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

SME - Synthetic UK Businesses financial statistics

Contains the financial and basic information about the 1000 small and medium enterprises in the UK. It contains attributes as far-reaching as the profit and losses of the entities and even their credit scores. It can be used to analyze the survival and success prediction of the enterprise.

This sample data is part of the statistically accurate representation of the UK economy that can be found at https://nayaone.com/digital-twin/. Our mission is democratization and quality data governance in areas where the lack of data is a major hurdle for innovation and progress. To learn more, contact us: contact@nayaone.com

Content

All the Synthetic datasets have been generated with programmatic stimulation to represent the real-world data. Description of the datasets are as follows: - Account Receivable: Funds that customers owe your company for products or services that have been invoiced. - Businesses: List of enterprises and their information - Covid: Financial stats of the companies during the pandemic waves - Credit Account History: History of a credit account and usage of - Credit Card History: History of the credit card usage and debt amount of an enterprise - Credit Rating: credit rating of listed businesses which is a quantified assessment of the creditworthiness of a borrower in general terms or with respect to a financial obligation. - Director: UK Individual who is on the Director position in companies listed in Businesses - Factoring: Financial transaction and a type of debtor finance in which a business sells its accounts receivable to a third party at a discount. - Individual: UK Individuals information - Loan: Information of the paid and unpaid Loans by the enterprise

Acknowledgements

The real data stats used to generate synthetic data are mainly gathered from the ONS, Public datasets and Known statistics.

Inspiration

This data can be used to train Machine learning models for better accuracy.

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

In January 2004, a consortium of public and private sector organisations commissioned Warwick Business School to carry out the United Kingdom Survey of Small- and Medium-sized Enterprises' (SME) Finances, 2004. This was the first representative survey of SMEs to offer a close analysis of businesses with fewer than 250 employees, their main owners and their access to external finance. A second survey was conducted in 2008, where business owners were interviewed by telephone about the finances they have used or applied for in the last three years, their financial relationships, the characteristics of the business and personal details.

In 2007, another consortium of UK public sector bodies, small business representative organisations and finance providers agreed to sponsor a similar survey to the 2004 survey, conducted by the Centre for Business Research based at the University of Cambridge. This study is held at the UKDA under SN 6049, with the title United Kingdom Survey of Small- and Medium-Sized Enterprises' Finances, 2007. It aimed to compile another benchmark and to identify any changes or trends that had emerged since 2004, but made a number of changes to the 2004 questionnaire, so that it is not a direct member of the UKSMEF series, but stands alongside it as a separate cross-sectional survey. The UKSMEF 2008 survey was conducted by the same Principal Investigator as the 2004 survey, based at Warwick Business School, and the 2008 report provides direct comparison between the 2004 and 2008 surveys.
The aims of the 2009 survey were to:

• provide benchmarking data on the availability of credit to SMEs and the types of finance used
• collect information on the relationship between SMEs and their providers of finance
• develop a general purpose micro database for quantitative research on business finance (offering, for example, scope for comparisons with the US Survey of Small Business Finances)

The 2009 sample consisted of 1,250 follow up interviews with businesses interviewed for the 2008 survey. Telephone interviews were conducted by IFF Research Ltd during autumn 2009. These interviews focused on the cost and availability of overdrafts and term loans to businesses in the previous year due to policy makers concerns about the affect of the Credit Crisis on bank lending to SMEs. The data can be used for panel data analysis, in conjunction with UKSMEFs 2004 and 2008, or for standalone cross-sectional analysis. A set of population weights is included in the dataset so that this analysis can be weighted to the UK SME population. These weights were calculated using statistics provided by the Department of Business, Innovation and Skills Enterprise Directorate - see Business population estimates, formerly 'SME Statistics'.

Further information may be found on the ESRC UK Survey of SME Finances 2009 Follow On Study award webpage.

Business intelligence and analytics software publishers' revenue is expected to swell at a compound annual rate of 1.7% over the five years through 2025-26 to reach £964.5 million. Strong growth has been fuelled by rising business software investment, IT and telecommunications adoption, advances in computing technology and the digitalisation of business processes. This has driven the advent of big data, providing new data sets which can interface with business analytics software. Many software products, including customer relationship management and enterprise resource planning systems, have become basic tools for managing large companies. The largest publishers have pursued acquisition activity to take control of cloud companies and data analytics businesses. These industry giants are generally selective with acquisitions, embracing the switch to software as a service and adopting the low-cost cloud model. Leading BI suites, LIKE Tableau, SAP Analytics Cloud, Qlik Sense and IBM’s Cognos Analytics, have all transformed to provide real-time KPI dashboards and robust remote management capabilities, supporting decentralised operations. Intensified merger and acquisition activity, particularly by SAP, has allowed major software publishers to rapidly enhance product ecosystems with niche digital adoption and enterprise architecture tools, further cementing their dominance and spurring innovation. As remote work became the new norm and businesses faced the necessity of managing expansive data sets efficiently, they turned to analytics software. Despite fiscal stresses, companies continued investing in software subscriptions, recognising the indispensable use of applications in a remote work environment. As such, subscriptions and sales of cloud-based software witnessed noticeable growth. Revenue is forecast to climb by 1.7% in 2025-26, with profit also expected to edge up as demand remains strong. Over the five years through 2030-31, revenue is expected to climb at a compound annual rate of 3% to reach £1.1 billion. Heightened adoption of industry-specific software among small and medium-size enterprises (SMEs) is projected to fuel growth. Ongoing e-commerce expansion, which has seen the online share of retail sales climb steadily, will keep demand for BI and analytics tools rising as retailers and supply chains seek deeper insights into customer behaviour and operational efficiencies. Cloud adoption will remain central, with hybrid and distributed models expected to persist, yet competition from cloud infrastructure giants like Amazon Web Services is likely to intensify. Investment in artificial intelligence and machine learning is anticipated to accelerate, with publishers needing to embed AI-driven analytics and automation to stay competitive, bolstered by the UK’s substantial public and private AI investment. However, talent shortages and heightened corporation tax could dampen growth, particularly for smaller publishers struggling to absorb higher costs or secure skilled staff. The industry's resilience will hinge on strategic upskilling, smart automation and continued innovation, ensuring UK BI and analytics software remains at the forefront of enterprise digital transformation.

Background

Late payments remain a thorny issue for SMEs. Big businesses often continually fail to pay their suppliers on time which results in huge financial losses for suppliers esp SME suppliers all over the world. UK's modest-sized enterprises are currently owed £26 billion in overdue payments, according to research by payments processing company Bacs. On average, the 307 large businesses that filed payment reports to the UK government met invoice payments late 71 % of the time.

To arrest these morally unacceptable tactics, the UK Government has decided to make all the information public so that buyers are accountable in the future. It is aimed at helping suppliers to make more informed decisions about who they do business with. It also seeks to alleviate the administrative and financial burdens faced by thousands of small and medium-sized businesses due to late payments.

Under new rules introduced in April 2017, all large UK companies are required to publish specific information regarding their payment policies, practices, and performance - including the average time taken to pay supplier invoices - twice yearly. Failure to comply with the rules is a criminal offense and can result in a hefty fine.

This dataset is available under the Open Government Licence v3.0.

How to read the data?

The dataset contains records from 2017 onwards till Dec 2019. Each row of data contains:

• The reporting period (start date and end date or the duration for which the buyer company has to report the payment numbers)
• filing information (When did the company file the records)
• Whether Payments were made during the reporting period
• Payment Metrics like Average time to pay
• Distribution of Invoices spanned across different Payment duration buckets
• Standard Payment Period (Shortest and Longest)
• Typical Payment Contractual terms agreed with Suppliers
• Changes made in Payment terms and have suppliers been notified of changes
• Does this company offer e-invoicing in relation to qualifying contracts?
• Does this company offer supply chain finance?
• Under its payment practices and policies, can this business deduct sums from payments under qualifying contracts as a charge for remaining on a supplier list?
• During the reporting period, did the company deduct sums from payments as a charge for remaining on a supplier list?

Acknowledgements

Thanks to Govt of UK to make this data available publicly

Ideas of what you could do with this dataset:

• Can you come up with a buyer credibility score? - the buyer with a high score can be trusted to make payments on time
• Can you come up with any useful insights or recommendations for groups of buyers that can be useful for any supplier for future transactions?

Information is compiled from the Agricultural and Horticultural Census. This is an annual survey, conducted by the Statistics and Analytical Services Branch, DAERA. Information is on Number of Farms, Number of LFA Farms, Number of Non LFA Farms, Area Farmed (ha), Average SO/SGM (‘000) per farm, Crops (ha), Grass (ha), Number of Cattle, Number of Sheep, Number of Pigs, Number of Poultry, Number of Farmers, Number of self Employed, Number of Spouses, Number of Other Workers, Total Labour on Farms, Number of v. small/small/medium/large farms. Note that all small area data relating to less than 5 farm businesses has been suppressed and replaced with the number '3' to prevent disclosure. Due to the small number of farms within Belfast areas all data based on farm businesses or people has also been supressed in order to avoid large amounts of secondary suppression. For further details, please see The Agricultural Census in Northern Ireland webpage -https://www.daera-ni.gov.uk/articles/agricultural-census-northern-ireland.