Being data experts allows us to understand your business
At Pickgeo, we work with real territorial data to help you make expansion, opening, or optimization decisions with greater confidence.
Explore location intelligence by sector
Each sector has different needs. Select yours and discover how location intelligence helps you choose better locations with real data.
How to choose the best area to open a supermarket
Opening a supermarket is not just about finding an available premises. The profitability of a new opening depends on multiple territorial factors, ranging from population density to consumption habits, existing competition, and customers’ daily accessibility.
Location intelligence applied to supermarkets makes it possible to analyze all these factors together, helping chains and franchises decide where to open, where not to open, and how to optimize their existing network.
Location intelligence applied to supermarkets makes it possible to analyze all these factors together, helping chains and franchises decide where to open, where not to open, and how to optimize their existing network.
What data is key for supermarkets
Unlike other businesses, supermarkets need a strong understanding of the residential and everyday environment. With Pickgeo, this type of analysis includes:
- Resident population and its evolution
- Socioeconomic profile and spending capacity
- Household typology and average size
- Presence of competing supermarkets and similar formats
- Real distance to other own stores (cannibalization)
- Accessibility on foot and by car
These data help answer common questions such as:
- Is there enough population to support a supermarket here?
- Am I opening too close to another store?
- Is a small format better, or a large-format store?
Examples of decisions supermarket chains make
Thanks to territorial analysis, chains can:
- Detect areas with high unmet demand, even in small municipalities
- Compare neighborhoods within the same city to prioritize openings
- Adjust the supermarket size according to the profile of the surrounding area
- Justify decisions to management, franchisees, or investors
Which Pickgeo solution is the best fit
For this sector, the most commonly used tools are:
Expansion and retail network analysis
How to choose the best area to open a gym
Opening a gym goes far beyond finding a large, visible premises. Success depends on understanding who lives in the area, how they move, their purchasing power, and what sports offer already exists nearby. Location intelligence applied to gyms makes it possible to anticipate real demand before investing.
Key data to decide on a gym location
In the fitness sector, Pickgeo makes it possible to analyze specific variables that directly influence member acquisition and retention:
- Resident population and demographic evolution
- Predominant age group (young people, active adults, families)
- Income level and recurring spending capacity
- Presence of competing gyms and their typology (low cost, premium, boutique)
- Accessibility on foot, public transport, and parking
- Daily attraction of the area (offices, schools, mixed-use areas)
These variables help answer common questions such as:
- Can this neighborhood support a monthly-fee gym?
- Is a low-cost model a better fit, or a specialized center?
- Am I entering an already saturated area?
Examples of common decisions in gym chains
Thanks to territorial analysis, chains can:
- Identify areas with a high concentration of active population
- Compare neighborhoods to prioritize openings
- Adjust the gym’s positioning to the profile of the area
- Detect opportunities in residential growth areas
Which Pickgeo solution is the best fit
For this sector, the most commonly used tools are:
Expansion and network analysis
Open a premises where people actually pass by
For cafés and bakeries, location is decisive. It is not enough to have population nearby: it is essential to understand daily foot traffic, neighborhood habits, and nearby points of attraction. Location intelligence applied to cafés makes it possible to identify where a premises can become the area’s go-to spot.
What variables influence the success of a café
Pickgeo makes it possible to analyze highly specific factors for this type of business:
- Real foot traffic by street and time slot
- Presence of offices, schools, or residential areas
- Socioeconomic profile of the surroundings
- Direct and indirect competition
- Connectivity to public transport and natural pedestrian routes
This makes it possible to answer questions such as:
- Do enough people pass along this street every morning?
- Does the environment favor daily or occasional consumption?
- Am I competing with too many similar premises?
Examples of common decisions in this sector
With territorial data, cafés and bakeries can:
- Detect streets with high pedestrian flow within the same neighborhood
- Adjust opening hours and offering according to traffic patterns
- Justify locations to franchisees
- Prioritize areas with recurring consumption over occasional tourist areas
Which Pickgeo solution is the best fit
For this sector, the most commonly used tools are:
Analysis of specific streets
Scale a food concept with data
When a restaurant works, the next challenge is to grow without losing profitability. Location intelligence applied to restaurant franchises makes it possible to identify areas where the concept is still not covered and where there is enough demand to replicate success.
Key variables for restaurant expansion
Pickgeo analyzes essential indicators for this sector:
- Demographic and socioeconomic profile of the area
- Existing restaurant typologies and market saturation
- Pedestrian traffic and attractiveness of the area
- Peak activity times
- Consumption potential according to residential, work, or mixed environments
These variables help answer questions such as:
- Is this type of cuisine a fit for this area?
- Is there enough demand for another similar restaurant?
- Does this premises make sense to attract franchisees?
Common decisions in restaurant franchises
Restaurant chains use territorial data to:
- Detect areas with incomplete dining offer
- Estimate average ticket and revenue potential
- Compare locations between cities or neighborhoods
- Support decisions in front of franchisees and investors
Which Pickgeo solution is the best fit
For this sector, the most commonly used tools are:
Structured expansion
Expansión estructurada
Choose a location while meeting regulations and profitability goals
The pharmaceutical sector has unique characteristics: location not only determines demand, but is also highly regulated. Location intelligence applied to pharmacies makes it possible to analyze the surroundings before starting a transfer, opening, or expansion, reducing legal and commercial risks.
Key data for pharmacies and parapharmacies
Pickgeo makes it possible to analyze critical variables such as:
- Resident population and demographic aging
- Proximity to other pharmacies (legal criteria)
- Closeness to health centers and hospitals
- Income level and healthcare consumption profile
- Pedestrian flow and daily accessibility
These metrics help answer questions such as:
- Does this location meet legal requirements?
- Is there enough demand to support a pharmacy?
- Is a transfer better, or a new opening?
Common decisions in the sector
With location intelligence, pharmacies can:
- Assess the real viability of a transfer
- Prioritize areas with high healthcare demand
- Justify decisions to financial institutions
- Analyze the impact of the urban environment on revenue
Which Pickgeo solution is the best fit
For this sector, the most commonly used tools are:
Regulations, demand, and surroundings
Detect the hottest spots within a street
For bakeries, just a few meters can make all the difference. Pedestrian traffic, visibility, and the neighborhood’s daily habits directly influence revenue. Location intelligence applied to bakeries makes it possible to analyze micro-areas with great precision.
What variables influence a profitable bakery
Pickgeo makes it possible to analyze:
- Pedestrian traffic by street segment
- Transport stops and natural crossing points
- Residential profile of the immediate surroundings
- Direct competition at very short distance
- Peak movement times
This makes it possible to answer questions such as:
- Which sidewalk has more traffic?
- At which exact point does the flow concentrate?
- Where would people buy bread on a recurring basis?
Examples of common decisions
Bakeries use data to:
- Choose the best premises on the same street
- Adjust opening hours based on traffic patterns
- Detect strategic spots before renting
- Reduce risk in neighborhood openings
Which Pickgeo solution is the best fit
For this sector, the most commonly used tools are:
Micro-areas and key crossing points
Open where the model actually works
Laundries depend on daily habits and consistent volume. Choosing the wrong area can make the business unviable. Location intelligence applied to laundries makes it possible to analyze real demand before opening.
Key variables for laundries
With Pickgeo, the following are analyzed:
- Type of housing and household size
- Residential density and population turnover
- Presence of students, tourists, or small households
- Existing competition
- Nearby professional clients (hotels, restaurants)
Common questions this analysis answers:
- Does this area use laundries?
- Is there enough customer turnover?
- ¿Puedo abrir varias sin solaparlas?
Common decisions in the sector
Chains and franchises use data to:
- Segment cities by exclusive areas
- Estimate potential revenue
- Detect nearby professional clients
- Design organized expansion networks
Which Pickgeo solution is the best fit
For this sector, the most commonly used tools are:
Consistent residential demand
Plan expansion with a demographic perspective
The toy sector depends directly on population structure and its evolution. Location intelligence applied to toy stores makes it possible to anticipate demand and avoid openings in declining areas.
Key data for toy stores
Pickgeo makes it possible to analyze:
- Child population and future evolution
- Family typology and birth rate
- Existing competition and similar formats
- Family accessibility and retail environment
This answers questions such as:
- Will this area still have children in 5 years?
- Am I entering an aging neighborhood?
- Is there an oversupply in the area?
Common decisions in the sector
Toy stores use data to:
- Estimate potential sales
- Avoid cannibalization between stores
- Prioritize neighborhoods with family growth
- Justify openings to franchisees
Which Pickgeo solution is the best fit
For this sector, the most commonly used tools are:
Child demographics and evolution
Location Intelligence to open storage units in areas with real demand
The success of a self-storage center depends on something very specific: recurring demand in the surrounding area. It is not enough to have a good premises; you need an area where people genuinely need extra space (small households, high residential density, frequent moves, etc.). Location intelligence applied to storage units makes it possible to detect those areas with precision.
What data is key for storage units
With Pickgeo, you can analyze variables such as:
- Population density and housing type (apartments vs single-family homes)
- Average household size and family structure
- Socioeconomic level and monthly spending capacity
- Urban growth and residential expansion areas
- Competition and existing storage supply
- Accessibility and ease of access (vehicle, loading/unloading)
Typical questions it answers:
- Does this area have households with storage needs?
- Is there enough density to sustain occupancy?
- Where can I open without overlapping with other centers?
Examples of common decisions
Storage companies use data to:
- Identify cities or neighborhoods with high potential demand
- Compare central vs peripheral areas in terms of expected occupancy
- Choose locations with a better balance between premises cost and demand
- Justify openings to partners or investors
Which Pickgeo solution is the best fit
For this sector, the most commonly used tools are:
Residential density and need
Densidad residencial y necesidad
Location Intelligence to detect neighborhoods with high student demand
Demand for a driving school depends on very clear territorial factors: target-age population, presence of educational centers, daily mobility, and accessibility. Location intelligence applied to driving schools helps choose areas with real potential and avoid locations where acquiring students is more expensive.
Key data for driving schools
Pickgeo allows you to analyze:
- Population by age (young segment and adults)
- Demographic evolution of the neighborhood/municipality
- Proximity to high schools, universities, and vocational training centers
- Socioeconomic level and spending capacity
- Direct competition and density of academies
- Accessibility by public transport and usual routes
Questions it usually answers:
- Is there enough target population here?
- Is it better near a campus or residential neighborhoods?
- Does the competition still leave room for me?
Examples of decisions made with data
Driving schools use data to:
- Identify demand generators (education areas, young neighborhoods)
- Compare neighborhoods and prioritize openings with better expected return
- Adjust acquisition strategy and promotions according to the local profile
- Decide on expansion to nearby municipalities with unmet demand
Which Pickgeo solution is the best fit
For this sector, the most commonly used tools are:
Target population and accessibility
Choose a location with data for delivery and local consumption
In delivery, a location must not only work in terms of footfall: it must optimize delivery times, demand density, and coverage of target areas. Location intelligence applied to delivery makes it possible to better decide where to place kitchens, dark kitchens, or hybrid premises.
Key variables in a delivery model
With Pickgeo, you can assess:
- Residential density and consumption profile
- Presence of offices (midday peaks) vs residential areas (evening peaks)
- Accessibility and connectivity of the surroundings
- Competition by offer typology
- Mobility and territorial patterns affecting delivery
- Areas where it makes sense to strengthen coverage or open a new point
Typical questions:
- Does this location cover my delivery areas well?
- Will demand be higher at midday or at night?
- Where should I open to reduce times and increase orders?
Examples of common decisions
With location intelligence, delivery businesses can:
- Estimate sales by separating local consumption from delivery
- Choose locations that improve average delivery times
- Optimize existing premises by detecting overloaded areas or coverage gaps
- Decide where to open a support kitchen for expansion
Which Pickgeo solution is the best fit
For this sector, the most commonly used tools are:
Efficient territorial coverage
Plan expansion by area without overlaps
Home services agencies (cleaning, care, assistance) need one key thing: territorial balance. Opening without data can lead to areas with little demand or overlaps between branches. Location intelligence applied to home services helps design a sustainable network.
Key data for this sector
Pickgeo makes it possible to analyze:
- Household density and family typologies
- Socioeconomic profile and ability to hire services
- Concentration of older population (care demand)
- Territorial distribution for area assignment
- Competition and existing offer
- Accessibility and mobility between neighborhoods
Common questions:
- How many areas with real demand exist in this city?
- How do I divide the territory without overlapping branches?
- How many franchisees fit in each municipality?
Examples of common decisions
Home services agencies use territorial data to:
- Calculate the optimal number of branches per locality
- Define balanced areas for franchisees
- Prioritize neighborhoods with sustained demand and compatible profiles
- Justify expansion to management or partners
Which Pickgeo solution is the best fit
For this sector, the most commonly used tools are:
Balanced territorial distribution
Measure visibility with people and mobility data
In outdoor advertising, the asset is attention: how many people pass by, when they pass by, and what profile they have. Location intelligence for OOH makes it possible to sell locations with solid arguments, combining pedestrian traffic with demographic context.
Key variables for outdoor advertising
With Pickgeo, you can analyze:
- Pedestrian traffic by time slot and day
- Density and population profile of the surroundings
- Area attraction (retail, leisure, transport)
- Comparison between locations to optimize inventory
- Data-based arguments for clients
Typical questions:
- Which location generates the most real impacts?
- At what times is there greater exposure?
- What audience profile am I reaching?
Examples of common decisions
With territorial data, advertising agencies can:
- Select locations with the highest impact potential
- Design proposals by audience (young people, families, tourists, etc.)
- Compare billboards/mupis and justify pricing with data
- Improve campaign results by optimizing locations
Which Pickgeo solution is the best fit
For this sector, the most commonly used tools are:
Real impact measurement
Choose locations that make student acquisition easier
The location of a language school directly influences student acquisition and retention. It is not only about visibility, but about being close to the right audience, in areas compatible with schedules, mobility, and economic capacity. Location intelligence applied to language schools makes it possible to identify areas with real demand before opening.
What data is key for language schools
With Pickgeo, you can analyze specific variables for this type of educational center:
- Population distribution by age (children, young people, adults)
- Socioeconomic level and ability to spend on education
- Proximity to schools, high schools, universities, and educational centers
- Accessibility on foot and by public transport
- Direct and indirect competition in the area
- Daily attraction of the area (residential, educational, work-related)
These metrics help answer common questions such as:
- Is there enough school-age population in this area?
- Is this a neighborhood compatible with weekday and weekend classes?
- Am I too close to other similar language schools?
Examples of common decisions in language schools
Thanks to territorial analysis, schools can:
- Identify neighborhoods with a high concentration of target population
- Prioritize locations close to educational centers and transport
- Compare areas to decide where to open a new branch
- Adjust schedules and offering according to the profile of the surroundings
- Justify decisions to partners or franchisees
Which Pickgeo solution is the best fit
For this sector, the most commonly used tools are:
Student acquisition by educational profile
We provide a platform that integrates your company’s data with over 2,000 geolocated variables to leverage geographic information and make the best decisions based on solid predictions.
Contact
- Calle de Alfonso I, 17, 2nd Floor
- 50003, Zaragoza (Spain)
- Call us: +34 606 589 356
- Email: contact@pickgeo.com
- Monday – Friday: 9:00 AM – 5:00 PM