Research 101 Series
Part 1: Distance Decay
I love numbers and research, but also know that numbers and research can be overwhelming and frustrating to understand and determine how to make it actionable. However, there is hope! And we’re here to help you make sense of the data, how to read and extract key details from it, and how to apply those insights to help you be more successful. Rather than being overwhelmed by the vast amount of data and numbers available in our Visitor Research Program reports, we will break down the data one report at a time, in simple language, to increase your proficiency in data literacy, in our new ‘Research 101’ series of articles.
This month, we will look at a ‘Distance Decay’ report. And it’s OK if you don’t quite know what this refers to yet. Read on to learn what distance decay means, why it is important to understand, and how you can use it to grow visitation to your business and community.
What is ‘Distance Decay’?
The simple answer is “distance decay” is how far people have travelled to the area you want information on. This can be a single business or part of a municipality, up to an area of five million square feet, which is a great way to learn more about visitation to a downtown core, for example, or even to a conservation area.
Why is ‘Distance Decay’ important?
Distance Decay is important because it tells us three key insights:
- The number and percentage of locals (within 40kms) and visitor (>40kms) that arrived at your location in a year.
- What percent of the total households within each radius visited your location each year. This info can help you increase your market penetration.
- How far the vast majority of your visitors are travelling. If 95% of them are visiting from within 120kms, you know you can focus your marketing and communications efforts to reach people who live 60-90 minutes from your location.
How is this information collected?
There are two ways I get visitation information: 1) from your collected visitors’ postal codes that you provide me (analyzed through our Visitor Research Program), and 2) from cell phone data (analyzed through our Geofencing Research Tool). In both cases, the software calculates the distance from the house to the location we want information on.
For cell phone data, the software determines the location of the house based on where it rests overnight for the majority of the year.
PLEASE NOTE: We and our data providers take privacy very seriously and all of the data is scrubbed to eliminate the possibility of identifying any personal information.
How else do I use information from this report?
This report is central to all other reports because it is the one that tells us how far people are travelling from. I am able to provide specific information about the demographics and psychographics of the visitors travelling more than 40kms each way. I can tell you how many visited by month and even by day of the week. I can find out how many times people visited in a year. I can use the information to provide the economic impact from the people visiting because they are not just going to spend money with you.
It is the cornerstone report, so let’s dissect how to read it.
How do I read a ‘Distance Decay’ table?
Next, we will dissect the data set.
Unit Bands:
These are the radius circles from the centre of the area we want information on and are in 5km increments.
Absolute Count:
This is the number of households within the specific circle that visited the area we want information on.
Absolute %:
This report keeps measuring (in 5km increments) the number of households that visited until it captures all (100%) of the households that visited the area we want information on. The Absolute % tells us what percentage of the total visits came from that specific 5km band.
Cumulative Count:
This adds the number of visitors per band until it gets to the total measured households and lets you know the total number of visitors that came to the area you are measuring.
Cumulative %:
This adds the percentage of your total visitors that arrived from each band and can help you determine where you are getting the majority of your visitors from. It also easily lets you know how many of your visitors are considered local (up to 40km) and non-local (>40km). The next example will clearly show this.
Understanding Base Counts
The above chart includes all of the datasets that the Distance Decay Report provides. You will notice that the first five headings from left to right are explained in the section above. The final three provides you will additional insights.
Base Absolute Count:
This is the TOTAL number of households within each specific circle.
Base Cumulative Count:
Similar to ‘Cumulative Count’, this adds the number of households per band.
% Pen (% Penetration):
This is the percentage of total households within each specific circle that visited the area we want information on, essentially, what % of the ‘Absolute Count’ are we penetrating of the ‘Base Absolute Count’ (‘Absolute Count’ ÷ ‘Base Absolute Count’).
Putting it all together
Below is the majority of the Distance Decay Report. Let’s take what we just learned about to analyze what it is telling us.
To view the full Distance Decay report in PDF format, click here.
- The area being analyzed is in a smaller town. We know that because there are only 8,356 households within a 5km radius and a total of 13,795 (cumulative count at 5-10km) households within a 10km radius.
- Heavy visitation by locals to this area! 91.06% of all households within a 5km radius visited at least once during the year (% Pen).
- The area being analyzed has larger population centres starting at 10+kms. You can see this by looking at the Base Absolute Count which jumps to 38,008 households within a 10-15km radius and staying large after that.
- 43.95% of your total unique visitors are considered “local”. This is the Cumulative % in the 35-40km row, which measures the total unique visitors from 0-40km and divides it by the total unique visitors to the area we want information on.
- 95% of total unique visitors to the area travel 125km or less. This is the Cumulative % in the 120-125km row.
- The types of people that live within 20-25km of the area we want information must like what is offered. I started by looking at the % Pen. The band before is 6.84% and the band after is 4.23%. But 9.59% of households in the 20-25km radius visited. This should have you asking to find out more about the types of people living there.
- Lots of people visit from within 55-60km from the area we want information on. I started by looking at the Absolute % and noticed that a full 10.65% of unique visitors were from that radius band. I looked over and that equated to 13,306 households. But there are 939,959 households in that area which means that 1.42% of them visited at least one. However, I look at it as an area of low hanging fruit. If we can get even another 1.42% of them to visit, we will increase visitation to the area by a full 10%!
How I show you the data
In addition to getting the raw data from the Distance Decay report, I provide an Excel spreadsheet that summarizes all that the data provides. For the purposes of this article, we have only focused on Unique Visitors, however, the data also includes the number of visits from each household and can be sorted by day of the week and month. So as not to confuse things, I have only added the numbers we have talked about above into the chart template below.
Spend a few minutes to see what other insights you can glean from the above report. Now that you understand what each of the rows and columns mean and how they connect, I have no doubt that you will be able see many interesting tidbits in the data.
And that is where it starts. Answering one question through the analysis and coming up with several other “I wonder if it will tell me this..” questions and then figuring out how to find that answer in the data.
Each month we are going to tackle another dataset so that you can become an expert on how to use the data to implement new programs and initiatives to grow your success.
If you have any questions about this, other research, or data in general, feel free to contact Tom.
Written by:
Tom Guerquin
