You want to start using location analytics and intelligence to improve your business profitability but do not know where to start?
Read on to learn all you need to know about location data and geospatial intelligence.
The geographic positions of location data are called coordinates,, and they are commonly expressed in Latitude and Longitude format.
Additional attributes such as elevation or altitude may be included and helps data users get more accurate picture of the geographic positions of their data.
People commonly mean GPS data when they talk about location data. In reality, there are various types of location data.
It is important to know how the data is collected as it determines the accuracy and depth of the collected data, this have direct implications on the suitability and usability of the data for a business.
SDK are codes that app developers put into their applications.
These codes tells the app to collect location data from the device it is installed on. These codes requires express user permission to collect location information.
Data collected by SDKs have the potential to be very accurate and insightful. User's daily habits can be tracked which may uncover deeper insights for businesses.
However, the biggest challenge with SDK method is in achieving scale.
Bidstream data is data collected from the ad servers when ads are served on mobile apps and websites.
Bidstream data is one of the easiest type of location data to obtain and scale.
However, the quality of Bidstream data can be a mixed bag. In general, most Bidstream location data is incomplete, inaccurate, or illegitimate.
Beacons are hardware transmitters that can sense other devices when they come into close proximity.
The location data collected by beacons is very accurate. They can also collect details such as name and birthdays, which can be very valuable to businesses.
Since beacons are hardware, they have to be purchased and installed at locations businesses want to track. Therefore, as with SDK data, it can be challenging to achieve scale through this method.
Wi-Fi enables devices to emit probes to look for access points (routers).
These probes can be measured to calculate the distance between the device and the access point.
The precision of Wi-Fi location data is entirely dependent on the Wi-Fi network it is built on.
POS data is data that stems from consumer transactions. This data usually contains adjacent information such as purchase items, amount spent, and method of payment, which can provide valuable information.
Because POS data is decentralized, it would be difficult to match multiple data sources through this method. POS data also only captures customers who have made an in-store purchase, and does not capture information on people who entered the store but did not buy anything.
POI data refers to data points about specific locations that people might find useful or interesting.
POI data is typically used together with other types of location data to derive insights and better understand consumer traffic and behaviour.
There are advantages and disadvantages to each source of location data.
Businesses should consider various factors such as budget, accuracy requirements, and use cases when evaluating the source of their location data.
Businesses should also consider the ways different types of location data can compliment each other.
Most businesses usually purchase location data or location data feeds from data providers. As they do not have the time, resource, and expertise to collect location data.
However, businesses should be aware that the quality of data from each data provider will vary. Data providers that specialise in providing location data tend to have higher quality data, while the more general data vendors might not have the expertise to provide good quality data.
Due to the nature of data, it is near impossible to verify if a provider is selling authentic data. Businesses should assess the credibility of the data provider to avoid purchasing poor quality or even fake data.
Quality location data is important as it correlates with the accuracy and reliability of the findings and insights. Bad data can result in false findings, which causes businesses to waste lots of time, effort, and money.
Location data generally have some attributes or data fields in common such as latitude, longitude, and horizontal accuracy. Other data fields tend to be dependent on the source of the data.
Below is a non-exhaustive list of attributes found in location data:
Latitude and longitude shows the position of a device or structure. They are commonly accompanied by horizontal accuracy, which tells users the degree of error in a particular data point.
Altitude or elevation pinpoints the height above a reference point, usually sea level.
The Mobile Ad ID field is a unique identifier of smartphones.
Google's Ad ID version is known as the Google Advertiser Identification (GAID) while Apple's Ad ID version is called Identifier For Advertisers (IDFA).
Mobile Ad IDs helps to identify, track and differentiate between mobile devices.
Timestamps are typically used for logging events alone or in a sequence.
In the case of location data, they provide context to the movement of a particular device.
Location data feeds commonly record timestamps in Unix time, otherwise known as Unix Epoch time, or Epoch for short.
Internet Protocol Address, or commonly known as IP address, is a numerical label assigned to each device connected to a computer network. IP addresses can be used for host or network identification or location.
However, the location accuracy from IP addresses varies. One common occurrence when looking up an IP address's location is being directed to the network provider's location.
Depending on the business uses, IP address can provide a good rough measure of geographic location, but would not be recommended if accurate location data is required.
Identify trends in foot traffic to determine popular places of interest or commonly travelled routes. One common method of visualising foot traffic is through heatmaps.
Using the insights gained, businesses could analyse the potential traffic and profitability of retail or advertising locations, estimate the peak days or times.
Businesses could also perform movement traffic analysis to uncover audience behaviour and visitation pattern. These findings provides more depth when segmenting audience and customers.
Origin-Destination Study is used to understand the travel patterns of people. They are commonly used for transportation planning, however, their usefulness reaches beyond that.
Traditionally, O-D studies are performed manually through roadside surveys. The growth of GPS and tracking technology makes O-D studies less time consuming and delivers much more accurate results.
A geo-fence is a virtual perimeter for a real-world geographic area. They could be a radius around a single point, or a predefined set of boundary. Once a geo-fenced boundary is defined, the opportunities what businesses can do is limited by only their creativity.
One common use of geo-fencing is for businesses to set up geo-fences around their competitors. And push marketing promotions to customers that enters the zone. This is sometimes referred to as geo-conquest.
Businesses could also provide Location Based Services within geo-fenced region.
A catchment is an area from which businesses expects to draw their customers from.
Catchment areas can help businesses identify where to run their next marketing campaign or set up their next store.
By sending your advertisements to the right people at the right time, you can improve the effectiveness of your advertisements and increase your conversions. Marketers often use location-based audiences to better deliver their ads to the right people.
Context is key when it comes to delivering the right marketing communication to your audience. By knowing where they come from, you can craft contextually relevant marketing messages that resonates with your audience. Resulting in a more effective marketing campaign.
Analysing your customer's movement and visitation patterns may uncover insights which you could leverage on to attract and retain customers.
Use location data to plan and select the best site to open your next store or to place your next outdoor advertisement.
Uncover correlation between footfall levels, inventory levels and business performance. Good for demand and supply planning or for business and economic research.
Quadrant's entire data feed.
Great for organisations who want to conduct all data analysis in-house.
Mobile location data processed and filtered based on your specified criteria.
Deploy the data almost immediately with minimal processing.