What’s the Difference Between Location Data and Location Intelligence?
September 25, 2019 | Contributed by: Mike Boland
To prepare for Localogy’s Place Conference next month and get the juices flowing, we’ve begun to interview speakers throughout the program. The latest is with Place IQ CEO Duncan McCall. As we wrote recently, Place IQ just received a strategic investment from Experian to focus in on its location data core strengths.
McCall will speak on a panel discussion on Day 2 of Localogy’s Place Conference on the state of location-targeted marketing. See our full interview with him below.
LSA Insider: What’s the biggest challenge facing location intelligence today? What are some of the looming uncertainties, whether they be regulatory or technological (e.g. shifting standards and policies at the mobile OS level)
Duncan McCall: Whilst there are indeed uncertainties around regulatory or technology aspects, some type of uncertainty always exists in a young evolving market and industry, and there have been extensive musings in the press as to these somewhat unquantifiable ‘challenges’ as they pertain to the likes of regulation or technology.
Perhaps more interesting to discuss is that, at PlaceIQ, given our broad arch of experience and observation in this market, on a day-by-day basis we observe that the biggest challenge is the difficulty existing businesses have with embracing new approaches and new KPIs such as visitation.
To give you a clear example: The QSR and casual dining sector spend huge amounts of money on digital advertising each year, with the fundamental goal (no matter how it is wrapped) of driving consumers into their restaurants. Startlingly, this industry is still overwhelmingly optimizing marketing spend to ‘digital metrics’ (clicks on ads, online actions, video completion rates etc) even though time and time again it’s been proven these metrics have no correlation to foot traffic.
In testing, optimizing marketing spend to the actual KPI you are looking to drive – foot traffic – has now been empirically proven to drive quantifiable ROI (stay tuned for a really interesting upcoming case study on that topic from PlaceIQ very soon). Yet, we see tremendous inertia in shifting toward instituting marketing tactics and measures that are foot traffic based.
We recognize that change is hard. To move an industry off existing KPIs, to realign incentives, is far easier said than done, but I honestly think that is simply the biggest challenge right now to larger mainstream adoption.
LSAI: There are many different location data gathering methods and practices. What are some of the practices and methodologies that you believe are most effective?
DM: Despite what you read, if you were to look at the set of companies in this industry that people would consider the ‘scaled players’ — who have been around for a while, and have built real technology — you would find that there is very little to almost no differentiation in the location data they collect. This may seem a provocative statement, but it isn’t meant to be – it is fundamentally a truth of the marketplace. This is a result of the fact that many ‘scaled’ companies are overwhelmingly using background / persistent data – data that comes from SDKs that are heavily controlled by the phone OS. When you combine the prevalence of smartphones and mobile apps with OS constraints, and a natural limit to the average amount of apps that would be in common use by consumers, it is easy to see that there is very little ‘exclusive data’ anywhere in the ecosystem.
With little diversity in data or collection practices, it’s important to note that this is raw probabilistic data that — on its own — tells you next to nothing in terms of ‘location intelligence’. It is merely a lat/long. It is necessary to translate that raw data into an actionable signal: was that device actually at a location? How long? What type of location? How many signals at what accuracy did we see to make an informed decision? What other behaviors and characteristics of the data and the place itself helps translate all this raw probabilistic data into actionable intelligence?
So, the real differentiation here is not the data inputs themselves or collection mechanisms, but the technology and software that translate these data points into actionable business intelligence. Many real evaluations of the space have borne this fact out.
LSAI: Are you seeing any notable trending in the sophistication of companies that use location data (your customers)? What are the questions they’re asking and is that changing? What are the questions they should be asking?
DM: Whilst the pace of change is slower than we would all like, change is indeed happening.
In terms of the PlaceIQ customer base, we are lucky to have a broad set of very sophisticated companies thoughtfully using our data and product suite. We see that they are increasingly using the data to make critical business decisions inside and outside of the marketing arena.
Because of the expansion of sophisticated analysis, and the larger set of use cases, the questions they are asking are often around accuracy of the data — meaning how accurately does your data represent reality? How closely does it correlate to my own view of reality? If you are using the data to really understand and make business decisions, you need to understand how accurate that data represents that company’s reality. We’ve done this kind of testing against truth sets with our clients and data partners and it has proven crucial to the larger organization really investing in and supporting the data when they see how well it mirrors, and even fills in, their own understanding.
LSAI: Location intelligence was once primarily used for advertising and marketing, such as ad targeting and attribution. But it’s evolved and broadened into other areas such as product planning, operational support and even equity research. What are the untapped or underserved areas where you believe location intelligence could thrive in 2020 and beyond?
DM: I believe we are literally still scratching the surface of the use of location data within marketing — an opportunity being constrained primarily by the speed of adoption.
But outside of that direct market, we are experiencing a very real and significant opportunity across a whole host of industries. To name a few: we see tremendous traction across consultancies, transportation and logistics planning, and real-estate based market definition/trade areas. Each is experiencing truly breakthrough advances based on the sophisticated analytics they can design based on real human movement.
Given the fact that location-based data now is being accepted as a new dimension to understand behavior, and to understand how that behavior pertains to our physical world, these are applications I believe will increasingly be horizontal in nature serving a whole series of verticals. We are still in the early stages, but with the accelerating sophistication and importance of deployments, it is an exciting time to be in this industry.
See more about the Place conference here.
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