Travelplanet.pl is a leader in the sale of international holiday packages. Part of the international INVIA Group, it has been operating on the Polish market since 2001. By combining a traditional sales model with modern technology, Travelplanet.pl aims to strengthen its market presence through a strategic approach to developing its network of sales outlets. However, the dynamically changing tourism market presents the company with a number of challenges related to the effective expansion of its franchise network.
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The main challenge for Travelplanet.pl was identifying areas with the greatest potential for network development, without creating direct competition for the tour operators with whom the company collaborates. An additional challenge was streamlining the franchisee acquisition process by providing them with reliable data on the business potential of specific locations.
The previous approach was based primarily on experience and fragmented data, which did not provide sufficient business certainty for either the company itself or potential franchisees. Travelplanet.pl needed a solution that would standardize and accelerate the decision-making process while minimizing business risk for new franchisees.
"We were looking for a solution that would objectify the location decision-making process and give our franchisees a competitive advantage right from the start," explains Radosław Damasiewicz, CEO of Travelplanet.pl
"Thanks to our partnership with dataplace.ai we can now confidently tell our franchisees: 'This location has proven business potential, and here is the data to back it up.' This fundamentally changes our conversations with both potential partners and existing ones who want to grow and open new Travelplanet.pl branches." – Grzegorz Chabior, Franchise Director.
To meet the complex challenges of expansion, Travelplanet.pl decided to leverage the technology and tools of dataplace.ai, which were used to develop a comprehensive, two-stage location selection process.
The first step was a comprehensive analysis of all of Poland, which allowed us to identify areas with the highest potential for expanding our travel agency network, while taking boundary conditions into account.
We took into account indicators such as:
Competition saturation
We mapped data on travel industry sales points and analyzed a total of 2,256 locations, which allowed us to identify already saturated areas and exclude them from further stages of analysis. These defined boundary conditions allowed us to focus on areas that met the established criteria in the next stage.
Identification and mapping of frequent travelers
In the next step, we analyzed where the Travelplanet.pl target audience is located. First, we isolated the "travellovers" behavioral segment—people who travel actively and regularly appear at airports or travel abroad.
Demographics, population, and income
To ensure new sales points are placed in the right types of locations, our analysis included the minimum number of residents within range, their demographic profile, and the area's characteristics in terms of income levels.
Traffic type and dynamics
We analyzed traffic intensity and dynamics for nearly 500,000 hexagons across the country. This allowed us to identify areas characterized by high traffic, with a particular focus on places with a high share of people stopping—those that attract local residents for various reasons, such as pedestrian zones, high streets, or retail parks.
For each indicator, we first checked whether a given area met the set boundary conditions, and then treated them as key ranking variables—the higher the values for each element, the greater the chance of success for a new office.
"Digital transformation isn't just for e-commerce. Thanks to dataplace.ai we have also brought it into our franchise expansion process, replacing intuition with precise analysis based on real consumer behavior. As a result, our franchisees receive not only a well-known brand and a great product, but also the certainty that their business is being built in a location with proven potential.” – Radosław Damasiewicz, CEO of Travelplanet
After filtering out hexagons that did not meet the defined boundary conditions, we assigned weights to individual variables based on their significance to business potential and proceeded to build a scoring model. This allowed us to identify four categories of locations with varying business potential – from premium locations to acceptable ones. Importantly, even lower rankings do not imply a lack of value – every location evaluated met the minimum criteria for attractiveness, i.e., the so-called boundary conditions.
The analysis results revealed areas with high potential that are often not visible at first glance, confirming that precise spatial data analysis can uncover promising locations even in a seemingly saturated market.
After identifying the areas with the highest potential for network expansion, Travelplanet.pl gained access to the placeme application, which enables detailed analysis of specific locations. The team simply enters an address, selects a catchment area, and within seconds receives a detailed report in the form of actionable business insights, including analyses such as:
Thanks to the two-stage location analysis, Travelplanet.pl has gained a precise system for identifying areas with the highest business potential for its franchisees. A comprehensive white-spot analysis combined with the precise verification of specific locations in the placeme application allows the company to make decisions based on hard data rather than intuition. As a result, Travelplanet.pl has significantly reduced investment risk and shortened the decision-making process when analyzing new locations.
The tools used have also increased the perceived attractiveness of the franchise system among potential partners interested in joining the network. Existing partners are now interested in opening additional branches in high-potential locations identified through these tools.
