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About Our guest
Apu Kumar - CEO at LotaData
LotaData transforms location into context. They connect the digital and physical realms by providing geo-temporal real-time situational context to large enterprises, smartcities, businesses, and app developers.
Apu’s Background and LotaData (03:57)
LotaData is an alternative data company. We like to think of ourselves as the real world knowledge graph for mobile apps, smart cities, and enterprise businesses. We started three years ago in San Francisco. We continuously collect data streams about people, their activity and movement. We do this in a completely anonymous manner.
What Access To Location Data Do Marketers Have (05:30)
There is a wide range of data that marketers can access from our mobile phones. One of those data points is the location signal or the geo signal. Depending on the apps that are being used on the device, if the GPS is turned on, that location is being shared.
They would know where we are in the real world whether that’s a shopping mall, a restaurant, or even when we are commuting. They could have a good sense for our behaviors in the real world.
Privacy Concerns (08:18)
How to make data anonymous is one of the most important debates lately. If you are using Google Maps to get from point A to point B using navigation, your location is being shared continuously and we could say that this is a fair use case because you are requesting this service.
If the same data would be shared with the third parties and marketers who would then try to push you ads, then that would result in creaky behaviors.
Most companies collect your location and the device type, but that's where it starts to go down this spiral very quickly because they can start collecting even more personal information that could help them identify the person.
Historically, data which is collected for mobile devices have included all types of personal identifiers such as your phone number, email, name, even your age. When you’re collecting these pieces of data, essentially you are building a complete profile of that individual.
The Use Cases for Marketers (12:44)
Using commuting data is a good example. You can present the appropriate content to people while they are commuting. Marketers can usually benefit from running two-mile radius campaigns. You could use the real world location data and develop people profiles and behaviors in an anonymized manner.
For example, MasterCard has an open dataset about transactions at some stores and these transactions are anonymized. In general, there’s a lot of very interesting ways to understand the impact of proximity campaigns.
What Industries Are Interested In Your Location Data (16.36)
For digital marketers, especially mobile marketers, location tends to be one of the top datasets that they would like to understand. We have large enterprise customers who are actively collecting data from their customer base with full consent. Then they try to understand what these behaviors mean.
Surprisingly, we’ve found use cases even in the local government space. City governments are the largest owners of real estate and they want to understand some things deeper. For example, how many people visited a certain park in the past month, or how many people were in a certain area and where did they come from. Many of these answers lie in location intelligence.
There are also real-time use cases. The most common example is passing by a McDonalds and then seeing their ad.
Governments And Their Interest In Data (21:50)
When we first started looking at the smart cities and local government use cases, it wasn’t really obvious to us why they would need such data. When we embedded ourselves in the mayor’s office we have realized that everything from budgeting to forecasting and even resource allocation depends on usage.
They want to know usage and a good way to understand it is to look at anonymous location data. Everything from maintenance to events can be done better if there’s a deeper understanding of usage.
Getting Data Without Crossing The Line (03:38)
There have been many new regulations in the privacy space in Europe and most likely this will happen in the US too. Many apps on our phones collect data which is uploaded to the cloud and some of that data may go to the app developers, it may be shared with third parties etc. This is where the things start to go downhill very quickly.
So far, the market has not been very good about letting the end users know that their data is being collected. Marketers have not been great at asking permission before collecting data.
These are the reasons why the GDPR has come into force in Europe, but also the Californian version of the GDPR.
Tools and Practices for Data Conversion (05:53)
If you are going to ask the user to opt into sharing their location data with additional prompts or if you show your users the third party sites that would have access to your data as well - it is something that will definitely impact conversions.
In the EU, GDRP is very strict with each and every point and most of these actions need to be done upfront. When the mobile app is launched, the app developer or the publisher needs to be very upfront about what data is being collected and why it is being collected. Also, can I as an end user access my data and even request for my data to be deleted.
California is going the same way, but so far there is no federal law that limits or regulates the collection and use of data.
The Rules For Data Collection (08:35)
One of our requirements for any data that comes into our platform is that the provider of data has to have received consent from the end users and should have displayed adequate notice. We are making sure that our data suppliers are compliant with the GDPR requirements. If that is not the case, we choose not to work with such data suppliers.
How Can You Target Your Data Usage (12:43)
There is the possibility to target by an individual device. This is true of programmatic networks, DSP’s, even platforms like Facebook which lets you upload accustomed segment or a custom audience based on the data that you have.
Advice For Marketers Who Are Trying To Use Location Data (13:52)
My first recommendation is to try not to use the raw location data or the device level data. There is a great deal of sophistication with machine learning and AI that can be used to build behavioral cohorts, so you don’t have to target an individual device. All you need to know are the places where such devices might be and what the affinities might be to other places or other brands. This allows you to create some very sophisticated campaigns without individually targeting the devices.
The other recommendation would be to pay close attention to the quality of the data and the granularity of the data that is being collected in the first place. The accuracy of data is critical for everything that happens downstream and marketers tend to not pay attention to this technical aspect of data collection, which in my opinion is critical for anything.
Ways To Have More Accuracy With Location Data (16:52)
WiFi is a good data source, especially if you have a public WiFi. It tends to be accurate down to 10 meters. You could also start to use the Bluetooth beacons.
Words of Advice For People That Are Using Location Data (17:45)
Ensure that you work with the data providers who are neutral.