The retail market all across Asia, and actually most of the world, is extremely competitive. No matter what your business is, your competition is always seeking to take your market share and outperform you in one way or another.
There are not many “mantras” to success that cross industries like the simple adage “location, location, location”. The locations you chose are one of the most important decisions your company can make and factors heavily in your success against your competitors. This is true regardless of whether you are opening restaurants, cafes, schools, retail outlets, fashion shops, convenience stores, or many others. Location can make one house worth $100,000 and another $20 million, and it can often determine the success or failure of your business.
But how can we tell what makes a good location? I mean sure there are some basics like high traffic, good visibility, easy access, and sufficient parking. We understand these and they of factor into any decisions we make. But is this enough?
It does not. We need more meaningful data. Data that that answers all these questions and many more. Data that was never available ….. until recently.
Single locations, even when they do achieve forecasted returns, still may miss the opportunity to build network strength and awareness for a brand across a territory. They may remove a better nearby option, or prevent several units being built in the same area, reducing the overall growth of your brand.
Now we have location intelligence. I’ll refer to Wikipedia to help us out here. Wikipedia defines it as: “In business intelligence, location intelligence (LI), or spatial intelligence, is the process of deriving meaningful insight from geospatial data relationships to solve a particular problem. It involves layering multiple data sets spatially and/or chronologically, for easy reference on a map, and its applications span industries, categories and organizations.”
Maps have been used to represent information throughout the ages, but what might be referenced as the first example of true location ‘intelligence’ was in London in 1854 when John Snow was able to debunk theories about the spread of cholera by overlaying a map of the area with the location of water pumps and was able to narrow the source to a single water pump.
This layering of information over a map was able to identify relationships between different sets of geospatial data. Location or geographical information system (GIS) tools enable spatial experts to collect, store, analyze and visualize data. Location intelligence experts can use a variety of spatial and business analytical tools to measure optimal locations for operating a business or providing a service. Location intelligence experts begin with defining the business ecosystem which has many interconnected economic influences. Such economic influences include but are not limited to culture, lifestyle, labor, healthcare, cost of living, crime, economic climate and education.
Now, what does all that mean for us? It means we can now make fully educated decisions using data to avoid mistakes and help make sure every location we open has the best possible chance to succeed.
So, how does it work? Putting it in simple terms it uses a combination of Census data and other government statistics, mobile phone tracking, and automated and manual data “scraping” to create a map with a large amount of data in it. Data scraping is a process where internet websites are researched and information is extracted. For example, a company, like ours, that provides location intelligence would check the websites of popular international food & beverage (F&B) franchises like McDonald’s, Burger King, KFC, Pizza Hut and many others to add all their locations into our maps. The process is the same in other industries, including but not limited to fashion, shopping malls, cafes, retails shops, schools of all types, language and other education centers, and so on.
Now, using our new populated map with all of our data, we can do many amazing things that are designed to help us determine if this would be a suitable location for our businesses. I think it is easier to explain by example, so let’s look at one.
Let’s say we are the franchisee of a popular quick service restaurant chain in Vietnam. We can turn on all our locations in our map. Let’s say in a big city we draw most of our customers from a 0.5 km radius. We can show it like this:
From here we can do many informative things, but let’s do something simple. I can see on this map there are many gaps where we do not have locations, but how can I start to tell if they would be suitable? This is where we can turn on some filters. Let’s turn on the filter “consuming class”, which is the population in the area that has disposable incomes and would be our target customers. Now, we can see the darker the colors on the map, the higher the population that we are targeting. We can go further like identifying this population during the day (workers) or at night (residents). We can add competitors to see where they have opened stores. We can compare our own location data to see why some stores are busier than others and then search the map for similar future locations. So many options.
When we have identified a potential location, we can then run whatever suitable information we have identified as important for our brand to be successful. For simplicity sake, I have picked a location and let’s just take a few criteria. We will assume we need a target age group of 20-39, targeting the consuming class, 0.5 km. radius, and our focus is daytime businesses.
I have only pulled a few pieces of data for the chart below, but you can see that this spot has a significantly higher consuming class 56.85% (compared with 35% for the city, and 19% for the country). It is highly populated with almost 51,000 people who live there, of which 37% are in the target age group. It also has a very high daytime worker population of 34,521. All of these would be positive indicators that show this particular spot has high potential.
I love a certain quote from Idries Shah in his Reflections. He says, “Opinion is usually something which people have when they lack comprehensive information.” I have opened a wide variety of restaurants, schools, and language centers throughout Asia. These units cost anywhere between $150,000 USD to more than $1.0 million to open. When a bad decision is made and you need to close or move, you recover only around 25-30% of the investment (typically in equipment that is transferable elsewhere). This gives us a failed location cost of between $105,000 and more than $700,000. If this is that very critical first or second location for your brand in a region, the cost could be astronomical as your whole project might fail and get abandoned.
This process really allows your company to have a well-planned strategy growth strategy which provides many benefits.
So, instead of risking such a huge investment on the “opinions” of your team, why not invest a relatively small amount into getting comprehensive information? Lower your risk, make the best possible decisions, and achieve market penetration in the most efficient way possible. And that is what Location Intelligence is all about.
Starting in November, VF Franchise Consulting began offering Location Intelligence / GIS mapping services for Vietnam and many other countries across Asia (India, Indonesia, Myanmar, and Taiwan). Please contact me for more information on how your company can benefit from this new tool that will allow your team to make important real estate decisions based on real data.
About the author:
Robert has over 30 years of F&B and franchise experience and has lived in ASEAN for more than 13 years. He is currently the Director of Franchise Development & Operations at VF Franchise Consulting, based in Ho Chi Minh City, Vietnam. He may be reached by email at [email protected]