Creating simplified data sets from complex analytical information to help our clients make better informed decisions

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Customer profiles are generated from targeted hyper-local data sets.
Ultimately, this site is designed to define aspects of local life within real estate,
retail and automotive traffic patterns and population concentrations.


Real estate data of a given targeted hyperlocal market represents a robust component in creating tabulated data sets that can spawn analysis of potential trends in that market.

These trends can include investment opportunities and asset pricing parameters from outside investors in the community, locations of new businesses and expansion of existing ones coupled with localized  housing expansions of single family as well as multi unit buildings and local real estate agents can use this raw data to assimilate competitive price points for investment.

Rents and customer and automotive traffic flow statistics in a given market are also key in assessing the viability and discretionary income potential of a given market to future expansion via these tabulated statistics. It also lends itself to pitching bank products and services thru embedded finance indigenously created data fueled local environments.


Retail, defined as the sum total of  establishments that support critical lifestyle needs & services is a key benchmark in assessing the economic lifeblood of a given hyperlocal community.

The intersection of property values infused with the business profile of a given community as determined by the business mix that has developed over time to service the areas primary “needs” creates a data set that can be used as a foundation to assess the indigenous wealth and growth potential of any given community. It also establishes the social personality of a given area, something we have witnessed that changes from town to town, either by ethnic or community tradition.

This identity, fueled by the proper datasets, provides a roadmap that can be used to evaluate the fiscal health of any given community as how a bank or financial institution can pitch products and services most effectively via embedded finance options.


Traffic is a key component to assessing the growth potential of a given hyperlocal market.

Whether the data is derived from pedestrian crosswalk sensors or traffic light auto  trackers or discretionary purchase concentrations, population movement in a given area leaves a data foundation by which to project property expansions (defined as housing and commercial) and potential business development to support that growth.

From a banking standpoint, it targets embedded finance markets within that particular community to develop in those data sets and sales pitches more effectively