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Political
Consultancy
We dig what nobody digs
Our in-house state of art technology not only refine and provide the quality data but also in real time provides the accuracy of the data. Our platforms unique design helps to capture the lateral intelligence that otherwise goes unnoticed.
Our core Data Intelligence Expertise
Demographic Intelligence
We try to best segregate data layer by layer to get you the best demographic intelligence
Geolocation Intelligence
Geolocation intelligence is the critical aspect of data especially human driven data
Cluster Intelligence
Accuracy level are most important and that is why our in-house deep tech helps gauging the best cluster level intelligence to get most accurate data
We collect, analyze, and disseminate real-time data and insights related to the characteristics of a population, such as age, gender, income, education, and location. This information can help make informed decisions about a wide range of issues, from marketing and advertising to public policy and resource allocation.
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Understand the preferences and behaviors of different demographic groups in real-time
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Optimize marketing and advertising campaigns to better reach target audiences
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Inform public policy and resource allocation decisions based on real-time demographic data
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Identify emerging trends and respond quickly to changes in the market or population demographics
Our real-time demographic intelligence can provide valuable insights and help organizations and political institutes stay ahead of the curve in a rapidly changing world.
Cluster intelligence is a powerful tool for identifying patterns and insights in large datasets. By grouping entities based on their similarities, we help you better understand your voters, opponents voter base and let you make informed and more accurate decisions. There several key steps to it as mentioned below
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Collecting data: We collect data on the entities under consideration through our opinion gathering platform. This data can be collected through surveys, social media, or other sources.
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Preprocessing the data: The data is then cleaned and preprocessed to remove any outliers or irrelevant information.
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Choosing a clustering algorithm: We use various clustering algorithms available, including k-means, hierarchical clustering, and density-based clustering. The choice of algorithm depends on the type of data being analyzed and the goals of the analysis.
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Running the clustering algorithm: The algorithm is then run on the preprocessed data to group entities based on their similarities.
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Interpreting the results: The results of the clustering algorithm are then interpreted to identify patterns or insights that can be used to inform decision-making.
We do thorough analysis of geolocation data to understand political trends and behaviors. This includes analyzing data on where political events and activities are taking place, where voters are located, and how different geographic areas are voting or engaging with political campaigns.
We use Geo location intelligence to:
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Target voters: By analyzing location-based data, political campaigns can target specific groups of voters based on their location and the issues that matter most to them.
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Understand voting patterns: By analyzing how different geographic areas are voting, political campaigns can identify trends and tailor their messaging to appeal to specific regions or demographics.
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Plan events: we plan events and rallies in areas where there is high voter engagement or where the campaign needs to build support.
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Monitor and respond to political events: By monitoring social media and other sources of location-based data, political campaigns can quickly identify and respond to emerging trends and events.
Geolocation intelligence is a valuable tool for political campaigns looking to engage voters and understand political trends. By analyzing location-based data, campaigns can better target their messaging and resources, and respond quickly to emerging events and trends.
We identify, remove, or transform irrelevant or redundant data from a dataset to improve its quality, accuracy, and usefulness. Data filtration is a critical step in data preparation and analysis as it helps to ensure that the data being used is relevant, accurate, and complete.
Our data filtration process typically involves the following steps:
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Defining of the objective: we first define the objective of the data filtration process. This involves identifying the specific data attributes that need to be filtered, and the criteria for determining what data is relevant or irrelevant.
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Collect and clean the data: Data is collected from various sources, cleaned and transformed into a format suitable for analysis.
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Analyze the data: The data is then analyzed to identify patterns, trends, and other insights.
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Identify irrelevant or redundant data: Based on the objective of the analysis, irrelevant or redundant data is identified and tagged for removal.
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Remove of the data: The identified data is then removed from the dataset
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Validate the filtered data: Finally, the filtered data is validated to ensure that the filtration process has not introduced any errors or biases into the dataset.
Deeper understanding comes with in depth intelligence
Merely looking at tip of the iceberg may not provide the entire picture. It is the relevant and accurate portrayal that provides the complete outlook.