Enabling Critical Decision-Making with Valuable Data Insights from Melissa Marketplace

By: Hristo Hristov   |   Updated: 2024-10-21   |   Comments   |   Related: > Data Cleansing for Validation

Problem

Are you always looking for quality data to serve as the basis for your decision making? Do you struggle to find consistent, up-to-date, and validated real-life data to plug into your business application or process? You are not alone. At any given moment, thousands of business owners and employees stare at an incomplete picture drawn with a lack of data or low-quality data.

Solution

The data quality and validation specialists at Melissa have recently introduced the Melissa Marketplace—a rich data catalog comprised of exceptionally accurate data products for your industry and business needs. It's as easy as:

1. Researching/locating the relevant data
2. Requesting the required data product
3. Consulting an overview page that describes how to access and use the data

Melissa also offers several accessibility options:

• Via an API
• A one-time file
• A subscription agreement
• An integrated service application

Let us examine several scenarios where the Melissa Marketplace truly shines. After reviewing these scenarios, more ways can be imagined to leverage this extensive data catalog and harvest the many opportunities it offers for data quality and validation services.

Industry-based Use Cases

Real Estate

Melissa fully encompasses the real estate domain with highly curated proprietary datasets. One or a combination of these datasets can be leveraged to gain deep insights along several vectors of interest. For example, the home equity distribution and change over time, real estate home ownership evolution, and the profile of the typical homeowner for a given area can be explored. Additionally, the appearance of new construction or foreclosure dynamics can also be tracked. Below is a non-comprehensive list of real estate scenarios:

Healthcare and Medical

Healthcare and medical domains are also areas where high-quality data is of the utmost importance. Here, Melissa provides another set of helpful and always available quality datasets. For example, we can get a map of the different healthcare professionals for a given area. For the more marketing-driven professionals, we can also propose plotting the business profile of businesses concentrated in the healthcare and medical fields in a local area. Below is a quick list, along with links, to the data products:

ERP and CRM and Line of Business Applications

Regarding client and vendor data, you want to ensure that entities are correctly represented in the business applications. ERP, CRM, and other line-of-business applications that manage client or vendor data are suitable programs to leverage the Melissa Marketplace. Under any circumstance, operating with high-quality, verified data is a stepping stone for a successful business relationship. The rich API integration options the Melissa Marketplace offers add a great deal of trust to the business relationship. Here are a few pointers in that area:

Government

Finally, the Melissa Marketplace provides options to leverage data insights for a more detailed picture using government-curated data. An example of this would be plotting the profile of registered voters in a given area. Melissa can facilitate reaching out or getting a list of users who regularly donate to cultural, environmental, or political causes. Comprehensive data profiles are available to be explored via an integration service or visualized with a BI tool. Furthermore, Melissa has an accurate and comprehensive list of the NAICS/SIC code nomenclature exposed as a service. With Melissa's dedicated service, companies can be accurately classified across 20 sectors, 99 subsectors, and 312 industry groups. Here is a list of related data products:

Demo Reports

To highlight the power of some of the datasets available on Melissa Marketplace, several example reports have been built to visualize important aspects of the real estate market and trends in Orange County (OC), California.

New Construction Units

Using the new construction dataset from Melissa Marketplace, we can see an overview of how new construction evolves in Orange County, California, using the image below. In Section 1, we were able to plot a map displaying the number of newly constructed units by city, along with an indicator classifying the unit (residential or other). Section 2 provides a breakdown of the non-residential versus residential number of newly constructed units by the biggest cities in OC as a percentage. Here, we see Newport Beach leads in non-residential, newly constructed units. Finally, Section 3 highlights the price evolution per property type depending on the year it was built. It is interesting to see the significant dips in total sales for the years 2008 and 2020 corresponding to major market events.

New Homeowners

In addition to the new construction analysis, we can also take a detailed look at the new homeowner dynamics in OC, as seen in the image below. Melissa defines a new homeowner as someone who recently acquired and moved to a property. Section 1 displays a map of new homeowners by city. The bar chart provided in Section 2 displays their numbers. The dataset contains a field for the sell date, where a slicer is provided in Section 3 and can be used to filter to a specific period. Finally, Section 4 illustrates an area chart of the new homeowners by year.

Property Price Analysis

The picture would not be complete without a closer look at the price aspects of properties in OC. Section 1 in the image below shows bubbles on the map indicating the average sales price per city. (Note: The major cities have been prefiltered to make the plot more focused.) On the right, Section 2 provides a column chart comparing the average number of baths and bedrooms per city while plotting the average sales price on the secondary y-axis. As a result, we can see how the areas chosen (Fullerton, Irvine, Aliso Viejo, and Santa Ana) compare. For example, a buyer will get more bedrooms in Fullerton at lower sales prices than those in Irvine.

Business Overview

How about the types of businesses in Orange County? There is a dedicated dataset for that topic in the Melissa Marketplace, as well. For example, we can examine the business type distribution by SIC code by city in Section 1 of the image below. Additionally, the tree map plot in Section 2 provides a more detailed overview of the five pre-selected business types: Physicians, Attorneys, Real estate, Accountants, and Restaurants. Section 3 allows for slicing and filtering by city.

Inquire about how to access and use the datasets behind these plots by contacting Melissa.

Summary

Someone once said, "Data is the new gold." Would you be willing to dig for gold on your own? Probably not. But from a verified vendor? Absolutely!

Melissa aims to fulfill the "gold-standard” data promise. Check out the verified, accurate, and curated data available at Melissa Marketplace via the various endpoints and service applications to enhance your business app, process, or decision-making.

Next Steps

• Melissa Marketplace
• Melissa New Homeowners Lists
• Melissa Property Owners List
• Melissa Data Quality Solutions for SSIS
• Trusted Data & AI for Clinical Insight & Discovery

About the author

Hristo Hristov is a Data Scientist and Power Platform engineer with more than 12 years of experience. Between 2009 and 2016 he was a web engineering consultant working on projects for local and international clients. Since 2017, he has been working for Atlas Copco Airpower in Flanders, Belgium where he has tackled successfully multiple end-to-end digital transformation challenges. His focus is delivering advanced solutions in the analytics domain with predominantly Azure cloud technologies and Python. Hristo's real passion is predictive analytics and statistical analysis. He holds a masters degree in Data Science and multiple Microsoft certifications covering SQL Server, Power BI, Azure Data Factory and related technologies.

This author pledges the content of this article is based on professional experience and not AI generated.

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