Sacra estimates that DataSnipper hit $45M in annual recurring revenue (ARR) in 2023, up 150% YoY from $18M in 2022, as they expanded into the United States and landed contracts with the Big 4 accounting firms in the United States—EY, PwC, KPMG, and Deloitte. 

DataSnipper reached a valuation of $1 billion following its Series B funding round in 2024. The company has raised a total of $100 million across two funding rounds. Index Ventures led the most recent Series B round and secured a board seat as part of the investment. Insight Partners participated in an earlier funding round in September 2022. These two rounds represent the company's total institutional funding to date.

DataSnipper was founded in 2017 by Maarten Alblas, Jonas Ruyter and Kai Bakker in Amsterdam.

The founders, with backgrounds in auditing and technology, aimed to automate tedious data extraction and cross-referencing tasks in Excel for auditors. Initially launched as a standalone platform, they quickly pivoted to an Excel add-in based on user feedback.

In 2018, DataSnipper secured early contracts with major accounting firms like EY and KPMG, providing crucial social proof.

DataSnipper found product-market fit with external auditors at Big 4 firms by automating mundane Excel-based tasks like data extraction and reconciliation. The tool allowed junior auditors to complete routine procedures in minutes instead of hours, while maintaining familiar Excel workflows.

The core product is an Excel add-in that offers several key features:

Text Snip: Connect a snippet of text or numerical information in a PDF to a specific cell in the Workbook.

Validation Snip: This Snip is used to validate a requirement or detail in the source document, such as a valid signature or date range.

Sum Snip: By drawing a box around two or more values, DataSnipper automatically sums the values in the target cell, and cross-references the cell to the correct area of the PDF or other source document. 

Exception Snip: Similar to Validation Snip except that it is for the user to flag an inconsistency between a spreadsheet’s cell and the source.

Table Snip: Similar to Text Snip, except that the tool captures tables in the source document and carries it over, without formatting glitches, to the Excel sheet.

The company has since expanded its offerings with add-ons like the Financial Statement Suite and Cloud Collaboration Suite, aiming to broaden its use cases beyond external auditing into areas such as internal audit, tax, and financial advisory.

As DataSnipper continues to grow, it faces challenges in balancing its core strength of local, secure Excel integration with the increasing demand for cloud-based and AI-driven features in the financial technology sector.

DataSnipper is a subscription SaaS company that has found product-market fit by providing audit and finance professionals with an Excel-native tool for automating mundane data extraction and reconciliation tasks. The company's core revenue model is based on per-seat licensing, with a minimum of 5 seats per contract. DataSnipper charges roughly $175 per month per seat for its Professional package.

The company's pricing strategy is tiered, with add-on modules available for purchase on top of the core platform. These include the Financial Statement Suite and the recently relaunched Cloud Collaboration Suite, which adds $62 per month per user. This tiered approach allows DataSnipper to capture additional value from customers as their needs grow and evolve, creating opportunities for upselling and expanding revenue per account.

DataSnipper's growth has been driven largely by product-led, bottom-up adoption within audit firms. The company initially focused on external auditors at large accounting firms, leveraging word-of-mouth and inbound marketing to fuel expansion. As junior auditors moved between firms, they often became advocates for DataSnipper, driving adoption in new organizations. This strategy has proven highly effective, with DataSnipper reporting explosive growth in 2021 and 2022.

In recent years, DataSnipper has begun expanding beyond its core external audit use case, targeting internal audit, tax, and financial advisory professionals. This expansion has been facilitated by the versatility of its core platform, which requires minimal adaptation to serve these adjacent markets.

DataSnipper has tailwinds from the increasing digitization of financial processes and the growing demand for automation in audit and accounting. The company has the opportunity to grow and expand into adjacent markets like internal audit, tax advisory, and broader financial services.

DataSnipper's core product is an Excel add-in, putting it in direct competition with other Excel-native audit and data extraction tools. Key competitors in this space include Audit File, which offers similar functionality for automating audit workflows within Excel.

However, DataSnipper differentiates itself through its focus on intuitive "snipping" of data from source documents and its strong positioning within large accounting firms. DataSnipper's early adoption by Big 4 firms gave it a significant advantage in building credibility and driving word-of-mouth growth among auditors.

Large accounting firms often develop their own proprietary audit software platforms. These in-house tools can offer deep integration with firm-specific workflows but may lack the flexibility and continuous innovation of a dedicated software provider like DataSnipper.

DataSnipper has managed to penetrate even firms with proprietary solutions by offering superior ease-of-use and efficiency gains, particularly for tasks like data extraction and cross-referencing. The company's focus on maintaining a local, offline-first approach has also helped it address data security concerns that can arise with cloud-based proprietary platforms.

As DataSnipper expands beyond external audit into areas like internal audit, tax, and financial advisory, it increasingly competes with more comprehensive financial automation platforms.

Companies like BlackLine and Workiva offer broader suites of financial close and reporting tools. DataSnipper's advantage in this segment lies in its Excel-native approach, which allows for easier integration into existing workflows without requiring a full platform switch. However, DataSnipper faces challenges in matching the breadth of features offered by these more established players.

DataSnipper's competitive position is strengthened by its focus on user experience and its ability to automate tedious, manual processes within familiar Excel environments.

DataSnipper has tailwinds from the increasing digitization of financial processes and the growing demand for automation in audit and accounting. The company also has the opportunity to grow and expand into adjacent markets like internal audit, tax advisory, and broader financial services.

DataSnipper's primary growth driver remains the expanding market for external audit automation. As regulatory requirements become more complex and the volume of financial data increases, the demand for efficient audit tools is likely to grow. DataSnipper's Excel-native platform is well-positioned to capture this growth, especially as it continues to penetrate large accounting firms globally. The company's success in signing global contracts with major firms like PwC demonstrates its potential to scale within its core market.

Moreover, the high turnover rate in the audit profession works in DataSnipper's favor. As auditors move between firms or transition to in-house roles, they often become advocates for the tool, driving bottom-up adoption across the industry. This network effect could accelerate DataSnipper's growth without significant additional marketing spend.

DataSnipper has begun expanding beyond external audit into related fields such as internal audit, tax advisory, and financial controls. These adjacent markets represent significant growth potential, as they share similar pain points around data extraction, reconciliation, and documentation. The company's core "snipping" functionality translates well to these use cases, allowing for expansion without major product overhauls.

The internal audit market, in particular, presents a substantial opportunity. As companies increasingly focus on risk management and compliance, the demand for efficient internal audit tools is growing. DataSnipper's ability to streamline documentation and cross-referencing aligns well with internal auditors' needs.

Furthermore, the company's move into investor use cases, particularly for private equity and venture capital firms, opens up new avenues for growth. The ability to quickly extract and analyze financial data from various sources is valuable for due diligence and portfolio management processes. As DataSnipper continues to refine its offering for these users, it could capture a significant share of this market.

1. Overreliance on Excel and local deployment: DataSnipper's core value proposition is deeply tied to Excel and local deployment, which could become a liability as more enterprises shift to cloud-based solutions.

While this approach has been a strength in security-conscious industries like auditing, it may limit DataSnipper's ability to expand into other verticals or keep pace with AI advancements that require cloud computing. The company's recent struggles with cloud collaboration features highlight this challenge.

2. Difficulty scaling beyond audit use cases: Despite efforts to expand into tax, internal audit, and financial advisory, DataSnipper's product remains heavily optimized for external auditors.

The company may struggle to gain traction in these adjacent markets without significant product changes, potentially limiting its long-term growth. The lukewarm reception to the Financial Statement Suite illustrates the challenges of expanding beyond the core audit use case.

3. Vulnerability to AI-powered competitors: As AI capabilities advance, DataSnipper could face competition from new entrants offering more sophisticated automation for audit and financial workflows.

While DataSnipper's local deployment model provides a moat in security-conscious industries, this advantage may erode if competitors can offer compelling AI-powered features while still meeting security requirements. DataSnipper's constraints around implementing AI in a local environment could leave it vulnerable to disruption.