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Big Winners ‘Under The Radar’: Location Intelligence, Geo-Coded Behavioral Analysis

Continuing his series on disruptive companies identified at the "Under The Radar" event, Brian Singh profiles several firms exploring how to use geo-location data to drive deep behavioral data insights. These are very much the types of capabilities that brands are exploring.



Editor’s Note: Continuing his series on disruptive companies identified at the Under The Radar event, Brian Singh digs in deeper and profiles several firms that are exploring how to use geo-location data to drive deep behavioral data insights. These are very much the types of capabilities that brands are exploring to address gaps in the traditional MR wheelhouse and we’d do well to pay attention to this rapidly growing group of new entrants into the competitive landscape.


By Brian Singh

At this session, four companies – GoSpotCheck, Nearbuy, Placed and PlaceIQ presented their offerings of capturing and interpreting geo-specific data. Some were straightforward in replacing or augmenting a service (GoSpotCheck and PlaceIQ) to aggregating data for mining purposes (PlaceIQ) and the detail grabbing of data to deliver better customer offers (Nearbuy and Placed).

The core themes emerging were that the future of location intelligence is mobile driven. And the full functionality of and data available from mobile devices will be explored. There is also the creative aggregation of public and private data sources to yield detailed databases that can be integrated with mobile environments, to yield new forms of normative data, to facilitate insights in decision making. At this same time, there is an emerging “creep” factor – there are lots of data being offered up unknowingly by mobile device wielding consumers and being appended to these databases – the cost of free has an information offering and public profile attached. The research industry must take note of this as emerging platforms continue to keep pushing the envelope of these boundaries.


GoSpotCheck’s proposition is better location intelligence. Their goal is to replace third party teams and (likely) mystery shopping, with a core offering to streamline onsite data collection into a single, unified reporting platform. GoSpotCheck seeks to empower employees and their smart phones to deliver specific “missions” that quantify and resolve problems in certain locations. Using the philosophy of BYOD (Bring Your Own Device), they are seeking to provide more in-store accountability via building advocacy from within an organization. While based on a mobile app, their primary focus is on cost saving – for the speed of data collection and processing time, the reduction in staff and the use of third parties, and the improved efficiency of onsite decision-making and delivering on promotional offers for brands and customers. Case studies have already indicated, as a result of deployment of this platform, that there is substantial improvement in sales.

For the research industry there is a challenge and an opportunity presented via this platform. From a challenge perspective, this potentially eliminates third party field teams and diminishes the use of mystery shopping. From an opportunity perspective research firms can incorporate GoSpotCheck into their offering to gather onsite intelligence and contribute to helping organizations build a high performing culture through the incorporation of LEAN processes into their consumer facing business functions.


NearBuy presents itself as offering a location shopping solution, specifically through mobile shopping. It capitalizes on the in-store experience in attempting to transform the online with the offline experience to support commerce. NearBuy leverages existing in-store wifi and connects customers via a geo-fenced application – as they enter the store, a pop up notice appears on customers smart phones with an offer to connect to the store wifi with the store’s terms and conditions appended. NearBuy capitalizes on the browsing activities in the stores and then tailors offers as customers browse. The platform offers to align campaign effectiveness and to glean customer insights so as to present more relevant offers in-store.

NearBuy is seeking to develop their API (Application Programming Interface) to retailers, CRMs and POS systems. NearBuy further positions itself as the next generation of the in-store buying experience.

From a research industry perspective, we need to consider platforms such as Nearbuy in their approach to obtaining customer related data. For retailers, this presents a fantastic opportunity to grasp a treasure trove of extremely useful data and to test and deliver relevant, tailored, time-appropriate offers. But it also presents a seemingly innocuous approach to gleaning a host of personal data. This is an evolving concern as to what private information platforms are obtaining to refine their insights. Is this strictly an efficiency gain that benefits the consumer or is it presenting challenges to personal privacy?  This is a question that needs to be carefully considered as the dialogue evolves between start-ups such as these and users of consumer insights.


Placed is a location analytics platform. As stated at their site, they measure, aggregate and analyze the paths and places people visit in the real world. Placed was established to grasp the offline actions of customers.

Based on an initial panel (Placed Panels), participant behaviors were quantified and norms established. The Placed application emerged from the insights from this panel into a simple application that is easy to set up for businesses. Businesses are able to obtain a “place filter” to get the propensity of places visited. As indicated at their site, there are a host of reports that business subscribers can obtain – including analytics, session coverage, persistence of coverage, precision of nearby actions and a rating scheme. The company has cataloged over 300 million places and has validated data on over 2 million people.

One of the stated benefits of the platform is that businesses can see their own brand against competitors and can observe the traffic patterns of their customers. In quantifying such behaviors, Placed is able to complement a host of marketing and promotional efforts including out of home advertising, detailed analytics as to purchase and visitation behavior and exploration of co-branding and packaging of services and products in meaningful ways as to a customer’s actual location base and purchase behavior.

From a research industry perspective, such path analysis is becoming commonplace to determine appropriate points of intervention in ways and means that are relevant to customers; thus, intervening at a point beyond base awareness to facilitate decision making at a particular location or point of purchase. For small to mid-sized businesses, it presents a reasonable, low-cost “research agency” option to deliver benchmarking and consumer insights to refine their promotional and engagement strategies. It would appear that there is an opportunity for niche players to partner with Placed to provide the strategic insights filter for local businesses, and for larger research and communications agencies to work with regional and national retailers.


PlaceIQ was established based on the premise that location is the best indicator of interest. Their platform seeks to help brands convert time and location into context. PlaceIQ was based on a GIS application developed five years ago, where they were seeking to extract more intelligence from the ever increasing mass of location-specific data being created. The system has mapped 100 meter square “cells” across the entire United States. All data is ingested into the system and stacked accordingly in the platform and includes census, weather, transportation and other publicly available data. Thus, a “master database of tremendous insight” is readily available for data mining. PlaceIQ indicates their platform is able to deliver detailed data analysis to assist brands in projecting audience, improve ad placement and refine messaging by mode and context by geographic market.

Such approaches are becoming the norm and the research industry needs to improve the depth of their insights beyond basic consumer behavior to integrate with platforms such as PlaceIQ. This will bring forth more strategic insights based on pre-existing databases which corporations will increasingly seek to improve the bottom line of their marketing and business development. Such platforms can complement and/or augment proprietary geo-demographic, geo-attitudinal databases such as PRIZM, but operational platforms that have already migrated to a GIS platform.

The notion of remixing and aggregating is at the heart of emerging location intelligence platforms. We have already seen MR firms adapt by having GIS specialists in house. However, have we adapted existing methodologies to the opportunities presented by the mobile universe? While there has been an adoption of mobile platforms in conducting consumer research, this continues to be a top-down, limited application of the technology. It is evident that new players, as identified above, have adopted a bottom-up approach in rethinking and delivering insights to businesses and brands who are seeking more up-to-date, relevant behavioral data. And data that can be incorportated in point-of-sale and supply chain systems to fully incorporate consumer insights at the operational level. Where the currency of insight has defined behavioral analysis as a product, incorporating an integrated approach to location intelligence in our offerings will likely prove to be a growing and necessary asset.

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One response to “Big Winners ‘Under The Radar’: Location Intelligence, Geo-Coded Behavioral Analysis

  1. What I find interesting in all these services is that (a) they rely on shoppers to make it happen, whether actively or passively and (b) they either provide no, or Brian does not mention, any benefit to the shopper. It appears that all the benefits are to the retailer. Also, it’s been 14 years or so since Paco Underhill came out with “Why We Buy” and made the [now obvious] point that dead spots can occur and you need to understand how people walk through the store and see what is there. Are we not surprised that most big retailers haven’t figured this out? Or is there less to this data than we think now?

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