Podcast: Play in new window | Download
On the sixth episode of this Attribution Acceleration round-up series, Lawrence Chan joins Sima Vasa. He talks about location intelligence and how persistent and accurate location data play important roles in market research and attribution.
“When you have those types of signals basically dictating whether or not somebody went somewhere, without that persistent context of where someone came from or where they spent time, it becomes really, really good for folks to do meaningful attribution.” – Lawrence Chan
Lawrence Chan – Cuebiq and Location Intelligence
Lawrence Chan is the SVP of Innovation and Strategic Partnerships at Cuebiq. They are a location intelligence company focused on data quality and persistent location data.
He has been part of the team since its inception. He now identifies innovative opportunities and strategic partnerships to drive the company’s expansion. They have found a way to scale the usage of persistent and accurate location data in a way that could be meaningful for many marketers as well as retailers to use for decision making.
Persistent Location Data
The importance of looking at persistent location data when assessing marketing strategies and consumer behavior can’t be undermined. Using a single location data point to break down and conclude that one’s advertising worked is often erroneous. You can never be 100% accurate when making this attribution.
“When you have sparse amounts of data that’s not persistent, you can’t really do much with it. It’s a guess that’s not based on anything.” – Lawrence Chan
The Importance of Context
This is especially obvious when taken in the context of real-life establishments like the movie theater. It may be inconclusive to say that a marketing effort was effective if a consumer spends five minutes in a theater. It’s also important to take note of the pathways that led them to the location to ascertain their interaction.
“That time context really creates a huge difference in terms of understanding what a consumer actually did versus what we saw from the location data.” – Lawrence Chan
Quick links to connect with Lawrence Chan:
Sima loves to hear from her listeners with input, questions, suggestions and just to connect! You can find her at the links below!
Sima is passionate about data and loves to share, learn and help others that share that passion. If you love data as much as her, subscribe on iTunes and don’t forget to leave a rating and review!
