The Boulder BI Brain Trust


Recently in Internet Category

CMOs are Starting to Drive the Next-Gen Application Agenda

| | TrackBacks (0)

A couple of weeks ago my partners and I hosted a meeting of our SaaS advisory board.  This is one of our firm’s four advisory boards.  I had written about the role of these boards and the value our firm and portfolio companies derive from our advisors’ insights, feedback and help.  Our SaaS advisory board includes executives from SaaS application vendors, CIOs and CTOs of companies that are heavy users of SaaS applications, and leading SaaS consultants.  One of the most interesting insights that came out of our meeting was that the Chief Marketing Officers (CMOs) are starting to drive the corporate application agenda.  This is consistent with Laura McLellan’s position who in a recent Gartner webinarstated that by 2017 the CMO will spend more on IT than the CIO, as well as the conclusions presentedhere

There are several reasons for the CMO’s emerging power:

  1. The accelerating move from offline to online for commerce, entertainment, and socialization.  The web with its various personas (desktop, social, mobile, local) is enabling corporations to finally become truly customer-centric, i.e., to understand the problems customers face and provide mutually advantageous solutions.
  2. The big data that is collected from the various online and offline interactions between a consumer and a brand can now be utilized effectively through a new generation of analytic solutions that enable corporations to better target existing customers and prospects with the right message, at the right time through the right channel, as well as to assess the effectiveness of each message based on the resulting actions.
  3. Through the consumerization of the enterprise we are seeing a new generation of easier to “consume” applications that don’t resemble the monoliths of the past but instead take their cues from mobile applications, i.e., task-specific pieces of functionality that are easy to install, learn and use effectively.
  4. The cloud that is making acquisition and deployment of these next-generation applications easier and faster.
  5. The new generation of marketing personnel, including CMOs, that is more analytical, data-driven and technology-savvy.

Today we are seeing marketing departments acquiring applications to address online advertising for brand development and direct response commerce, social and mobile marketing and commerce, and analytics.  Having anticipated this trend, over the past several years Trident Capital has been investing in such applications and today our relevant portfolio includes the online advertising technology companies TurnExelateJiwireBrightrollSojern, the social marketing and commerce applicationsExtole and 8thbridge, and the retail analytic applications company Pivotlink.

Though the opportunities may appear brilliant, based on our experiences with these portfolio companies we have learned that working with the marketing organization also presents several challenges:

  1. There is little tolerance for long application-implementation periods, inappropriately functioning software and need for specialized personnel to operate these applications.  Marketing departments want to see results quickly and, under today’s typical corporate budget environments, they don’t want to have to hire new people just so that they can use a new application.
  2. Short period during which to demonstrate meaningful ROI.  Marketing departments may be willing to evaluate several different applications but they will ultimately commit to the ones that give them quick time to value with sustainable and growing ROI.
  3. Data is not always well organized and structured.  This is area where most frequently application vendors see a big difference between working with the marketing and the IT departments.  For marketing departments managing data and maintaining its quality are new tasks.  This task becomes harder as the volume, velocity, complexity, and structure of customer data are increasing.  Marketing application vendors must be prepared to help by providing appropriate services in this area and thus ensuring that the application’s time to value will be short.
  4. Skills for data analysis for insight-generation are lacking.  While marketing departments are becoming awash in data, they often don’t have the people who can effectively analyze this data.  Again, the marketing application vendors need to step and fill the void by offering their own data analytics and insight generation services.
  5. Shorter initial licensing contracts and smaller marketing campaigns.  As they try to understand the value of the myriad of applications offered to them in order to implement their customer-centric strategies, marketing departments feel that they must first “get their feet wet.“  In most cases this approach results in application licensing contracts that initially are short-term (1-3 months), or in smaller-dollar (typically $10-50K) marketing campaigns.
  6. Need sales people who can first speak the marketer’s language rather than IT’s language.  Over the past 30 years we have trained a cadre of application sales people who are expert at interacting with IT organizations, speaking IT’s language.  This was necessary because front- and back-office enterprise applications, regardless of who was using them, were mostly purchased by the IT organization.  If the next generation of marketing application companies is to be successful, they will need to hire sales people who can interact with marketing executives.
  7. The sales cycles for these applications are becoming longer and more complex (see also here).  Before the final decision for the licensing of these applications is made, IT is now becoming involved, and will continue to do so.  Though the CMO’s prominence is rising, don’t expect the CIO’s role in marketing technology decisions to disappear.  Over the past year our relevant portfolio companies started to see CIOs participating in important procurement decisions involving solutions for the marketing department.
  8. The application’s user experience must be tailored to the marketing department’s users.  We are starting to see application developers creating user experiences that are more akin to the practices being established around consumer software, particularly PostPC consumer applications.  To easily adopt the multitude of new applications offered to them, marketing departments must want to interact with them and must be able to do so easily and with little or, preferably, no training.

As corporations become more customer-centric and the move to online continues, data-driven marketing departments stand to reap big rewards.  For this reason they are acquiring a new generation of applications to help them improve their interactions with customers and prospects regardless of channel. Marketing application vendors must understand this trend along with its positive and negative implications, as well as the evolving roles of CMOs and CIOs, in order to best capitalize on it.

Enhanced by Zemanta

Insight as a Service (Part 3)

| | TrackBacks (0)

A few days ago I presented a webinar on Insight as a Service. In the presentation I tried to provide further details on the concept which I first introduced here and later elaborated here.  I am including the webinar presentation (click on the slide below) and the notes because they elaborate further on Insight as a Service and provide some examples.


Social Business SaaS Applications

| | TrackBacks (0)

A couple of years ago while analyzing the ways SaaS business applications could evolve we started thinking about the social web’s impact on business processes.  At the time, Facebook’s success was accelerating while Twitter and Zynga were emerging. We know that consumer-oriented companies want to engage their customers and prospects in the places they frequent, i.e., the social web.  We also started seeing early signs of consumer-oriented technology adoption by corporations. These realizations made us hypothesize that the social web will figure prominently in the next generation of business applications and that these applications will be built on top of new platforms that have the social web at their core.  To date we have invested in three social application companies: Extole, a company that provides a social marketing application, 8thbridge, a company that provides a social shopping and commerce application, and Jobvite, a company that provides a social recruiting application.

As we examine the characteristics of our three investments as well as those of other relevant companies we have considered investing, we have concluded that the applications developed by such companies:

  1. Are delivered over the cloud.
  2. Automate businesses processes that target individuals (consumers or employees), e.g., marketing, shopping, recruiting, customer experience management, collaboration.  For example, Starbucks’ 13M Facebook fans or Coke’s 11M Facebook fans do nothing for these brands unless they can somehow demonstrate their engagement with each brand. A couple of weeks ago 8thbridge, working with Paramount Pictures, created the Facebook store for the recent Transformers movie.  In the first two days the store went up in resulted in 900K new fans that, most importantly, generated 77K content interactions and also led to many ticket sales.  As consumers increase their participation in social media, business executives continue to create programs to engage with them. In fact, 70% of interactive marketers are currently piloting processes to drive word-of-mouth marketing through their most vocal consumers, 58% have launched systems encouraging consumers to spread company messages; and 47% have launched social tools that allow consumers to support each other, e.g., forums.
  3. Are implemented on new platforms with social networking structures, e.g., enable access and operations on a social graph, and capabilities, e.g., capitalize on the social graph to enable viral distribution, at their core.  In addition, these platforms have global reach, support large partner ecosystems, are device agnostic, support online and mobile communications, advertising and commerce.  Facebook has emerged as the strongest platform with these characteristics, in the same way that Google a few years earlier emerged as a platform for applications that had search at their core.  However, we expect that Google, Microsoft and Apple will soon augment their own web platforms with such features as well.
  4. Are data-centric, in that they generate and operate on big data, and use analytics to provide a variety of insights pertinent to the business.  Insights on how a fan uses his social graph to spread a message about a brand, how to improve user engagement around a brand, identify which customers must be nurtured because they are brand influencers or can attract talent to a particular company, which customers or brand fans must be rewarded because they can address product problems, and which consumers shall be offered a reward, e.g., more frequent flier miles, because they can drive a particular group-buying behavior, e.g., organizing a vacation with a group of their Facebook friends and purchasing plane tickets, identify customers that are ready to defect because they are dissatisfied with a company’s service quality.
  5. Require significant consulting services as corporations are in the very early stages of trying to determine how to take advantage of the social web and appropriately adjust their business processes and practices.  In general, we are seeing that as much as 50% of these companies’ revenue could come from consulting services.  Unfortunately, the established professional services organizations are not yet able to field the right solutions.  As a result, the social application companies end up offering the services themselves.

We continue to look for additional investment opportunities in early and expansion stage companies whose applications use the social web to address important business processes in unique and valuable ways.  Some application categories are becoming overcrowded with companies that have little differentiation and overfunded by investors.  We, however, are looking for the companies that have developed social applications whose value will not become obvious for another couple of years.

eXelate’s DMP

| | TrackBacks (0)

A few days ago eXelate (, one of my portfolio companies, announced the latest release of its Data Management Platform (DMP).  A DMP is software that centralizes the management of online audience data.  It enables marketers to manage pixels, control data access and latency, package and segment data, gain insight into audience activity through the use of analytics, and control privacy.  Similar to Demand Side Platforms (DSP) that enable Real Time Bidding (RTB) and are radically transforming online display advertising, Data Management Platforms are becoming an essential and important component of the emerging display advertising technology stack. 

Because of the DMP’s importance to display advertising, over the past year several companies have announced such solutions.  I organize these solutions into three categories: a) pureplay technology offerings, b) solutions aimed at the advertiser, and c) solutions aimed at the publisher.  The best example of the first category is Demdex ( that was recently acquired by Adobe.  The best examples in the second category are the DMPs offered by BlueKai and by our own portfolio company Turn.  In my opinion, the best example of the final category is eXelate’s DMP, with Rubicon having a potential competitor.

eXelate’s DMP enables publishers and data owners to manage access to their data through a system of configurable connectors.  As publisher websites are increasingly pixelated, eXelate’s DMP helps reduce the impact of these pixels by monitoring site latency and leveraging pixel-free integrations.  eXelate’s DMP also helps publishers leverage data on their own ad inventory and through media extensions.  It enables publishers to build direct relationships with data buyers, set pricing and prioritize their data buying queue, and get visibility into how much revenue audience data is generating including analytics on historical trends relating to pricing and volume.

A major concern for publishers today is data theft.  They want to control audience access by detecting and monitoring third party trackers running on their websites.  However, today they are challenged in determining who is accessing data on their sites and what the associated monetary and privacy risk may be.  eXelate’s DMP allows them to gain the appropriate visibility.  By also incorporating the latest consumer privacy policies it allows audiences to control what information a publisher’s site can collect on them and provides an easy opt-out of all third party cookie activity.  In this way, publishers learn more about their audience.  Publishers can then incorporate eXelate’s data about their visitors in order to serve them more relevant ads.

Exelate offers both a data marketplace and a DMP.  The work the company is doing to support its data marketplace customers has provided particularly useful know-how that has been directly reflected in the DMP’s functionality.  For example, the marketplace is already interfacing with hundreds of publishers and has server to server integration with many DSPs.  Making these integrations successful in a way that enables RTB has provided valuable knowledge that is reflected in the DMP’s configurable connectors and has resulted in improving its performance, thus reducing latency.  Pureplay DMPs don’t have extensive knowledge in this area unless their customers choose to share their relevant experiences with them and even then one would assume that it will take some time before these are reflected as appropriate DMP characteristics.  Similarly, eXelate has been working for the past couple of years on defining analytics that help its publisher customer analyzing the big data that is transacted in eXelate’s marketplace in order to understand their audience.  Determine which of these analytics need to be supported by the DMP only comes from having such experiences. 

Over the next 12-18 months I expect that Data Management Platforms will be a very active technology area with new offerings specialized by intended user (publisher or advertiser) entering the market, and with several startups being acquired by larger companies, e.g., software providers, data providers, ad agencies, that are in the process of creating complete RTB systems.

Enhanced by Zemanta

Social Commerce and Our Investment in 8thbridge

| | TrackBacks (0)

Today we are announcing our investment in 8thbridge (, a company that provides social commerce solutions to mid- and upper-enterprise customers.  Following our successful investment in Extole (, a company that provides social marketing solutions to the same market segment, we had been looking for an investment in social commerce to round out or portfolio.  The meteoric success of social commerce companies like Groupon, LivingSocial, Gilt, Rue La La, and Haute Look convinced that there will be a need for integrated solutions that enable companies to participate in social commerce.  Brands are aggressively building their Facebook presence to take advantage of where consumers spend their time.  For this reason we believe that they will invest in solutions which enable social interaction on Facebook and use it as an important sales channel.  Over the past two years 8thbridge’s team led by Wade Gerten has developed an innovative social commerce application and has signed up a significant number of large customers including companies such as Delta Airlines, Haute Look, Brooks Brothers, and Mark Avon’s fastest-growing division. 

Consumers connect to a brand on Facebook for three reasons: 1) to stay current on available new products, 2) to receive coupons and discount offers, and 3) to let their friends know about the products they support.  Corporations like Coca Cola, Starbucks, P&G, and Disney have come to realize that consumers are engaging around their brands on Facebook and during the past year they have started investing heavily on marketing programs that to facilitate and enhance this type of engagement.  Social commerce may be a key to demonstrating ROI to brands on Facebook.  Companies use 8thbridge’s solution to enable in-stream shopping in Facebook’s brand’s pages, essentially the equivalent of natural search for a brand.  A recent report published by Booz& Co puts social commerce of hard goods (apparel, tickets, etc.) at $5B during 2011 and projects it to grow to $30B by 2015 split almost evenly between US and the rest of the world, for a growth rate of 56%.

During a relatively short time we’ve seen social commerce solutions evolve in three phases.  The solutions of the first phase offered stores built on the tabs of a brand’s fan page.  The solutions of the second phase offered shopping in the news feed.  Brands can market to consumers who opt-in and they in turn market to their friends.  The most recent solutions are able to utilize the power of the Open Graph enabling consumers to engage their friends, participate in a truly social shopping experience and in the process get better deals.  Several of 8thbridge’s customers, with Delta Airlines being the leading one, have already implemented such third-phase social commerce programs using the company’s solution.

We view social commerce as an extension and complement to ecommerce; certainly not a replacement.  Whereas consumers go to ecommerce sites seeking needed items, they engage in social commerce more for impromptu purchases.  Ecommerce is fueled by paid search, SEO programs.  Social commerce on the other hand is fueled by fans and their friends, paid Facebook ads, and social marketing programs driven by ecommerce sites.  Finally, whereas ecommerce sites use affiliates to drive traffic and sales, social commerce uses affiliates to drive sales within social networks. 

Social commerce is still in its infancy.  We expect that during 2011 brands will continue experimenting with both social marketing solutions as they look to expand their presence on Facebook as well as with social commerce solutions such as those provided by 8thbridge as they try to determine how to best sell to consumers without distracting from the overall Facebook social experience.  We also anticipate that around the 2011 Christmas holiday season companies will start looking for hard ROI metrics for these solutions.  In addition, merchants are also waiting for Facebook’s approach to commerce and how parallel it will be to its approach towards social games.  We look forward to working together with 8thbridge’s team to build a great company around this exciting opportunity.

Areas of Investment Interest for 2011

| | Comments (2) | TrackBacks (0)

Happy New Year to all!  Like every year I am writing about the technology areas I will be following and focusing on during 2011.  These areas build upon those my partners and I followed during 2010.  During the holidays I wrote about online advertising, mobile and social web as areas Trident will continue to target.

  1. Tablets and smartphones.  In a couple of days I’ll be heading to CES where I expect that several vendors will be introducing new tablets and smartphones targeting different customer segments.  My interest around these devices centers on the platforms they support, e.g., HTML5, novel features they will incorporate, e.g., NFC, the new types of applications these features will enable, e.g., mobile wallets, and the types of data they will be generating.  Tablets and smartphones are sensor platforms
  2. Cloud computing, SaaS, and virtualization.  Cloud computing was one of the biggest technology trends for 2010 and corporations continued to virtualize their data centers (see my comments from the Goldman conference). Cloud management and management of virtualized environments are two important areas we are targeting.  Cloud management in particular is becoming a hot space.  We just lost a deal in this area after significant competition with two other venture firms.  I am also following closely the evolution of PaaS platforms and the SaaS applications they will be enabling, particularly now that enterprises have started aggressively adopting SaaS applications and developing their own cloud-based applications.  We will continue looking for context-aware, social (see below) and vertical SaaS applications.  In 2010 we invested in Acclaris (healthcare IT) but passed on several others.
  3. App stores and application models.  I am watching how the app store is developing as a general purpose applicaiton distribution mechanism.  App stores are moving beyond smartphones (see what Apple is doing with the Mac App Store) into other consumer electronics devices, e.g., TVs, cars, (another area I’ll be watching at CES) and finally the enterprise.  An area of interest is application discovery within app stores.  As the number of applications offered by an app store increases, identifying those with the functionality that is appropriate for a particular task or specific business process will become very important.  Finally, between the proliferation of app stores and the more extensive use of PaaS for application development we see a new model emerging for enterprise application delivery and licensing.  Enterprise application functionality will be developed in much smaller chunks and will be priced accordingly, very much like it is happening today in smartphones. 
  4. Social computing for the enterprise. We are focusing on three areas within social computing for the enterprise: customer service where I think there is opportunity for significant innovation in business settings, marketing, where word of mouth and friend referral programs are proving very effective for B2C and B2B businesses, and Facebook ecommerce, because so many companies are now setting up their stores within Facebook.  We are rethinking the workflows and business processes as we try to better understand how social computing can be used effectively in the enterprise.
  5. Big data and analytics. We will be moving from just collecting and managing/organizing big data (web site data, social data, mobile data, data from the Internet of Things) to thinking how to effectively analyze it.  In-memory analytics, Hadoop, Google’s Percolator are technologies we follow.  Privacy and security will be important data-related issues that started coming to fore during 2010 and will remain so during 2011.  While I don’t expect to see technology-driven solutions to these issues, I anticipate that during 2011 we will need to engage in healthy dialogs about what data privacy in today’s environment really means.
Enhanced by Zemanta

Mobile Data Analytics

| | TrackBacks (0)

Over the past couple of years I have met with several startups that offer analytic solutions for mobile data.  I have not invested in any of them.  I had felt that the data captured from feature phones and early generations of smartphones was not rich enough to lead to interesting and distinct analytics.  For example, while data captured from a mobile web browser such as sites visited, pageviews, time spent browsing could be analyzed, we didn’t need a new company to do that.  Omniture could do that just fine.  However, the new smartphones capture more interesting data.  These data sets could drive the creation of a new and interesting analytics.  As a result, I am becoming interested in mobile data analytics and have been actively looking for investment opportunities in this sector.

The new smartphones are becoming sensor platforms, as well as being computing platforms.  In addition to photo and video camera, touch screen, GPS and accelerometer, new types of sensors are being connected to smartphones.  For example, Bling Nation has introduced a sensor that adheres to a smartphone and is linked to the user’s PayPal account.  Our own portfolio company Zeo has announced that it will connect its sensor to the iPhone in order to capture sleep-related data.  Some of the data sets generated by all these sensors that I find interesting include:

  1. The time-series of GPS and accelerometer data for each subscriber.  By analyzing these time-series one can predict where and when the subscriber will be next and offer relevant services at the predicted location, e.g., parking availability with offers from parking garages.
  2. Data generated from the use of augmented reality (AR) application can create new advertising opportunities, as well the opportunities to serve up relevant content the user had not thought to ask for.
  3. Configuration data on the complete software stack running on each phone (from firmware to operating system to application software).  This data can then be used, for example, by an app store to recommend new available applications that will be augment the user’s productivity.  Such configuration databases today exist only in corporate IT settings.
  4. Mobile payments data combined with geolocation data.  Analyzing this data can lead to predictions about customer brand or product loyalty.

Entertainment-related applications, e.g., gaming, and health care applications, e.g., prescription dispensing, will also benefit from the analysis of this type of data.  I am not certain whether new data management systems will be necessary for such data sets, though I imagine that the data will be big and complex, particularly as various time-series are captured, and will be stored in the cloud.

The wireless carriers may not be in the best position of collecting this data, not only because of their lack of experience with diverse data types, but also because they are regulated businesses.  Google and Apple are in a much better position because they already collect much of this data through their Android and iOS platforms respectively.  While these companies may also be best able to mine the data, they won’t enter this business in the near term.  Instead it will be startups that will first experiment with creating interesting data sets out of the collected data and analyzing them.  My assumption, also driving my interest in the sector, is that companies like Google will wait to see how these “experiments” go and proceed to acquire the more interesting of the analytics startup companies.

Users will need to give their permission for this rich data to be collected and combined.  Vendors, including wireless carriers, will get the users’ permission by offering free services (something for which consumers have shown interest and affinity), better experience (optimized bandwidth, improved application performance, more accurate recommendations around applications, products, services, social connections, etc), and more accurate targeting of ads in ad-supported services.

The mobile space remains highly fragmented and the talent to create and analyze these data sets may be hard to find.  The new smartphone platforms present opportunities for collecting valuable data sets that will lead to the development of unique analytics which will in turn drive important and novel decisions.  Startups can lead the way to create these analytics and the enterprise platforms that manage them.

Enhanced by Zemanta

Insight as a Service

| | TrackBacks (0)

The survey data presented in last August’s Pacific Crest SaaS workshop pointed to the need for a variety of data analytic services.  These services that can be offered under, Insight-as-a-Service, can range from business benchmarking, e.g., compare one business to its peers’ that are also customers of the same SaaS vendor, to business process improvement recommendations based on a SaaS application’s usage, e.g., reduce the amount spent on search keywords by using the SEM application’s keyword optimization module, to improving business practices by integrating syndicated data with a client’s own data, e.g., reduce the response time to customer service requests by crowdsourcing responses.  Today I wanted to explore Insight-as-a-Service as I think it can be the next layer in the cloud stack and can prove the real differentiator between the existing and next-generation SaaS applications (see also here, and Salesforce’s acquisition of Jigsaw).

There are three broad types of data that can be used for the creation of insights:

  1. Company data.  This is the data a company stores in a SaaS application’s database.  As SaaS applications add social computing components, e.g., Salesforce’s Chatter, or Yammer’s application, company data will become an even richer set.
  2. Usage data.  This is the Web data captured in the process of using a SaaS application, e.g., the modules accessed, the fields used, the reports created, even the amount of time spent on each report.
  3. Syndicated data.  This is third-party data, e.g., Bloomberg, LinkedIn, or open source, which can be integrated (mashed) with company data and/or usage data to create information-rich data sets. 

Some of the issues that will need to be addressed for such services to be possible include:

  1. Permission to use the data.  For this to be possible, corporations must give permission for their company data to be used by the SaaS vendor for benchmarking.  For example, if Salesforce customers are willing to make their data available then their sales forces’ effectiveness can be benchmarked against that of peer companies.  It may be more likely for companies to give their permission if the data is abstracted or even aggregated in some way.
  2. Data ownership.  The ownership of usage data has not been addressed thus far.  Before creating and offering insights, ownership will have to be addressed by the SaaS vendors and their customers.  Once ownership is established, as I had written before, this data can, at the very least, be used by the SaaS vendor to provide better customer service or even to identify upsell opportunities and customer churn situations.  While some vendors, e.g., Netsuite, are starting to utilize parts of usage data, utilization remains low and scarce. 
  3. Data privacy.  Company and usage data will most definitely include details that may need to be protected and excluded from any analysis.  The SaaS vendors will have to understand the data privacy issues and provide corporate clients with the necessary guarantees.  Thus far SaaS vendors have only had to make data security guarantees.  Privacy concerns around this data will be similar to those that currently surround the internet data that is being used to improve online advertising.
  4. Potential need for pure-play Insight-as-a-Service vendors.  The SaaS application companies may not prove capable of providing such insight services.  It may be necessary to create specialized vendors to offer such services.  Such pure-play vendors may have more appropriate and specialized know-how which will be reflected in their software applications (essentially analytic applications that can organize, manipulate and present insights).  In addition they will be able to offer a broader range benchmarking since they will be able to evaluate data across SaaS vendors.  However, having such vendors will also necessitate the move of company and usage data to yet another location/cloud thus increasing the security and privacy risks. 
  5. Eligibility for accessing these insights and business models under which they can be offered.  One approach would be to only offer such insights to as a separate product by the SaaS application’s vendor to its customers.  Another approach, particularly if the insights are to be created by a pure-play insights vendor, would be for such vendors to create data coops.  Under this scheme corporations contribute company and usage data to the coop, the Insight-as-a-Service vendor analyzes all contributed data, and only offers the results to the companies that belong to the coop.  For this service the vendor can use an annual subscription fee not unlike what industry analysts like Forrester and Gartner charge.  Internet data companies such as Datalogix, that has created a coop with retail purchase data, can serve as good models to consider.  Another business model may be for the vendor, either the SaaS application vendor or the Insight-as-a-Service vendor, to share revenue with the companies providing the company and usage data.  Internet data exchanges like Blue Kai and eXelate would provide good business model examples to imitate. 
  6. Geography.  As we’ve learned with consumer internet data, each country approaches data differently.  For example, European countries are more restrictive with the use of collected data.  SaaS companies must try to learn from the relevant experiences of internet data companies as they determine how to best offer such insight services.
  7. Data normalization.  Usage data will need to be normalized and then aggregated since each customer, and maybe even each individual user, uses a SaaS application differently.  This could be tricky.

Hosted applications need not apply.  Not all vendors will be able to offer such services.  For these services to be successful, data from the entire customer base needs to be aggregated and organized.  This implies that vendors claiming to offer SaaS solutions when they are only offering single-tenant hosted solutions deployed in, what amounts to, private clouds will not be able to provide such insight services.  In fact, multi-tenant architectures will be even more important for insight-generation because they make data aggregation easier.

Insight-as-a-service can become the next layer of the cloud stack (following Infrastructure-as-a-Service, Platform-as-a-Service and Software-as-a-Service).  In addition to SaaS application vendors that can start offering such services, there exists an opportunity to create a new class of pure-play Insight-as-a-Service vendors.  Regardless, vendors will need to start addressing the issues and many more that I can’t anticipate at present.  But since surveyed customers are already starting to ask for such services, it is time to start creating them.  It means that the time for Insight-as-a-Service has arrived.

Enhanced by Zemanta

Trident Capital Internet Portfolio Company Summit

| | TrackBacks (0)

On Friday my partners and I hosted in our office in Palo Alto a meeting with the executives of our online advertising and ecommerce companies.  Executives from Syndero, HomeAway, Zeo, AccountNow, Advanced Payment Solutions, Turn, Sojern and Tellapal participated in the meeting.  The purpose of the daylong meeting was to enable the participants to exchange information and best practices for customer acquisition and improving lifetime value (LTV).  Below are some of the major points that were made during the day:

  1. Being best in class on customer acquisition implies combining the right people, an efficient process, and best in class tools.  The process typically being used involves: creating a control group, hypothesizing a particular behavior of this group that will be capitalized during the marketing campaign, testing the hypothesis on the desired customer touch points (email, search, display, affiliates, etc.), analyzing the test results, learning from the analysis and optimizing, forming a new hypothesis, repeating.  As one of the participating CEOs mentioned “every minute, some aspect of a customer acquisition campaign is being optimized.”
  2. Social media is becoming an increasingly important channel for generating interest in a category but once a company starts promoting their particular brand through the social channel, user engagement appears to drop.  Word of mouth is important but it has not yet been integrated effectively with social media.  This is an area that holds great promise and where the participating companies will be investing over the next 12 months.
  3. Test and measure every parameter that goes into customer acquisition.  Best in class companies can manage very complex test matrices.  It is important to be able to quickly hypothesize and test offers, creative, etc.
  4. The right analytics around the data being collected define best in class companies with the lowest customer acquisition and retention numbers.  Our portfolio companies, by constantly sharing best practices, have moved beyond measuring the effectiveness of customer acquisition campaigns in terms of clicks, and impressions, i.e., website analytics.  Instead they are now measuring the impact of each customer interaction on a particular outcome. 
  5. While companies are investing heavily on improving the quality and the uses of the data they capture through their customer interactions, they were less definitive about the impact of data they purchase from data exchanges.
  6. A good off-the-shelf software platform for direct response/branded response doesn’t exist (investment opportunity?).  The portfolio companies have created such platforms by manually integrating stand-alone applications.  As a result, the operational complexity of working with multiple applications rather than a single platform presents a big challenge for marketers.  Good direct response software platforms can be used not only to improve the effectiveness of customer acquisition and customer retention of existing products, but they can also be used to effectively test the likely success of new products before introducing them to the market. 
  7. Success with online channels is leading our ecommerce companies to start experimenting with offline channels such as Direct Response TV.  Every test associated with an online customer acquisition campaign can become a leading indicating for the effectiveness of a corresponding offline campaign.
  8. The companies are being proactive about data privacy issues.  They are using services, including legal services, on how to best safeguard and use the data they collect and what to include in the creative they test for customer acquisition.
  9. Metrics on how to calculate lifetime value per customer are still evolving.

Not only were the executives able to share best practices and share ideas about how to improve the operations of their respective companies, but after the meeting ended several stayed behind working on business deals between their companies.  A great way to end the week!

New Analytic Applications for the New Data Sets

| | Comments (1) | TrackBacks (0)

On a daily basis Internet publishers (e.g., Yahoo, MTV) and Internet applications such as e-commerce sites (e.g., Amazon, eBay), social networks (e.g., Facebook, MySpace, Tweeter), and ad networks (e.g., VideoEgg, Valueclick) generate very large data sets with new types of data.  For example, a site like may generate 90TB of raw data per year which, after being augmented with demographic and geotagging data, can easily balloon to 700TB.  A recent post on the management of large data states that eBay has a 6.5PB data warehouse and Facebook a 2.5PB data warehouse.  Facebook is capturing 15TB of data daily.  This new, Internet-based data consists of various types of logs, user generated content, etc.  The size of these data sets dwarfs the corporate data, e.g., sales transactions, collected and stored in more “traditional” data warehouses used by the non-internet members of the Global 2000.  These “traditional” data warehouses typically store 600GB-1TB of data.  Most mid-size companies, i.e., companies that do about $400M in annual sales, operate even smaller data warehouses that rarely cross the 300-400GB level.  The existing analytic tools and applications, e.g., Business Objects, or Cognos, were not developed with the intent of operating on anything that resembles the king-size, Internet-based data sets.

During the last couple of years we’ve seen significant innovation in the area of the area of data management, first with the introduction of data warehouse appliances by companies such as Netezza, Datallegro, Greenplum (that were based on relational database technology) and more recently with the introduction of appliances such as Aster’s and Vertica’s that are using column-based databases.  The latter two are starting to be adopted for the management of the Internet-based data.  We have also seen the development of systems such as Hadoop that provides a framework which applications can use to work on very large data sets.  These products are maturing quickly and their use is significantly reducing the cost of managing very large data sets.

While companies are making good progress on managing these very large data sets, their ability to effectively and efficiently analyze these sets is lagging.  Companies like Google, eBay and Yahoo are using internally-developed frameworks (e.g., Google’s MapReduce) and home-grown routines to analyze the data they generate because, in most cases, the existing analysis products they throw at them can’t scale to operate on these sets, or don’t have the necessary functionality to address the questions that must be answered through these analyses.  Sample questions that e-marketers (who represent only one of the constituencies that need to analyze this data) are trying to answer include:

  1. What should my keyword-bidding strategy be (which keywords, what price) for each of Google, Yahoo, and MSN?  How should I allocate my budget between SEM and SEO?
  2. Which ad networks are giving me the best performance?
  3. Across which channels and at what percentages should I allocate my marketing budget to reduce lead acquisition costs and increase conversion rates?

Over the past few months I’ve been meeting with several startups that are developing new analytic applications to address such questions, and am particularly excited about the data analysis innovations they are working on.  Because more money is shifting online and the importance of the decisions made using this new data is rapidly increasing, this area will attract strong investor interest and has the potential of producing several winners.



This page is a archive of recent entries in the Internet category.

E-Commerce is the previous category.

New Media is the next category.

Find recent content on the main index or look in the archives to find all content.