Points of interest: Using POI data to scout locations for parcel lockers and PUDOs
When building parcel locker and PUDO networks, success depends on choosing locations that are convenient for recipients and can drive consistent volume.
Focusing on the ones where people already spend time and understanding where other players are can help increase the chances of your out-of-home delivery network performing well. These locations, also known as points of interest (POIs), offer valuable insights into where to go next.
In this article, we explore how to source POI data, evaluate its quality, and use it to scout promising locations.
What are points of interest (POIs)?
Points of interest are real-world locations, such as gas stations, train stations, coffee shops, and other places with steady traffic. In spatial analytics, they are used to make informed decisions. POIs help narrow down the list of possible locations by evaluating their potential and relevance to your network goals.
Examples of using POIs in location scouting
Choosing which category of POIs to analyse really depends on what you’re trying to achieve. To show how the goal shapes the data you use, let’s walk through a few examples.
Placing parcel lockers along daily routes
Out-of-home delivery only works if it’s actually convenient for recipients. One smart strategy is to position parcel lockers along people's daily routes. Public transport hubs are a great example. Bus stops, train stations, and metro stations are all POIs you can use to scout ideal parcel locker locations.
By mapping these POIs, you can identify which stations see the most traffic and where there’s available space for installation.
Partnering with local stores
Let’s say you want to expand your PUDO network by partnering with small shops or retailers. However, not every store is equal in terms of value.
You need to evaluate the location potential of these points of interest based on foot traffic, population density, and operating hours to make sure they have enough daily visitors for the partnership to pay off.
Entering a saturated market
When you’re entering a market as a latecomer, finding new locations that add value can be challenging.
But by mapping out where other players are present, and combining that with additional data, you can visualize market coverage and spot underserved sites that could be a good opportunity.
How can you source POI data?
Once you know what points of interest to focus on, you can move on to gathering the needed data. POI data contains information about a location, such as the address, description, opening hours, and more.
You can collect it in various ways:
- Web scraping: This is an automated process of extracting information from websites, such as store locators or public directories. It’s crucial to ensure the site’s terms of service do not prohibit these activities. The quality of the data collected this way is inconsistent. You will need to spend some time preparing it for analytics, which includes normalizing names, geocoding, and removing duplicates.
- Forming data partnerships: Instead of scrapping, you can take the collaborative route. A data partnership is a mutual agreement with businesses or organizations to share their location data. For example, if you have a long-term partnership with a gas station or retail chain, they may be willing to provide detailed and up-to-date data.
- Using open-source databases: These are geospatial databases, such as OpenStreetMap, that cover a wide range of categories and countries with a consistent structure. They are free to use, but you have to provide attribution.
- Working with a commercial data provider: These data companies specialize in offering rich POI datasets, which typically include visit frequency, mobile signal data, demographic overlays, and more. They often charge based on volume, geography, or per access.
How to evaluate the quality of POI data?
For effective spatial analytics and decision-making, POI data must be complete, accurate, and accessible. Whichever method you choose for collecting this data, make sure that it includes all key components and meets your specific needs.
When it comes to key components, the POI data should include:
- The geocoordinates (latitude and longitude) for accurate positioning, as well as the physical address of the location.
- Additional helpful information, such as the operating hours and contact information.
- The category of the POI, such as gas stations, public transportation stations, stores, restaurants, etc.
It's also crucial that the data aligns with your intended use case. For instance, if you plan to expand your network into multiple markets, the dataset should cover all the countries you require.
Finally, it needs to be usable by your team. Make sure the dataset can be exported in common formats, such as CSV or Excel files, and integrated into your existing mapping and spatial analytics tools. This is especially important if your team isn’t highly technical or familiar with APIs.
Getting the most out of POIs with Mily Tech
Choosing the right points of interest and sourcing the data is only one part of the process. A common challenge for teams is effectively managing this data and using it to evaluate location potential.
With the Mily Tech platform, you can easily import targeted POIs and enrich them with additional information, such as rent fees or notes on why you went for or skipped a location. You can also get access to POI datasets from our partners to round out your analysis.
Once you have your desired POIs, the platform enables you to evaluate their potential and get optimal location recommendations, moving from a long list of possibilities to a focused rollout plan.
