Success.ai’s UK SME Database gives your business a powerful edge in reaching verified small and medium-sized companies across the United Kingdom. Whether you’re selling business services, SaaS, finance tools, or logistics solutions—this dataset offers direct access to growth-stage companies that are ready to buy.

With rich company data and verified contact info for founders, directors, and operational managers, you’ll have everything needed to identify, engage, and convert high-potential UK SMEs.

Included Data Points:
- Company name and domain
- Business category and industry
- Company size (employee range)
- Location (city, postcode, region)
- Contact name, job title, email, LinkedIn

Why Success.ai?
- Covers 2.5M+ UK small and mid-sized businesses
- Verified data for owners, directors, and decision-makers
- Great for outreach in services, SaaS, HR, and legal sectors
- Curated for accuracy and delivered your way
- Best Price Guarantee – always competitive, always complete

Use Cases:
- B2B sales outreach to UK growth companies
- Local ABM for regional campaigns
- Market expansion for service providers
- SME-focused research and segmentation
- Email marketing and CRM enrichment

Access 2.5 million verified UK small and medium-sized business profiles with decision-maker contacts and firmographics. Ideal for B2B sales and market expansion. Best Price Guarantee.

The SME data warehouse is based on existing administrative data sources from Statistics Canada and Canada Revenue Agency. Data covers tax year 2001 to tax year 2006. The SME Data Warehouse contains a complete, up to date and unduplicated list of all businesses in Canada based on Statistics Canada's Business Register for tax years 2001-2006. This product currently produces data for Small and Medium Sized Enterprises (SMEs). SMEs are defined as enterprises with less than 250 employees and less than $50 million in total revenue.

Success.ai’s UK SME Dataset gives you unmatched access to 2 million small and medium-sized enterprises across England, Scotland, Wales, and Northern Ireland.

Whether you’re targeting small business owners or departmental heads in growing firms, this dataset provides structured and verified company records for precise targeting.

Built for B2B sales, marketing, investment prospecting, and market research, each dataset includes detailed firmographics, ownership structure, and (optional) verified contact data for C-level or decision-making staff.

What You’ll Get:
- Company name, domain, and LinkedIn URL
- Headcount and revenue range
- Region, country, postal code
- SIC/NAICS codes or industry categories
- Contact info (owner, founder, CMO, etc. – optional)

Why Success.ai?
- 2M+ updated SME records in the UK alone
- Segment by geography, sector, or company size
- Perfect for SMB-focused B2B vendors and service providers
- Best Price Guarantee for small business data
- GDPR-ready datasets for peace of mind

Use Cases:
- Small business marketing campaigns
- B2B CRM data enrichment
- Investor scouting and growth tracking
- Local ABM by city or region
- Lead generation for SME-focused SaaS and fintech tools

Explore 2M+ verified UK SMEs with rich company data: size, domain, industry, contacts & more. Ideal for marketing, research, and B2B targeting. GDPR-compliant. Best Price Guarantee

Abstract copyright UK Data Service and data collection copyright owner. The proposed objectives for the study were to explore the use and barriers to use of electronic commerce by small and medium-sized enterprises (SMEs) in Great Britain. By means of a postal questionnaire, the study sought to understand: which SMEs are using electronic commerce (e-commerce) applications and for what business activities? What benefits they are reaping - are these consistent with those forecast for larger corporations or can SMEs gain unique advantages from adopting e-commerce? What are the challenges faced in developing and adopting such services - what are the key success factors for SMEs achieving business benefits from e-commerce? In particular, it was intended that the research would demonstrate the following: the characteristics and incidence of SMEs adopting e-commerce; the business applications it is being used for in those companies; the benefits and challenges of e-commerce adoption; best practice for deployment of e-commerce. Main Topics: The dataset contains responses to the postal questionnaire, and is available from the UKDA in either Excel or SPSS format. Each case is identified by a unique respondent number. Variables are numbered according to the question order on the questionnaire, e.g. Q1P2P1 contains the responses to Question 1, Part 2, item 1. Topics covered include use of e-commerce, factors driving consideration/use of e-commerce, exactly which activities it is used for, company information systems, benefits and challenges of e-commerce, and background information. The database contains two separate samples: 1. A database of SMEs held internally at Cranfield School of Management (variable Database = 1.00) was used. This contains companies that have attended, or made enquiries about, an executive education programme aimed at SMEs. 2. Names and company addresses were bought from a commercial database company (Database = 2.00). Companies were chosen from their records on the basis that they had 250 employees or less. All data have been anonymised to protect respondent confidentiality.

In 2022, there were more than eight million small and medium-sized enterprises (SMEs) in South Korea, up from about *** million in the previous year. The number of SMEs has increased steadily in recent years, particularly in wholesale and retail trade and the information and communications technology (ICT) sector. More than half of the SMEs were located in the metropolitan area of Seoul, Incheon, and Gyeonggi Province (also known collectively as Sudogwon). Classification of SMEs in South Korea South Korean SMEs comprise micro, small, and medium-sized enterprises. Each is classified by revenue rather than by the number of employees, which is the case in many other countries. According to this definition, SMEs are for-profit companies and, in some cases, social enterprises and cooperatives whose total assets do not exceed *** billion South Korean won. In addition, they should not be a subsidiary of a large company.Companies are classified as SMEs depending on their average three-year revenue, with different thresholds depending on the industry. For real estate companies, the threshold is ** billion won or less, whereas, for some sectors of the manufacturing industry, *** billion won or less would be the standard to be categorized as an SME. Domestic SME employment SMEs in South Korea account for about **** percent of all enterprises and have always been a crucial source of job creation. The number of people employed by SMEs in South Korea amounted to about **** million in 2020, accounting for more than ** percent of the country’s total workforce. Most workers were employed in wholesale and retail SMEs, followed by SMEs operating in the manufacturing sector.

Underlying data from the publication 'Research to understand the barriers to take up and use of business support' [URN 11/1288]. Data from a survey of 1,202 employer SMEs in England undertaken in March 2011. The survey was designed to provide statistically robust evidence of business use and non use of external business support services, differentiating between private sector and public sector sources of both routine information and strategic advice. The survey aimed to produce a broadly representative sample of SME employers and used a random stratified sample from the Experian database adopting quotas in order to capture sufficient numbers of businesses across key categories (age, size, sector, region). The data presented in the published report was weighted by size band to correct for over-sampling amongst larger SMEs.

Data collected as part of the City of Melbourne's Census of Land Use and Employment (CLUE). The data covers the period 2002-2023. It shows number of jobs and number of business establishments by business size, classified by their CLUE industry, ANZSIC1 and CLUE small area allocation. Business size is determined by the total number of jobs at ech business establishment and is categorised as follows: Non employing, no jobs allocated to the establishment.Small business, 1 to 19 jobs employed at a business establishment.Medium business, 20 to 199 jobs employed at a business establishment.Larger business, 200 or more jobs employed at a business establishment. This dataset has been confidentialised to protect the commercially sensitive information of individual businesses. Data in cells which pertain to two or fewer businesses have been suppressed and are shown as a blank cell. The 'City of Melbourne' row totals refer to the true total, including those suppressed cells.Non-confidentialised data may be made available subject to a data supply agreement. For more information contact cityfacts@melbourne.vic.gov.auFor CLUE small area spatial files see https://data.melbourne.vic.gov.au/explore/dataset/small-areas-for-census-of-land-use-and-employment-clue/mapFor more information about CLUE see http://www.melbourne.vic.gov.au/clueFor more information about the ANZSIC industry classification system see http://www.abs.gov.au/ausstats/abs@.nsf/mf/1292.0

Open Source Database Market Outlook

The global open source database market size was valued at approximately USD 15.5 billion in 2023 and is projected to reach around USD 40.6 billion by 2032, expanding at a compound annual growth rate (CAGR) of 11.5% during the forecast period. The growth of this market is primarily driven by the increasing adoption of open-source databases by both SMEs and large enterprises due to their cost-effectiveness and flexibility.

A significant growth factor for the open source database market is the rising demand for data analytics and business intelligence across various industries. Organizations are increasingly leveraging big data to gain actionable insights, enhance decision-making processes, and improve operational efficiency. Open source databases provide the scalability and performance required to handle large volumes of data, making them an attractive option for businesses looking to maximize their data-driven strategies. Additionally, the continuous advancements and contributions from the open-source community help in keeping these databases at the cutting edge of technology.

Another driving factor is the cost-efficiency associated with open-source databases. Unlike proprietary databases, which can be expensive due to licensing fees, open-source databases are usually free to use, offering a significant cost advantage. This factor is especially crucial for small and medium enterprises (SMEs), which often operate with limited budgets. The lower total cost of ownership, combined with the flexibility to customize the database according to specific needs, makes open-source solutions highly appealing for businesses of all sizes.

The increasing trend of digital transformation is also playing a crucial role in the growth of the open source database market. As businesses across various sectors accelerate their digital initiatives, the need for robust, scalable, and efficient data management solutions becomes paramount. Open-source databases provide the agility and innovation that organizations require to keep up with the rapidly changing digital landscape. Moreover, the support for cloud deployment further enhances their appeal, providing businesses with the scalability and flexibility needed to adapt to evolving technological demands.

From a regional perspective, North America holds a significant share in the open source database market, driven by the presence of major technology companies and a highly developed IT infrastructure. The region's focus on technological innovation and early adoption of advanced technologies contributes to its dominant position. Europe follows closely, with increasing investments in digital transformation initiatives. The Asia Pacific region is expected to witness the highest growth rate during the forecast period, fueled by rapid technological advancements, a burgeoning IT sector, and increased adoption of open-source solutions by businesses.

Relational Databases Software plays a crucial role in the open-source database market, offering structured data management solutions that are essential for various business applications. These databases are known for their ability to handle complex queries and transactions, making them ideal for industries that require high levels of data integrity and consistency. The flexibility and robustness of relational databases software allow organizations to efficiently manage large volumes of structured data, which is critical for applications such as financial systems, enterprise resource planning, and customer relationship management. As businesses continue to prioritize data-driven decision-making, the demand for relational databases software is expected to grow, further driving the expansion of the open-source database market.

Database Type Analysis

The open source database market is segmented into SQL, NoSQL, and NewSQL databases. SQL databases are the most widely used and have been the backbone of data management for decades. They offer robust transaction management and are ideal for structured data storage and retrieval. The ongoing improvements in SQL databases, such as enhanced performance and security features, continue to make them a preferred choice for many organizations. Additionally, the availability of various SQL-based open-source solutions like MySQL, PostgreSQL, and MariaDB provides organizations with reliable options to manage their data effectively.

NoSQL databases are gainin

The Small Business Survey (SBS) is a large scale telephone survey commissioned by the Department for Business, Innovation and Skills (BIS) as a follow up to the Annual Survey of Small Businesses 2007/8. The main aims of the first SBS survey in 2010 were to:

• monitor key enterprise indicators (e.g. employment, turnover, finance, business growth) and how these have changed in comparison to previous surveys. In particular the survey measures characteristics of Small and Medium-sized Enterprises (SME) such as the proportions which are women and minority-ethnic led, and the proportions applying for and obtaining external finance


• gauge SME intentions, needs, concerns and the obstacles to fulfilling their potential
• provide evidence for possible Government interventions to assist SMEs
• create a database which can be used for follow-up studies among the general SME population, or sub-groups within it

The main aims of the next survey in 2012 were to:

• monitor key enterprise indicators and how these have changed in comparison to previous surveys, the 2010 SBS in particular
• create a database that can be used for follow-up studies among the general SME population, and sub-groups within it.

From 2015, the survey methodology has changed to include a longitudinal tracking element. The Longitudinal Small Business Survey: Secure Access is available under SN 8261.

Linking to other business studies
These data contain Inter-Departmental Business Register reference numbers. These are anonymous but unique reference numbers assigned to business organisations. Their inclusion allows researchers to combine different business survey sources together. Researchers may consider applying for other business data to assist their research.

The second edition (August 2014) includes data from 2012.

This data publication contains SME climate data for more than 200,000 firms across Germany, Austria, Netherlands, France, and Spain. The methodology and software behind the data were developed under the project CB-PASTAX within the programme tilt. The data are created using webscraped company-data and links them on product-level to climate databases such as Life-Cycle-Assessment (LCA) data and climate scenario data to derive three climate indicators (relative emission indicator, sector decarbonisation indicator, transition risk indicator) on product- and company-level. The data can be used to analyse the climate profile of SMEs across various regions and sectors. This version published on Zenodo contains an anonymised dataset, which means that the company names as well as the original product names are faked. The sector classification as well as the data we match from climate databases still gives an indication of the products. Real company and product names can be requested.

For more information on the methodology behind the data and on how to use them, please refer to the project website with a link to the online portal where you will find extensive documentation: https://www.tiltsmes.org/tilt-under-the-cb-pastax-grant. The code developed to create the data is published open source on GitHub. You can find an overview here: https://2degreesinvesting.github.io/tilt/.

This project is co-funded by the European Union under Grant No. LIFE20 GIC/DE/001765, recognised under the CB-PASTAX programme. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or CINEA. Neither the European Union nor the granting authority can be held responsible for them.

Abstract copyright UK Data Service and data collection copyright owner. The main objective of the research project was to create a longitudinal panel database of SME data relating to a wide range of non-financial and attitudinal characteristics, and a limited number of financial variables not normally available in modified company accounts, from a national postal survey. This database forms the beginning of the second panel - the first panel was started in 1991. A postal survey was sent to over 10,000 independent small and medium-sized enterprises (SMEs) in the manufacturing and business services sectors in England, Scotland and Wales. Just over half (5,430) the firms were telephoned prior to being sent the questionnaire, and 4,640 firms were sent the questionnaire blind. One other study concerned with SMEs by the same Principal Investigator(s) is held at the UK Data Archive under SN 4156. Main Topics:

Directory Software Market size was valued at USD 161.03 Million in 2024 and is projected to reach USD 405.59 Million by 2031, growing at a CAGR of 12.24% from 2024 to 2031.

Directory Software Market Drivers

Digital Transformation Across Industries: As businesses increasingly move towards digital solutions, the demand for directory software has surged. Organizations are adopting directory software to manage and organize vast amounts of contact information, employee directories, and customer databases efficiently.

Growth of Remote Work: The rise of remote and hybrid work models has heightened the need for centralized directories that allow easy access to employee information and communication channels. Directory software supports remote teams by providing a centralized platform for accessing contact information, thus facilitating seamless communication and collaboration.

Data Security and Compliance: With growing concerns over data privacy and stringent regulations like GDPR, companies are investing in directory software that ensures secure storage and management of sensitive information. Directory software helps organizations maintain compliance with regulatory standards while protecting against data breaches.

CF: MI: S: Curr. Term (MoM, SA): DI data was reported at -13.200 % in Mar 2025. This records an increase from the previous number of -16.500 % for Dec 2024. CF: MI: S: Curr. Term (MoM, SA): DI data is updated quarterly, averaging -15.700 % from Jun 2005 (Median) to Mar 2025, with 80 observations. The data reached an all-time high of -9.200 % in Dec 2017 and a record low of -49.300 % in Jun 2020. CF: MI: S: Curr. Term (MoM, SA): DI data remains active status in CEIC and is reported by The Small and Medium Enterprise Agency. The data is categorized under Global Database’s Japan – Table JP.S088: SME Business Survey Report: Cash Flow.

CF: CI: S: Curr. Term (MoM, SA): Recover data was reported at 5.700 % in Mar 2025. This records a decrease from the previous number of 6.900 % for Dec 2024. CF: CI: S: Curr. Term (MoM, SA): Recover data is updated quarterly, averaging 6.700 % from Jun 2005 (Median) to Mar 2025, with 80 observations. The data reached an all-time high of 10.600 % in Jun 2013 and a record low of -36.500 % in Mar 2009. CF: CI: S: Curr. Term (MoM, SA): Recover data remains active status in CEIC and is reported by The Small and Medium Enterprise Agency. The data is categorized under Global Database’s Japan – Table JP.S088: SME Business Survey Report: Cash Flow.

To select the group of UK firms we initially searched in the FAME database (available from the University of Manchester Library) with keywords relating to the green goods sector, please see the publication Shapira, et al (2014, in Technological Forecasting & Social Change, vol. 85, pp. 93-104) for further details on the keywords. This database contains anonymized firm data from a sample of UK firms in the green goods production industry. We combine data from structured sources (the FAME database, patents and publications) with unstructured data mined from firm's web-sites by saving key words in text and summing up counts of these to create additional explanatory variables for firm growth. The data is in a panel from 2003-2012 with some observations missing for firms. We collect historical data from firm's web-sites available in an archive from the Wayback machine.This project probes the growth strategies of innovative small and medium-size enterprises (SMEs). Our research focuses on emerging green goods industries that manufacture outputs which benefit the environment or conserve natural resources, with an international comparative element involving the UK, the US, and China. The project investigates the contributions of strategy, resources and relationships to how innovative British, American, and Chinese SMEs achieve significant growth. The targeted technology-oriented green goods sectors are strategically important to environmental rebalancing and have significant potential (in the UK) for export growth. The research examines the diverse pathways to innovation and growth across different regions. We use a mix of methodologies, including analyses of structured and unstructured data on SME business and technology performance and strategies, case studies, and modelling. Novel approaches using web mining are pioneered to gain timely information about enterprise developmental pathways. Findings from the project will be used to inform management and policy development at enterprise, regional and national levels. The project is led by the Manchester Institute of Innovation Research at the University of Manchester, in collaboration with Georgia Institute of Technology, US; Beijing Institute of Technology, China, and Experian, UK. We collected the financial information on the UK firms by downloading Companies House data from the FAME database available through the University of Manchester Library (see http://www.library.manchester.ac.uk/searchresources/databases/f/). Grant information on companies came from the Technology Strategy Board. Patent information was from the Derwent database and publication information was from the Web of Science. The Consumer Price index was from the Office for National Statistics (http://www.ons.gov.uk/ons/rel/cpi/consumer-price-indices/index.html). The Human Resources in Science and Technology variable was from the Eurostat database (http://ec.europa.eu/eurostat/data/database). Unstructured data was mined from firm's web-sites. The UK Intellectual Property Office has clarified that the data mining we are doing and the way we are doing it is permissible. See: https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/375954/Research.pdf

CF: CI: Curr. Term (MoM, SA): DI data was reported at -6.300 % in Mar 2025. This records an increase from the previous number of -7.400 % for Dec 2024. CF: CI: Curr. Term (MoM, SA): DI data is updated quarterly, averaging -3.700 % from Jun 2005 (Median) to Mar 2025, with 80 observations. The data reached an all-time high of 44.700 % in Mar 2009 and a record low of -23.100 % in Jun 2020. CF: CI: Curr. Term (MoM, SA): DI data remains active status in CEIC and is reported by The Small and Medium Enterprise Agency. The data is categorized under Global Database’s Japan – Table JP.S088: SME Business Survey Report: Cash Flow.

This dataset explains the subsidy status of the SMEs Mobile Smart Application Project over the years, providing relevant information such as subsidy recipients, subsidy amounts, affiliated municipalities or counties, and approval dates, providing a reference for the industry to promote mobile smart application.

Business Information Services Market Outlook

The global business information services market size was valued at approximately USD 150 billion in 2023 and is projected to reach around USD 265 billion by 2032, growing at a compound annual growth rate (CAGR) of 6.5% during the forecast period. This growth can be attributed to the increasing demand for data-driven decision-making solutions and the rising need for competitive intelligence across various industries.

One of the primary growth factors driving the business information services market is the rapid digital transformation across industries. Enterprises are increasingly relying on data analytics and business intelligence solutions to gain insights into market trends, customer behavior, and competitive landscapes. This shift towards data-driven decision-making is fueled by the exponential growth in data generation, coupled with advancements in technologies such as artificial intelligence (AI) and machine learning (ML). These technologies enable businesses to extract valuable insights from vast amounts of data, thereby enhancing their strategic decision-making capabilities.

Another significant factor contributing to market growth is the increasing complexity of business environments. Companies are operating in a highly competitive and dynamic landscape, which necessitates the need for accurate and timely information. Business information services provide organizations with critical data on market trends, financial performance, credit risk, and regulatory changes, among others. This information is crucial for businesses to mitigate risks, identify opportunities, and make informed decisions. The demand for such services is particularly high in sectors such as BFSI, healthcare, and IT & telecommunications, where timely and accurate information is paramount.

Moreover, the proliferation of cloud-based solutions is also driving the growth of the business information services market. Cloud computing offers several advantages, including scalability, cost-effectiveness, and accessibility, which are particularly beneficial for small and medium enterprises (SMEs). Cloud-based business information services allow organizations to access critical data and analytics tools without the need for significant upfront investments in IT infrastructure. This democratization of information services is expected to drive market growth, especially among SMEs, which are increasingly adopting these solutions to gain a competitive edge.

In this evolving landscape, the role of an Information Broker becomes increasingly vital. Information Brokers act as intermediaries who gather, analyze, and distribute data to businesses, enabling them to make informed decisions. They specialize in sourcing hard-to-find information and synthesizing it into actionable insights, which is crucial for companies navigating complex market environments. As businesses strive to stay competitive, the demand for Information Brokers is expected to rise, as they provide the expertise needed to interpret vast amounts of data and offer strategic recommendations. This growing reliance on Information Brokers underscores their importance in the business information services market, particularly as industries continue to embrace data-driven strategies.

Regionally, North America holds a significant share of the global business information services market, primarily due to the presence of major market players and the high adoption rate of advanced technologies in the region. The United States, in particular, is a major contributor to market growth, driven by a strong emphasis on research and development and a highly competitive business environment. Meanwhile, the Asia Pacific region is expected to witness the highest growth rate during the forecast period, owing to the rapid economic development and digital transformation initiatives in countries such as China and India. The increasing penetration of internet and mobile technologies in this region is also expected to drive the demand for business information services.

Service Type Analysis

The business information services market can be segmented by service type into financial information, market research, credit and risk management, news and media, and others. The financial information segment holds a significant share of the market, driven by the critical need for up-to-date financial data and analysis. Businesses use financial information services to monitor market trends, analyze company performance, and