Here we compiled and list down 12 leading business intelligence companies and have identified their products, initial product differentiation, their sales strategy, timeline of venture capital fundraising and revenue, their notable success and failures, and the number of their exits, if any. The key companies analyzed here are Tableau, Domo, Mode Analytics, Statsbot, Birst, LogiAnalytics, Izenda, Pentaho, Sisense, Alteryx, Periscope, and Looker.

Competitive Analysis of the top and most recognized business intelligence companies
1. Tableau
Website: https://www.tableau.com/
Products: Tableau Desktop, Tableau Prep, Tableau Online, and Tableau Server
Initial Product Differentiation: “The prime logic behind creating this tool was developing a simple and user-friendly tool that cannot only help you create graphs, charts, maps, reports but assist you in the next-gen concepts like predictive and prescriptive analysis.” Some of the core differentiating features includes real-time data analysis and visualizations; visualizations don’t require coding and can be embedded in multiple platforms; and powered by VizQl language. Tableau makes data analytics accessible to all business users. It integrates securely with almost any data source, including popular data sources such as Hadoop, Oracle, Teradata, and more.
Sales Strategy: As a data analytics company, Tableau’s sales strategy is fundamentally data-driven. The company analyzes key sales data metrics every quarter and adjusts its strategy appropriately, looking at which customers and segments to target, for example. In 2017, the company introduced a new subscription licensing model for its key software products, and the sales strategy for this model was focused on first expanded the new model among the company’s existing client base, converting existing customers to this new model. After getting established among this client base, the company then planned to move forward to expanding the product’s overall footprint.
Timeline of venture capital fundraising and revenue:
Fundraising:
- 2004: $5 million Series A
- 2008: $10 million Series B
- 2010: Venture Round, undisclosed amount
Revenue:
- 2009: $18 million
- 2011: $62 million
- 2012: $127 million
- 2013: $232 million
- 2014: $412 million
- 2015: $653 million
- 2016: $826 million
- 2017: $877 million
Notable success and failures:
1. Failure: In February of 2016, after the company announced that it expected a soft 2016 in terms of both revenue and profits, the company’s stock lost about half its value in one day.
2. The company experienced rapid growth in just a matter of years; from 2009-2015, sales grew from $18 million to $654 million. As of 2017, the company had a $3.8 billion market cap.
Exit: IPO in 2013 for $254 million, $31 per share on the NYSE
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2. Domo
Website: https://www.domo.com/
Products: “Domo is a cloud-based business management suite that integrates with multiple data sources, including spreadsheets, databases, social media and any existing cloud-based or on-premise software solution. It is suitable for company sizes ranging from small businesses to large enterprises, and is compatible with Windows or Mac platforms, iPad tablets, and also works on mobile devices.”
Initial Product Differentiation: One key competitive advantage of Domo is that the product is results- and action-oriented. All of the dashboards and other features are action-oriented, providing the user not only with insights, but with next steps, as well as alerting the user when something is out of place. Another advantage of Domo is that it is an all-inclusive platform, meaning it integrates sales, operations, finance, marketing, IT, and all other business aspects that use data. This includes 450 built-in API connectors to give the user easy access to their data.
Sales Strategy: From the beginning, a big part of Domo’s sales strategy has been building hype and scarcity around its product to drive interest. For the first several years, the company was very secretive about its product, and only began talking about itself publicly in 2015. Domo turned its product into a VIP club that only a select few could enter; this is a tactic similar to what Apple is known for using around the iPhone and other key products.
Timeline of venture capital fundraising and revenue:
Fundraising: 11 funding rounds since 2010, for a total of $689 million. The largest funding rounds include:
- 2011: Series A, $33 million
- 2013: Series B, $60 million
- 2014: Series C, $125 million
- 2015: Series D, $210 million
- 2016: Series D, $121 million
Revenue:
- 2010: $2.1 million
- 2014: $50 million
- 2016: $80 million
- Current: $150 million
Notable success and failures:
1. Success: In 2017, Domo was ranked as the number one vendor in the Dresner 2017 Cloud Computing and Business Intelligence Market Study and in the Dresner Advisory Services’ 2017 Collective Insights Market Study.
Exit: No exit to date; there is evidence as of April 2018 that the company is moving towards an IPO.
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3. Mode Analytics
Website: https://modeanalytics.com/
Products: Mode is an SQL-powered, collaborative data analytics platform. It has three core components: ad hoc analysis, visualizations, and data dashboards.
Initial Product Differentiation: Mode is known for its ease-of-use, collaborative capabilities and intuitive interface.Mode specifically targets data analysts, as opposed to some of the other products such as Tableau that are meant to be accessible to everyone. It was built “for analysts by analysts”. The unique selling points of Mode’s platform include streamlined data tables and charts, an HTML editor to build custom visualizations, Python analysis, interactive dashboards, internal and external sharing, and more.
Sales Strategy: According to Mode’s CEO, key sales strategies used by the company include listening to customer feedback, understanding the core problems faced by customers, and showing how your offering can address those problems. Moreover, as a data analysis company, Mode has used analytics from the beginning to shape its strategy. Mode used analytics to determine who its customers would be and how best to take its product to market.
Timeline of venture capital fundraising and revenue:
Fundraising:
- 2013: Seed, $550,000
- 2014: Debt, $375,000
- 2015: Seed, $2 million
- 2016: Series A, $7.5 million
- 2017: Series B, $13 million
Revenue:
Current: $8 million
Notable success and failures:
1. Success: The company built a content marketing microsite, called SQL School, that is the company’s biggest driver of inbound leads, generating more than 500 leads per month.
Exit: No exit to date.
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4. Statsbot
Website: https://statsbot.co/
Products: Statsbot is a powerful, all-in-one analytical tool that can be utilized by both engineers and users with non-technical backgrounds. Statsbot transformations utilize SQL and Javascript, as well as query optimization. Statsbot does not require ad hoc SQL queries for each request.
Initial Product Differentiation: Statsbot differentiates itself from competitors by providing a powerful analytical product that can be used by both engineers and users with non-technical backgrounds. This approach makes the product accessible to a wide spectrum of users. For example, non-technical users can ask Statsbot a natural language query, and the tool will incorporate insights from Google Analytics, Salesforce, and others directly into Slack. Statsbot also offers a dedicated data analyst for non-technical users who require additional assistance. On the other hand, engineers and data analysts can process raw data into actionable insights using Statsbot, and the platform can be developed in a similar manner to developing software.
Sales Strategy: Statsbot sales strategy initially emphasized company growth as the most significant target. In contrast to startups that focus on monetization, Statsbot approached sales with the understanding that in the early development stage, “your business must grow or die.” This strategy was enhanced by timely launches on Slack App, Hacker News, and Product Hunt, which ultimately went viral on Twitter and increased overall website traffic. Statsbot currently offers a free trial subscription, and subscribers also have access to a number of unlimited features at the enterprise level.
Timeline of venture capital fundraising and revenue:
Fundraising:
- July 2016: Seed, $200,000
- September 2016: Seed, $125,000
- December 2016: Seed, $1.6 million
Revenue:
Current: less than $1 million
Notable success and failures:
1. Statsbot participated in 500 Startups and Betaworks Bootcamp in 2016.
2. Statsbot has reportedly been installed by an estimated 20,000 businesses.
3. One of the primary reasons Statsbot is successful is that it fits organically within the “conversational workflow of modern tech companies.” Whereas some companies provide meaningful data, Statsbot provides this data in the “right context.”
Exit: No exit to date
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5. Birst
Website: https://www.birst.com/
Products: Birst provides a user-friendly consumer experience that “virtualizes the entire analytics and data ecosystem.” This approach effectively transforms an organization’s overall approach to data analytics. Additionally, Birst supports a variety of platforms for data analytics, including mobile and web-based options.
Initial Product Differentiation: Birst offers the only enterprise business intelligence platform that links the entire organization, meeting the needs of various users across the company. This is accomplished via a network of “interwoven virtualized BI instances on-top a shared common analytical fabric” Birst offers the first platform that is capable of meeting both scale and data governance needs while maintaining the agility, speed, and usability traditionally associated with desktop tools. Birst offers a solution for organizations with a mixture of local and enterprise data, and the company boasts that it “blurs the lines between BI dashboards and discovery,” creating a highly adaptive and flexible user experience.
Sales Strategy: Birst’s sales strategy relied on the development of proprietary techniques to fully automate a number of analytical applications. As a result, complex enterprise application data was made “analytically ready” at unprecedented speeds and scale, making Birst’s business intelligence platform the first to deliver enterprise-level data in such a rapid and agile format. Birst is unique in this strategy; most organizations begin with desktop tools and build up to platforms capable of managing enterprise data.
Timeline of venture capital fundraising and revenue:
Fundraising:
- 2005: Series A1, $1.2 million
- Series A2, $7 million
- 2012: Series D, $26 million
- 2013: Series E, $38 million
- 2015: Series F, $65 million
- 2017: Acquisition, $101 million
Total Funding: $129 million
Notable success and failures: Birst has received over 50 industry awards, and notable awards include mentions on the 2017 Gartner Critical Capabilities for BI & Analytics Platforms, Forrester Wave 2015 Cloud Business Intelligence Platforms, and Forbes 2016 Top 100 Startups.
Exit: On July 1, 2017, Birst was acquired by Infor to enhance the company’s cloud services. However, the terms of the agreement were not disclosed publicly.
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6. LogiAnalytics
Website: https://www.logianalytics.com/
Products: LogiAnalytics boasts that it offers the top platform for embedded analytics, with powerful native features (Logi Elements) that are highly customizable without the need for technical knowledge. These pre-built features include “data, visual, analysis, security, input, process/action, styling, formatting, layout and design” options. The platform is also reported to be the “most agile reporting and data visualization platform” accessible in a web-based format.
Initial Product Differentiation: LogiAnalytics focuses on providing a user-friendly, affordable business intelligence platform that appeals to both technical and non-technical users. It competes directly with IBM Cognos and Microstrategy, and is considered the industry leader in providing a platform for embedded analytics. The company has benefitted from a strong reputation in embedded analytics for over ten years. However, LogiAnalytics platform is considered less monolithic than its competitors, while also providing data visualization through the Logi Info BI platform and exploration features via Logi Vision. Utilized together, these two platforms can meet all enterprise-level organizational needs, including “reporting, dashboards, charts, data visualizations, and portals. LogiAnalytics’s capabilities are considered “very broad,” applicable to both data creators and consumers.
Sales Strategy: LogiAnalytics emphasizes the affordability of its platform as a key component of its sales strategy, often referencing the platform as providing “the best value” among competitors. The company focuses on providing strong customer service, outlining a number of favorable awards and industry recognition for this aspect of its operations. LogiAnalytics also emphasizes its status as an industry leader in embedded analytics, noting that the platform allows organizations of all sizes to integrate analytics into the very “fabric” of the company. LogiAnalytics offers a free demo of its platform.
Timeline of venture capital fundraising and revenue:
Fundraising:
- 2007: Venture, $5 million
- 2008: Venture, $3 million
- 2010: Venture, $2.5 million
- 2011: Private Equity, $10 million
- 2013: Private Equity, $27.5 million
- 2017: Acquisition (undisclosed)
Total Funding: $48 million
Notable success and failures:
1. It is estimated that 1,800 consumers globally use LogiAnalytics.
2. In 2013, LogiAnalytics became a member of the “Challengers” quadrant in Gartner’s Magic Quadrant for Business Intelligence and Analytics Platform Report.
3. The company earned the ranking of “Perfect Recommend” in Dresner Advisory Services Wisdom of Crowds BI Market Study.
4. LogiAnalytics was named an Overall Leader in Customer Experience and Vendor Credibility.
Exit: Marlin Equity Partners acquired LogiAnalytics on October 26, 2017.
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7. Izenda
Website: https://www.izenda.com/
Products: Izenda provides embedded BI and self-service analytics that aids in reporting and analyzing data. Embedded analytics helps the client get to the market faster and keep customers engaged. Meanwhile, the self-service feature enables administrative functions without the need for code related technical support.
Initial Product Differentiation: Izenda offers “real-time data-driven decisions.” Izenda’s platform is “fast and easy to embed”, flexible and scalable. Izenda underscores that it offers a more user friendly platform.
Sales Strategy: Izenda aims to demonstrate to the client that use of its platform results in sales increases, higher user engagement and differentiate the business from its competitors.
Timeline of venture capital fundraising and revenue:
Fundraising:
2014 – $3 million
Revenue: $5.8 million
Notable success and failures: Izenda was ranked in the top 5 embedded BI for small businesses by G2 Crowd. It was also listed as one of six embedded analytics vendors to watch in 2017 by Solutions Review.
Exit: No exit reported.
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8. Pentaho
Website: http://www.pentaho.com/
Products: Pentaho offers cloud services, cloud application developments, cybersecurity analytics, predictive analysis, and data center modernization. Further, it works on IoT solutions and outcomes.
Initial Product Differentiation: Pentaho’s advantage relative to competitors like, Jaspersoft, is that its platform provides “greater flexibility in connecting third party systems.” According to a study, Pentaho offers “great usability, maintainability and flexibility” and “integrates all transformation resources into a single operating platform.”
Sales Strategy: Pentaho’s sales strategy includes a “comprehensive enterprise software training program” designed to help customers learn about the software and enhance work habits.
Timeline of venture capital fundraising and revenue:
Fundraising:
- 2005 – $13 million
- 2006 – $24 million
- 2010 – $7 million
- 2011 – $5 million
- 2012 – $23 million
Total fundraising: $72 million
Revenue: $85.3 million
Notable success and failures: Pentaho won the 2018 Fortress Cybersecurity Security Awards for product innovation and was named as the Enterprise Solution of the Year by the 2018 IoT Innovation Award.
Exit: Pentaho was acquired by Hitachi Data Systems on February 10, 2015.
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9. Sisense
Website: https://www.sisense.com/
Products: Sisense products include SQL reporting and business user analytics. According to the company, its BI platform was designed to “eliminate the barrier between the users and the business analytics software they need to make smarter, faster data-driven decisions.”
Initial Product Differentiation: Sisense’s data discovery tools offer “faster data visualization” and “comprehensive data storage.” Additionally, its open source BI platforms cost “lower overall compared to any open source solutions.”
Sales Strategy: Sisense offers the first single-stack solution data analytics tool. Its BI platforms also offer in-chip technology, machine learning and Sisense everywhere. The company promises to deliver not only different but better products.
Timeline of venture capital fundraising and revenue:
Fundraising:
- 2010 – $4 million
- 2013 – $10 million
- 2014 – $30 million
- 2016 – $50 million
- Total fundraising: $94 million
Revenue: $10.6 million
Notable success and failures:
– Named a Visionary in the 2018 Gartner Magic Quadrant for Analytics and Business Intelligence Platforms.
– Named by the Software & Information Industry Association as Best Business Intelligence Tool and Platform.
-“perfect recommend” ranking and recognized as market leader in Dresner’s 2017 Wisdom of Crowds BI Market Study.
– 2018 Best BI Software by FinancesOnline
– Picked as one of NYC’s top tech companies by Built in NYC
Exit: No exit reported.
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10. Alteryx
Website: https://www.alteryx.com/
Products: Alteryx offers products such as SAP analytics, in-database processing, data blending software, spatial analysis software, data profiling software and data visualization.
Initial Product Differentiation: Alteryx’s platform allows for a “repeatable workflow” that can automate manual data tasks, and a friendly interface that does not require coding. Further, it has the ability to process large volumes of data from various sources and applications.
Sales Strategy: Alteryx emphasizes strong product vision. Its “land and expand” strategy aims to move customers from data integration to predictive analysis. Alteryx combines “the growing data discovery market by offering both data preparation and advanced analytics.”
Timeline of venture capital fundraising and revenue:
Fundraising:
- 2013 – $18 million
- 2014 – $60 million
- 2015 – $85 million
- Total fundraising: $163 million
Revenue: $131.6 million
Notable success and failures:
‘- Gold Winner of Gartner Peer Insights Customer Choice Awards for Business Intelligence and Analytics (2017)
– Deloitte’s Technology Fast 500™: Rank 392 (a ranking of the 500 fastest growing technology, media, telecommunications, life sciences and energy tech companies in North America)
– KeyBanc Capital Markets: Top 20 AI All-Stars in Technology
Exit: IPO in 2017. Raised $ 126 million at IPO. $14 per share on the NYSE.
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11. Periscope
Website: https://www.periscopedata.com
Products: Periscope offers two major products, an SQL Editor that was built “by experts, for experts” and a related product they call a Unified Data Platform. Both of their products are pitched toward experts and one of Periscope’s major boons is that data and computer scientists who understand the field developed their products.
Initial Product Differentiation: Periscope’s SQL Editor is more than a simple SQL editor. Periscope’s SQL Editor is a rich environment that aims to increase productivity and efficiency. Their editor supports a Snippets feature that allows data analysis teams to keep a shared database of commonly used pieces of code and queries for easy access. Their editor also supports three major languages, SQL, Python, and R, to ensure both a wide range of audiences are able to easily use the problem as well as teams being able to use the language most capable of solving the problem. The editor also supports a wide range of third party libraries with the ability to request more which allows teams access to well tested APIs and functions. Data is even easier to analysis with their editor’s GUI which has functions to build charts.
Periscope’s Unified Data Platform creates a “data warehouse” that acts as one source of truth. Rather than having different databases scattered across services, teams have one source of data that’s managed by the Unified Data Platform with “deep analytical” capabilities.
Sales Strategy: Periscope Data is driven by its commitment to develop products that are designed for data analysts. Data analysts are often overlooked in the business intelligence community. Their tools often do not reflect how analysts actually work and understand data. Periscope’s sales strategy is to present and develop tools that are for data scientists but also reflect an understanding of data science as a craft. Their products spread through word of mouth, reviews, and the hype generated by its products.
Timeline of venture capital fundraising and revenue:
Fundraising:
- 2016: Bessemer Venture Partners, $25 million
- 2015: DFJ, $9.5 million
- 2012: Seed amount not mentioned
- Total Funding: $34.5 million
Revenue: <$1 million
Notable success and failures:
‘ -Received 15 Comparably awards
– GlassDoor’s employee reviews are extremely high
– “Voted Top Places to Work by the Bay Area News Group”
– “Voted 2017 Best Places To Work by the SF Business Time and the Silicon Valley Business Journal”
– Periscope has over one thousand clients including Adobe, Flexport, EY, Uber, ZipRecruiter, Fender, Meredith, Tinder etc.
– “Super sticky product: customers companies spend 20 hours per week, per person, using Periscope Data!”
– Periscope has extremely high customer retention – “better than best in class for a SaaS company”
Exit: No exit reported yet.
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12. Looker
Website: https://looker.com
Products: Looker’s major product is its Business Intelligence Platform with its LookML data modeling language.
Initial Product Differentiation: Looker aims to make business intelligence easy. Rather than sell itself as a data analyst platform, Looker presents its products as specifically for business intelligence. Looker’s Business Intelligence Platform sports its own, in house developed data modeling language known as LookML. Looker’s platform tries to engage everyone by making it easy to answer data related questions as well as having the resulting SQL presented as output for data scientists to use.
Sales Strategy: Looker aims to make data analysis easy for everyone involved rather than being a platform for data analysts. Thus, Looker’s Business Intelligence platform provides a simple interface to allow anyone to answer data related questions. Companies such as Docker, eBay, Sony, Uber, Instacart and Warby Parker, and Kohler make use of Looker’s platform. Companies who use Looker say they are “finally able to start building a data culture” due to the ease of use of Looker’s platform. Looker notes that companies often collect tons of data but do not adequately use it or even misuse their data. Looker sells its product based on the simplicity of using it, as well as updates constantly to keep up to date with the changing industry.
Timeline of venture capital fundraising and revenue:
Fundraising:
- 2017: CapitalG, $81.5 million
- 2016: Kleiner Perkins Caufield & Byers, $48 million
- 2015: Meritech Capital Partners, $30 MIllion
- 2013: First Round Capital, $16 Million
- 2013: Seed Round, $2 MIllion
- Total Funding: $177.5 million
Revenue: $20 million
Notable success and failures:
-Looker releases updates at a steady drumbeat of every four weeks to ensure it stays ahead of the rapidly changing data analysis industry.
-Forrester ranked Looker as a “Strong Performer” in its first year of operation.
-Looker received the Google Cloud Global Partner award for its contributions to Google Cloud in 2016
Exit: No exit reported yet.
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What is business intelligence software?
Business intelligence software is a set of tools used by companies to retrieve, analyze, and transform data into useful business insights. Examples of business intelligence tools include data visualization, data warehousing, dashboards, and reporting. In contrast to competitive intelligence, business intelligence software pulls from internal data that the business produces, rather than from outside sources.
As Big Data has gained in prominence, so has the popularity of BI software. Companies generate, track, and compile business data at a scale never before seen. But all this data is nothing if we can’t make sense of it and use it to improve business outcomes.
To make informed choices, businesses need to base their decisions on evidence. The mountains of data that businesses and their customers produce contain evidence of purchasing patterns and market trends. By aggregating, standardizing, and analyzing that data, businesses can better understand their customers, better forecast revenue growth, and better protect themselves against business pitfalls.
Business intelligence has traditionally taken the form of quarterly or yearly reports, but today’s software-backed business intelligence tools work continuously and at light speed. These insights can help a company choose a course of action in a matter of minutes.
BI software interprets a sea of quantifiable customer and business actions and returns queries based on patterns in the data. BI comes in many forms and spans many different types of technology. This guide compares the top business intelligence software vendors, breaks down the three major stages data must go through to provide business intelligence, and provides considerations for purchasing business intelligence software for different sized businesses. (Source)
As per customer study, PowerBI is leading in BI; would be interested to know why is it not listed in your page; what are the criteria’s it is filtered from top BI products?
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