In the current context of strong economic comeback after the pandemic, we have been approached by a famous food chain with yet another amazing challenge to help them sustain their crazy growth plan!
First, a bit of context…
This prominent food chain operates over 130 franchise restaurants in APAC and EMEA and plans to increase this number to 400 in just a few years.
- They plan to open new locations but also to relocate and remodel existing ones.
- The goal is to find the most profitable locations for new openings and relocations
By furthering our understanding of the challenges they faced, we realised that up until now, they had had some difficulties pinpointing the best locations for their new openings. Their decision making process consisted of some simple raw data analysis (outdated census and human-calculated footfall data) and a lot of local knowledge.
The limits of such an approach, coupled with the way the pandemic has reshuffled the economy and distressed the market, mean that strategic location decision making must be carried out precisely.
The effectiveness of such an approach has reached its limits, the pandemic reshuffled everything and in a distressed market, strategic location decision must be taken with the most precise criteria.
In order to make the best and most efficient decisions, they realised they had to transfer their market and client knowledge to a map so they could accurately pinpoint the ‘hottest spots’ in town.
They realised they wanted to make sure they could:
- be found effectively by their target market
- duplicate existing successful locations
- make these changes whilst maintaining their image
In order to achieve this ambitious task, we analysed billions of multi-source randomised data points to find the best locations.
To open new locations, our Global location finder (GLF), fed us back a list of the best locations, each of which met a set of business criteria from our client.
The new locations should be located in areas where “young adults” (aged 22–31 years old) spend most of their time, not too close to business centres, and near or inside shopping centres.
Thanks to the GLF, our client was able to make targeted lists for their retail expansion team to explore.
With the objective of duplicating successes, our “twin location finder” started by analysing the DNA of their most successful locations in order to understand what it was that made them so successful. Our “twin location finder” then listed and ranked locations that were similar
Moreover, it provided the client with detailed explanations of what made two locations so similar.
Thanks to our technology, our client was able to come up with a comprehensive action plan for it’s retail expansion. This action plan was created in the space of a few days using top-of-the-art data intelligence.
If you too have cross-continental retail expansion challenges, feel free to contact us. Our expert team can help you with your goals!
Symaps is an AI-powered location intelligence platform that helps you find the best locations for your business.
Our platform is built for emerging and established brands & retailers looking to scale their business or optimise their existing locations. With a strong focus on retail, FMCG, and real estate, Symaps combines the power of machine learning & AI and acts as the backbone of companies for whom location matters when it comes to making key strategic decisions.
Our team of experienced data scientists gathers, processes, and models large volumes of raw multidimensional data (public and private) to distill it into actionable, easy to use, and visually appealing map based insights.
Our proprietary machine-learning algorithm actively learns what drives your business success and offers advanced data capabilities and predictive technology to empower a company of any size to perform in-depth market research and gain strategic insights in a matter of minutes.
Visit our website to discover more business cases.