Tuesday, March 16, 2021

ActiveNav Automates Data Inventory Updates

Our on-going tour of privacy systems has already included stops at BigID  and Trust-Hub, which both build inventories of customer data. Apparently I’m drawn the topic, since I recently found myself looking at ActiveNav, which turns out to be yet another data inventory system. It’s different enough from the others to be worth a review of its own. So here goes.

Like other inventory systems, ActiveNav builds a map of data stored in company systems. In ActiveNav’s case, this can literally be a geographic map showing the location of data centers, starting from a global view and drilling down to regions, cities, and sites. Users can also select other views, including business units and repository types. The lowest level in each view is a single container, whose contents ActiveNav will automatically explore by reading metadata attributes such as field names and data formats.

The system applies rules and keywords to the metadata to determine the type of data stored in each field, without reading the actual file contents. (A supplementary module that allows content examination is due for release soon.)  It stores its findings in its own repository, again without copying any actual information – so there’s no worry about data breaches from ActiveNav itself.

One disadvantage of ActiveNav’s approach is that relying only on metadata limits the chances of finding sensitive information that is not labeled accurately, something that BigID does especially well. Similarly, ActiveNav doesn’t map relations between data stored in different containers, so it cannot build a company-wide data model. This is a strength of Trust-Hub.

Still, ActiveNav’s ability to explore and classify data repositories without human guidance is a major improvement over manually-built data inventories. Its second big benefit is a “data health” score based on its findings. This is calculated for each container with scores for factors including: risk, including intellectual property and security issues; privacy compliance, based on presence of IDs and other data types; and data quality, including duplicate, obsolete, stale and trivial contents. Scores for each container are combined to create scores for repositories, locations, business units, and other higher levels. This gives users a quick way to find problem areas and track data health over time.

ActiveNav addresses what may be the biggest data inventory pain of all: keeping information up-to-date. The system automates the update process by receiving continuous notifications of metadata changes from systems that are set up to send them. In other cases, ActiveNav can query repositories to look for metadata that has been updated since its last visit. Of course, this requires providing the system with credentials to access that information.

ActivNav was founded in 2008. Until recently, it offered only a conventional on-premise software license with one-time costs starting around $100,000. This is sold this primarily through partners who work on data management projects for heavily regulated industries and governments. The company has recently introduced a SaaS version of its data inventory system that starts at $10,000 per year. It also offers data governance and compliance modules.

Wednesday, February 17, 2021

Is Peak Martech Approaching At Last?

Contrary to popular belief, forecasting is easy: tomorrow is nearly always like today. What’s hard is predicting when something will change: a snowstorm, stock market crash, or disruptive technology. Of course, predicting change is also where forecasting is most useful.

In marketing technology, we’ve seen a long succession of sunny days. Every year, the number of systems grows, fed by a proliferation of channels, declining development costs, and easily available funding. The safe bet is the number will grow next year, too. But I think one day soon the pendulum will reverse direction.

I can’t point to much data in support of my position. Surveys do show that marketers don’t use the full capabilities of their existing stacks, which might mean they’re inclined to take a break before making new purchases. But marketers have never used every feature in their old systems before buying new ones. The pandemic probably led to a temporary dip in martech purchases but budgets appear to be opening up again. So the appetite for new martech will likely reappear.

My prediction is based less martech trends than a general impression that many people feel the world is spinning out of control and want to rein it in. Tech in particular is having impacts that no one fully understands. Concerns about disinformation, social media-induced radicalization, lost privacy, and biased artificial intelligence are all part of this. Even in the narrower spheres of martech and adtech, many users feel their systems are too complicated to really understand. Worries about ad fraud, ads appearing in the wrong places, inappropriate personalization, and unintended campaign messages all come down to the same thing: people worry their systems are making unseen bad decisions.

Technologists tend to feel the cure is more technology: smarter AI, systems checking on other systems, and democratized development to let more people build systems for themselves. But there’s an air of hubris to this. Stories from Daedalus to Frankenstein to Jurassic Park warn us advanced technology will ultimately destroy its creators. Every data breach and wifi outage reminds us no technology is entirely reliable and fixing it is beyond most people’s control.

As a result, non-technologists increasingly doubt that technology can solve its own problems. Some people will bury their worries, accepting technology’s risk as the price for its benefits. Others will take the opposite extreme, rejecting technology altogether, or at least to the great degree possible.

But there’s a middle ground between blindly surfing the net and leaving the grid entirely. This is to consciously seek technology that’s simpler and more controllable than current extremes, even if it’s also less powerful as a result. The key is willingness to make that trade-off, which in turn implies willingness to invest the effort needed to assess the relative value vs. risk of different technical options.

Making that investment is probably the biggest change from the current default of accepting technical progress as inevitable and trusting the technologists to appropriately balance risk against rewards when they decide which products to release. In many cases, the cost of assessment will probably be higher than the cost of using the diminished technology itself: that is, the difference in value between a more secure system and a less secure one may be less than the value of the time I spend comparing them. This means the main cost of making this adjustment isn’t the lost value from using safer technology, but the cost of assessing that technology.

In theory, the assessment cost might be reduced by splitting it among many people who would share their results. But here’s where trust comes back into play: if you can’t trust someone else to do accurate research, you can’t decide based on their results. Since loss of trust is arguably the defining crisis of today’s society, you can’t just wave it away with an assumption that people will trust others’ assessments of technology tradeoffs. Rather, the need will be to build technology that is self-evidently understandable, so that each person can assess it for herself. This will reduce the assessment cost that blocks them from choosing simpler solutions.

So here’s where I think we’re headed: away from ever-increasing, and increasingly opaque, technical complexity, and towards technology that’s simpler and more transparent. Remember: simplicity is the goal, and transparency is what makes it affordable. I call this the “new pragmatism”, although I doubt the label will catch on. As the word “pragmatism” suggests, it’s rather boring and a lot of hard work. But compared with the chaos or authoritarianism that seem to be the main alternatives, it’s about the best way we can hope our current chapter will end. After we turn the page, people may later learn to rebuild the presumption of trust that enables non-verifiable relationships.

If you’re still reading this, thanks for your indulgence; I know you don’t come to this blog for half-baked social theories. But these ideas do have direct implications for marketing and martech. If I’m right, both consumers and martech buyers will want simpler, more transparent products. For marketers, this means:

  • The time may finally have come when stripped-down versions replace feature-rich products, with a stress on ease of use rather than power. I know this idea has been tried before without success. But that was during the earlier age of techno-optimism.

  • Buyers may be more interested in products whose actual operation is transparent. This will usually mean status indicators, meters, and diagnostics to show’s happening. In some cases may literally mean see-through designs that let users watch, say, as the dishes are cleaned or the vacuum bag fills with dirt. Whatever it takes for a feeling of control.

  • Privacy will continue to gain importance, with particular emphasis on systems that are private by design rather than user choice. Privacy policies and options are poorly understood and mistrusted, so many consumers would rather buy a system that makes them unnecessary because it can’t collect data or connect to the internet. Of course, they need to be confident the system behaves as promised.

  • Marketing messages should also switch from promoting advanced technology to promoting simplicity, reliability, and clarity. Explanations about what’s inside a product, in terms of the technology, design and manufacturing processes, materials, and people may be more important to buyers looking for reasons to trust.

  • Marketing methods should match the claims, avoiding unnecessary personalization and staying away from mistrusted media. This is a tricky balance because few marketers will want to sacrifice the performance benefits that come from data-driven targeting. But they do need to weigh long-term brand value against short-term campaign results. For what it’s worth, relying more on basic branding and less on advanced technology is itself consistent with the return to simplicity.
  • Martech vendors will want to make all these adjustments in their own marketing. Other considerations include:

    • Artificial intelligence must be understandable. It’s tempting to suggest discarding AI altogether, since it may be the ultimate example of complicated, opaque, and ungovernable technology. But the apparent benefits of AI are too great to discard. The pragmatic approach is to demand proof that AI really delivers the expected benefits. Then, assuming the answer is yes, find ways to make AI more controllable. This means building AI systems that explain their results, let users modify their decisions, and make it easy to monitor their behaviors. These are already goals of current AI development, so this is more a matter of adjusting priorities than taking AI in a fundamentally different direction.

    • Reconsider the platform/app model. This may be blasphemy in martech circles, since the martech explosion has been largely the result of platforms making it easier to sell specialized apps. But the platform/app model relies on trust that apps are effectively vetted by platform owners. If that trust isn’t present, assessment costs will pose a major barrier to new app adoption. At best, buyers with limited resources (which is everyone) would be able to afford fewer apps. At worst, people will stop using apps altogether. So the pragmatic approach for platforms and app developers alike is to work even harder at trust-building. We already see this, for example, in Apple’s new requirements for data privacy labels and tracking consent rules. https://developer.apple.com/app-store/user-privacy-and-data-use/ What Apple hasn’t done is to aggressively audit compliance and publicize its audit programs. The dynamic here is that users will make more demands on platforms to prove they are trustworthy and will concentrate their purchases on platforms that succeed. Since selecting a platform carries its own assessment cost, we can expect users to deal with fewer platforms in total. This means the trend for every major vendor to develop its own platform ecosystem will reverse. Looking still further ahead: fewer platforms gives the remaining platforms have more bargaining power with the app developers, so we can expect higher acceptance standards (good) and higher fees (not so good). The ultimately is fewer app developers as well.

    • Rebirth of suites. That’s not quite the right label since suites never died. But the point is that buyers looking for simplicity and facing higher assessment costs will find suites more appealing than ever. Obviously, the suites themselves must meet the new standards for simplicity, value and transparency, so integrated-in-name-only Frankensuites don’t get a free pass. But once a buyer has decided a suite vendor is trusthworthy, it’s far more attractive to use a module from that suite than to assess and integrate a best-of-breed alternative. Less obvious but equally true: building a system in-house also becomes less attractive, since in-house developers will also need to prove that their products are effective and reliable. This will necessarily increase development costs, so the build/buy balance will be tilted a little more towards buying – especially if the assessment costs of buying are minimal because the purchased option is part of a trusted suite. It’s true that this doesn’t apply if companies require users to accept whatever their in-house developers deliver. But that doesn’t sound like a viable long-term approach in a world where the gap between poor in-house systems and good commercial products will be larger than ever.

    • Limits on citizen developers. If blasphemy comes in degrees, this takes me to the professional-grade, eternal-damnation level. On one hand, nothing is more trusted than something a citizen developer creates for herself: she certainly knows how it works and can build in whatever transparency and monitoring she sees fit. So the new-pragmatic world is likely to see more, not fewer, user-built systems. But if we’re learned anything from decades of using Excel, it’s that complex spreadsheets almost always contain hidden errors, are opaque to anyone except (maybe) the creator, and are exceedingly fragile when change is required. Other user-built solutions will inevitably have similar problems. So even if users trust whatever they’ve built for themselves, everyone else in the organization will, and should be, exceedingly cautious in accepting them. In other words, the assessment cost will be almost insurmountably high for all but the simplest citizen-developed applications. This puts a natural, and probably shrinking, limit on the ability of citizen-developed systems to replace commercial software or in-house systems built by professional developers. In practice, citizen development will be largely limited to personal productivity hacks and maybe some prototyping of skunkworks projects. This doesn’t mean that no-code and low-code tools are useless: they will certainly be productivity-enhancers for professional developers. Don’t sell those Airtable options just yet.

    I’ll caution again that the picture I’m drawing here is far from certain to develop. I could be wrong about the change in social direction – although the alternative of continued disintegration is ugly to contemplate. Even if I’m right about the big shift, I could be wrong about its exact impact marketing and martech. Still, I do believe that current trends cannot continue indefinitely and it’s worth considering what might happen after their limits are reached. So what I’ll suggest is this: keep an eye out for developments that fit the pattern I’m suggesting and be ready with suitable marketing and martech strategies if things move in that direction. 

    *                *                 *

    Addendum: The core argument of this post is “people feel the world is spinning out of control and trust will solve that problem”. That feels like a non sequitur, since it’s not obvious how trust creates control. It also feels uncomfortably hierarchical, and perhaps elitist, if “control” implies a central authority.  (Note: you might read “control” as referring to people controlling their own personal technology and data. But fully self-sovereign individuals can still cause chaos if there’s not some larger control framework to constrain their actions.)

    But it's not a non sequitur because there is in fact a clear relationship between trust and control. Specifically:

    • Trust can be defined as the belief that someone will act in the way you want them to
    • Control is a way to force someone to act in the way you want. 
    • Thus, trust and control are complementary: the greater trust you have in someone, the less control you need over them (to still ensure they act the way you want).
    Although power-hungry people might enjoy control for its own sake, most people will care only about achieving the desired result. So the solution to a world “spinning out of control” isn’t necessarily reinstating hierarchical, elite authority; it can also be generating trust.  Both yield the same outcome of predictable desired behaviors. 

    This applies in particular to the discussion of citizen development and no-code software, which seems to imply that applications can only be used by more than one person if there’s a central authority to coordinate and approve them.  This is where "governance" comes in.  It's correct that self-built software needs to meet certain standards to be safely used and shared.  But "governance" can be achieved either through control (a central authority enforces those standards) or through trust (convincing users to apply those standards by themselves).  Either approach can work but trust is clearly preferable.


    Wednesday, January 27, 2021

    Lego Blocks, Pickup Trucks, and Why Bloomreach Bought Exponea

    Yesterday brought news that CDP Exponea had been purchased by ecommerce recommendation engine Bloomreach. The deal almost exactly parallels last year’s merger between RichRelevance and Manthan, as well the smaller-scale combination of CrossEngage with Gpredictive. It also recalls other recent CDP acquisitions including Acquia buying AgilOne, Chapsvision buying NP6, SAP buying Emarsys, and Wunderkind buying SmarterHQ.

    It’s easy (and correct) to see these deals as efforts to assemble comprehensive marketing suites. But it's not just that the buyers want to add a CDP their collection.  These deals all involve CDPs with marketing automation functions (that is, segmentation, message selection, campaigns, personalization, and cross-channel orchestration). CDP Institute labels these as “campaign" or "delivery”; others sometimes refer to them as “activation” or “execution” CDPs. This type of CDP provides the biggest headstart towards building a marketing suite. The drive to build suites clarifies why predictive analytics vendors Bloomreach, RichRelevance, and Gpredictive are such frequent partners: stand-alone predictive tools are missing nearly all the features needed for a full marketing platform, so they have the most to gain from buying a CDP that fills those gaps.

    Of course, the biggest CDP acquisition of all, Twilio’s purchase of Segment, doesn’t fit this mold. Segment was more of a pure-play or "data" CDP, limited to assembling and sharing customer profiles. But Twilio isn’t looking to build a marketing suite; their core business is call centers and (after buying SendGrid) email messaging. They have their sights set on providing a communications layer to support all customer-facing operations, including sales and service. Still a suite, but a different kind.

    The drive to construct comprehensive marketing suites is interesting because it conflicts with the current notion that marketers don’t want big, integrated products but instead want to create their own collections of components, building some parts with the latest self-service tools and connecting the rest through microservices, open APIs, and other technical wizardry. The pure vision is a distributed, non-hierarchical architecture, modeled roughly on the Internet itself, where any system can connect with any other system. The more practical vision is a platform-centric world where any system can plug into a central platform that provides basic services. In both visions, companies construct their own, highly customized collections of systems that are perfectly tailored to their needs.

    Simply put, the vendors assembling these suites are betting that vision is wrong. They believe – based no doubt on what buyers are telling them – that companies still want to buy an integrated product that meets their needs without any assembly required. The purely practical reason is that companies don’t assemble systems for their own sake; they assemble them as tools to do what’s really important, which is to make money (usually by delivering goods and services to customers). Sure, you can build a pickup truck from Lego blocks and you might even do that for fun.  But if you actually need to haul something, you’ll go to a dealer and buy one.

    In other words, we still live in a world ruled by Raab's Law, which is “Suites win”. (More formally: In the long run, suites always win the competition between suites and best-of-breed systems.) Platforms don’t change this as much as you’d think, because customers always want the platforms themselves to add more features and make them tightly integrated. It's true that buyers want third-party applications that can extend platform capabilities.  It's also in the platform vendors’ interest to be open to those applications since they add value to the platform at little cost to the platform owner. But there’s a time and effort cost to the user of selecting, connecting, and learning to use each new application, regardless of whether the app is “free” or how easily it connects. Users are very aware of these costs, which is why they want the core platform to offer as many features as possible. Put another way: the value of applications is they enable users to add features a platform lacks; but the more features a platform provides internally, the more value it provides from the start. This pushes platform vendors to add features that save users from the need to install apps. Of course, the art of platform management is knowing which features are popular and standardized enough to be incorporated.

    As new features are added, platforms increasingly resemble integrated suites. The significant difference from suites is that platforms offer users the option to replace the platform’s default components with external alternatives. But if the platform builders do their jobs correctly, users will find less need to do that over time.

    This is what makes campaign CDPs so attractive to companies attempting to construct a new marketing suite. The marketing features of the CDPs provide a core of functionality that marketers are looking for. In addition, and crucially, the core CDP features make it easier for the suite vendor to integrate components of its own system and also enable the vendor to offer platform-style flexibility by connecting with external systems.

    What, then, do these acquisitions tell us about the future of the CDP industry? The first thing to realize is that most CDPs already fall into the campaign and delivery categories (70% of the industry, measured on company count or employment, according to our statistics).  Most of these firms actually started as marketing automation, personalization, or delivery systems and added CDP capabilities later. Some already provide an integrated marketing suite; the others can expand in that direction on their own or through combinations with other products.  

    It will be increasingly difficult for this type of CDP to survive without a broad set of marketing functions. Competitive pressures will force them to improve those features while treating core CDP capabilities of building and sharing unified profiles as just one talking point.  We've already seen limit their investment in CDP features and instead partner with other data-oriented CDPs to meet those needs.  (We also expect these firms to increasingly specialize by industry and company size. This makes it easier for them to build connectors to operational systems such as point of sale in retail or reservations in travel, as well as building industry-specific features, hiring industry-expert staff, and fine-tuning delivery and pricing models to meet target price-points.)

    The other 30% of the CDP industry are vendors specializing in data management and analytics. We uncreatively call these "data" and "analytics" CDPs.  Many started life as tag managers, data collection, or predictive modeling systems; others were built as CDPs from the begining. As the Twilio/Segment deal illustrated, data CDPs may also be acquisition targets, especially for companies that are aiming to build a corporate-level backbone rather than a marketing suite.  Firms that aren't acquired will be able to remain independent by offering best-of-breed customer data unification services to companies that need and can pay for a best-of-breed solution. These will likely be large enterprises. This type of CDP will increasingly be purchased by IT and data departments, rather than marketing, and will come to look more like IT tools than end-user applications. As such, they’ll find themselves increasingly competing with general purpose data management tools from other software providers and from data management and analytics tools built into the big cloud platforms (Google Cloud, AWS, Azure). So far, the specialized features of the most sophisticated data CDPs are more advanced than what’s available elsewhere. Some of these vendors will continue to innovate and ultimately emerge as strong leaders in this segment. Others will probably withdraw into niches or sell themselves to other companies that want to jumpstart their own CDP offerings.

    One happy byproduct of these developments may be a final end to the theological debate over the proper definition of “Customer Data Platform”. As the campaign and delivery CDPs position themselves as marketing suites or platforms, they’re likely to move away from CDP as their primary label. But they’ll still need the world to know that they offer the core CDP capabilities of unified profile creation and sharing. With any luck at all, they’ll handle this by labeling those features as "CDP" when they describe their system capabilities. This should eventually lead to a more consistent use of the CDP term throughout the market and, thus, less confusion over what it means. The data and decision CDPs already define CDP in terms of the same core capabilities. Some of those firms are today pulling away from verbal confusion by labeling themselves as “infrastructure” or “pipeline” customer data platforms. If the narrower definition of CDP reasserts itself, they may come back to adopting the CDP label itself.

    Sunday, January 03, 2021

    Software Has Stopped Eating the World

    This August will see the tenth anniversary of Marc Andreessen’s famous claim that software is eating the world. He may have been right at the time but things have now changed: the world is biting back.

    I’m not referring to COVID-19, although it’s fitting that it took an all-too-physical virus to prove that a digital bubble of alternate facts could not permanently displace reality. Nor am I juxtaposing the SolarWinds hack with the unexpectedly secure U.S. election, which showed a simple paper trail succeed while the world’s most elite computer security experts failed.

    Rather, I’m looking at the most interesting frontiers of tech innovation: self-driving vehicles, green energy, and biosciences top my list. What they have in common is interaction with the physical world. By contrast, recent years haven’t seen radical change in software development. There have certainly been improvements in software, but they’re more about architectures (cloud, micro-services) and self-service interfaces than fundamentally new applications. And while most physical-world innovations are powered by software, the importance of those innovations is that they are changing physical experiences, not that they are replacing them with software-based virtual equivalents.

    Even the most important software development of all – artificial intelligence – measures much of its progress by its ability to handle physical-world tasks such as image recognition, autonomous vehicle navigation, and recognizing human emotion. Let’s face it: it’s one thing for a computer to beat you at Go, but quite another for it to beat your dance moves.  Really, what special talent is left for humans to claim as their own?

    The shift is well under way in the world of marketing. One of the more surprising developments of the pandemic year was the boom in digital out-of-home advertising, which includes outdoor billboards and indoor signage. The growth seemed odd, given how much time people were forced to spend at home. But the industry marched ahead, spurred in good part by increased ability to track devices as they move through the physical world. It’s a safe bet that out-of-home ads will grow even faster once people can move about more freely.

    Indeed, the industries hit hardest by the pandemic – travel and events – also show that virtual experiences are not enough. Whatever their complaints before the pandemic, almost everyone who formerly traveled for business or attended business events is now eager to return to seeing people and places in person. The amount of travel will surely be reduced but it’s now clear that some physical interaction is irreplaceable.

    In a similarly ironic way, the pandemic-driven boost to ecommerce has been accompanied by a parallel lesson in the importance of physical delivery. Almost overnight, fulfillment has gone from a boring cost center to a realm of intensive competition, innovation, and even a bit of heroism. Software plays a critical role but it’s a supporting actor in a drama where the excitement is in the streets.

    Still closer to home for marketers, we’ve seen a new appreciation for the importance of customer experience, specifically extending past advertising to include product, delivery, service and support. If the obsession of the past decade has been targeted advertising, the obsession of the next decade will be superior service. This ties into other trends that were already under way, including the importance of trust (earned by delivering on promises through fulfillment, not making promises in advertising) and the shift from prospecting with third party data to supporting customers with first party data. Even at the cutting edge, advertising innovation has now shifted to augmented reality, which integrates real-world experiences with advertising, and away from virtual reality, which replaces the real world entirely.

    This shift has substantial implications for martech.

    - The endless proliferation of martech tools may well continue, especially if the definition of “tools” stretches to include self-built applications. But the importance of tools that only interact with other software will diminish. What will grow will be tools that interact with the real world, and it’s likely those tools will be harder to find and (at least initially) take more skills to use. It’s the difference between building a flight simulator game and an actual aircraft. The stakes are higher when real-world objects are involved and there’s an irreducible level of complexity needed to make things work right.

    - As with all technology shifts, the leaders in the old world – the big software companies and audience aggregators like Facebook and Google – won’t necessarily lead in the new world. Reawakened anti-trust enforcement comes at exactly the worst moment for big tech companies needing to pivot. So we can expect more change in the industry landscape than we’ve seen in the past decade.

    - New skills will be needed, both to manage martech and to do the marketing itself. The new martech skills will involve learning about new technologies and tighter integration with non-marketing systems, although fundamentals of system selection and management will be largely the same. The marketing skill shift may be more profound, as marketers must master entirely new modes of interaction. But, again, the marketer’s fundamental tasks – to understand customer motivations and build programs that satisfy them – will remain what they always were.

    It’s been said that people overestimate short-term change and underestimate long-term change.  The shift from software to physical innovation won’t happen overnight and will never be total. But the pendulum has reversed direction and the world is now starting to eat software. Keep an eye out for that future.

    Sunday, December 13, 2020

    MarTech Plot Lines for 2021

    “Apophenia” – seeing patterns where none exist – is both occupational hazard and job requirement for an industry analyst. The CDP Institute Daily Newsletter provides a steady supply of grist for my pattern detection mill. But the selection of items for that newsletter isn’t random. I have a list of long-running stories that I follow, and keep an eye out for items that illuminate them. I’ll share some of those below.

    Feel free to play along at home and let me know what stories you see developing. Deep State conspiracy theories are out of bounds but you’re welcome to speculate on the actual author(s) of the works attributed to “Scott Brinker”. 


    Everyone knows the pandemic accelerated the shift towards online media that was already under way. A few points that haven’t been made quite so often include:

    - connected TVs and other devices allow individual-level targeting without use of third-party cookies. As online advertising is increasingly delivered through those channels,  the death of cookies becomes less important. Nearly all device-level targeting can also include location data, adding a dimension that cookies often lack.

    - walled gardens (Facebook, Google, Amazon) face increasing competition from walled flower pots – that is, businesses with less data but a similar approach. Retailers like Walmart, Kroger, Target, and CVS have all started their own ad networks, drawing on their own customer data. Traditional publishers like Meredith have collected their formerly-scattered customer data to enable cross-channel, individual-level targeting.  Compilers like Neustar and Merkle are also entering the business. None of these has the data depth or scale of Facebook, Google, or Amazon but their audiences are big enough to be interesting. The various “universal ID” efforts being pursued by the ad industry will enable the different flow pots to cross-pollinate, creating larger audiences that I’ll call walled flower beds unless someone stops me.

    - shoppable video is growing rapidly. Amazon seems unstoppable but it faces increasing competition from social networks, streaming TV, and every other digital channel that can let viewers make purchases related to what they’re watching. The numbers are still relatively small but the potential is huge. And note that this is a way to sell based purely on context, so targeting doesn’t have to be based on individual identities. That will become more important as privacy regulations become more effective at shutting off the flow of third-party personal data.

    - digital out-of-home ads will combine with augmented and virtual reality to create a fundamentally new medium. The growth of digital out of home advertising is worth watching just because DOOH is such a great acronym  . But it’s also a huge story that doesn’t currently get much attention and will explode once people can travel more freely post-pandemic. Augmented and virtual reality are making great technical strides (how about an AR contact lens?) but so far seem like very niche marketing tools. However, the two technologies perfectly complement each other, and will be supercharged by more accessible location data. Watch this space.

    Marketing Technology

    - data will become more accessible. That marketers want to be “data-driven” is old news. What’s changing is that years of struggle are finally yielding progress toward making data more available and providing the tools to use it. As with digital advertising, the pandemic has accelerated an existing trend, achieving in months digital transformations that would otherwise have taken years.  Although internal data is the focus of most integration efforts, access to external data is also growing, privacy rules notwithstanding. Intent data has been a particular focus with recent announcements from TechTarget, ZoomInfo, Spiceworks Ziff Davis, and Zeta Global.

    - artificial intelligence will become (even more) ubiquitous. It seems just yesterday that we were impressed to hear that a company’s product was “AI-powered”. Today, that’s as exciting as being told their offices have “electric lights”. But AI continues to grow stronger even if it doesn’t get as much attention (which the truly paranoid will suspect is because the AIs prefer it that way). Marketers increasingly worry that AI will ultimately replace them, even if it makes more productive before that happens. The headline story is that AI is taking on more “creative” tasks such as content creation and campaign design, which were once thought beyond its capabilities. But the real reason for its growth may be that interactions are shifting to digital channels where success will be based more on relentless analytics than an occasional flash of uniquely human insight.

    - blockchain will quiet down. I’ll list blockchain only to point out that’s been an underachiever in the hype-generation department. Back in 2018 we saw it at least as often as AI. Now it comes up just rarely.  There are many clear applications in logistics and some promising proposals related to privacy. But there’s less wild-eyed talk about blockchain changing the world. Do keep an ear open, though: I suspect more is happening behind the scenes than we know.

    - no-code will continue to grow. If anything has replaced AI as the buzzword of the year, it’s “no code” and related concepts like “self-service” and “citizen [whatever]”. It’s easy to make fun of these (“citizen brain surgeon”, anyone?) but there’s no doubt that many workers become more productive when they can automate processes without relying on IT professionals. The downside is the same loss of quality control and integration posed other types of shadow IT – although no-code systems are more often governed than true shadow IT projects.  In addition, no-code’s more sophisticated cousin, low-code, is widely used by IT professionals.  It’s possible to see no-code systems as an alternative to AI: both improve productivity, one by letting workers do more and other by replacing them altogether. But a more realistic view is to recognize AI as a key enabling technology inside many no-code systems. As the internal AIs get smarter, no-code will take on increasingly complex tasks, making it more helpful (and more threatening) to increasingly skilled workers.


    The pandemic has changed how marketers (and everyone else) do their work. With vaccines now reaching the public, it’s important to realize that conditions will change again fairly soon. But that doesn’t mean things will go back to how they were.

    - events have changed forever. Yes, in-person events will return and many of us will welcome them with new appreciation for what we’ve missed. But tremendous innovation has occurred in on-line events and more will surely appear in coming months. It’s obvious that there will be a permanent shift towards more digital events, with in-person events reserved for situations where they offer a unique advantage. We can also expect in-person events to incorporate innovations developed for digital events – such as enhanced networking techniques and interactive presentations. I don’t think the significance of this has been fully recognized.  Bear in mind that live events are often the most important new business source for B2B marketers, so major changes in how they work will ramify throughout the marketing and sales process.

    - remote work is here to stay. Like events, marketers’ worksites will drift away from the current nearly-all-digital mode to a mix of online and office-based activities. Also like events, innovations developed for remote work, such as improved collaboration tools, will be deployed in both situations. The key difference is that attendance of most events is optional, so attendees can walk away from dysfunctional changes. Workers have less choice about their environments, so harmful innovations such as employee surveillance and off-hours interruptions are harder for them to reject. Whether these stressors outweigh the benefits of remote work will depend on how well companies manage them, so we can expect a period of experimentation and turmoil as businesses learn what works best. With luck, this will mean new attention to workplace policies and management practices, something many firms have handled poorly in the past. Companies that excel at managing remote workers will have a new competitive advantage, especially since remote work lets the best workers choose from a wider variety of employers.

    - privacy pressures will rise. The European Union’s General Data Protection Regulation (GDPR) wasn’t the first serious privacy rule or the only reason that privacy gained more attention. But its enforcement date of May 25, 2018 does mark the start of an escalating set of changes that impact what data is available to marketers and how consumers view use of their personal information. These changes will continue and companies will find it increasingly important to manage consumer data in ways that comply with ever-more-demanding regulations and give consumers confidence that their data is being handled appropriately. (A closely related subplot is continued security breaches as companies fail to secure their data despite best efforts.  Another is the continued misbehavior of Facebook and other social media firms and increasing resistance by regulators and consumers.  That one is worth a channel of its own.)  Marketers will need to take a more active role in privacy discussions, which have been dominated by legal, security, and IT staffs in businesses, and by consumer advocates, academics, and regulators in the political world. Earning a seat at that crowded table won’t be easy but making their voice heard is essential if marketers want the rules to reflect their needs.

    - trust is under fire. This is a broad trend spanning continents and stretching back for years (see Martin Gurri’s uncannily prescient The Revolt of the Public, published in 2014),  Socially, the trend presents itself as a loss of trust in institutions, the benefits of technology, and credentialed experts in general. In marketing, it shows up as companies voicing disappointment with data-driven analytics and personalization, as consumers not trusting companies to manage or protect their data, as workers' fear that AI systems will harm creativity and codify unfair bias, as widely-noted gaps between what customers want and companies deliver, as “citizen developers” preferring to build their own systems, and as buyers preferring peers, Web searches, social media, and pretty much any other information source to analysts reports.  

    Trust is the theme that connects all the stories I’ve listed above.  Without trust, consumers won’t share their data, respond to marketing messages, or try new channels; governments will push for more stringent privacy and business regulations; workers will be less productive; and all industry progress will move more slowly. The trust crisis is too broad for marketers fix by themselves. But they need to account for it in everything they do, adjusting their plans to include trust-building measures that might not have been needed in a healthier past.  The pandemic will end soon and technologies come and go.  But trust will be a story to follow for a long, long time.

    Wednesday, November 11, 2020

    Trust-Hub Maps Company Data for Privacy and Other Uses

    Marketers care about privacy management primarily as it relates to customer data, but privacy management overlaps with a broader category of governance, risk, and compliance (GRC) systems that cover many data types. Like privacy systems (and Customer Data Platforms), GRC systems require an inventory of existing customer data, including systems, data elements within each system, and uses for each element.   These inventories form the foundation for functions including risk assessments, security, process documentation, responses to consumer data requests, and compliance monitoring.

    Having a single inventory would be ideal. But each application needs the inventory to be presented in its own way. One reason so many different systems gather their own data inventories is that each is limited to its own type of presentation.

    Trust-Hub Privacy Lens avoids this problem by creating a comprehensive data inventory and then enabling users to create whatever views they need. This requires gathering not just a list of data elements, but also documenting the users, systems, geographic locations, and business processes associated with each element. These attributes can then be filtered to create views tailored to a particular purpose. The system builds on this foundation by creating applications for related tasks such as risk analysis, privacy impact assessments, and security risk analysis. Users access the system through customizable dashboards that can highlight their particular concerns.

    Privacy Lens offers a range of methods to collect its inventory. It can import existing information, such as spreadsheets prepared for s compliance reporting or security audits. It can read metadata from common systems including Salesforce and BigID or import metadata gathered by specialized discovery tools. When the data is not already assembled, Trust-Hub can scan existing data sources to create its own maps of data elements or let users enter information manually. In addition to data elements, the system can track business processes, user roles, individual users, resources, locations, external organizations, legal information, and evidence related to particular incidents. This information is all mapped against a master data model, helping users track what they’ve assembled and what’s still missing. The data is held in a graph database, Neo4J, a technology that is particularly good at tracking relationships among different elements.

    Although some Privacy Lens users will focus on loading data into the system, most will be interested in using that data for specific purposes. Privacy Lens supports these with applications. Privacy managers, for example, can see an over-all privacy risk score, a list of open risks, a matrix that helps to prioritize risks by plotting them against frequency and impact, detailed reports on each risk, and additional risk scores for specific data types and processes. These risk scores are based on ten factors such as confidentiality, accuracy, volume, and regulation. The scores enable users to assess not just the risk of violating a privacy regulation, but risk of a security breach and the potential cost of such a breach. Trust-Hub argues that companies tend to focus on compliance risk even though the costs of litigation and reputation loss from a breach are vastly higher than any regulatory fines.

    Privacy officers can also use the system to conduct formal assessments, such as Privacy Impact Assessments, by answering questions in a system-provided template. The system keeps a copy of each assessment report along with a snapshot of the data model when the report is created, making it easy to identify subsequent changes and how they might change the assessment. Compliance and security officers can conduct other assessments within the system, such as tracing risks created when data is shared with external business partners.

    Risks uncovered during an assessment can be assigned a mitigation plan, with tasks assigned to individual users and reports tracking progress towards completion. Data in the model can also create other reports, such as Record of Processing Activity (ROPA), consent dates, and legal justifications. Personal data usage reports can take multiple perspectives, including which systems and processes use a particular data element, which elements are used by a particular system or process, and where a particular individual’s data is held.

    Trust-Hub has two additional products that exploit the Privacy Lens data map. Privacy Hub loads actual customer data from mapped systems, where it can be used to respond to data requests by consumers (Data Subject Access Requests, or DSARs) or answer questions from business partners without revealing personal information (for example, to verify that a particular individual is over 18). Privacy Engine loads masked versions of personal data and makes it available for analysis, so that users can run reports and create lists without being given access to private data.

    Trust-Hub was founded in 2016 and released its first product in 2018. The company now has more than one hundred clients, primarily large organizations selling directly to consumers, and service providers to those companies, such as consultants, system integrators, and law firms. Pricing is based on the number of users and starts around $25,000 per year.

    Sunday, October 11, 2020

    Twilio Buys CDP Segment for $3.2 Billion

    Friday afternoon brought an unconfirmed Forbes report that communications platform Twilio is buying CDP Segment for $3.2 billion. (The all-stock deal was officially announced on Monday.)  It's Twilio’s third acquisition this year, following much smaller deals in January for telephony platform Teravoz and in July for IoT connector Electric Imp.  It comes two years after Twilio’s $3 billion purchase of email platform SendGrid.

    The deal is intriguing from at least three perspectives:

    Valuation: the $3.2 billion price is impressive by any standard. Segment’s current revenue isn’t known, although one published estimate put it at $180 million for 2019.  That sounds a bit high for a company with 450 employees at the time, but let's go with it and assume $200 million for 2020 revenue.  This has Twilio is paying 16x revenue, which is less than the 20x that Salesforce paid for Mulesoft ($6.5 billion on roughly $300 million) but in line with the 15x that Adobe paid for Marketo ($4.7 billion on $320 million)  or 14x that Twilio itself paid for SendGrid ($2 billion on $140 million when the deal was announced; the $3 billion price reflects the subsequent rise in Twilio’s stock). Note that these prices are well above the run-of-the-mill SaaS valuations, which are below 10x revenue.

    Twilio: the SendGrid acquisition marked a major movement of Twilio beyond its base in telephone messaging to support a broader range of channels. If they’re to avoid the fragmentation that has plagued the larger marketing clouds, which also grew by acquisition, they need a CDP to unify their customer data. The big clouds (Oracle, Adobe, Salesforce, Microsoft, SAP) all chose to build their CDPs internally, but Twilio is much smaller and lacks the resources to do the same in a timely fashion. (Even the big clouds struggled, of course). On the other hand, Twilio’s surging stock price makes acquisition much easier. So buying a CDP they can deploy immediately gains them time and a mature product. It also offers entry to 20,000 accounts that might buy other Twilio products, especially given Segment’s position at the heart of their customer data infrastructure.

    Of course, if Twilio really wants to compete with the marketing clouds, it will need to support other channels, most notably Web site management and ecommerce. Note that vendors beyond the clouds are pursuing the same strategy, including Acquia (which bought CDP AgilOne), IBM-spinoff Acoustic, MailChimp, and HubSpot. So the strategy isn’t unique, but it may be the only way for companies like Twilio to avoid being marginalized as apps that depend on major platforms controlled by other vendors. By definition, apps are easily replaced and are therefore easily commoditized. That’s a position to escape if you have the resources to expand beyond it.

    CDP Industry: Segment is/was the largest independent CDP vendor, although Tealium and Treasure Data are close. Other recent CDP acquisitions were mostly mid-tier vendors (AgilOne, Evergage, QuickPivot, Lattice Engines, SessionM). Of these deals, only AgilOne seemed central to the product strategy of the buyers. Segment’s decision to sell rather than try to grow on its own may signal a recognition that it will be increasingly difficult to survive as a general-purpose independent CDP. We’ve already seen much of the industry shift to more defensible niches, including integrated marketing applications and vertical industry specialization. There’s certainly still a case to be made for an independent CDP as a way to avoid lock-in by broad marketing clouds. But there’s no doubt that the marketing cloud vendors’ own CDPs will grab some chunk of the market, and more will be lost to CDPs embedded in other systems (email, ecommerce, reservations, etc.), offered by service vendors (Mastercard, Vericast, TransUnion, etc.) and home-built on cloud platforms like Amazon Web Services and Google Cloud.

    Given these pressures, we’re likely to see additional purchases of CDPs by companies who are trying to build their own complete marketing platforms, including Shopify, MailChimp, HubSpot, and a number of private-equity backed roll-ups. Faced with a daunting competitive situation, many CDP vendors will be interested in selling, even at prices that might not be as high as they once hoped.

    Ironically, none of this bodes ill for the fundamental concept of the CDP itself. Companies will still need a central system to assemble and share unified customer profiles. It is indeed the platform on which the other platforms are built. Whether their CDP is stand-alone software or part of a larger solution doesn’t really matter from the user’s perspective: what matters is that clean, consistent, complete customer data is easily available to any system that needs it. Similarly, companies will still need the skills to build and manage CDPs.  Marketing, data, and IT departments will wrestle with customer data long into the future, and the winners will be best positioned to achieve business success.