There are several reasons why video consumption is moving online. First, it is consistent with the general trend of consuming media online, e.g., news, and music, because of changing lifestyles, e.g., time constraints, place shifting, etc. Second, even though there are now multiple routes for online video to find its way to the living room, e.g., connected TV, tablet. However, online video consumption is primarily driven by the accelerating adoption of mobile devices, particularly by the Millennials, and the expanding availability of broadband speeds that enable bandwidth hogs, such as video, to be consumed through such devices, e.g., 4G LTE. Third, because the online consumption of video enables “unbundling,” i.e., the idea of paying only for the content a consumer wants to watch, rather than the pre-packaged channel collections offered today by the distributors of linear TV.
While online video advertising budgets are growing and the CPMs of video ads are the highest among those of other online advertising formats, the price of online video ads remains very low compared to the corresponding linear TV ads. Until now three reasons were presented for this discrepancy. First, TV’s large reach, i.e., the audiences for TV content, even low quality content, tends to be much larger than the audience for online video content. Second, agreements that have been in place for decades dictate the allocation of video ad revenues between linear TV video content producers and distributors. This is why, for example, Comcast, a video content distributor, decided to acquire NBC, a video content producer. Online video advertising contracts have been handled separately from linear TV advertising contracts.
This price discrepancy is about to change for four reasons. First, big advertisers want access to Millennials. Second, more original video content developed particularly for online consumption and through mobile devices is becoming available. Third, advertisers and their agencies are packaging online video ads together with linear TV ads. Fourth, accelerating rollout of broadband with speeds that accommodate the consumption of online video.
Millennials are developing completely different habits than any of their preceding generations. The sharing economy is one such characteristic. Their wide use of online resources is another. Advertisers realize that the analytics and segments they had used over the years for TV advertising do not apply to Millennials. In order to create new analytics they need the appropriate audience data. And in order to get the audience data they need to start interacting with Millennials through their preferred channel, i.e., online, and across multiple devices, from smartphones to large screen connected TVs. As a result, advertisers are not only increasing their online spending, but they are also increasing the budgets for the acquisition of online data and associated analytics. Whereas with linear TV the price of a video ad is driven by the overall size of the audience the content can attract, with online video ads the price will be determined by our ability to precisely understand an audience and associating the appropriate content that is surrounded by the right video ads to that audience.
Over the past few years we started seeing the formation of studios targeting exclusively the creation of online video content, including mobile video content. More recently we saw the formation of Multi Channel Networks (MCNs), such as Maker Studios. In the last few days Disney acquired Maker Studios and Dreamworks acquired AwsomenessTV. Other such studios, e.g., Alloy Entertainment and Machinima are also attracting significant investor and acquirer interest. The reason for this activity is because these studios have developed original online video content that is starting to get strong following, particularly in the demographic segments advertisers are interested in.
Our adtech portfolio companies that work on video campaigns, e.g., Brightroll, which until recently were used to dealing with online-only advertising RFPs, are now seeing integrated campaigns that package online and linear TV ads around specific goals and themes. We had started to see that approach initially around the Super Bowl but we are not seeing it around other premium content or events. Advertisers and their agencies realize that because of the duration and format of mobile content there may be very few advertising slots around each piece of content. Determining how to take advantage of these slots in a way that is well integrated with linear TV campaigns becomes an advantage.
Video distributors such as Comcast, Verizon (see Verizon’s acquisitions of Edgecast and Intel’s TV assets), AT&T, DirectTV, and others are accelerating their investments in IPTV and in broadband Internet, rolling out networks that will enable them to offer online video to a larger portion of their subscriber bases. The continued increase in the prices of online video ads will depend greatly on the ability of the IP infrastructure to handle the demand for online video content.
I’m also watching for the adoption of programmatic approaches, currently being used by online advertising including online video advertising, by linear TV advertising. While the public markets have shown that they are disinterested in first generation video advertising networks (see the market performance of recently public companies Tremor Video and YuMe), they have also shown great support for companies with platforms that support programmatic approaches and Real Time Bidding (see acquisition of Adap.tv by AOL). Programmatic approaches enable not only streamline the video advertising process and make it more efficient, but they will also make it more transparent as they will enable better attribution, and measurement. Attribution and measurement, along with verification, have been identified by IAB as three important problems that need to be addressed effectively before online video advertising can be adopted even more broadly.
I expect that programmatic techniques will start being adopted first in conjunction with local TV advertising and particularly around not premium content, instead of premium content, e.g., Super Bowl. The adoption of such technologies will enable media planners to fill out their advertising plans faster and more efficiently. I expect that by 2020 we may see 5% of local TV advertising budgets being addressed through programmatic approaches.
Online video advertising has a great future by itself. However, as it starts to be combined with linear TV advertising to address the realities of today’s video market it represents a very large opportunity that we just started uncovering.
]]>Enterprises must pay attention to 3rd party mobile applications for two reasons. First, in order to determine which of the 3rd party desktop, including browser-based, applications they have previously adopted will need to be mobilized. Second, in order to consider such applications as viable alternatives to internally developed applications whose mobilization is proving unfeasible.
With regards to the horizontal and vertical desktop applications they have already licensed, enterprises face an interesting dilemma. In some cases they may be able to license an adopted application’s mobile version. Because enterprises are increasing the use of mobile devices, many vendors have already developed, or are developing, mobile extensions to their flagship products, e.g., Salesforce, SAP, Microstrategy. In many instances this is the preferred approach because the enterprise is already familiar with the application vendor, has the appropriate license agreements in place, and the relevant data and application integration (and configuration) tasks have already been performed. However, because mobile application development talent is in short supply, many of these mobile application extensions tend to have several issues such as incompatible and even clunky User Experience (UX), security flaws, web-only implementation while a native application would have been a better fit, and poor functionality compared to their desktop counterparts. In many cases the software vendor is not able to incorporate in the mobile app key pieces of functionality that the enterprise had previously configured for the desktop app. For these reasons alone, corporations may want to consider licensing a mobile-only enterprise application from one of the new vendors that are quickly emerging to fill the void (for a partial list of such vendors see here). For example, RoamBI provides a mobile-only application for business intelligence that competes with Microstrategy’s.
Corporations must consider mobile-only third party applications for four additional reasons.
While mobile consumer applications continue to dominate investment and M&A discussions these days, mobile enterprise applications present, internally developed or third-party, present an interesting set of issues that we consider as we determine in which parts of these ecosystems to continue investing.
We have broadly organized the custom mobile application ecosystem into six categories depending on whether the companies provide application:
Customers, employees and partners are expecting mobile enterprise applications that match their mobile consumer experiences. Moreover, as the portion of the enterprise workforce that is becoming mobile is increasing, the applications used must match the employee work norms. As IT departments are quickly finding out, adopting a mobile-first strategy, particularly for their internally developed applications, can be particularly tricky and expensive because in the process they need to:
For these reasons, IT organizations are considering mobile-only versions of applications as a means to better respond to customer, employee and partner needs for mobile applications while better capitalizing on their application development budgets.
]]>I remain bullish on the transformative potential of the Internet in the enterprise that we view as the channel for achieving scale inexpensively and transforming every industry. Three drivers feed our bullishness:
The Internet offers a great opportunity, but also a great challenge for marketers seeking to engage consumers at a time when publishers and platforms are ceding control to users. We see this impacting two areas of focus for Trident: online advertising and marketing applications and services.
Internet advertising has arrived at an important junction that will fuel the next leg of sustained growth. Over the past 10 years we have seen the sector change dramatically. The first wave of Internet advertising growth was driven by direct-response marketing budgets particularly from industries such as auto, travel, tech, telecom, retail, and financial services.
Several structural and technology improvements particularly to display advertising are attracting additional industries but also causing untapped brand budgets sitting inside leader categories to shift. They include:
Taken together, these structural developments will lead to a rising level of confidence among brand-oriented advertisers that will increasingly view online display (in its various forms) as a more desirable complement to, and replacement for, fragmented mass media channels. Brands are allocating an increasing mix of their ad spend to online video. The budget is coming from TV broadcast and print advertising. We see industries such as CPG starting to aggressively allocate budgets to display advertising. While they spend nearly $200 billion globally offline, such advertisers continue to under-invest online.
We are particularly encouraged by projections calling for the share of agency media budgets spent through programmatic channels to increase from 15-20% today to 40-50% by 2015. Some surveys project that between 2012 and 2017 RTB-based spending in the U.S. will grow at a 56% CAGR. Mobile will be a significant driver of overall RTB growth (IDC expects mobile RTB spend in the US will reach $1B by 2015 and $3B by 2017, representing 21% of the total RTB spending).
The accelerating move of consumers and businesses to Internet, as well as the rise of the subscription economy, namely the move to sell products as services sold on a subscription basis, are causing a re-examination of the marketing applications stack. Customers have more knowledge and control over how, when, and why they engage brands. They increasingly expect a unified experience that is consistent across all of their business interactions. Consumers in particular are increasingly empowered to avoid unwanted or undesired marketing. The line between offline and online continues to disappear, and as it does, the line between product and service is also becoming blurred.
As a result of these trends and the associated data explosion traditional marketing approaches are no longer working causing CMOs to reexamine their established practices and assumptions about advertising, demand generation, retention, and loyalty. In the process of this re-examination they are starting to adopt a new class of applications that power awareness, attention, affinity, action, loyalty and optimization. While the space of these new applications today remains extremely fragmented with hundreds of startups having been funded already, large vendors have started to aggressively build, partner with or acquire the technology enabling them to create a new marketing applications stack. To the traditional infrastructure vendors, like IBM, SAP, and Oracle new cloud-based application vendors like SFDC and Adobe have been added, as well as Internet pureplays such as Google, Facebook, Twitter, Linkedin.
The combination of these factors lead us to three observations:
The public enterprise SaaS companies we follow, e.g., Netsuite, Workday, Demandware, Marketo, ServiceNow, Splunk, Jive, Cornerstone OnDemand, have either started announcing or are expected to announce strong 3Q13 results, that are at least in-line with analyst expectations. A big event for the quarter was Veeva’s extremely successful IPO, which, along with the continued strong performance of Athena Health, and Realpage, provide proof points that vertically focused SaaS applications are another growth area for SaaS. The market is also becoming more positive on the public adtech companies driven primarily by RocketFuel’s strong IPO and Adap.tv’s acquisition by AOL for a very nice multiple. The market is also taking into consideration the potential benefits of Facebook’s exchange, starting with the companies that are already part of it. Valueclick and Millennial Media remain in the penalty box. In the case of Millennial the concern is primarily coming from Facebook’s and Google’s moves around mobile adtech. The market is now waiting for Criteo’s IPO in the next few days.
While there was no blockbuster SaaS company acquisition during the quarter, we continued to see strong M&A activity, particularly of smaller companies offering mobile applications. In addition to strategic acquirers, large private equity firms continued to aggressively invest in or acquire smaller, higher growth SaaS companies.
Some thoughts from the quarterly results and the broader market:
One final note: The subscription economy is taking hold in several industries. The SaaS model is quickly migrating to other industries, e.g., retail, publishing, manufacturing, travel. As a result there will be a need for the development of a broader software solution ecosystem that facilitates the functioning of this economy.
]]>Previous enterprise application platforms and their associated architectures were created in order to enable the development of applications that automate complex business processes. The typical enterprise application (internally developed or third-party) tends to have a large footprint, complicated user interface reflecting its complex functionality, long release, deployment and update cycles, and expensive maintenance. SaaS applications have improved on several of these issues, e.g., release, deployment and update cycles have shrunk and maintenance costs have decreased. Based on the examples we’ve seen from the consumer world, mobile applications have completely different characteristics. They provide simple and user-centric functionality, typically automating one task, e.g., making a restaurant reservation, have clean look and feel, small footprint, monetize through new and equally simple business models, and interface with other applications and data through well-defined APIs. Because of their characteristics, security and privacy become more manageable tasks.
Mobile consumer applications are starting to influence how mobile enterprise applications are designed, implemented, deployed and used, regardless of whether their intended user is the corporation’s customer, its employee, or its partner. However, mobile enterprise applications have not yet achieved (and here) the range of functionality, sophistication and refinement of consumer applications. They tend to be straight re-implementations of their desktop counterparts. Fortunately enterprise application developers are starting to re-think how mobile software can best automate business processes while adopting the norms established by mobile consumer applications. In the process they need to make the following important decisions:
After extensive experimentation over the past 8+ years (with the advent of the smartphone), we remain in the very early stages of enterprise mobility. Mobile consumer applications have taught, and continue to teach, enterprise application developers many lessons about design, implementation, distribution and appropriate business models. As the enterprise’s move to mobility is accelerating we will see the emergence of new third-party application leaders since, at least to date, the incumbent enterprise application providers remain too attached to the design and monetization models they established 20+ years ago. In the process, in Apple, Amazon, Google, we are already seeing a new set of mobile infrastructure leaders emerge that are seriously challenging the dominance of traditional enterprise infrastructure providers such as IBM, Oracle and Microsoft. These market conditions make this an excellent time to invest in companies that develop mobile-first enterprise applications. As we did during previous application platform shifts, Trident is aggressively investing in companies that will become tomorrow’s enterprise application leaders by utilizing the mobile platform.
]]>The public enterprise SaaS companies we monitor, e.g., Netsuite, Workday, Demandware, ServiceNow, Jive, Cornerstone OnDemand, have either started announcing or are expected to announce strong 2Q13 results, that are at least in-line with analyst expectations. In fact Netsuite beat analyst expectations. The public adtech companies had a rougher time during 2Q13. Tremor Video and Marin Software are two adtech companies that went public during the quarter and the market didn’t welcome them with open arms. They started trading down soon after their IPO. Similarly, Valueclick and Millennial Media continue to be scrutinized by public markets. Two other private adtech companies, Yume and Adap.tv, are expected to go public during this quarter, and a few more will file to go public before the end of the year. I believe that the companies which have either already filed to go public, or are planning to file, are of higher quality than the ones that have already gone public. As a result, I wouldn’t be surprised if their stocks perform better in the public markets than the current set of public adtech companies.
There were two acquisitions worth mentioning: Salesforce’s acquisition of ExactTarget and Adobe’s acquisition of Neolane. In addition to the size of these transactions, it is interesting to note that they allow both acquirers to strengthen their CMO suites. Another interesting SaaS transaction was the acquisition of CompuCom by TH Lee, a buyout firm. In the broader cloud category I should also mention IBM’s acquisition of SoftLayer. Large private equity firms are increasing the pace of their investments in SaaS and adtech companies, e.g., Insight Venture Partners’ investment in Brightedge. Finally, SAP acquired Hybris which derives a relatively small percentage of its revenue from a SaaS application even though the majority comes from on-premise software.
Positive aspects of our SaaS portfolio’s performance:
Negative aspects of our SaaS portfolio performance:
Under normal market conditions the second quarter tends to be better than the first and this year there was no exception. However, 2Q13 gave us more indications that this can end up being a strong year for our SaaS portfolio if the economy continues to mend and remains in its current trajectory.
]]>Insight generation depends on our ability to a) collect, organize and retain data, b) generate a variety of analytic models from that data, and c) analyze the generated models themselves. Therefore, in order to generate insights, we must have the ability to generate models. And in order to do that we must have data. Insights can be generated from collected data, data derived from the collected data, as well as the metadata of the collected data. This means that we need to be thinking not only about the data collection, management and archiving processes, but also about how to post-process the collected data; what attributes to derive, what metadata to collect.
In some cases data is collected by conducting reproducible experiments or simulations (synthetic data). In other cases there is only one shot at collecting a particular data set. Regardless, insight generation is highly dependent on how an environment is "instrumented." For example, consumer marketers have gone from measuring a few attributes per consumer, think of the early consumer panels run by companies such as Nielsen, to measuring thousands of attributes, including consumer web behavior, and most recently, consumer interactions in social networks. The "right" instrumentation is not always immediately obvious, i.e., it is not obvious which of the data that can be captured needs to be captured. Oftentimes, it may not even be immediately possible to capture particular types of data. For example, it took some time between the advent of the web and our ability to capture browsing activity through cookies. But obviously, the better the instrumentation the better the analytic models, and thus the higher the likelihood that insights can be generated. Knowing how to instrument an environment and ultimately how to use the instrumentation to measure and gather data can be thought of as an experiment-design process and frequently requires domain knowledge.
Insight generation also involves the ability to organize murky data, which is typically the situation with environments involving big data, and focus on the data that makes "sense," given a specific context and state of domain knowledge. Focusing on specific data given a particular data doesn't mean that the rest of the collected data is unimportant. It's just that one cannot make sense of it at that point in time.
It is important to not only collect and organize data, but also to properly archive it, since insight generation may only become possible when a body of archived data is combined with a set of newly collected data under a particular context. Or that the combination of archived with new data may lead to additional insights to those generated in the past. As the body of domain knowledge increases and new data is collected it may be possible to extract new insights even from data collected in the past. Consequently, having inexpensive and scalable big data infrastructures enables this capability.
Insight generation is serendipitous in nature. For this reason, insights are more likely to be generated from the examination of several analytic models that have been created from the same body of data because each model-creation approach considers different characteristics of the data to identify relations. We maintain that model analysis, and therefore insight generation, is facilitated when models can be expressed declaratively. A good example, of the advocated approach is used by IBM's Watson system. This system uses ensemble learning to create many expert analytic models. Each created model provides a different perspective on a specific topic. Watson ensemble learning approach utilizes optimization, outlier identification and analysis, benchmarking, etc. techniques in the process of trying to generate insights.
While we are able to describe data collection and model creation in quite detailed ways, and have been able to largely automate them, this is still not the case with insight generation. This is in fact the most compelling reason for offering insight as a service; because we have not been able to broadly automate the generation of insights. What we have characterized as insight today has to be generated manually by the analysis of each analytic model derived from a body of data, even though there there is academic research that is starting to point to approaches for the automatic generation of insights. The analysis of the derived analytic models will enable us to understand which of the relations comprising a model are simply correlations supported by the analyzed data set (but don't constitute insights because they don't satisfy the other characteristics an insight must possess), and which are actually meaningful, important and satisfy all the characteristics we outlined before.
As I mentioned, in most cases today utilizing insights that are generated manually by experts and offered in the form of a service may be the only alternative organizations have to fully benefit from the big data they collect. The best examples are companies like FICO, Exelate, Opera Solutions, Gaininsight and a few others. However, there are additional advantages to offering insights as a service:
I wanted to close by making the following point: I have argued that
for an insight to be valid it must have an action associated with it.
This action is applied during a decisioning process. The
characteristics of a particular decisioning process will also need to be
taken into consideration during the insight/action-generation process
because the time (and maybe even other costs) allocated to apply a
particular action during the decisioning process is very important.
Watson's Jeopardy play provided a great illustration of this point, as
the system had a limited amount of time to come up with the correct
response to beat its opponents. Below I provide an initial, rudimentary
illustration of the time it needs to take to action specific actions in
particular domains.
We are starting to make progress in understanding the difference between patterns and correlations derived from a data set and insights. This is becoming particularly important as we are dealing more frequently with big data but also because we need to use insights to gain a competitive advantage. Offering insight-generation manual services provides us with some short term reprieve but ultimately we need to develop automated systems because the data is getting bigger and our ability to act on it is not improving proportionately.
]]>An insight is the identification of cause and effect relations among elements of a data set that leads to the formation of an action plan which results in an improvement as measured by a set of KPIs. Insights are discovered by reasoning over the output of analytic models and techniques. This output can take the form of predictions, correlations, benchmarks, outlier identifications and optimizations.
The evaluation of a set of established relations to identify an insight, and the creation of an action plan associated with a particular insight needs to be done within a particular context and necessitates the use of domain knowledge.
Most analytic model outputs do not provide insights. There are two reasons for this. First, the models don't suggest a meaning for each of their findings. Second, they don't put each finding in an actionable context (even if the meaning were known). Finding a pattern doesn't imply that you automatically find meaning and that you understand it. It just implies that you are finding a correlation among a data set. Moreover, finding causality alone is not necessary and sufficient for generating an insight. One needs to be able to derive an action plan that can successfully and effectively, i.e., with impact, be applied in a particular context. This requirement implies that even knowing the meaning of the finding doesn't tell me how to generalize it and use it for something in the context I am trying to impact. That step requires knowledge of my environment (business, social, education, etc.), my strengths and weaknesses, other forces that may enhance or diminish my efforts, etc.
An insight must be:
Because of the above requirements, insight-generation necessitates the deeper analysis, including the causal analysis, of the underlying relation-identification models, rather than just the testing of each model's accuracy, as it is typically done in predictive analytics tasks. Such causal analysis implies that when trying to generate insights it is preferable to utilize machine learning techniques that describe patterns declaratively, e.g., decision trees, rather than black box approaches, e.g., neural nets and genetic algorithms. As a result of this requirement, one may need to sacrifice prediction accuracy and speed for expressiveness. Therefore, one needs to identify the domains where insight-generation may be more important than predictive accuracy. Moreover, because the models themselves need to anallyzed, simpler models may be prefered to more complex ones.
Insight-generation is not a single shot process. Once an insight is generated and the associated action plan is created, it is important to apply the plan in the particular context and measure its impact. The collected data must then be compared to the set of established KPIs in order to determine whether the particular insight/action-plan pair led to an improvement. Depending on this analysis, the system must then decide whether to attempt improving the action plan, create a completely new plan (assuming that alternatives can be found), or try to create a brand new insight. This means that from a set of initial input data the insight-generation system must seek to derive all possible predictions, based on the set of available models.
]]>The decision to employ a custom/private infrastructure for a SaaS application, or, alternatively, the decision to switch from a public to a private infrastructure to develop and deploy such an application are expensive propositions for a SaaS company of any size. Using a private infrastructure means that the SaaS company has full control of its infrastructure but also that a meaningful percentage of its capital is spent for the development, maintenance and upgrading of this private infrastructure. Switching from a public infrastructure to a private one, or even switching among public infrastructures, done without proper planning leads to delays in product release schedules, increased downtime and low customer satisfaction.
SaaS entrepreneurs and management teams are asking two questions regarding the platforms and infrastructures used for their applications so that they can accomplish their development, testing and deployment goals while building profitable companies, maintaining their customers trust and expectations:
We see entrepreneurs selecting a third party platform to start developing their SaaS applications because they instinctively believe that the associated costs, for both development and initial deployment, will low. They are often right about the startup phase of their business. However, the decision for the long term use of such infrastructures is not as simple as it first appears because several interdependent factors need to be considered. They include:
Based on the factors above,
SaaS companies start using public cloud infrastructures and remain in such infrastructures if they target consumer and SMB market segments under business models that allow them to make money using such infrastructures, and can satisfy the SLAs of their target segments. Companies start with public cloud infrastructures and completely migrate to custom/private ones when they want to target mid-upper and global enterprises. If they target both the SMB and the large enterprise segments then they can use a hybrid approach remaining on public infrastructures to address the needs of the SMB segment and using their own private infrastructure to address the large enterprise segment, as Workday does which runs its application on both its own infrastructure, as well as in AWS. In all of these cases when a migration from a public to a private cloud infrastructure is contemplated I advise the companies to build their application assuming a multi-cloud strategy. This means that the application can simultaneously utilize several public cloud infrastructures, or that can it easily migrate from one public infrastructure to another, in this way also avoiding vendor lock-in. The problem with hybrid environments is that you have to keep track of multiple different security platforms and ensure that all aspects of your business can communicate with each other. Finally, if a company develops a SaaS application targeting a regulated industry such as health care or financial services then it needs to build and deploy its application on its own private infrastructure.
Determining the infrastructure and platform on top of which to develop and deploy a SaaS application is not as easy as it may initially appear particularly if the company is thinking long term. The factors I provided above which have been derived from my years of experience in investing in SaaS application companies will hopefully help entrepreneurs and management teams put some structure around this decision.
]]>Based on the results announced to date by the public SaaS companies we monitor, e.g., Netsuite, Demandware, ServiceNow, Jive, Cornerstone OnDemand, their performance during 1Q13 remained strong, in-line with analyst expectations. Workday is also expected to report in-line results, based on analyst predictions. Valueclick and Millennial Media, two public online advertising platform companies we follow, are expected to announce results this week but analysts are already projecting strong results. Though the results are in-line we also hear that the public public SaaS companies continue to be impacted by the global macro environment and the decreasing IT spending.
The IPO market didn’t produce any significant exits during 1Q13. There were a few acquisitions worth mentioning, most notably Google’s acquisition of Channel Intelligence and AthenaHealth’s acquisition of Epocrates. The rest, acquisitions by Jive, Opera Software and Twitter can be characterized as tuck in transactions in the $50M range or below.
Positive aspects of our SaaS portfolio’s performance:
Negative aspects of our SaaS portfolio performance:
We are off to an OK start. We are still very bullish on the growth prospects of all our SaaS portfolio companies (enterprise and adtech) and continue to look for additional investment opportunities even in in these types when the investment conditions are not ideal due to the terms expected by management teams.
]]>Second, while the number of seed-stage companies is increasing dramatically because their founders see opportunities for a quick exit based on the first observation, the number of companies that can receive expansion rounds and make viable acquisition candidates remains small. This is because
Therefore, because the number of the desirable startup acquisition candidates will remain small, large corporations will need to find ways to foster innovation from within. Corporations must also become better at selecting which companies to acquire. In this way will be able to identify companies that can provide the desired innovation in the short term but also have the teams that will stay with the acquiring company thus providing long-term benefits. The capacity of institutional VCs to invest in seed-stage startups will not increase. In fact, it may continue to decrease further. Rather than creating as many seed-stage startups with weak teams, dubious innovations and no long-term prospects, entrepreneurs must seek to form strong teams that can innovate and build large and enduring companies.
]]>Marketing is about acquiring, retaining and growing the value of customers. Online advertising is proving very effective in achieving these goals. It is proving particularly effective for demand-generation through increasing awareness and interest. As a result, and as is shown below, the share of spending for online (or digital) advertising as a percent of total amount being spent on advertising has been increasing and is projected to continue to increase.
Like with every other form of marketing, for customers and prospects to want to engage through online advertising they expect to receive through appropriate channels contextually relevant messages that are specific to them. In a recent study conducted by Forrester, consumers showed that they notice online ads more than other forms of advertising even if they don’t click on them.
Big data is playing an increasingly important role, perhaps the central role, in the improving effectiveness of online advertising. This is because over the past couple of years online advertising has been moving to programmatic buying. Programmatic buying refers to the practice of automating the buying of online ads by using algorithms to drive the best possible price for each impression. This occurs in real time, on demand and on an impression-by-impression basis. Real-time bidding, RTB, refers to the impression-by-impression buying. As it is shown below, programmatic buying saw a significant influx of activity in 2012, growing over 100% in the US to $2.2bn, according to IDC, now represents close to 16% of display advertising, and is expected to grow to over 30% by 2016.
The share of programmatic buying is increasing because of:
Programmatic buying in general and RTB in particular are generating big data. Interestingly, it is not the volume characteristic of big data that is important in this case. The challenge comes from the velocity and variety of the data that is being used in order to make decisions. In RTB decisions have to be made in milliseconds. To make a bid decision, the RTB system must not only use one of more predictive models that have been developed using machine learning techniques, but it must also combine and consider data that is produced, and often changes, at different speeds; some data changes very fast, other less so. Specialized Data Management Platforms, called DMPs, are starting to be used by programmatic buying systems to address the issues relating to volume, variety and velocity of the data. They integrate, manage, and analyze first-, second-, and third-party online and offline data that is used to significantly improve the targeting of online advertising, increase the ability to measure advertising effectiveness by performing more detailed attribution. As online marketing budgets are increasing, and the number of marketing channels is multiplying (for example, for online marketing alone we use email, search, display, social, mobile, video), the importance of attribution is increasing. Marketers are not longer satisfied with last-click attribution but they want to understand which marketing channels contributed to a customer’s decision and by how much. Marketing channel attribution analysis requires sophisticated big data analytics.
While online advertising can benefit significantly from the use of big data management and analytics technologies, digital marketers are facing significant issues applying these technologies effectively. There are two reasons for that.
To succeed in effectively using online advertising solutions and getting the best possible ROI particularly from programmatic buying and RTB, marketers must develop the right big data strategies. These strategies must begin with the development of the appropriate understanding of the big data that is becoming available and being utilized by these increasingly sophisticated solutions, i.e., the “new big data,” rather than by just trying to process the marketing data the organization may have stored and used in the past, the “old big data,” using modern big data analysis techniques. These strategies must provide the proper balance between under-utilization and over-reliance on the new big data. Finally, these strategies must provide the ability to leverage the new big data in a sustainable way to produce repeatable outcomes.
]]>
Mobile World Congress (MWC) is the world’s largest conference focused on mobile technologies with over 70,000 attendees The conference marks a unique opportunity to get a truly global perspective on the trends that will shape the growth of the industry in the coming year. This was my fifth year attending as part of Trident Capital and below are some of the takeaways that I had from meetings with attendees from various carriers, handset manufacturers and software vendors.
No News Can Be Good News
The most noteworthy news to come out of MWC ’13 was a lack of noteworthy announcements. Past years have almost universally included some announcement about a seemingly major change to the mobile ecosystem. Last year was the release of Windows 8, the previous year it was really the coming out party for Android as it ramped from an upstart to the leading mobile OS provider. Yes, there was an announcement of the Firefox OS and yes there was some sabre rattling from Intel/Samsung over Tizen, but for the most part, there was a notable lack of notable news. While the lack of sea change might seem like a net negative, I would argue that the maturation of the market is a net positive for players in the ecosystem. Carriers, handset providers and software / app developers are all more likely to allocate significant resources behind longer term R&D efforts and true innovation with the improved visibility in the mobile landscape.
Impact For Investing: App developers (both consumer and enterprise) are getting more comfortable with supporting two OSs for at least the near term. We view this as a net negative for app development platforms that have been solely focused on solving fragmentation problems but a positive for other enablers of the app ecosystem (app security vendors like Mocana and Arxan, API management vendors, developers of vertical market apps).
Reaching the Next Billion Subscribers
Lots of discussion from carriers and handset makers about the opportunity to capitalize on further penetrating developing markets. Manoj Kohli, CEO of Bharti Airtel (4th largest carrier in the world) told his audience at MWC that the next billion mobile subscribers are going to come from markets like Asia and Africa. Kohli and others pointed to the increased penetration of 3G networks and the dramatic drop in smartphone prices (as low as $30). This was a theme that was opened by the announcement by Safaricom leading up to MWC that they have started to phase out feature phones altogether. While the penetration of smartphones in developed markets like the US and Europe (the penetration rate in both of these markets surpassed 50% last year) has been an important one, the penetration in developing markets has the potential to be much more disruptive. Access to smartphones and mobile broadband represents the first opportunity for many of these individuals to have any access to computers or the Internet. The potential impact for how goods and services are bought, sold and delivered will be massive.
Impact for Investing: This should be a positive across the board as consumer focused app developers see continued 30%+ organic growth. Secondary markets like mobile advertising (Appia, mBlox, Brightroll) that enable this expansion are also likely to see continued growth. Look also for apps that “hack” heretofore analog processes in developing markets (bill pay, government services, workforce management).
Rise of the Phablet / Handset Makers Continue to Try To Break Into Content
A Huawei banner at Barcelona’s airport proudly announced that they were the manufacturer of the “World’s Largest Smartphone”. While it is worth taking a moment to appreciate the irony of this announcement from an industry that spent the last 20 years trying to shrink the size of phones, it does imply an interesting trend as more and more manufacturers release crossover “Phablets” or hybrid tablet / phones. These supersized phones reflect an increased interest from mobile subscribers in consuming media, shopping and richer mobile apps. Carriers, recognizing the importance of this (and the increasing difficulty in differentiating through hardware) to consumers are working hard to find content deals or applications that appeal to consumers. Both of these themes were highlighted in January in Evangelos’ blog posting on the Consumer Electronics Show (CES) in Las Vegas.
Impact for Investing: This may mark a (relative) return in importance for content providers as goliaths like Samsung, Google and Apple look to drive handset sales through content deals. This is also a continuing positive for online retailers and the t-commerce market. Companies like CatalogSpree and Revel Touch that drive great tablet experiences for consumers will likely see the benefits of the continued rise in the market. Second order benefits will likely include players who help monetize the rich video experiences that are being consumed on tablets (Brightroll) as well as driving mobile app downloads (Appia).
Game On For the Mobile Security Market
One of the news items most talked about in the hallways of MWC was the $200M in capital raised by Airwatch and the reported $5M that they spent on their booth (which was almost as large as Samsung’s). There has been significant speculation both last year and this year that consolidation is coming in the MDM / mobile security market as the market matures and vendors start to shake out. This announcement of Airwatch raising a massive war chest (while IPO / other fundraising rumors for Good and Mobile Iron also swirl) may mark the start of this consolidation.
Impact for Investing: There is a tremendous amount of noise in the mobile security space (Trident tracks over 75 vendors in the space). Consolidation in this market and a focus on best in class solutions may be just what the market needs to allow the leading vendors to break out. We view this as a positive for our investments in Mocana, Arxan and Airwatch who are leaders in their respective markets.
Internet of Things
Over the last five years, “The Internet of Things” is likely only rivaled by mobile payments in terms of a meager reality vs hype ratio. Last year featured Vodafone’s connected house and this year was MWC’s Connected City. The big announcements in this space were Qualcomm’s AllJoyn open framework for connected devices (hoping to facilitate discoverability, interoperability and security) and GM’s decision to embed LTE modules in cars starting in 2014 (powered by AT&T). Rajeev Chand at Rutberg gives a good summary of both of these in his research note, but the takeaways can be summarized as: 1) Still a lack of clarity around business model for M2M - until this and consumer willingness to pay is clarified I remain skeptical on the potential for this market 2) GM’s announcement was impressive in that it involves clear guidance on timing of the roll out and which cars would be involved (including lower end models like the Malibu). To me the GM announcement was the most interesting. There is lots of potential for app distributors like Pandora and Yelp as in car apps represent a real opportunity to create value for consumers - which is core to successful mobile deployments. GM’s Vice Chairman Steve Girsky was on stage to make the announcement but his discussion with moderator Rajeev Change seemed to lack an understanding of the full potential of the business opportunity around connected cars. Girsky all but wrote off the opportunity, saying that GM generates $150B in revenues and this “would not move the needle for them.” Steve should note that GM’s EBIT was only $2.8B for 2012 and the potential to get a piece of the profits from reselling broadband connectivity or access to mobile apps through advertising could very easily move the needle at the bottom line.
Impact for Investing: It is likely best to take a “wait and see” approach in this market. While companies like Nest have made tremendous strides in this market, there are many others who are stuck in the starting gates.
Trident Mobile Investment Initiative
Our investment thesis for the mobile space focuses on mobile as a disruptive force- rather than looking at mobility as a vertical market, we look at it is a medium for delivery of information and applications that has the potential to change how business is conducted across the enterprise. This change is both internal (impacting how employees access information and improve productivity through mobile applications) as well as external (how the enterprise interacts with consumers and engages in marketing). We break these opportunities for disruption down into vertical markets and horizontal markets. The vertical markets include Education, Healthcare, Adtech, Retail / e-Commerce and Logistics / Workforce Management. The horizontal markets include CRM, HR Tech, Collaboration, Security and Mobilization of Enterprise Apps. While this list is by no means inclusive (and we expect it to evolve over time), these are the markets we believe are most prone for disruption within our investment horizon of 4-6 years. A more thorough overview of our investment thesis can be reviewed in a subsequent post that includes a presentation at the SEVC Conference that I gave in March (link to follow).
Several of the MWC themes discussed above are important for our investment initiatives and support the opportunities we are pursuing:
Trident Portfolio Companies See Tremendous Opportunity
Trident was well represented at MWC by portfolio companies mBlox, Appia, Brightroll, Turn www.turn.com and Bytemobile (as part of Citrix). mBlox enjoyed lots of buzz from the launch of their Engage product which is focused on broadening their mobile messaging platform to include in-app messaging. The Company received great response from customers and ecosystem partners that were interested in broadening their mobile customer outreach to include in-app messaging and the targeting / tracking capabilities that the Engage product offers.
Bytemobile was front and center as Citrix made a big push to expand their footprint into the mobile carrier market. The $430M acquisition was announced in June of last year following a partnership between the two companies that allowed Bytemobile to integrate Citrix’s load balancers into its mobile solution that was deployed across its 130 operator customers. The merger looks to be a rousing success as evidenced by the Bytemobile signage in the Citrix booth and the amount of foot traffic.
Mobile advertising continued to be a big part of the conference and Trident portfolio companies Appia, BrightRoll and Turn were no exceptions. Turn has enjoyed strong traction in the mobile space since their announcement last year of a partnership with AT&T to combine Turn’s DSP with AT&T’s AdWorks ad network. Appia has also been the beneficiary of telco carrier partnerships, powering app stores for AMX across 18 countries as well as deployments with Vodafone and Airtel. All three of these companies continue to enjoy triple digit growth in mobile advertising in 2012 and 2013.