In the competitive world of real estate, finding the right target market is crucial for success. A multinational real-estate and asset management company faced sluggish sales in their premium residential project in Delhi NCR. To address this, they turned to Transerve, a Goa-based Location Intelligence (LI) and data company specializing in spatial data handling, processing, and analysis. This article explores how Transerve’s innovative use of Location Intelligence and Big Data transformed the company’s marketing strategy, leading to significant improvements in sales performance.
The Challenge of Identifying the Right Market Segment
Initial Struggles and Limited Data
The real-estate company initially experienced suboptimal sales, having sold only 300 units over two years, with just 10 percent accounted for by direct sales. This heavy reliance on channel partners, local agents, and brokers resulted in significant commission costs, adversely impacting the company’s bottom line. Moreover, the challenge was further compounded by limited data attributes provided by the real-estate company and their lack of proficiency in geospatial technologies. This lack of expertise hindered their ability to ask pertinent questions of their customers during the project’s initial phase, leaving them ill-equipped to effectively target potential buyers.
Transerve stepped in to address these challenges, recognizing the necessity of a sophisticated approach to data. The initial phase of the analysis focused on tackling the limited data attributes issue by establishing workflows that enabled Big Data processing. By leveraging human mobility data and various geospatial datasets, Transerve calculated the Net Affluence Rating for specific grids. This allowed them to tailor their strategy based on city-specific grid resolutions, considering the unique urban fabrics, such as streetscapes, building types, road conditions, and other infrastructural details. For a sprawling urban area like Gurugram, a 350-meter grid resolution was deemed suitable. In contrast, a denser city like Mumbai required a finer, 150-meter grid resolution to capture the necessary data granularity.
Leveraging Location Intelligence
Using Location Intelligence, Transerve could identify the key variables, including building index, road index, mobile index, and Point of Interest (POI) index. By assigning weightages to these indices, they computed the final ratings of the grids, enabling a more precise understanding of affluence in various areas. Following this, a granular analysis of high affluence-rated grids was conducted, which focused on localities and the individuals and their mobile devices residing in those areas. Advanced algorithms were employed to analyze mobility patterns through mechanisms such as Origin Destination Time (ODT) analysis, dwell-time analysis, POIs, convergence grids, and footfall analysis.
This comprehensive analysis allowed Transerve to narrow down their search to High Net-Worth Individuals (HNIs) who exhibited similar mobility patterns to those seen in the project’s first phase. These insights were critical for refining the Out-of-Home (OOH) strategy and enhancing digital marketing campaigns. By overlaying Origin and Destination (O/D) analysis outputs onto existing road networks, Transerve could identify hotspots with high footfall of the targeted individuals or devices. These efforts ensured that marketing initiatives were more focused, effective, and capable of reaching the desired audience.
Advanced Data Analysis Techniques
Key Variables and Weightages
Assigning the right weightages to key variables, such as the building index, road index, mobile index, and Point of Interest (POI) index, was pivotal to the accuracy and relevance of the grids’ final ratings. Transerve deployed a rigorous methodology to ensure these weightages reflected the real-world scenarios of affluence distribution. For instance, building indices considered the type of structures present in an area, from luxurious residential buildings to commercial complexes, while road indices examined the quality and connectivity of the roads. Mobile indices provided insights into the density and movement of mobile devices, indicating how populated and dynamic an area was, and POI indices looked at the variety and prominence of points of interest, such as schools, hospitals, malls, and more.
With these indices accurately weighted and incorporated into their model, Transerve could perform a highly granular analysis of high affluence-rated grids. This analysis delved into the specific characteristics of localities, including the types of buildings and their conditions, the layout and quality of roadways, and the concentration of significant POIs. Advanced algorithms then dissected the data further, examining how individuals and their mobile devices moved within these grids. The algorithms tracked mobility patterns through Origin Destination Time (ODT) analysis, dwell-time analysis, convergence at key points of interest, and overall footfall—each of which contributed to a nuanced understanding of affluence and potential high-value customers.
Identifying High Net-Worth Individuals
After identifying the high-affluence grids and understanding their characteristics, Transerve focused its efforts on pinpointing High Net-Worth Individuals (HNIs). These individuals exhibited mobility patterns similar to those identified in the first phase of the project, allowing for a targeted approach in reaching potential premium homebuyers. To further refine this strategy, Transerve utilized Origin and Destination (O/D) analysis to overlay these patterns onto existing road networks. This enabled the identification of high-traffic areas where targeted individuals or devices were likely to be found, optimizing marketing initiatives for maximum impact.
By understanding where these HNIs frequently traveled and spent time, Transerve could adjust their Out-of-Home (OOH) marketing strategies accordingly. Digital marketing campaigns were also enhanced through the insights gained from the O/D analysis, ensuring that advertisements reached the desired audience effectively. These combined efforts resulted in a more strategic and focused approach to marketing, reducing wastage and increasing the likelihood of reaching prospective buyers who matched the profile of existing premium homebuyers. This integration of advanced data analytics into marketing strategies not only improved the precision of audience targeting but also enhanced the overall efficiency of marketing campaigns.
Implementation and Results
DIY Geospatial Analytics Platform
To facilitate the seamless integration and application of these analytics, Transerve employed its DIY geospatial analytics platform known as Transerve Online Stack (TOS). Offered on a monthly subscription basis, this platform specialized in performing AI and ML algorithms on spatial datasets to identify HNIs within the high affluence-rated grids. Image processing algorithms played a crucial role in land use classification at various levels, excluding non-residential grids to refine the analysis further. Statistical modeling was carried out to highlight the distinctive features of each grid, ensuring a precise and comprehensive differentiation.
The power of the TOS platform lay in its ability to process and analyze vast amounts of spatial data with unparalleled accuracy and efficiency. This capability enabled Transerve to provide its clients with insights that were not only data-driven but also actionable. By pinpointing areas with high concentrations of HNIs, the platform allowed for a targeted marketing approach, significantly enhancing the effectiveness of campaigns. With the application of advanced algorithms and modeling techniques, the TOS platform transformed raw data into valuable intelligence, driving strategic decisions and optimizing resource allocation for the real-estate company.
Remarkable Outcomes
The outcomes of this strategic implementation were nothing short of remarkable, showcasing the profound impact that Location Intelligence and the judicious application of geospatial tools and technology can have on business results. Transerve’s efforts enabled the real-estate company to reduce its marketing budget by an impressive 25 percent, while achieving up to 40 times the original Return on Investment (RoI). This translated into a substantial financial gain, demonstrating the efficacy of targeted, data-driven marketing strategies. Moreover, the enhanced targeting precision facilitated a 35 percent increase in sales speed, allowing the company to achieve its objectives at a much faster rate.
This case study stands as a testament to the transformative potential of Location Intelligence and Big Data in the real estate industry. By leveraging advanced analytics and geospatial technologies, businesses can gain a deeper understanding of their target markets, refine their marketing strategies, and achieve significant improvements in sales performance. Transerve’s innovative approach not only addressed the initial challenges faced by the real-estate company but also set a new standard for how data-driven insights can be applied to achieve business success in the competitive premium real estate market.
The Future of Location Intelligence in Real Estate
Market Growth and Applications
Transerve anticipates that the Indian Location Intelligence (LI) market will reach approximately $670 million, or ₹50.5 billion, by 2023, reflecting the growing recognition and adoption of spatial data analytics in various sectors. Beyond real estate, major applications for LI are expected to span across industries such as Banking, Financial Services and Insurance (BFSI), Fast-Moving Consumer Goods (FMCG), pharmaceuticals, and transport and logistics. The COVID-19 pandemic has further accelerated the adoption of technology, contributing to a surge in Transerve’s revenue. As businesses increasingly turn to digital solutions to navigate the challenges posed by the pandemic, the demand for Location Intelligence services continues to rise.
The real estate sector, in particular, stands to benefit significantly from the integration of LI and Big Data analytics. By identifying high-value locations, understanding customer demographics and behaviors, and optimizing marketing strategies, real estate companies can gain a competitive edge in the market. Whether it is targeting prospective homebuyers, streamlining operations, or enhancing service delivery, the applications of Location Intelligence offer numerous opportunities for growth and innovation. As the industry evolves, the role of Location Intelligence will become even more pivotal in driving strategic decision-making and achieving business success.
Policy and Industry Impact
In the fiercely competitive real estate sector, pinpointing the right target market is essential for achieving business success. A multinational real estate and asset management company faced a problem of sluggish sales for their upscale residential project in the Delhi NCR region. To tackle this challenge, they enlisted the help of Transerve, a Location Intelligence (LI) and data company based in Goa, known for their expertise in spatial data handling, processing, and analysis. This article delves into how Transerve’s innovative application of Location Intelligence and Big Data revolutionized the company’s marketing strategy. By leveraging advanced data analytics and spatial insights, Transerve was able to provide a deeper understanding of market demographics, consumer behavior, and location-based trends. This strategic shift not only enhanced the company’s targeting capabilities but also led to a notable increase in sales performance, underscoring the importance of sophisticated data applications in modern real estate marketing.
