13 of the hottest 34 cloud-based marketing startups are from the Bay Area, followed by Los Angeles with 3, and Bangalore and New York, both with 2.
14 are in Pre Series A, 7 in A-Stage, 5 in B-Stage and 3 in C-Stage funding rounds.
These and other insights are from a quick analysis completed today using Mattermark Pro, in response to reader requests for more research on marketing startups.
Mattermark uses a combination of artificial intelligence and data quality analysis to provide insights into over 1 million private companies, over 470,000 with employee data, and over 100,000 funding events. In the interest of full disclosure I’m not today and have never done any consulting work of any kind with Mattermark.
Finding The Hottest Cloud-based Marketing Startups
To find the hottest cloud-based marketing startups, an initial query requesting startups competing in the cloud computing and marketing industries was completed. Next, advanced query tools in Mattermark Pro were used to filter out all startups that had exited as indicated by their stage status in Mattermark’s data. This filtered out startups who had been acquired, completed an IPO or had exited through other means. The table below is the result of an analysis completed today with Mattermark data. You can download the table here in Microsoft Excel format.
The Mattermark Growth Score shown in the table below and downloadable Excel file is a measure of how quickly a company is gaining traction at a given point in time. It incorporates the Mindshare Score (web traffic, social traction) as well as business growth metrics (e.g. employee count over time, funding). The underlying assumption is that companies who see growth across these signals are shipping product and talking to customers, and are more likely to continue to grow as a result. This score is not meant to provide guidance on which startup to invest in. Rather it’s a measure of momentum across the metrics and KPIs that Mattermark measures.
The purpose of the index is to understand how business users perceive, plan for and utilize four key technologies: cloud, mobility, security and big data. Dell released the first wave of its results this week and will be publishing several additional chapters throughout 2016. You can download Chapter 1 of the study here (PDF, no opt-in, 18 pp.).
Key take-aways from the study include the following:
Orchestrating big data, cloud and mobility strategies leads to 53% greater growth than peers not adopting these technologies. Midmarket organizations adopting big data alone have the potential to grow 50% more than comparable organizations. Effective use of Bring Your Own Device (BYOD) mobility strategies has the potential to increase growth by 53% over laggards or late adopters..
73% of North American organizations believe the volume and complexity of their data requires big data analytics apps and tools. This is up from 54% in 2014, indicating midmarket organizations are concentrating on how to get more value from the massive data stores many have accumulated. This same group of organizations believe they are getting more value out of big data this year (69%) compared to last year (64%). Top outcomes of using big data include better targeting of marketing efforts (41%), optimization of ad spending (37%), and optimization of social media marketing (37%).
54% of an organization’s security budget is invested in security plans versus reacting to threats.Dell & TNS Research discovered that midmarket organizations both in North America and Western Europe are relying on security to enable new devices or drive competitive advantage. In North America, taking a more strategic approach to security has increased from 25% in 2014 to 35% today. In Western Europe, the percentage of companies taking a more strategic view of security has increased from 26% in 2014 to 30% this year.
IT infrastructure costs to support big data initiatives (29%) and costs related to securing the data (28%) are the two greatest barriers to big data adoption. For cloud adoption, costs and security are the two biggest barriers in midmarket organizations as is shown in the graphic below.
Cloud use by midmarket companies in France increased 12% in the last twelve months, leading all nations in the survey. Of the 11 countries surveyed, France had the greatest increase in cloud adoption within midmarket companies. French businesses increased their adoption of cloud applications and platforms from 70% in 2014 to 82% in 2015.
Key take-aways from the report include the following:
Software & computing (18%), financial (11.6%), manufacturing (10.9%) and retail (9.8%) industries have the highest percentage of programmers creating big data and analytics applications today. Additional industries where big data app development is active and growing include entertainment (7.7%), telecommunications (7.5%), utilities & energy (6.6%) and healthcare (4.6%). The following graphic provides an overview of the industries addressed.
Capturing more information than traditional database practices (22.60%), capturing and analyzing unstructured data (21.10%) and the potential for visualizing or analyzing data differently (20.70%) are the three top use cases driving app development today. Evans Data found that capturing more information than traditional database practices allow increased 6% since last year, making it the top use case in 2015. The following graphic provides the distribution of responses by use cases from the developers surveyed.
Total size of the data being processed (40.8%), complex, unstructured nature of the data (38.1%) and the need for real-time data analysis (17.7%) are the top three factors driving big data adoption over traditional database solutions. Evans Data found that the size and complexity of structured and unstructured data is the catalyst that gets enterprises moving on the journey to big data adoption. The ability to gain greater insights into their data with descriptive, predictive and contextually-driven analytics is the fuel that keeps big data adoption moving forward in all companies.
33.2% of all big data and advanced analytics developers are concentrating on the software & computing industry. Of these developers, 36.7% are working in organizations of 101 to 1,000 employees, 32.9% are in enterprises of 1,000+ employees, and 30.1% are in organizations of 100 employees or less. 42.6% of all big data software development in manufacturing begins in enterprises (1K+ employees).
Enterprises competing in the software & computing industry (17.5%), manufacturing (15.8%) and financial industry (14%) are investing the heaviest in big data and analytics app development. Overall, 32% of big data and analytics projects are custom-designed and produced by system integrators and value-added resellers (SI, VAR). 70% of big data and advanced analytics apps for manufacturing are created by enterprise and system integrator/value-added reseller (SI/VAR) development teams. The following graphic provides an overview of industries targeted by big data, segmented by developer segment.
Sales and customer data (9.6%), IT-based data analysis (9.4%), informatics (8.7%) and financial transactions (8.4%) are the most common big data sets app developers are working with today. In addition marketing, system management, production and shop floor data, and web & social media-generated data are also included. Evans Data found that informatics data sets grew the fastest in the last six months, and scientific computing is now competing with transaction processing systems as a dominant data set developers rely on to create new apps.
Marketing departments have quickly become the most common users of big data and advanced analytics apps (14.4%) followed by IT (13.3%) and Research & Development (13%). Evans Data asked developers which departments in their organizations are putting big data and advanced analytics apps to use, regardless of where they were created. 38.2% of all big data use in organizations today are in customer-facing departments including marketing, sales, and customer service.
Availability of relevant tools (10.9%), storage costs (10.2%) and siloed business, IT, and analytics/data science teams (10.0%) are the top three barriers developers face in building new apps. It’s interesting to note that compliance and having to transition from legacy systems did not score higher in the survey, as these two areas are inordinately more complex in more regulated, older industries. For big data and advanced analytics to accelerate across manufacturing and financial industries, compliance and legacy systems integration barriers will need to first be addressed.
Quality of data (19.2%), relevance of data being acquired (13.5%), volume of data being processed (12.6%) and ability to adequately visualize big data (11.7%) are the four biggest problem areas faced by big data developers today. Additional problem areas include the volume of data in storage (10.5%), ability to gain insight from big data (10.1%) and the high rate of data acquisition (7.6%). The remainder of problem areas are shown in the graphic below.
Providing real-time correlation and anomaly detection of diverse security data (29.9%) and high-speed querying of security intelligence data (28.1%) are the two most critical areas vendors can assist developers with today. Big data and analytics app developers are looking to vendors to also provide more effective security algorithms for various use case scenarios (17.6%), flexible big data analytics across structured and unstructured data (14.2%) and more useful graphical front-end tools for visualizing and exploring big data (5.1%).
Key take-aways from his presentation and the trends announced are provided below:
Enterprise 3D-printing shipments will attain a 64.1% Compound Annual Growth Rate (CAGR) through 2019. David Cearley mentioned during his keynote that jet engines are being 3D printed today. He gave the example to illustrate that 3D printing will continue to gain adoption in more demanding manufacturing environments including aerospace, automotive, energy, medical devices and military-based markets and industries.
Emergence of an entirely new class of business models based on smart machine technologies, advanced analytics and big data. Combining machine learning, continued adoption of Internet of Things (IoT) sensors and supporting data models, and advanced intelligence to interpret and act on the data, Gartner’s predictions set the stage of an entirely new class of business models. Manufacturing-as-a-Service and paying only for the production time used in a factory are within reach for more companies than before based on these predictions.
The device mesh will expand to include IoT-based devices that scale well beyond the enterprise. Gartner is predicting that in the next three years traditional computing and communication devices, including desktop and mobile devices will increasingly be augmented by wearable devices, home electronics including appliances with sensors, transportation-based sensors and data collection devices, and environmental devices all capable of capturing data in real-time.
A digital mesh will continue to proliferate, aligning apps and devices to individuals’ specific roles and tasks. Gartner sees this digital mesh as an expanding series of devices, services, platforms, informational networks and individuals that integrate together and provide contextual intelligence and enabling greater collaboration. The proliferation of the digital mesh will lead to more ambient, contextually intelligent and intuitive app design over time Gartner predicts.
The next twelve months will also see the proliferation of algorithm-based businesses enabling automated background tasks including smart machines. Gartner’s technology trends for 2016 set a solid foundation for the growth of globally-based smart factories and production centers. Acumatica, Plex Systems and other Cloud ERP providers are ideally positioned for this trend, having proven their ability to provide manufacturing intelligence from the shop floor to the top floor. In addition to cloud platforms, these algorithm-based businesses will need to support unstructured data analysis including latent semantic indexing (LSI), data taxonomy and classification algorithms to ensure data fidelity and scalability, and more robust analytics and predictive modeling systems.
Combining algorithms, analytics, data architectures and smart machines have the potential to revolutionize manufacturing quickly. General Electric’s Predix platform, IBM’s IoT Foundation and several other cloud-based IoT platforms are already making progress on transforming the vision of algorithm-based smart machine production strategies into a reality for manufacturers globally.
Gartner sees a new IT reality taking shape. Adaptive security, advanced systems, Internet of Things (IoT), mesh app & service architectures are the catalysts of the new nature of IT that Gartner is predicting.
A graphic illustrating the top 10 strategic trends is show below:
The global SaaS market is projected to grow from $49B in 2015 to $67B in 2018, attaining a CAGR of 8.14%.
Global spending on Infrastructure-as-a-Service (IaaS) is expected to reach $16.5B this year, an increase of 32.8% from 2014.
Cloud applications will account for 90% of worldwide mobile data traffic by 2019, compared to 81% at the end of last year.
These and other insights are from recent cloud computing forecasts and market estimates published by research and advisory consultancies including International Data Corporation (IDC), Forrester, Gartner, Ovum, Wikibon and others.
While the methodologies differ significantly, the findings from a recent Economist Intelligence Unit study provide the galvanizing thread across this diverse set of data. The Economist found that the most mature enterprises are now turning to cloud strategies as a strategic platform for growing customer demand and expanding sales channels. The study found low-maturity or lagging cloud adopters focus on costs more than growth.
Key take-aways from the round-up are provided below:
57% of IT architects and tech professionals are running apps on the Amazon Web Services (AWS) platform today. Rightscale’s 2015 State of the Cloud Report found that AWS adoption is over 4X greater than Microsoft Azure IaaS and 5X that of Rackspace Public Cloud. Rightscale found that AWS, Microsoft Azure IaaS, Azure PaaS, Rackspace Public Cloud and VMWare vCloud Air are the top five public cloud platforms used in enterprises today. Source: RightScale 2015 State Of The Cloud Report
Goldman Sachs is forecasting the cloud infrastructure and platform market will grow at a 19.62% CAGR from 2015 to 2018, reaching $43B by 2018. Their recent market analysis also forecasts that the global market for cloud infrastructure and platforms will grow from $21B this year to $43B by the end of the forecast period. Source: How Big Can The Amazon Web Services Business Grow In The Future?
46% of surveyed firms in the European Union (EU) are using advanced cloud services relating to financial and accounting software applications, customer relationship management or to the use of computing power to run business applications. In 2014, almost twice as many firms used public cloud servers (12%) versus private cloud servers (7%). The following graphic illustrates the degree of dependence on cloud computing, by economic activity, EU-28, 2014. Source: Eurostat Statistics Explained. Cloud computing – statistics on the use by enterprises.
64% of Small & Medium Businesses (SMBs) are already using cloud-based apps, with average adoption being 3 apps. 78% of businesses indicate that they are considering purchasing new solutions in the next 2-3 years creating the potential to move the average number of applications used to 7, with 88% consuming at least one service. Source: The small business revolution: trends in SMB cloud adoption.
Worldwide spending on enterprise application software will grow 7.5% to reach $149.9B in 2015, increasing to more than $201B in 2019 with accelerating cloud adoption driving new software sales. Gartner’s analysis of enterprise software spending shows that alternative consumption models to traditional on-premises licenses are accounting for more than 50% of new software implementations; these include SaaS, hosted license, on-premises subscriptions and open source. Gartner also predicts that by 2020, about a quarter of organizations in emerging regions will run their core CRM systems in the cloud, up from around 10 percent in 2012. Source: Gartner Says Modernization and Digital Transformation Projects Are Behind Growth in Enterprise Application Software Market.