likely to go to one or the other site.

Having determined the potential coverage area, you need to analyze the indicators:

• Where and how many people live (population figures).
• What kind of people live there (population distribution by gender and age).
• Where do they work (map of business centers).
• Incomes of the population. Direct (salary) and indirect (cost of housing, cost of housing rental) indicators.
• Where and how people travel (pedestrian and transport traffic).
• The prospects of the district development (housing under construction, roads, shopping and business centers under construction).

Finding out the traffic of a shopping facility is an indicator that most entrepreneurs are chasing. However, it is not always necessary. For example, for beauty salons, it is better to focus on the living and working population, and for catering outlets — on pedestrian traffic. The customer traffic is most often measured independently.

Measurements of people passing by within an hour are taken for several days. It is advisable to count at different times of the day, separately on weekdays and weekends. But there is a difficulty here as well: there is no guarantee that the traffic will be the same over the seasons. By the way, if a large retail facility, a traffic intersection, or a metro station opens in the immediate vicinity, the traffic will change.

It is convenient to combine field measurements with special applications by entering information in them instead of a diary or Exel on a tablet. This is especially useful for those who use field measurements for further analysis in online geomarketing services: field data is immediately displayed in the web version, and there is no need to transfer them from one place to another.

Geomarketing: how to evaluate the effectiveness of a shopping center location

When entering a trading facility, any network is guided, first and foremost, by the revenue forecast indicator. It is based on the following parameters: the location of the shopping center, the solvency of the target audience, and the competitive environment.

Location is the first criterion for the effectiveness of a shopping center. It defines its concept, the customer traffic, and the financial stability. Having a detailed analysis of the location of the shopping center, you can predict the actions of competitors; make the right and effective “cutting” of shopping center tenants for the target audience living in the shopping area, which means being one step ahead.

American economists M. Sullivan and D. Adcock, engaged in the analysis of approaches to the assessment of commercial facilities, pointed out two key stages of the process:

Macro-location analysis

Micro-location analysis

The macro-location analysis of a shopping center includes the following components:

Determining the district type (“bedroom”, business, industrial, etc.)

District population analysis (living, moving, working)

Transport infrastructure assessment

Predicting the shopping center flow

Macroanalysis is usually more or less clear. The data is available one way or another, the techniques are well-known. The customers are as well. Let's talk about the microanalysis of the shopping center location — often it is also called “geomarketing study of the shopping center environment”.

Shopping zone

Professionals refer to the “shopping” zone as the coverage territory of the target audience, for which it will be convenient to come or drive to the shopping center. Thus, it implies either pedestrian or transport (by car) accessibility.

It is shown what is the coverage area equal to 5 minutes of traveling by car. Cloud GIS analytics of Geointellect also includes the calculation by the road graph in the formula. The road graph is created for selected objects of the road network taking account of the average speed on a road section with traffic lights.

Analysis of the population of the shopping zone

It will not be superfluous to determine the share of the living and working population, as well as their income level. Based on the distribution of the population, one can draw the first conclusions about the potential buyers.

Competitors

The Huff model can be the basis for determining the potential of shopping centers as opposed to competitors. This model is a variety of gravitational models that come from Newton's theory of attraction. The Huff model is based on the hypothesis that the attractiveness of an individual shopping facility depends on its area and its remoteness from the consumer.

If the shopping center already exists, why do you need geomarketing?

Geomarketing of the trade zone allows you to “see” how it changed as a result of PR events. How does it actually look on the city map? How does it intersect with the shopping zone of the main competitors? Competitors for anchor tenants. Geomarketing tools answer the question of the effectiveness of the shopping center’s marketing strategy in a large city more accurately.