How high is the brand awareness of Match in the U.S.?When it comes to online dating users, brand awareness of Match is at ** percent in the U.S. The survey was conducted using the concept of aided brand recognition, showing respondents both the brand's logo and the written brand name.How popular is Match in the U.S.?In total, ** percent of U.S. dating service users say they like Match.What is the usage share of Match in the U.S.?All in all, ** percent of dating service users in the U.S. use Match.How loyal are the users of Match?Around ** percent of dating service users in the U.S. say they are likely to use Match again.What's the buzz around Match in the U.S.?In September 2024, about ** percent of U.S. dating service users had heard about Match in the media, on social media, or in advertising over the past three months.

This dataset shows the information on the program that supports the growth of early stage life science companies in Montgomery County. Grants provide financial assistance to life sciences employers to retain jobs and stimulate the organic growth of the life sciences industry. The Council enacted Bill 37-19 on 3/16/ 2021, effective 6/24/2021. A portion of the Bill changes the eligibility requirements for the SBIR/STTR Local Matching Grant Program, no longer restricting eligibility to NIH grant recipients, but requiring that the grant received from a Federal agency is for research in medicine, biotechnology or life sciences. The SBIR/STTR Local Matching Grant Program has a sunset date of July 1, 2025. The County’s SBIR/STTR Local Matching Grant Program allows Montgomery County companies that have at least 51% of their research & development operations in Montgomery County to apply for a County match to a Phase I or Phase II SBIR or STTR grant from the federal agency. Companies that received a Phase 1 SBIR or STTR grant may receive a County match of 25% of the grant amount, up to a maximum of $25,000. Companies that received a Phase II SBIR or STTR grant may receive match of 25% of the grant, up to a maximum of $75,000. Companies are eligible to receive a local match once per calendar year, up to a total of five grant awards

How high is the brand awareness of Match in the UK?When it comes to online dating users, brand awareness of Match is at ** percent in the UK. The survey was conducted using the concept of aided brand recognition, showing respondents both the brand's logo and the written brand name.How popular is Match in the UK?In total, ** percent of UK dating service users say they like Match.What is the usage share of Match in the UK?All in all, ** percent of dating service users in the UK use Match.How loyal are the users of Match?Around ** percent of dating service users in the UK say they are likely to use Match again. Set in relation to the ** percent usage share of the brand, this means that ** percent of their users show loyalty to the brand.What's the buzz around Match in the UK?In November 2023, about ** percent of UK dating service users had heard about Match in the media, on social media, or in advertising over the past three months.

This dataset is about books. It has 1 row and is filtered where the book is Matching software applications to business needs. It features 7 columns including author, publication date, language, and book publisher.

Factori's Company API empowers users to navigate the business landscape effortlessly. Simply input criteria such as industry, location, or other relevant parameters and retrieve matching company IDs and names. Discover companies that meet your requirements, gain valuable insights, and make informed decisions.

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Dataset

This dataset was created by Ricky Ng

Contents

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

BackgroundTo the extent that outcomes are mediated through negative perceptions of generics (the nocebo effect), observational studies comparing brand-name and generic drugs are susceptible to bias favoring the brand-name drugs. We used authorized generic (AG) products, which are identical in composition and appearance to brand-name products but are marketed as generics, as a control group to address this bias in an evaluation aiming to compare the effectiveness of generic versus brand medications.Methods and findingsFor commercial health insurance enrollees from the US, administrative claims data were derived from 2 databases: (1) Optum Clinformatics Data Mart (years: 2004–2013) and (2) Truven MarketScan (years: 2003–2015). For a total of 8 drug products, the following groups were compared using a cohort study design: (1) patients switching from brand-name products to AGs versus generics, and patients initiating treatment with AGs versus generics, where AG use proxied brand-name use, addressing negative perception bias, and (2) patients initiating generic versus brand-name products (bias-prone direct comparison) and patients initiating AG versus brand-name products (negative control). Using Cox proportional hazards regression after 1:1 propensity-score matching, we compared a composite cardiovascular endpoint (for amlodipine, amlodipine-benazepril, and quinapril), non-vertebral fracture (for alendronate and calcitonin), psychiatric hospitalization rate (for sertraline and escitalopram), and insulin initiation (for glipizide) between the groups. Inverse variance meta-analytic methods were used to pool adjusted hazard ratios (HRs) for each comparison between the 2 databases. Across 8 products, 2,264,774 matched pairs of patients were included in the comparisons of AGs versus generics. A majority (12 out of 16) of the clinical endpoint estimates showed similar outcomes between AGs and generics. Among the other 4 estimates that did have significantly different outcomes, 3 suggested improved outcomes with generics and 1 favored AGs (patients switching from amlodipine brand-name: HR [95% CI] 0.92 [0.88–0.97]). The comparison between generic and brand-name initiators involved 1,313,161 matched pairs, and no differences in outcomes were noted for alendronate, calcitonin, glipizide, or quinapril. We observed a lower risk of the composite cardiovascular endpoint with generics versus brand-name products for amlodipine and amlodipine-benazepril (HR [95% CI]: 0.91 [0.84–0.99] and 0.84 [0.76–0.94], respectively). For escitalopram and sertraline, we observed higher rates of psychiatric hospitalizations with generics (HR [95% CI]: 1.05 [1.01–1.10] and 1.07 [1.01–1.14], respectively). The negative control comparisons also indicated potentially higher rates of similar magnitude with AG compared to brand-name initiation for escitalopram and sertraline (HR [95% CI]: 1.06 [0.98–1.13] and 1.11 [1.05–1.18], respectively), suggesting that the differences observed between brand and generic users in these outcomes are likely explained by either residual confounding or generic perception bias. Limitations of this study include potential residual confounding due to the unavailability of certain clinical parameters in administrative claims data and the inability to evaluate surrogate outcomes, such as immediate changes in blood pressure, upon switching from brand products to generics.ConclusionsIn this study, we observed that use of generics was associated with comparable clinical outcomes to use of brand-name products. These results could help in promoting educational interventions aimed at increasing patient and provider confidence in the ability of generic medicines to manage chronic diseases.

67 Global import shipment records of Matching Bottom with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

Outcome incidence rates for patients initiating authorized generics (AGs) versus generics, and patients switching from brand-name products to AGs versus generics, after 1:1 propensity score matching in each database.

The global color matching software market is experiencing robust growth, driven by increasing demand across diverse industries. The market's expansion is fueled by several key factors, including the rising adoption of digital printing technologies, the growing need for precise color consistency in manufacturing processes, and the increasing complexity of color management in various applications like textiles, packaging, and automotive industries. Furthermore, advancements in software capabilities, such as improved color algorithms and enhanced user interfaces, are contributing to market growth. The competitive landscape is characterized by a mix of established players and emerging technology providers, each offering specialized solutions to cater to different market segments. While accurate market sizing requires comprehensive data, a reasonable estimate based on industry trends suggests a market valued at approximately $500 million in 2025, exhibiting a Compound Annual Growth Rate (CAGR) of around 8% over the forecast period (2025-2033). This growth is projected to continue, propelled by the ongoing integration of color matching software into various workflows, leading to increased efficiency and reduced waste. Despite the positive outlook, several factors could potentially restrain market growth. These include high initial software investment costs, the need for specialized training and expertise for effective utilization, and the potential for variations in color perception across different devices and displays. However, the increasing awareness of the crucial role of accurate color management in brand consistency and overall product quality is expected to outweigh these constraints. The market segmentation is likely diverse, encompassing solutions tailored for specific industries and applications, ranging from basic color matching tools to sophisticated systems integrated into broader color management workflows. Key players such as CHN Spec, 3nh, X-Rite, EIZO, Datacolor, Palette Technology, Shenzhen Peak of Science and Technology, and Iscolor are actively shaping the market dynamics through continuous innovation and strategic partnerships. The geographical distribution is likely widespread, with North America and Europe representing significant market shares, followed by growth in the Asia-Pacific region due to the expanding manufacturing base.

Comprehensive dataset of 16 Match box manufacturers in United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Computer Color Matching System Market Outlook

The global computer color matching system market size was valued at USD 1.2 billion in 2023 and is projected to reach USD 2.8 billion by 2032, growing at a compound annual growth rate (CAGR) of approximately 10%. This robust growth can be attributed to rising demand across various industries for precise color matching, driven by technological advancements and increasing consumer expectation for product quality and aesthetic appeal. The trend towards digitalization and automation in manufacturing and design processes further fuels the adoption of computer color matching systems, making them indispensable for achieving accuracy and efficiency.

A significant growth factor for the computer color matching system market is the escalating demand from the textile and automotive industries. These sectors require precise color matching to ensure consistency and quality in their products, which is critical for maintaining brand reputation and customer satisfaction. Moreover, advancements in software capabilities have significantly enhanced the accuracy and speed of color matching processes, making these systems more accessible and useful across different segments. Additionally, the reduction in costs associated with color mismatches and the subsequent wastage has prompted more industries to invest in these systems.

Another pivotal factor driving market growth is the increasing adoption of digital printing technologies. The shift from traditional printing to digital printing has necessitated the need for advanced color matching systems to maintain color fidelity and match the digital designs with the final print outputs. This is particularly critical in industries such as packaging and labeling, where brand colors are essential for product recognition and consumer trust. The continued rise of e-commerce and the subsequent demand for high-quality packaging also bolster the market for computer color matching systems.

The rise in environmental awareness and the push towards sustainable manufacturing practices have also influenced the demand for computer color matching systems. These systems enable more efficient use of dyes, pigments, and other coloring agents, thereby reducing waste and minimizing the environmental impact. They also facilitate the adoption of safer and more sustainable colorants, aligning with the global trend towards eco-friendly products. Furthermore, stringent regulations regarding product quality and safety in different regions necessitate the use of accurate and reliable color matching systems, further driving market growth.

Regionally, the Asia Pacific is expected to lead the market growth, driven by the rapid industrialization and expansion of the manufacturing sector in countries such as China, India, and Japan. North America and Europe also hold significant market shares, supported by technological advancements and the presence of key industry players. The Middle East & Africa and Latin America regions are anticipated to witness steady growth, primarily due to the increasing penetration of these systems in emerging economies and the growing demand for high-quality consumer goods.

In the realm of color matching, Material Color Matching Assessment Light Cabinets play a pivotal role. These specialized cabinets are designed to provide consistent lighting conditions, which are crucial for accurate color assessment. By simulating various lighting environments, these cabinets help in identifying color discrepancies that might not be visible under standard lighting. This is particularly important in industries like textiles and automotive, where precise color matching is essential for quality control and brand consistency. The use of such cabinets ensures that the colors remain true to their intended design, thereby reducing the risk of mismatches and enhancing overall product quality.

Component Analysis

The computer color matching system market by component can be segmented into software, hardware, and services. Each of these segments plays a critical role in the overall functionality and effectiveness of color matching systems. The software segment is particularly essential as it involves the algorithms and databases that enable precise color matching. These software solutions have evolved significantly, offering advanced features such as artificial intelligence and machine learning to enhance accuracy and efficiency. The continuous development in this are

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2021-05-10 PSM vs Entropy matching published at the "Open Code Community"

The global market for color evaluation and matching cabinets is experiencing robust growth, driven by increasing demand across diverse industries. The rising adoption of color management systems in sectors like coatings, printing, and cosmetics is a significant factor. Precise color matching is critical for maintaining brand consistency and product quality, fueling the demand for sophisticated color evaluation cabinets. Technological advancements, such as the integration of spectrophotometers and improved software for data analysis, are enhancing the accuracy and efficiency of these cabinets, further driving market expansion. While the precise market size in 2025 is unavailable, a logical estimation based on available data and industry trends suggests a market value of approximately $500 million, considering the various applications and regional distributions. The market is segmented into basic color evaluation cabinets and high-precision color matching cabinets, with the latter segment commanding a premium due to its advanced features and higher accuracy. Growth is further stimulated by the expanding e-commerce sector, necessitating accurate color reproduction across online platforms. However, the high initial investment cost for high-precision cabinets and the availability of alternative, albeit less precise, methods can act as restraints on market penetration. The geographical distribution of the market showcases strong growth in North America and Europe, driven by established industries and a strong focus on quality control. However, rapidly developing economies in Asia-Pacific, particularly China and India, are emerging as significant growth markets. These regions are witnessing rapid industrialization and increased adoption of advanced color management technologies. The competitive landscape comprises both established players and emerging companies, indicating a dynamic and evolving market. Future growth will be influenced by technological innovations in color measurement, the development of user-friendly software, and increasing regulatory compliance requirements in various industries related to color accuracy. This is expected to lead to a Compound Annual Growth Rate (CAGR) of approximately 8% between 2025 and 2033, significantly expanding the market by 2033 to an estimated $1.1 billion.

Comprehensive dataset of 0 Match box manufacturers in Finland as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Salutary Data is a boutique, B2B contact and company data provider that's committed to delivering high quality data for sales intelligence, lead generation, marketing, recruiting / HR, identity resolution, and ML / AI. Our database currently consists of 148MM+ highly curated B2B Contacts ( US only), along with over 4M+ companies, and is updated regularly to ensure we have the most up-to-date information.

We can enrich your in-house data ( CRM Enrichment, Lead Enrichment, etc.) and provide you with a custom dataset ( such as a lead list) tailored to your target audience specifications and data use-case. We also support large-scale data licensing to software providers and agencies that intend to redistribute our data to their customers and end-users.

What makes Salutary unique? - We offer our clients a truly unique, one-stop aggregation of the best-of-breed quality data sources. Our supplier network consists of numerous, established high quality suppliers that are rigorously vetted. - We leverage third party verification vendors to ensure phone numbers and emails are accurate and connect to the right person. Additionally, we deploy automated and manual verification techniques to ensure we have the latest job information for contacts. - We're reasonably priced and easy to work with.

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Services: Data Enrichment - We assess the fill rate gaps and profile your customer file for the purpose of appending fields, updating information, and/or rendering net new “look alike” prospects for your campaigns. ABM Match & Append - Send us your domain or other company related files, and we’ll match your Account Based Marketing targets and provide you with B2B contacts to campaign. Optionally throw in your suppression file to avoid any redundant records. Verification (“Cleaning/Hygiene”) Services - Address the 2% per month aging issue on contact records! We will identify duplicate records, contacts no longer at the company, rid your email hard bounces, and update/replace titles or phones. This is right up our alley and levers our existing internal and external processes and systems.

Matching grants are one of the most common types of private sector development programs used in developing countries. Matching grants consist of partial subsidies, typically 50 percent, provided by government programs to try to spur firms to undertake innovative activities. This study is a randomized experiment testing the impact of matching grants for business development services in the Republic of Yemen. The program provided firms with a matching grant of up to $10,000 as a 50 percent subsidy towards the cost of business services like finance and accounting systems, website creation, training, marketing, participation in exhibitions, and some associated goods such as office and IT equipment. The program was intended to run in two annual rounds, aimed to provide grants for business development services to 400 enterprises, 200 in each of two years. The program was launched in August 2013 and widely advertised through a 45-day campaign. Firms applied between October 1, 2013 and December 26, 2013. The first year of the program took place in 2014, but due to civil conflict outbreak in late March and early April 2015, the second year of the program was cancelled. The dataset documented here is based on the first round.

The “Company ID Linktables” dataset comprises ID linkage tables for the datasets BVD, MiDi, URS, USTAN,JANIS, BAKIS-M, LEI, RIAD (AnaCredit), SIFCT, SITS, and Schufa. The individual ID linkage tables are two-column tables containing a different company identifier in each column, resulting in a table of ID value pairs, showing which ID values of the two IDs refer to the same real-world company entity. The need for these ID linkage tables originates from the fact that company data is often held in separate databases, which use different company identifiers. The tables are produced by the RDSC through the use of current record linkage techniques, which,among other methods, include comprehensive data cleaning, matching based on common externalIDs, as well as name and place based matching, which includes probabilisic matching using supervisedmachine learning. The technical properties of this record linkage process are described by Gábor-Tóth, E., Schild, C., and Walter, S. (2023). Linking Deutsche Bundesbank Company Data. Technical Report 2023-05. Deutsche Bundesbank, Research Data and Service Centre. The size of the generated data overlaps / intersections is analyzed by Gábor-Tóth, E., Schild, C., and Walter, S. (2023). Understanding Overlaps betweenDifferent Company Data. Technical Report 2023-06. Deutsche Bundesbank, Research Data andService Centre.