Contributed by Margaret Glover-Campbell, Senior Vice President, Marketing and Communications for Poynt
There are more than six billion mobile subscribers in the world, and – according to industry analyst firm mobiThinking – more than 30 percent reside in China and India alone. India’s mobile subscriber base reached nearly 904 million in January 2012. These staggering numbers, coupled with the 100-percent year-over-year growth in smartphone sales in India since 2010, represent a huge opportunity for location-based services (LBS) in the region.
Already, there are early indicators of the tremendous potential of LBS in the India market. As an example, according to Rajan Anandan, managing director of Google India, about 40 percent of search queries for Google India come from mobile phones, compared against the United States (14 percent), UK (6 percent) and Russia (11 percent).
Industry studies have found that – after texting – search is the most-performed activity by smartphone users, followed by news, entertainment, maps, and social networking.
This is no surprise. With GPS technology becoming a standard feature on smartphones, there is an increasing demand for LBS services, such as POI (point of interest) searches, maps and traffic, multimedia and advertisements, resource tracking, and social networking, just to name a few.
Demand for LBS is changing how consumers shop, search, interact, share, even date.
Along with that demand, the importance of accuracy and relevance for LBS has never been higher due to the competitive landscape among operators and content providers, as well as heightened consumer expectations.
Consumers are dynamic. In the morning, they can be headed to work searching for a coffee shop. In the afternoon, they may search for a hot lunch spot. In the evening, they may plan where to have dinner, and on the weekend, they run errands, searching for the cleaners, a pet store, etc.
As a result, LBS must deliver a dynamic user experience. Many factors and filters can play a significant role in users’ search queries: proximity, time of day, day of the week, weather, holidays, user tendencies, user reviews/ratings, POI availability, and more. The key to all of these factors/filters is offering hyper-local, context aware data to users.
Context is King
Being “context aware” is about user intent. In other words, what are users searching for now?
Context is essential to deliver advertising that taps into what users want. That involves targeting by purchase intent, day part, location, demographics, device type, carrier, and other criteria that drives relevancy for someone performing a search. To optimize contextual targeting, brands and retailers must leverage a sophisticated backend system that can “layer” these different criteria for more results-driven ad delivery.
For example, a restaurant wants to bring a new line of morning coffee drinks to market. It will want to target by purchase intent, where someone searches on terms such as breakfast, coffee, etc. Targeting should be performed by day part, meaning that an ad for the coffee drinks should only be delivered in the morning hours when they are available for purchase. Further layering the context, targeting will include location, perhaps geo-fencing a radius of 10 miles around the restaurant’s location. Other criteria can be included if needed to further narrow down or expand audiences based on user context.
Interestingly, improving LBS context and relevance involves leveraging LBS users as producers of location-based data. As users perform searches, a sophisticated backend system “learns” what types of searches are performed, when and where they are conducted, and refines its delivery of contextually aware services based on that data.
For example, to provide contextually aware LBS services in India, Poynt partnered with The Times Group of India, the largest media company in the county. Through the Group’s TimesCity.com one-stop-shop website, Poynt delivers location-based information on movies, nightlife, restaurants and many more entertainment-related searches. In the near future, those LBS services will extend to other lifestyle-oriented applications. By pairing Poynt’s LBS services with TimesCity.com’s user data, the ultimate benefactors are consumers who receive a hyper-local, contextually aware search experience.
Challenges to LBS
While LBS promises tremendous potential in delivering value to consumers, there are some challenges that brands and advertisers must consider to ensure success. The three primary challenges involve performance, privacy, and relevance.
Regarding performance, there are a few dimensions to how users experience a location-based service. First, the quality of the app plays a large role. How is the user interface? Is it easy to navigate? Is information readily available and easy to view?
Second, the speed of the network – whether users access LBS via a 2G, 3G, or 4G connection – determines how quickly LBS queries and downloads occur. This speed has a direct correlation to the quality of experience when using an LBS app.
Privacy is a major factor in LBS, both from a consumer and brand/advertiser standpoint. Consumers choose whether to share their location to receive relevant LBS data with the expectation that their information will be kept private. LBS services must adhere to industry privacy standards and not mis-use consumer data for wrongful applications such as spying or flooding with spam messages.
Besides being highly relevant and accurate, location data must constantly evolve, get updated, and be easily navigated on limited screen real estate. LBS services must find ways to minimize the time and cost to maintain their data, and keep it relevant and up to date.
LBS apps are creating a major paradigm shift in how people transact with the world around them. The market winners in LBS will be those that offer real-time, socially intelligent apps that are contextually aware, convenient to use, and successfully navigate the challenges of performance, privacy, and relevance.