Internet of Things Sector Overview – Q4 2017

The Internet of Things sector (IoT) continues to get a lot of buzz in the technology industry. Connected devices have improved our professional and personal lives in every aspect from industrial operations to medical procedures to home security. Yet what are the different components of IoT and how do they make up this startup ecosystem? On our IoT research platform, we have classified the companies in the sector into functional categories. This blog post examines these categories and how they compare with one another through a series of graphics.

IoT Home Is the Largest Internet of Things Category

Let’s start off by looking at the Logo Map for the Internet of Things sector. As of January 2018, we have classified 2,130 IoT startups into 20 categories which collectively raised $50 billion in funding. The Logo Map highlights the number of companies in each category and a random sampling of these companies.

Internet of Things Logo Map
Internet of Things Logo Map

We can see from the Logo Map above that IoT Home is the largest Internet of Things category with 331 companies. This category is comprised of companies that provide connected devices focused on the residential real estate segment. Some example companies in this category include Nest Labs, WigWag, SmartThings, and LIFX.

We have seen what the different categories in IoT are and how many companies are within each category. What about their funding and maturity in relation to one another? Let’s look at our Innovation Quadrant to find out.

The Established and the Pioneers Comprise the Majority of IoT Categories

Our Innovation Quadrant for the IoT sector divides the categories within the sector into four different quadrants according to their average funding and average age. The Heavyweights are the categories with companies that have reached maturity with significant financing. The Established are those that have reached maturity with less financing. The Disruptors are less mature but with significant financing. The Pioneers are less mature and with earlier stages of financing.

Internet of Things Innovation Quadrant
Internet of Things Innovation Quadrant

We can see from our Innovation Quadrant above that most of the IoT categories belong in either the Established quadrant or the Pioneers quadrant, with 7 categories in each. The IoT Fitness, IoT User Interface, IoT Enterprise, and IoT Automotive categories have raised more funding and thus made their way into the Disruptors quadrant. The IoT Components and IoT Hardware Platforms categories are in the Heavyweights quadrant for having reached maturity with significant financing.

We’ve now seen how the Internet of Things sector is categorized and the relative stages of innovation for those categories. How do these categories stack up against one another in a holistic view? Let’s look at the Total Funding and Company Count Graph.

IoT Software Platforms Is the Most Funded IoT Category

The graph below shows the total amount of venture funding and company count in each IoT category.

Internet of Things Total Funding and Company Count by Category
Internet of Things Total Funding and Company Count by Category

We can see from the graph above that while IoT Home has the most companies in the Internet of Things sector with 331 companies, it’s the IoT Software Platforms category that leads the sector in total funding with $6.3 billion. The IoT Software Platforms category is comprised of companies that build backend software systems that provide infrastructural support for IoT technology. Some example companies in this category include DADO Labs, CloudPlugs, Buddy, and C3 IoT.

Conclusion: Most Internet of Things Categories Have Large Growth Potential

The graphics above indicate that most of the IoT categories are still in their infancy in terms of their funding and maturity. In addition, the sector is bustling with a good number of IoT Home companies. Yet the IoT Software Platforms companies are receiving more venture funding than those in all the other categories. It will be interesting to see if this trend continues in 2018.

What are your thoughts on this? Let us know in the comments section below.

To learn more about our complete Internet of Things report and research platform, visit us at www.venturescanner.com or contact us at info@venturescanner.com.

Martech Investments Increasing in Importance Over Time

The Marketing Technology (martech) sector has seen a lot of venture capital funding over the past few years. How have its funding trends evolved over time? On our martech research platform, we have analyzed the data through 2017 and can conclude that the investments in martech have become fewer in frequency but larger in amount.

We have come to this conclusion from the following three takeaways:

  • Martech funding amounts are on a general upward trend at the annual level
  • Martech funding event counts have seen a decline in recent years
  • Martech average funding event size has been growing consistently

We will illustrate these takeaways with a series of graphics to show the trend of martech investments over time.

Martech Funding Amounts on Upward Trend Annually

We will start off by examining the martech funding trends over the years stacked by quarter.

Marketing Technology Funding by Quarter - Stacked
Marketing Technology Funding by Quarter – Stacked

This graph illustrates that martech funding is on a stable upward trend at the annual level. Specifically, the CAGR in funding amounts from 2012 to 2017 is 19%.

We have seen that martech funding is steadily growing, but what about the total number of deals?

Martech Funding Event Count Declining in Recent Years

The following graph shows us the annual number of martech startup funding deals, stacked by quarters.

Marketing Technology Funding Count by Quarter
Marketing Technology Funding Count by Quarter

The above graphic illustrates that the number of martech funding events saw a healthy upward trend from 2011 to 2014 and declined thereafter. In fact, the CAGR in funding events from 2012 to 2017 is -5%, and the number of events in 2017 is 88% of that in 2016.

We have seen that martech funding amounts are increasing steadily but its funding events are seeing a decline. Let’s see if the trend in average deal size sheds any further insight.

Average Martech Funding Deal Size Growing Over Time

The following graph shows the average funding deal size in Marketing Technology over different quarters from 2011 to 2017, as well as the trendline.

Marketing Technology Average Funding Event Size Over Time
Marketing Technology Average Funding Event Size Over Time

This graphic does indicate that the average martech funding deal size has experienced steady growth over the past few years. The trendline shows that from Q3 2011 to Q4 2017 the average deal size has grown by approximately 500%. This stable upward trend in average deal size demonstrates that the investments in Marketing Technology have indeed become weightier over time.

Conclusion: Investments in Marketing Technology Are Increasing in Importance

In summary, we have seen from the above graphics that martech funding amounts are on a general upward trend at the annual level, yet its event counts have seen a decline in recent years. Moreover, the average funding deal size has been growing consistently over time. These takeaways lead us to conclude that the investment rounds in martech have become more substantial–in that the bets have become fewer but larger over time. It’ll be interesting to see if this trend continues in 2018.

What are your thoughts on this? Let us know in the comments section below.

To learn more about our complete Marketing Technology research platform, visit us at www.venturescanner.com or contact us at info@venturescanner.com.

Real Estate Technology Sector Overview – Q4 2017

The real estate technology (proptech) sector has seen a lot of funding and exit activity over the past few years. Yet what are the different components of proptech and how do they make up this startup ecosystem? On our real estate technology research platform, we have classified the companies in the sector into functional categories. This blog post aims to examine these categories and how they compare with one another through a series of graphics.

IoT Home Is the Largest Real Estate Technology Category

Let’s start off by looking at the Logo Map for the real estate technology sector. As of January 2018, we have classified 1,613 real estate technology startups into 12 categories which collectively raised $46 billion in funding. The Logo Map highlights the number of companies in each category and a random sampling of these companies.

Real Estate Technology Logo Map
Real Estate Technology Logo Map

We can see from the Logo Map above that IoT Home is the largest real estate technology category with 329 companies. This category is comprised of companies that provide Internet of Things (IoT) devices focused on the residential real estate segment. Some example companies in this category include Ayla Networks, Nest Labs, Dojo Labs, and Entia.

We have seen what the different categories in real estate technology are and how many companies are within each category. What about their funding and maturity in relation to one another? Let’s look at our Innovation Quadrant to find out.

Most of the Real Estate Technology Categories Are Pioneers

Our Innovation Quadrant for the real estate technology sector divides the categories within the sector into four different quadrants according to their average funding and average age. The Heavyweights are the categories with companies that have reached maturity with significant financing. The Established are those that have reached maturity with less financing. The Disruptors are less mature but with significant financing. The Pioneers are less mature and with earlier stages of financing.

Real Estate Technology Innovation Quadrant
Real Estate Technology Innovation Quadrant

We can see from our Innovation Quadrant above that most of the categories within real estate technology belong in the Pioneers quadrant. The Commercial Search category has raised more funding and thus made its way into the Disruptor quadrant. Construction Management and Facility Management are the most mature categories with less funding. Life, Home, P&C Insurance category is in the Heavyweights quadrant for having reached maturity with significant financing.

We’ve now seen how the real estate technology sector is categorized and the relative stages of innovation for those categories. How do these categories stack up against one another in a holistic view? Let’s look at the Total Funding and Company Count Graph.

Commercial Search Is the Best Funded Real Estate Technology Category

The graph below shows the total amount of venture funding and company count in each real estate technology category.

Real Estate Technology Total Funding and Company Count by Category
Real Estate Technology Total Funding and Company Count by Category

We can see from the graph above that while IoT Home has the most companies in the real estate technology sector with 329 companies, it’s the Commercial Search category that leads the sector in total funding with $8.5 billion. The Commercial Search category is comprised of companies that help consumers and businesses find commercial real estate for rent and sale. Some example companies in this category include WeWork, 42Floors, CoworkingON, and PivotDesk.

Conclusion: Most Real Estate Technology Categories Have Large Growth Potential

The graphics above indicate that most of the real estate technology categories are pioneers and show large potential for growth and development. In addition, the sector is bustling with a good number of IoT Home companies. Yet the real estate search companies, including Commercial Search, Short-Term Search, and Long-Term Search, are receiving the lion’s share of the venture funding in the market. It will be interesting to see if this trend continues in 2018.

What are your thoughts on this? Let us know in the comments section below.

To learn more about our complete Real Estate Technology report and research platform, visit us at www.venturescanner.com or contact us at info@venturescanner.com.

Insurtech Exit Activity Growing Over Time

Insurance Technology has become one of the hottest sectors in recent years, with a plethora of companies entering the space. How does its overall exit activity trend over time? On our insurtech research platform, we have analyzed the data through 2017 and can conclude that insurtech exit activity continues to be on a healthy upward trend.

This observation was derived from two takeaways:

  • Insurtech exit events are on a general upward trend at the annual level
  • Insurtech exit events are showing overall growth at the quarterly level

We’ll illustrate these takeaways with two graphics that show insurtech exit activity trends over time.

Insurtech Exit Events On General Upward Trend Annually

We’ll start off by examining the insurtech exit events from 2011 to 2017. Exit events include both acquisitions and IPOs. The below graph highlights the number of insurtech exit events by year stacked by quarters.

Insurance Technology Exits by Quarter - Stacked
Insurance Technology Exits by Quarter – Stacked

This graph illustrates that insurtech exit activity is on a robust upward trend at the annual level. Specifically, the CAGR in exit activity from 2012 to 2017 is 46%.

Let’s now see if the exit activity’s growth trend holds at a quarterly level as well.

Insurtech Exit Events Showing Overall Quarterly Growth

Below is a graph of the number of insurtech exit events by quarter.

Insurance Technology Exits by Quarter - Cluster
Insurance Technology Exits by Quarter – Cluster

The above graph shows that insurtech exit activity is demonstrating overall growth at the quarterly level, with some outlier spikes and dips which are to be expected. The number of exit events in Q1 2017 was 120% of those in Q1 2016. Q2 2017 numbers were 167% higher than the year before. However, Q3 and Q4 of 2017 saw a decline compared to 2016 figures.

Conclusion: Insurtech Exit Activity Is Seeing Overall Growth

In summary, we can conclude from these takeaways that insurtech companies are getting acquired and going public at an increasing pace over time. It’ll be interesting to see if this trend continues into 2018.

What are your thoughts on this? Let us know in the comments section below.

To learn more about our complete Insurance Technology report and research platform, visit us at www.venturescanner.com or contact us at info@venturescanner.com.

Financial Technology Sector Overview – Q4 2017

As we’ve examined in our previous analyses, the overall funding trends in Financial Technology (fintech) are stable and its exit activity is seeing robust growth, indicating that the sector is maturing as a whole. Yet what are the different components of fintech and how do they make up this startup ecosystem? On our fintech research platform, we have classified the companies in the sector into functional categories. This blog post aims to examine these categories and how they compare with one another through a series of graphics.

Payments-Related Companies Form the Largest Fintech Category

Let’s start off by looking at the Logo Map for the fintech sector. As of January 2018, we have classified 2,285 fintech startups into 16 categories which collectively raised $80 billion in funding. The Logo Map highlights the number of companies in each category and a random sampling of these companies. Please note that, for the sake of brevity, certain related categories have been combined into the same box on the Logo Map. Examples include combining Business Lending and Consumer Lending into Lending, and combining Consumer Payments, Payments Backend, and Point of Sale Payments into Payments.

Financial Technology Logo Map
Financial Technology Logo Map

We have seen what the different categories in fintech are and how many companies are within each category. What about their funding and maturity in relation to one another? Let’s look at our Innovation Quadrant to find out.

Most of the Fintech Categories Are Pioneers

Our Innovation Quadrant for the fintech sector divides the categories within the sector into four different quadrants according to their average funding and average age. The Heavyweights are the categories with companies that have reached maturity with significant financing. The Established are those that have reached maturity with less financing. The Disruptors are less mature but with significant financing. The Pioneers are less mature and with earlier stages of financing.

Financial Technology Innovation Quadrant
Financial Technology Innovation Quadrant

We can see from our Innovation Quadrant above that most of the categories within fintech belong in the Pioneers quadrant. The Point of Sale Payments, Business Lending, Consumer Payments, and Consumer Lending categories have raised more funding and are in the Disruptor quadrant. Infrastructure and Transaction Security are the most mature categories with less funding. Payments Backend is in the Heavyweights quadrant for having reached maturity with significant financing.

We’ve now seen how the fintech sector is categorized and the relative stages of innovation for those categories. How do these categories stack up against one another in a holistic view? Let’s look at the Total Funding and Company Count Graph for Fintech.

Consumer Lending Is the Leading Fintech Category

The graph below shows the total amount of venture funding and company count in each fintech category.

Financial Technology Total Funding and Company Count by Category
Financial Technology Total Funding and Company Count by Category

We can see from the graph above that the Consumer Lending category leads all the other fintech categories by a substantial margin, with a total funding of $24 billion and 302 companies. This category is comprised of companies that offer new ways for consumers to obtain personal loans and have their credit risk assessed. Some example companies in this category include SoFi, Avant, CommonBond, and Affirm.

Conclusion: Lending and Payments-Related Categories Dominate Fintech

The graphics above indicate that the Consumer Lending category stands out against other fintech categories in terms of funding and company count. Moreover, other lending and payments-related categories have also acquired significant financing. It will be interesting to see how this sector turns out in 2018.

What are your thoughts on this? Let us know in the comments section below.

To learn more about our complete Financial Technology report and research platform, visit us at www.venturescanner.com or contact us at info@venturescanner.com.

Marketing Technology Startup Highlights  – Q4 2017

Here is our Q4 2017 summary report on the Marketing Technology (Martech) startup sector. The following report includes an overview, recent activity, and a category deep dive.

To learn more about our complete Marketing Technology (Martech) report and research platform, visit us at www.venturescanner.com or contact info@venturescanner.com.

Artificial Intelligence Sector Overview – Q4 2017

As we previously noted, interest in AI has exploded. Its applications can be found in virtually every industry from marketing to healthcare to finance. On our AI research platform, we have classified the companies in the sector into functional categories. This blog post aims to examine these categories and how they compare with one another through a series of graphics.

Machine Learning Applications Is the Largest AI Category

Let’s start off by looking at the Logo Map for the AI sector. As of January 2018, we have classified 2,029 AI startups into 13 categories which collectively raised $27 billion in funding. The Logo Map highlights the number of companies in each category and a random sampling of these companies.

Artificial Intelligence Logo Map
Artificial Intelligence Logo Map

We have seen what the different categories in AI are and how many companies are within each category. What about their funding and maturity in relation to one another? Let’s look at our Innovation Quadrant to find out.

Most of the AI Categories Are Pioneers

Our Innovation Quadrant for the AI sector divides the categories within the sector into four different quadrants according to their average funding and average age. The Heavyweights are the categories with companies that have reached maturity with significant financing. The Established are those that have reached maturity with less financing. The Disruptors are less mature but with significant financing. The Pioneers are less mature and with earlier stages of financing.

Artificial Intelligence Innovation Quadrant
Artificial Intelligence Innovation Quadrant

We can see from our Innovation Quadrant above that most of the categories within AI belong in the Pioneers quadrant. The Smart Robots and Recommendation Engines categories have raised more funding and are in the Disruptor quadrant. Speech-to-Speech Translation and Speech Recognition are the most mature categories with significant funding.

We’ve now seen how the AI sector is categorized, and the relative stages of innovation for those categories. How do these categories stack up against one another in a holistic view? Let’s look at the Total Funding and Company Count Graph for AI.

Machine Learning Applications Category Dominates the Sector

The graph below shows the total amount of venture funding and company count in each AI category.

Artificial Intelligence Total Funding and Company Count by Category
Artificial Intelligence Total Funding and Company Count by Category

We can see from the graph above that the Machine Learning Applications category dominates all the other AI categories by far, with a total funding of $13 billion and 669 companies. This category is comprised of companies utilizing computer algorithms to automatically optimize some part of their operations. Some example companies in this category include CustomerMatrix, Ayasdi, Drive.ai, and Cylance.

Conclusion: The AI Sector is Thriving

The graphics above indicate that the Machine Learning Applications category stands out against other categories in terms of funding and maturity, while most other AI categories are pioneers and show huge potential for growth and development.

What are your thoughts on this? Let us know in the comments section below.

To learn more about our complete Artificial Intelligence report and research platform, visit us at www.venturescanner.com or contact us at info@venturescanner.com.