Tuesday, August 21, 2018

BadTech Is the Next New Thing

Forget about Martech, Adtech, or even Madtech. The next big thing is BadTech.

I’m referring to is the backlash against big tech firms – Google, Amazon, Apple, and above all Facebook – that have relentlessly expanded their influence on everyday life. Until recently, these firms were mostly seen as positive, or at least benignly neutral, forces that made consumers’ lives easier.  But something snapped after the Cambridge Analytica scandal last March.  Scattered concerns suddenly became a flood of attacks.  From those troubled waters rose a new avatar of world-crushing evil: BadTech.

As a long-standing skeptic (see this from 2016), I’m generally pleased with this development. The past month alone offers plenty of news to alarm consumers:
There's more bad news for marketers and other business people:
Not surprisingly, consumers, businesses, and governments have reacted with new skepticism, concern, and even some action:
But all is not perfect.
  • BadTech firms still plunge ahead with dangerous projects. For example, despite the clear and increasing dangers from poorly controlled AI, it’s being distributed more broadly by Ebay, Salesforce, Google, and Oracle
  • Other institutions merrily pursue their own questionable ideas. Here we have General Motors and Shell opening new risks by connecting cars to gas pumps.  Here – this is not a joke – a university is putting school-controlled Amazon Echo listening devices in every dorm room
  • The press continues to get it wrong. This New York Times Magazine piece presents California’s privacy law as a triumph for its citizen-activist sponsor, when he in fact traded a nearly-impossible-to change referendum for a law that will surely be gutted before it takes effect in 2020.
  • Proponents will overreach. This opinion piece argues the term “privacy policy” should be banned because consumers think the label means a company keeps their data private. This is a side issue at best; at worst, it tries to protect people from being lazy. Balancing privacy against other legitimate concerns will be hard enough without silly distractions.
So welcome to our latest brave new world, where BadTech is one more villain to fear   It's progress that people recognize the issues but we can't let emotion overwhelm considered solutions.  Let’s use the moment to address the real problems without creating new ones or throwing away what’s genuinely good.  We can't afford to fail.

Saturday, August 18, 2018

CDP Myths vs Realities

A few weeks ago, I critiqued several articles that attacked “myths” about Customer Data Platforms. But, on reflection, those authors had it right: it’s important to address misunderstandings that have grown as the category gains exposure. So here's my own list of CDP myths and realities. 

Myth: CDPs are all the same.
Reality: CDPs vary widely. In fact, most observers recognize this variation and quite a few consider it a failing. So perhaps the real myth is that CDPs should be the same. It’s true that the variation causes confusion and means buyers must work hard to ensure they purchase a system that fits their needs. But buyers need to match systems to their needs in every category, including those where features are mostly similar.

Myth: CDPs have no shared features.
Reality: This is the opposite of the previous myth but grows from the same underlying complaint about CDP variation. It’s also false: CDPs all do share core characteristics. They’re packaged software; they ingest and retain detailed data from all sources; they combine this data into a complete view of each customer; they update this view over time; and they expose the view to other systems. This list excludes many products from the CDP category that share some but not all of these features. But it doesn’t exclude products that share all these features and add some other ones. These additional features, such as segmentation, data analysis, predictive models, and message selection, account for most of the variation among CDP systems. Complaining that these mean CDPs are not a coherent category is like complaining that automobiles are not a category because they have different engine types, body styles, driving performance, and seating capacities. Those differences make them suitable for different purposes but they still share the same core features that distinguish a car from a truck, tractor, or airplane.

Myth: CDP is a new technology.
Reality: CDPs use modern technologies, such as NoSQL databases and API connectors. But so do other systems. What’s different about CDP is that it combines those technologies in prebuilt systems, rather than requiring technical experts to assemble them from scratch. Having packaged software to build a unified, sharable customer database is precisely the change that led to naming CDP as a distinct category in 2013.

Myth: CDPs don’t need IT support.
Reality: They sure do, but not as much. At a minimum, CDPs need corporate IT to provide access to corporate systems to acquire data and to read the CDP database. In practice, corporate IT is also often involved in managing the CDP itself. (This recent Relevancy Group study put corporate IT participation at 49%.)   But the packaged nature of CDPs means they take less technical effort to maintain than custom systems and many CDPs provide interfaces that empower business users to do more for themselves. Some CDP vendors have set their goal as complete business user self-service but I haven’t seen anyone deliver on this and suspect they never will.

Myth: CDPs are for marketing only.
Reality: It’s clear that departments outside of marketing can benefit from unified customer data and there’s nothing inherent in CDP technology that limits them to marketing applications. But it’s also true that most CDPs so far have been purchased by marketers and have been connected primarily to marketing systems. The optional features mentioned previously – segmentation, analytics, message selection, etc. – are often marketing-specific. But CDPs with those features must still be able to share their data outside of marketing or they wouldn’t be CDPs.

Myth: CDPs manage only first party, identified data.
Reality: First party, identified data is the primary type of information stored in a CDP and it’s something that other systems (notably Data Management Platforms) often handle poorly or not at all. But nothing prevents a CDP from storing third party and/or anonymous data, and some CDPs certainly do.  Indeed, CDPs commonly store anonymous first party data, such as Web site visitor profiles, which will later be converted into identified data when a customer reveals herself. The kernel of truth inside this myth is that few companies would use a CDP to store anonymous, third party data by itself.

Myth: Identity resolution is a core CDP capability.
Reality: Many CDP systems provide built-in identity resolution (i.e., ability to link different identifiers that relate to the same person).  But many others do not.  This is by far the most counter-intuitive CDP reality, since it seems obvious that a system which builds a unified customer profiles should be able to connect data from different sources.  But quite a few CDP buyers don’t need this feature, either because they get data from a single source system (e.g., ecommerce or publishing), because their company has existing systems to assemble identities (common in financial services), or because they rely on external matching systems (frequent in retail and business marketing). What nearly all CDPs do have is the ability to retain links over time, so unified profiles can be stitched together as new identifiers are connected to each customer’s master ID. One way to think about this is: the function of identity resolution is essential for building a unified customer database, but the feature may be part of a CDP or something else.

Myth: CDPs are not needed if there’s an Enterprise Data Warehouse.
Reality: It’s a reasonable simplification to describe a CDP as packaged software that builds a customer-centric Data Warehouse. But a Data Warehouse is almost always limited to highly structured data stored in a relational database.  CDPs typically include large amounts of semi-structured and unstructured data in a NoSQL data store. Relational technology means changing a Data Warehouse is usually a complex, time-consuming project requiring advanced technical skill. Pushing data into a CDP is much easier, although some additional work may later be required to make it usable. Even companies with an existing Data Warehouse often find a CDP offers new capabilities, flexibility, and lower operating costs that make it a worthwhile investment.

Myth: CDPs replace application data stores.
Reality: Mea culpa: I’ve often explained CDPs by showing separate silo databases replaced by a single shared CDP.  But that’s an oversimplification to get across the concept. There are a handful of situations where a delivery system will read CDP data directly, such as injecting CDP-selected messages into a Web page or exposing customer profile details to a call center agent. But in most cases the CDP will synchronize its data with the delivery system’s existing database. This is inevitable: the delivery systems are tightly integrated products with databases optimized for their purpose. The value of the CDP comes from feeding better data into the delivery system database, not from replacing it altogether.


Myth: CDP value depends on connecting all systems.
Reality: CDPs can deliver great value if they connect just some systems, or sometimes even if they only expose data from a single system that was otherwise inaccessible.  This matters because connecting all of a company's systems can be a huge project or even impossible if some systems are not built to integrate with others.  This shouldn't be used as an argument against CDP deployment so long as a less comprehensive implementation will still provide real value.

Myth: The purpose of CDP is to coordinate customer experience across all channels.
Reality: That's one goal and perhaps the ultimate.  But there are many other, simpler applications a CDP makes possible, such as better analytics and more accurate data shared with delivery systems.   In practice, most CDP users will start with these simpler applications and add the more demanding ones over time.

Myth: The CDP is a silver bullet that solves all customer data problems.
Reality: There are plenty of problems beyond the CDP's control, such as the quality of input data and limits on execution systems.  Moreover, the CDP is just a technology and many obstacles are organizational and procedural, such as cooperation between departments, staff skills, regulatory constraints, and reward systems.  What a CDP will do is expose some obstacles that were formerly hidden by the technical difficulty of attempting the tasks they obstruct.  Identifying the problems isn't a solution but it's a first step towards finding one.

Of course, everyone knows there are no silver bullets but there's always that tiny spark of hope that one will appear.  I hesitate to quench that spark because it's one of the reasons people try new things, CDPs included.  But I think the idea of CDPs is now well enough established for marketers to absorb a more nuanced view of how they work without losing sight of their fundamental value.  Gradual deflation of expectations is preferable to a sudden collapse.  Let's hope a more realistic understanding of CDPs will ultimately lead to better results for everyone involved.

Thursday, August 02, 2018

Arm Ltd. Buys Treasure Data CDP

Customer Data Platform vendor Treasure Data today confirmed earlier reports that it is being purchased by Arm Limited, which licenses semi-conductor technologies and is itself a subsidiary of the giant tech holding company SoftBank. The price was not announced but was said to be around $600 million.

The deal was the second big purchase of a Customer Data Platform vendor in a month, following the Salesforce’s Datorama acquisition. Arm seems a less likely CDP buyer than Salesforce but made clear their goal is to use Treasure Data o manage Internet of Things data. That’s an excellent fit for Treasure Data’s technology, which is very good at handling large volumes of semi-structured data. Treasure Data will operate as a separate business under its existing management and will continue to sell its product to marketers as a conventional Customer Data Platform.

While Arm is an unexpected CDP buyer, the deal does illustrate some larger trends in the CDP market. One is the broadening of CDP beyond pure marketing use cases: as critics have noted, unified customer data has applications throughout an organization so it doesn’t make sense to limit CDP to marketing users. In fact, the time has probably come to remove “marketer-managed” from the formal definition of CDP.  But that’s a topic for another blog post.

A complementary trend is use of CDP technology for non-customer data. Internet of Things is obviously of growing importance and, although you might argue thats IoT data is really just another type of customer data, there’s a reasonable case that the sheer volume and complexity of IoT data rightly justifies considering it a category of its own. More broadly, there are other kinds of data, such as product and location information, which also should be considered in their own terms.

What’s really going on here is that one category of CDPs – the systems that focus primarily on data management, as opposed to marketing applications – is merging with general enterprise data management systems. These are companies like Qubole and Trifacta that often use AI to simplify the process of assembling enterprise data.  These systems do for all sorts of information what a CDP does for customer information. This is a new source of competition for CDPs, especially as corporate IT departments get more involved. There are also a handful of CDP systems, including ActionIQ, Aginity, Amperity, and Reltio, that have the potential to expand beyond customer information. It’s possible that those vendors will eventually exit the CDP category altogether, leaving the field to CDPs that provide marketing-specific functions for analysis and customer engagement. (If that happens, then “marketer-managed” should stay in the definition.)

In any case, the Treasure Data acquisition is another milestone in the evolution of the CDP industry, illustrating that at least some of the systems have unique technology that is worth buying at a premium. I can imagine some of the other data-oriented vendors being purchased for similar reasons. I can also imagine acquisition of companies like Segment and Tealium that have particularly strong collections of connectors to source and target systems. That’s another type of asset that’s hard to replicate.

So we'll see how the industry evolves.  Don't be surprised if it follows several paths simultaneously: some buyers may take an enterprise-wide approach while others limit CDP use to marketing. What I don't yet see is any type of consolidation around a handful of winners who gobble up most of the market share.  That might still happen but, for now, the industry will remain vibrant and varied, as different vendors try different configurations to see which most marketers find appealing.

Wednesday, August 01, 2018

Salesforce Buys Datorama Customer Data Platform: It's Complicated

News that Salesforce had purchased Datorama crossed the wire just as I was starting on two weeks of travel, so I haven’t been able to comment until now. This was purchase was noteworthy as the first big CDP acquisition by a marketing cloud vendor. That the buyer was Salesforce was even more intriguing, given that they had purchased Mulesoft in March for $6.5 billion and that Marketing Cloud CEO Bob Stutz (who announced the Datorama deal) had called CDPs “a passing fad” and said Salesforce already had “all the pieces of a CDP” in an interview in June.

The Salesforce announcement didn’t refer to Datorama as a CDP and Datorama itself doesn’t use the term either. They do meet the requirements – packaged software building a unified, persistent customer database that’s open to other systems – but are definitely an outlier. In particular, Datorama ingests all types of marketing-related data, notably including ad campaign- and segment-level performance information as well as customer-level detail. Their stated positioning as “one centralized platform for all your marketing data and decision making” sure sounds like a CDP, but their focus has been on marketing performance, analytics, and data visualization. Before the acquisition, they told me some of their clients ingest customer-level detail but most do not. So it would appear that while Salesforce’s acquisition reflects recognition of the need for a persistent, unified marketing database (something they didn’t get with MuleSoft), they didn’t buy Datorama as a way to build a Single Customer View.

Datorama’s closest competitors are marketing analysis tools like Origami Logic and Beckon. I’ve never considered either of those CDPs because they clearly do not work with customer-level detail. Datorama competes to a lesser extent with generic business intelligence systems like Looker, Domo, Tableau, and Qlik. These traditionally have limited data integration capabilities although both Qlik and Tableau have recently purchased database building products (Podium Data and Empirical Systems, respectively), suggesting a mini-trend of its own. It’s worth noting that one of Datorama’s particular strengths is use of AI to simplify integration of new data sources. The firm’s more recent announcements have touted use of AI to find opportunities for new marketing programs.

Datorama is much larger than most other CDP vendors: it ranked third (behind Tealium and IgnitionOne) in the CDP Institute’s most recent industry report, based on number of employees found in LinkedIn. The company doesn’t release revenue figures but, assuming the 360 employees currently shown on LinkedIn generate $150,000 each, it would have a run rate of $54 million. (This is a crude guess: actual figure could easily be anywhere from $30 million to $80 million.) Sticking with the $54 million figure, the $800 million purchase price is 15x revenue, which is about what such companies cost. (Mulesoft went for 22x revenue.)  The company reports 3,000 clients, which again is a lot for a CDP but gives an average of under $20,000 per client. That’s very low for an enterprise CDP.  It reflects the fact that most of Datorama’s clients use it to analyze aggregated marketing data, not to manage customer-level details.

Seeing Datorama as more of an marketing analysis system than CDP makes it a little easier to understand why Salesforce continues to work with other CDP vendors. The Datorama announcement was followed a week later by news that Salesforce Ventures had led a $23.8 million investment in the SessionM CDP, which had announced an expanded Salesforce integration just one month earlier  SessionM builds its own database but its main strength is real-time personalization and loyalty. Salesforce in June also introduced Marketing Cloud Interaction Studio, a licensed version of the Thunderhead journey orchestration engine. Thunderhead also builds its own database and I consider it a CDP although they avoid the term, reflecting their primary focus on journey mapping and orchestration. The Salesforce announcement states explicitly that the Interaction Studio will shuffle customers between campaigns defined in the Marketing Cloud’s own Journey Builder, clarifying what any astute observer already knew: that Journey Builder is really about campaign flows, not true journey management.

So, how do all these pieces fit with each other and the rest of Salesforce Marketing Cloud? It’s possible that Salesforce will let Datorama, SessionM, and Interaction Studio independently build their own isolated databases but the disadvantages of that are obvious. It’s more likely that Salesforce will continue to argue that ExactTarget should be the central customer database, something that’s been their position so far even though every ExactTarget user I’ve ever spoken with has said it doesn’t work. The best possible outcome might be for Salesforce to use Datorama as its true CDP when a client wants one, and have it feed data into SessionM, Interaction Studio, ExactTarget, and other Marketing Cloud components as needed.  We'll see if that happens: it could evolve that way even if Salesforce doesn't intend it at the start.

Looking at this from another perspective: the combination of Datorama, SessionM, and Interaction Studio (Thunderhead) almost exactly fills every box in my standard diagram of CDP functions, which distinguishes the core data processing capabilities (ingest, process, expose) from optional analytics and engagement features.  Other Marketing Cloud components provide the Delivery capabilities that sit outside of the CDP, either directly (email and DMP) or through integrations.  The glaring gap is identity linkage, which Datorama didn't do the last time I checked.  But that's actually missing in many CDPs and often provided by third party systems.  Still, you shouldn't be too surprised to see Salesforce make another acquisition to plug that hole.  If you're wondering where Mulesoft fits, it may play a role in some of the data aggregation, indexing, reformatting, and exposing steps; I'm not clear how much of that is available in Datorama.  But Mulesoft also has functions outside of this structure.

In short, it's quite true that Salesforce has all the components of a CDP, especially you include  Datorama in the mix.


The idea of stringing these systems together raises a general point that extends beyond Salesforce.  The reality is that almost every marketing system must import data into its own database, rather than connecting to a shared central data store. I’ll admit I’ve often drawn the picture as if there would be a direct connection between the CDP database and other applications.  This should never have been taken literally. There are indeed some situations where the CDP data is read directly, such as real time access to data about a single customer. But even those configurations usually require the CDP data to be indexed or extracted into a secondary format: absent special technology, you don’t do that sort of query directly against the primary “big data” store used by most CDPs.

Outside of those exceptions, a subset of CDP data will usually be loaded into the primary data store of the customer-facing applications (email, DMP, Web personalization, etc.). Realistically, those data stores are optimized for their own application and the applications read them directly.  There’s no practical way the applications can work without them.

This is a nuance that was rightly avoided in the early days of CDP as we struggled to explain the concept. But I think now that CDP is well enough understood that we can safely add some details to the picture to make it more realistic and avoid creating false expectations. I'll try to do that in the futre.

Friday, July 27, 2018

Get Ready for CDP Horror Stories as Customer Data Platforms Enter the Trough of Dillusionment

It’s nearly a year since Gartner placed Customer Data Platforms at the top of its “hype cycle” for digital marketing technologies. The hype cycle shouldn’t be taken too literally but it does capture the growing interest in CDPs and reminds us to expect this attention to attract critics.

Sure enough, we’ve recently started to see headlines like “Customer Data Platforms: A Contrarian’s View”, “Why Your Customer Data Platform Is a Failure”  and “CDPs: Yet Another Acronym That Lets Marketers Down”.  It's tempting to dismiss such headlines as competitive attacks or mere attempts to piggyback on wide interest in CDPs.   But we should still take a look at the underlying arguments.   After all, we might learn something.

Let’s start with the “Contrarian’s View”, written by Lisa Loftis, a customer data industry veteran who current works for SAS. She offers to debunk two common CDP “myths”: that “CDPs solve a problem unique to marketing” and that “'marketing-managed' means you don’t need IT’s help”.

Regarding the first myth, Loftis says that systems to match customer identities have been available for decades and that departments outside of marketing also need unified data. Regarding the second, she states its best for marketing and IT departments to work together given the complex technical challenges of marketing systems in general and customer data matching in particular.

She’s right.

That is, she’s right that these technologies are not new, that unified data is useful outside of marketing, and that deploying CDPs requires some technical skills. So far a I know, though, she's wrong to suggest that CDP vendors and advocates (obviously including me) claim otherwise. False belief in these myths are not the reasons marketers buy CDPs.

To put it bluntly, the problem that CDP solves isn’t the lack of technology to build unified customer databases: it’s that corporate IT departments haven’t used that technology to meet marketers’ needs. That failure has created a business opportunity that CDPs have filled. It’s the same reason that people hire private security guards when the government's police fail to maintain order.

And, just as good security guards cooperate with the police, CDP systems must integrate with corporate systems and CDP vendors must work with corporate IT.  CDP vendors have designed their systems to be easier to use than traditional customer matching and management technologies, but that only reduces the technical effort without eliminating it. The remaining technical work may be done by the CDP vendor itself, by a service provider, or even by the corporate IT group. The term “marketer-driven” in the CDP Institute’s formal CDP definition is intended to express this: marketers in control of the CDP, which isn’t the same as doing the technical work.

“Why Your CDP is a Failure” offers an even more provocative headline. But hopes for juicy disaster tales are quickly dashed: author Alan J. Porter of Simple [A] only means that CDPs “fail” because customer data should be shared by all departments. Again, no CDP vendor, buyer, or analyst would ever argue otherwise. There’s no technical reason a CDP can’t be used outside of marketing and some CDP vendors explicitly position their product as an enterprise system. The reason that CDPs are not used outside of marketing is that companies fail to fund enterprise-wide customer databases, not that CDPs can’t deliver such databases. Your CDP is a failure for this reason only if building such a database was its goal. That’s rarely the case.

“CDPs: Yet Another Acronym That Lets Marketers Down” starts with the airy assertion that “When you strip all the nonsensical nuances away from these companies -- the CRMs, the TMSs [tag management systems], the DMPs, the CDPs -- they’re all one simple thing at their cores: identity companies.”  This will be news to people who use such systems every day to run call centers, manage sales forces, capture Web site, run advertising campaigns, and assemble detailed customer histories.

The article continues qirh assertions that “identity isn’t everything”, “brands don’t have a complete understanding of their customers”, and “behaviors without motivations teach us nothing."  Few would argue with the first two while the third is surely overstated.  But the relevance of CDP to all three is questionable.  It seems that author Andy Hunn’s main message is that marketers need the combination of anonymized third party data and survey panel results offered by his own company, Resonate. This may be, but Resonate clearly serves a different purpose from CDPs.  So there's little reason to measure one in terms of the other.

Let me be clear: CDPs are not perfect. Like many new technologies, they are often expected to deliver more than is possible.   We are surely entering the “disillusion” stage of the hype cycle when tales of failed implementations and studies showing mixed satisfaction levels are common (and prove nothing about the technology's ultimate value).  Critical articles can be helpful in clarifying what CDPs do and don’t offer.  It's easy to lose sight of those boundaries in the early stages of a product category, when the main task is building a clear picture of the problems it solves, not on establishing its limits.

This is why the most productive discussion around CDPs right now revolves around use cases. Marketers (and other departments) need concrete examples of how CDPs are being used.  In particular, they need to be told what applications typically become possible when a CDP is added to a company’s marketing technology stack. These generally do one or more thing: combine data from multiple sources, share that data across channels, and rely on real-time access to the assembled data. It's these applications that justify investment in a CDP.

Complaining that CDPs don’t do other things isn’t very helpful – especially if CDP vendors don’t claim they do.  Nor is it a flaw in CDPs if other solutions can achieve the same thing.  Buyers can and should consider all alternatives to solving a problem: sometimes the CDP will be best and sometimes it won’t. It takes a clear understanding of each possibility to make the right choice.   Blanket claims about the value or failures of CDP may be inevitable but they don't really advance that discussion.





Tuesday, July 03, 2018

Interpublic Group is Buying Acxiom Marketing Services for $2.3 Billion. Here's Why.

Yesterday brought news that Acxiom had agreed to sell its marketing services business to Interpublic Group, a major ad holding company, for $2.3 billion. Acxiom will retain LiveRamp and do business under that name. Acxiom had restructured itself in March into the Market Services and LiveRamp groups and announced it was looking at strategic options, so the deal wasn’t especially surprising. But it’s still a milestone in the on-going evolution of the marketing industry.

For historical perspective (and assuming Wikipedia is correct), Acxiom got its start in 1969 compiling mailing lists from public sources such as telephone directories. The company grew to do all sorts of list processing, to manage custom marketing databases, to do identity resolution and to provide data enhancements for marketing lists. Although technology was always central to Acxiom's business, it was ultimately a services organization whose chief resource was a large team of experts in databases and direct marketing. It was also a favorite target of privacy advocates in those quaint days before online data gave them something much scarier to worry about.

Acxiom bought LiveRamp in 2014 for $310 million, as a logical extension of its identity data business. Since then, LiveRamp has grown much more quickly than the rest of Acxiom, currently accounting for about one-quarter of total revenue. Interesting financial note: Acxiom stock closed today at 39.45, giving it a market cap of $2.66 billion. Extracting the $2.3 billion that Interpublic is paying for everything else, this leaves LiveRamp with an implicit value of $360 million – not much more than Acxiom paid, and even less if you add the $140 million LiveRamp paid in 2016 for identity matching firms Arbor and Circulate. That’s shockingly low and suggests either an error in my calculations (let me know if you spot one) or that the market has serious doubts about something.

But we’ll worry about LiveRamp another day. What’s interesting at the moment is Interpublic as Acxiom’s buyer. At first it seems to buck the trend of private equity firms buying martech companies: see Marketo, Integral Ad Science, Aprimo, and Pitney Bowes. But this report from Hampleton Partners gives a more comprehensive perspective: yes, private equity’s share of marketing deals doubled in 2017, but the main buyers are still big agencies and consultancies. Indeed, Interpublic competitors Denstu and JWT are among the top three acquirers in the past 30 months, along with Accenture. And bear in mind that Acxiom is really more of a services company than technology developer.  It will be right at home with an agency parent.

So, what will Interpublic do with Acxiom? Some comments I saw said their main interest is Acxiom’s data business, which compiles and sells information about individuals (remember those phone books that started it all?)  However, I disagree.  It's not that I fear privacy regulations will kill that business: I expect third party data sharing will continue.  In fact, new rules should work in Acxiom’s favor.  As a company that privacy watchdogs have barked at for decades, Acxiom is likely to thrive after less responsible providers are driven from the business and as data buyers seek sources they can trust.  Indeed, Interpublic’s own discussion of the deal (click here to download) makes several references to data sales as an incremental revenue stream.

But it seems pretty clear that Interpublic’s main interest lies elsewhere. One of the nice things about ad agencies as buyers is they’re really clear in their explanations of their purchases. Interpublic’s deck lists their strategic rationale for buying Acxiom Marketing Services as acquiring “data solutions that enable omnichannel, closed-loop marketing capabilities and power exceptional marketing experiences.” A bit further on, they define the strategic fit as gaining “world class data governance and management capabilities [which] allow us to fully support clients’ first-party data”.  They also say “data assets have intrinsic value that will grow over time”, but I read this to mean they're most interested in managing each client’s own (first party) data.

This makes total sense. When Acxiom was founded in 1969, customer data was only used by a handful of direct mail marketers who were considered something between irrelevant and sleazy by the “real” marketers at big agencies and advertisers. Today, customer data management is considered the key to success in a future where every buyer expects a personalized experience. Ad buying itself, once an art form based on obscure (and often imaginary) distinctions among audience demographics, has become a mechanical process run by programmatic bidding algorithms. Indeed, the fraud-infested, brand-unsafe online ad market is now the shadiest corner of the industry.

The change is perfectly symbolized by the Association of National Advertisers (ANA) purchasing the DMA (originally Direct Mail Marketing Association): data-driven marketing is now main stream, even though the data-driven marketers are still not in charge. (If the data marketers had really taken over, DMA would have bought ANA, not the other way around.)

This is the world where Acxiom's expertise at managing customer data is needed for Interpublic to remain at the center of its clients’ marketing programs. If Interpublic doesn’t have that expertise, other agencies and digital consultancies like Accenture and IBM will provide it and displace Interpublic as a result. It’s not a new trend but it’s one that will continue. Don’t be surprised to see other data-driven marketing services firms find similar new homes.

Wednesday, June 20, 2018

Not the CDP Daily News

The World Health Organization has just declared that video addiction is a real disease but they've missed something even more insidious: the dangers of newsletter publishing. The CDP Institute Web site has been down for two days now (hopefully it will be back up by the time you read this and test that link), which means I haven't been able to publish the Institute's daily newsletter. (Yikes -- was my authorship a secret?)  This turns out to be very stressful for me, especially since I feel obligated to write the newsletter anyway so I'm ready whenever the site reappears. Gives a whole new meaning to the term "news junkie".

But, like the gun in a Chekov play, any copy that's created is begging to be used. So I'll post yesterday and today's items here for your enjoyment and my relief.  If you don't already subscribe and like what you see, visit the Institute site (once it's running) and join.

June 19, 2018


Google Invests $550 Million in Chinese E-Commerce Merchant JD.com
Source: GlobalNewswire
Just in case you had doubts that Google is serious about competing with Amazon in retail, consider this: Google just invested $550 million in Chinese e-commerce merchant JD.com. Google doesn’t do much business in China so this is about expanding in other markets and listing JD.com as a seller in Google Shopping. Google also announced several enhancements last week that help retailers display their inventory on-line and drive traffic to local stores. See this from The Street for more thoughts on the JD.com deal.

Adobe Expands Attribution Features
Source: Adobe
Adobe has expanded its attribution capabilities with Attribution IQ, an enhancement to Adobe Analytics that estimates the impact of campaigns in all channels on purchases. The offering includes ten different attribution models and lets users drill into results by customer segments, campaigns, and keywords.


IBM Computer Competes Effectively with Human Debaters
Source: CNET
I could tell you about Tru Optik’s Cross-Screen Audience Validation (CAV) service,
which draws on Tru Optik’s 75 million household database of smart TV viewers to give advertisers detailed information on audience demographics, reach and frequency by audience segment. But I doubt you care. So instead, ponder this: an IBM computer is now competing effectively with human debaters, showcasing skills like marshalling facts and choosing the most effective arguments. In other words: you’ll soon be able to argue with Alexa and lose.

June 20, 2018


RichRelevance Launches Next-Generation AI-Based Experience Personalization
Personalization vendor RichRelevance has launched its next generation of AI-based personalization tools. Key features include dynamic assembly of individual experiences, real-time performance tracking and continuous optimization. A helpful “Experience Browser” overlays the client’s Web site to display data, rules, and results for each decision in context. Marketers can set business rules to constrain the AI decisions and data scientists can draw on system data to define custom personalization strategies.


Automated Data Management: Immuta Raises $20 Million and Crate.io Raises $11 Million
Compared with AI-based personalization, automated data management gets relatively little attention, at least in martech circles. But its potential for solving the data unification problem is huge. Immuta, which marshals sensitive data for machine learning projects, just raised a $20 million Series B.
And Crate.io, an open source SQL database to manage feeds from machines and IoT devices, raised an $11 million Series A.  Now you know.

Mobile Phone Operators Take Baby Steps to Protect Location Data
I have a slew of other items about AI being used for cool things including seeing around corners, rendering 3D objects from photos, and delivering packages via two-legged robots (creepy!).  But let’s get back to reality with a report that several mobile operators were recently caught selling location data with little control over how it was used. The good news is that Verizon, AT&T and Sprint have shut off access to the two companies that were identified as misusing it. The bad news is, they’re still selling it to pretty much anyone else. Apple also recently changed App Store rules to limit apps publishers' access to people’s iPhone contact lists.  So maybe this is progress.

Saturday, June 02, 2018

Is the Bloom off the Blockchain Tulip?

Blockchain is the sort of cool technology that should excite me, but for some reason it does not. Part of my resistance is the whiff of humbug that accompanies so many blockchain-based ventures, whose founders often seem more excited about their Initial Coin Offering than building the actual business. But even ignoring that, I fail to see how the advantages of blockchain will create the revolution its proponents expect.

I’m not the only skeptic. Gartner recently found that just 1% of CIOs have any blockchain adoption and 77% have no plans. GlobalData predicted that blockchain will lose its gloss as projects are shelved or evolve in non-blockchain directions.  Like the Dutch tulip mania in 1637, the blockchain bubble is bound to burst.

Let’s start at the beginning. Blockchain is a “distributed public ledger”, which means it provides a provides a public stream of transactions that are stored in multiple places and can only be updated by verified agents. How the verification happens is a little vague in the discussions I’ve seen, but for now let’s assume that it’s fast, cheap, and perfectly secure. You might want to be a bit more cautious in real life.

The twin advantages of blockchain are that the data can’t be changed once it’s accepted (because it’s stored in multiple places) and the data is public (so anyone can easily see it). To be clear, data can still be encrypted, so blockchain contents can be kept private if the owners wish.

That’s cool in its own nerdy little way, I guess. But in practical terms, the benefit is much lower transaction costs because there’s no need for intermediaries to verify identities or register transactions.  This in turn makes possible things like micro-payments, which aren’t feasible if the cost of processing each transaction is too high, and public inspection of data, which again isn’t feasible if you need to control access for security reasons.  Here we’ll accept another dubious assumption, that the blockchain processing is essentially free. In real life somebody has to pay to verify identities and move, process, and store all that data.

So, what wonderful new things is blockchain supposed to make possible?

• Direct sale of personal data. At least half the discussions of blockchain in marketing propose some form of paying people for their personal data. The usual plan is to get direct payment from advertisers who want to send messages based on your information.  Sometimes the payment would be in return for viewing ads, completing surveys, or taking other actions. I’m hugely skeptical of this idea.  The practical roadblocks have nothing to do with blockchain: they're signing people up, getting them to update their data, and ensuring their data is accurate. Overcoming these depends on paying consumers enough money to make the effort worthwhile. I suspect most consumers won't be bothered, and that advertisers will really be interested in relatively few, high-value individuals.  (These are also the least likely to want to participate.  That some consumers are more valuable than others is never mentioned when these programs are discussed.). Transaction costs are not the problem, so blockchain isn't the solution.

• Loyalty systems and coupons. These also depend on consumers being willing to participate. But they’re familiar programs with proven consumer appeal.  Blockchain makes sense here because transaction costs, verification, and fraud are significant expenses for program operators.  Most blockchain-based loyalty and coupon schemes also propose payment in a cryptocurrency.  But this is probably more important to the promoters than consumers.

• Media buying. The premise for blockchain in media buying is that adtech vendors currently gobble up more than half of every media dollar , and, as Jeff Bezos says, “your margin is my opportunity”. If blockchain let advertisers and publishers connect directly, it could reduce the “adtech toll” significantly. But it's not that simple: each vendor in the adtech space is providing some useful service in exchange for its fees. So any blockchain solution would need to replicate those services or make them unnecessary. That takes more than just accepting blockchain payments.

• Ad fraud and brand safety. Blockchain is often proposed as a way to eliminate ad fraud by ensuring buyers only pay for ads that are seen by real people. It could also ensure that ads are only placed on brand-safe Web sites. These are highly feasible applications: they involve a relatively small number of parties (advertisers and publishers); the parties have existing commercial relationships;  and they all want to cut out the middlemen. One concern is that verifying that ads are seen by real people may require managing billions of individual identities.

There’s also a major scalability issue, since current blockchain networks handle just a few transactions per second.  Ternio claims to have solved this  but their product isn’t released yet…and as I write this, their Web site is disconcertingly focused on promoting their coin sale.

• Content rights. This is paying for commercial use of photographs, music, articles, and other copyrighted materials. Blockchain could easily reduce costs by replacing existing payment mechanisms. It could also streamline other parts of the process, such as recognizing content as it’s used, identifying the user, and connecting the user to the owner.

• Payment processing. This has applications well beyond marketing, although marketers can certainly benefit. Blockchain has good potential to reduce costs and cut out some middle men. As with media buying, blockchain must climb some steep scalability mountains before it can replace processes like clearing stock trades or processing credit card transactions.

• Supply chain. Yes, blockchain can be used to track products from producer to consumer. But it’s not clear that it removes significant bottlenecks. If you’re going to trace a head of lettuce from farm to grocer, the real challenge is having sensors in place to record each step in its journey.  Conventional databases can store the resulting data quite nicely. Similarly, if you want to detect counterfeits by verifying an item’s origin, the biggest hurdle is creating an unalterable physical identifier like an engraved serial number.  Blockchain doesn’t help with that. You might use blockchain to store an unalterable registry of the identifiers, but conventional security methods already do a pretty good job of keeping such data secure.

• And so on.  Here's a nice graphic from Jeremiah Owyang that includes additional blockchain applications.  (Read the original article here.)  Each is intriguing and highly threatening if you're a middleman in that industry.  But in every case, the process can already be done with existing technology or faces problems that blockchain doesn't solve.



My conclusion is that blockchain applications will be more evolutionary than revolutionary. They’ll make existing processes more efficient but not introduce entirely new business models.  The biggest exception is direct sale of personal data, but I don’t think that will happen.

True believers will argue that it’s too early to understand how blockchain will play out. I’ll grant it's impossible to foresee the long-term impact of any major technology. But one way to think about new technology is to imagine a world where that technology is fully deployed: say, where all devices were sentient or communication was free and instantaneous. Your vision won’t get the details right but you will get a sense that things would be radically different.

Try that with blockchain: take a few moments to imagine a world where financial transactions are free and data security is absolute. I'll wait.

How’d it go? Personally, I didn’t see much of a change. Truth be told, financial transaction costs are already pretty low and security is already pretty good. Existing trust mechanisms aren’t perfect but lack of trust doesn’t get in the way very often. It might be nice in some highly abstract sense to be free from central identity authorities but they don’t interfere much with day-to-day living. In any event, most authorities would remain in place in a blockchain world.  Even identity and financial authorities would still exist, even if they were not under central control.

In short, blockchain is interesting and has its advantages. But if you think it will be the biggest change since the Internet, I have some tulip bulbs you might want to buy.

Tuesday, May 29, 2018

Announcing the Talking Stack Podcast on Martech News

Over the past several months, I’ve been conspiring with MarTech Advisor’s Chitra Iyer and Amit Varshneya and industry expert Anand Thaker to produce a podcast devoted to martech news of the week. I’m happy to announce that the first two episodes of Talking Stack were released yesterday, available here.

Why this podcast? Well, there’s an awful lot of martech news every week. It’s covered quite comprehensively by MarTech Advisor, MarketingLand, CMS Wire and other industry publications. I even offer my own thoughts in the CDP Institute Daily Newsletter.

But reporting the news is different from talking about it. So far, Chitra, Amit, Anand and I have had different views on the items we’ve discussed, creating a richer perspective than you’d get from any one of us alone. The round table format also forces us to be brief, creating a higher ideas-to-words ratio than you’d get in a written article, interview or panel discussion. Hopefully that translates into greater value per minute for the listeners as well.

Plus, I won’t hide the fact that doing the podcast is fun. It’s a treat to talk about the industry with others who follow it as closely as I do and who share – or at least tolerate – my sense of humor. Whether we’ll repeat the silliness of the Episode 2 lead-in remains to be seen.

I suppose it also depends on what feedback we get. So do let us know what you think about that and the podcast in general. We look forward to hearing from you and hope you’ll make listening to Talking Stack a regular habit.

Tuesday, May 22, 2018

Adobe's Magento Deal Makes Great Sense

Adobe yesterday announced its purchase of the Magento Commerce platform, a widely used ecommerce system, for a cool $1.68 billion.

That Adobe would purchase an ecommerce system was the least surprising thing about the deal: it fills an obvious gap in the Adobe product line compared with Oracle, Salesforce, IBM, and SAP, which all have their own ecommerce systems. Owler estimates that Magento had $125 million revenue, which would mean that Adobe paid 13x revenue. That seems crazy but Salesforce paid $2.8 billion for Demandware in 2016 on $240 million revenue, giving a similar ratio of I2x. It’s just what these things cost these days.

More surprising was the mismatch between the two business’s client bases. Magento sells primarily to small and mid-size firms, while Adobe’s Experience Cloud products are sold mostly to enterprises. The obvious question is whether Adobe will try to use Magento as an entry point to sell Experience Cloud products to smaller firms, or use Experience Cloud as an entry point for selling Magento to big enterprises. The easy answer is “both”, and that’s more or less what the company said when asked that question on an analyst conference call about the deal. But my impression was they were more focused on adding Experience Cloud capabilities like Sensei AI to Magento. References during the call to cloud-based micro-services also suggested they saw the main opportunity as enhancing the product Magento offers in the mid-market, not selling Magento to big enterprises.

This could be very clever. Selling enterprise software packages to mid-market firms doesn’t work very well, but embedding enterprise-class micro-services would let Adobe add advanced features without asking mid-market IT managers or business users to do more than they can handle. It would also nicely skirt the pricing problems that come from trying to make enterprise software affordable to smaller firms without cutting prices to large enterprises.

The approach is also consistent with the Adobe Experience Cloud Profile announced last month, which uses an open source customer data model co-developed with Microsoft and is hosted on Microsoft Azure. This is also at least potentially suitable for mid-size firms, a market where Microsoft’s CRM products are already very strong. So we now see two recent moves by Adobe that could be interpreted as aimed at penetrating the mid-market with its Experience Cloud systems. Given the crowded, competitive, and ultimately limited nature of the enterprise market, moving downstream makes a lot of sense. Historically, it’s been very hard to do that with enterprise software but it looks like Adobe has found a viable path.

(As an aside: it would make total sense for Microsoft to buy Adobe, a possibility that has been mentioned for years. There’s no reason to think Adobe wants to be bought and the stock already sells at over 16x revenue compared with 8x revenue for Microsoft. So it would be hard to make the numbers work. But still.)

Perhaps the most intriguing aspect of the deal is that Magento is based on open source.. This isn’t something that most enterprise software vendors like to buy, since an open source option keeps prices down. Like other open-source-based commercial products, Magento includes proprietary enhancements to justify paying for something that would otherwise be free. Apparently Adobe feels these offer enough protection, especially among mid-size and larger clients, for Magento to be a viable business. And, Adobe’s comments show it’s very impressed at the size of the open source community supporting Magento, which it pegs at more than 300,000 developers. That does seem like a large work force to get for more-or-less free. Again, there’s a parallel with the open source data model underlying Experience Cloud Profile. So Adobe seems to have embraced open source much more than its main competitors.

Finally, I was struck by Adobe’s comments in a couple of places that it sees Magento as the key to making “every experience shoppable”, an extension of its promise to make every experience personal. The notion is that commerce will be embedded everywhere, not just isolated in retail stores or Web sites. I’m not sure I really want to live in a world where everything I see is for sale, but that does seem to be where we’re headed. So, at least from a business viewpoint, let’s give Adobe credit for leading the way.




Tuesday, May 08, 2018

Will GDPR Burst the Martech Bubble?

Some people have feared (or hoped) that the European Unions’ General Data Protection Regulation would force major change in the the marketing and advertising ecosystems by shutting off vital data flows. I’ve generally been more sanguine, suspecting that some practices would change and some marginal players would vanish but most businesses would continue pretty much as they are. The most experienced people I’ve spoken with in recent days have had a similar view, pointing to previous EU privacy regulations that turned out to be mostly toothless.

But even though I respect those experienced opinions, I’m beginning to wonder GDPR might have a much greater than most of us think. The reason isn’t that GDPR requires major changes in how data is collected or used: by and large, consumers can be expected to grant consent without giving it much thought and most accepted industry practices actually fall within the new rules. Nor will the limited geographic reach of GDPR blunt its impact: it looks like most U.S. firms are planning to apply GDPR standards worldwide, if only because that’s so much easier than applying different rules to EU vs non-EU persons.

What GDPR does seem to doing is create a shake-out in the data supply chain as big companies reduce their risks by limiting the number of partners they’ll work with. The best example is Google’s proposed consent tool for publishers, which limits consent to no more than twelve data partners. This would inevitably lead to smaller firms being excluded from data acquisition.  Some see this as a ploy by Google to hobble its competitors, and maybe they're right. But the real point is that asking people to consent to even a dozen data sharing options is probably not going to work. So even though publishers are free to use other consent tools, there’s a practical limit on the number of data partners who can succeed under the new rules.

A similar example of market-imposed discipline is contract terms proposed by media buying giant GroupM , which requires publishers to grant rights they might prefer to keep. GroupM may have the market power to force agreement to its terms, but many smaller businesses will not. With less legal protection, those smaller firms will need to be more careful about the publishers they work with. Conversely, advertisers need to worry about using data that wasn’t acquired properly or has been mistreated somewhere along the supply chain before it reached them. Since they can’t verify every vendor, many are considering cutting off smaller suppliers.  Again, the result is many fewer viable firms as a handful of big companies survive and everyone else is shut out of the ecosystem.  (Addendum: see this Marketing Week article about data supplies being reduced, published the day after I wrote this post.)

There’s nothing surprising about this: regulation often results in industry consolidation as compliance costs make it impossible for small firms to survive. The question I find more intriguing is slightly different: will a GDPR-triggered reduction in data processing will ramify through the entire adtech and martech ecosystem, causing the long-expected collapse of industry growth?

So far, as uber-guru Scott Brinker recently pointed out, every prediction of consolidation has been wrong.  Brinker argues that fundamental structural features – including low barriers to entry, low operating costs of SaaS, ever-changing needs, micro-services architectures, and many more – favor continued growth (but carefully avoids making any prediction).  My simplistic counter-argument is that nothing grows forever and sometimes one small jolt can cause a complex system to collapse. So something as seemingly trivial as a reluctance of core platforms to share data with other vendors could not only hurt those vendors, but vendors that connect with them in turn. The resulting domino effect could be devastating to the current crop of small firms while the need to prove compliance could impose a major barrier to entry for new companies.

I can’t say how likely this is. There’s a case to be made that GDPR will have a more direct impact on adtech than martech and adtech is particularly ripe for simplification.  You could even note that all my examples were from the adtech world. But it’s always dangerous to assume trends will continue indefinitely and it’s surely worth remembering that every bubble is accompanied by claims that “this time is different”. So maybe GDPR won’t have much of an impact. But I suspect its chances of triggering a slow-motion martech consolidation are greater than most people think.



Monday, May 07, 2018

The Black Mirror Episode You'll Never

I’m no fan of the TV show Black Mirror – the plots are obvious and the pace is excruciatingly slow. But nevertheless, here’s a story for consideration.

Our tale begins in a world where all data is stored in the cloud. This means people don’t have their own computers but can instead log into whatever machine is handy wherever they go.

All is lovely until our hero one day notices a slight error in some data. This is supposed to be impossible because the system breaks every file into pieces that are replicated millions of times and stored separately, blockchain-style. Any corruption is noted and outvoted until it’s repaired.

As he investigates, our hero finds that changes are in fact happening constantly. The system is infected with worms – we’ll call them snakes, which has nice Biblical overtones about corruption and knowledge – that move from node to node, selectively changing particular items until a new version becomes dominant. Of course, no one believes him and he is increasingly ignored because the system uses a reputation score to depreciate people who post information that varies from the accepted truth. Another security mechanism hides “disputed” items when they have conflicting values, making it harder to notice any changes.

I’m not sure how this all ends. Maybe the snakes are controlled by a master authority that is altering reality for its own purposes, which might be benevolent or not. The most likely result for our hero is that he’s increasingly shunned and ultimately institutionalized as a madman. Intuitively, I feel the better ending is that he ends up in a dreary-but-reality-based society of people who live outside the cloud-data bubble. Or perhaps he himself has been sharded and small bits begin to change as the snakes revise his own history. I can see a sequence of split-second images that illustrate alternate versions of his story co-existing. Perhaps the best ending is one that implies the controllers have decided the episode itself reveals a truth they want to keep hidden, so they cut it off in mid

Tuesday, May 01, 2018

Facebook, Privacy, and the Future of Personalization

Readers of this blog and the CDP Institute newsletter know that I’ve been fussing for years about privacy-related issues with Facebook, Google, and others. With the issue now attracting much broader public attention, I’ve backed off my own coverage. It’s partly because people can now get the information without my help and partly because there’s so much news that covering it would consume too much precious reader attention. But, ironically, the high level of noise around the topic also means that some of smaller but significant stories get lost.

I’ll get to covering those in a minute. But first a general observation: the entirely coincidental convergence of the Facebook/Cambridge Analytica story and implementation of the European Union’s General Data Protection Regulation (GDPR) seems to have created a real possibility of changes to privacy policies everywhere, and most particularly in the United States. In a nutshell, the Facebook news has made people aware of how broadly their data is shared and GDPR has shown them it doesn’t have to be this way. Until now, few people in the U.S. really seemed to care about privacy and it seemed unlikely that they would overcome the resistance of commercial interests who largely determine what happens in the government. (Does that make me sound horribly cynical? So be it.) It’s still very much uncertain whether any significant change will take in U.S. laws or regulatory agencies. But that there is any significant chance at all is brand new.

So much for that. Just wanted to get it on the record so I can point to it in case something actually happens. Here are some developments on the Facebook / Walled Garden / Privacy fronts that you might have missed.

More Bad News

One result of the heightened interest in these issues that public agencies, academics, and especially the media are now looking for stores on the topic. This in turn means they find things that were probably always there but went unreported. So we have:

- CNN discovers that ads from big brands are still running on YouTube channels of extremist groups.
This has been a known problem forever, so the fact that it gets reported simply means that journalists chose to look for it and decided people would be interested in the results.

- Washington Post finds paid reviews are common on Amazon, despite being officially banned.  Again, this comes under the heading of “things you could always find if you bothered to try”.

- Journalism professor Young Mie Kim found that fully half the groups running political advertising on Facebook during the 2016 election couldn’t be traced.  Kim started her research before the current news cycle and it was probably accepted for publication before then too. But would Wired have picked it up?

- PricewaterhouseCooper’s FTC-mandated privacy review of Facebook in 2017 failed to uncover the Cambridge Analytica breach.  It’s more evidence for the already-obvious fact that current privacy safeguards don’t work. But it never would have seen the light of day if this hadn’t been a hot issue.

Attacks from All Sides

Politicians, government agencies, and business rivals are all trying to gain advantage from the new interest in privacy.

- Immediately after the Zuckerberg hearings in Congress, two Senators introduced a bill to give consumers more rights over their data.  The language was highly reminiscent of GDPR.

- A group of 31 state attorneys general opposed a bill to create a Federal law with standards for reporting about data breaches, fearing that Federal standards would override more stringent state regulations. Of course, this is exactly what the sponsors intend. But now the state AGs are more motivated to resist.

- The Securities and Exchange Commission (SEC) fined Yahoo $35 million for failing to discuss a 2014 data breach involving over 500 million accounts.  Data protection isn’t usually a SEC concern, so it’s equally interesting that they chose to make it an issue (arguing the breach was news that should have been shared with investors, which seems a bit of a stretch) and the Republican-majority Federal Trade Commission is steadfastly unengaged.

- Four major publisher trade groups have attacked Google’s proposed approach to gathering advertising consent, which places the burden on the publishers but requires them to share user data.  This would have been an issue under any circumstances but I suspect that publishers are emboldened to resist by the expanded interest in privacy and greater hostility to the Google, Facebook, et. al.

Scrambling by Facebook

Facebook has been scrambling to redeem itself, although it has so far avoided changes that would seriously (or even slightly) impact its business.

- It has ended a program to target ads using data from external compilers, such as Acxiom.  How this helps privacy isn’t clear but it sounds good and conveniently makes Facebook’s own data even more valuable.

- It announced major API changes that limit the amount of data shared with developers.  Note carefully: they’re not limiting data collected by Facebook, but only how much of that is shared with others. Similar changes applied to Facebook-owned Instagram. Again, the actual effect is to add value to ads sold by Facebook itself.

- It announced just today that it will let members block it from collecting data about their visits to non-Facebook Web sites.  By now you see a pattern: less data from outside of Facebook makes Facebook data more important. This reflects perhaps the most disturbing revelation from the Zuckerberg hearings: that Facebook collects such data even on non-members. But the change doesn’t address that issue, since only members can tell Facebook to stop the data collection. If you find this confusing, that’s probably no accident.

- It promised to add an “unsend” feature to Messenger.  Nice, but it only happened after reports that Facebook executives themselves already had this capability.

- It rolled out a new centralized privacy center that made settings easier to manage but apparently didn’t change what users can control.

- More substantively, it promised to apply GDPR consent rules globally.  Signals were a bit mixed on that one but maybe it will happen. Who wants to start a betting pool?

- It dropped opposition to a proposed consumer privacy law in California.  Good but it would have been a public relations disaster to continue opposing it. And who knows what they’re doing in private?

- On the Google front: Google-owned YouTube has touted its efforts to flag objectionable videos.  That’s not exactly a privacy issue but probably overlaps the public perception of how online tech giants impact society. Remember they’re also motivated by tough laws in Germany and France enacted early this year, which require to remove illegal content within 24 hours.

Business as Usual for Everyone Else

How much of this is unique to Facebook and how much reflects a fundamental change in attitudes towards data privacy? Certainly Google, Amazon, and others are tip-toeing quietly in background hoping not to be noticed. Per the above, YouTube has occasionally wandered into the spotlight, especially when extremist videos on YouTube intersect with extremist content on Facebook. Over-all, I’d say it’s very much business as usual for most firms that gather, sell, and employ consumer data.

- Amazon continues to offer amazingly intrusive concepts with little evidence of pushback. For example, they’re expanding their Amazon Key in-home delivery program to also leave packages in your car.  And they continue to expand the capabilities of Alexa ‘smart speaker’ (a.k.a. ‘always listening’) systems, most recently by making it easier for people to build their own custom capabilities into the system.

- Similarly, Waze has been merrily promoting its ability to share data about traffic conditions, setting up any number of integrations such as deals with Carto and Waycare to help traffic planning and, in Waycare’s case, warn drivers about current road conditions. Waze’s data is truly anonymized, at least so far as we know. But they certainly don’t seem to be worried a general privacy backlash.

- Another announcement that raised at least my own eyebrows was this one from Equifax, which headlined the blending of consumer and commercial data to predict small business credit risks. Anything that suggests personal data is being used for business purposes could worry people – but apparently it that doesn’t worry Equifax marketers.

What Do Consumers Think?

The big question in all this is whether consumers (should we just call them “people”?) remain concerned about privacy or quickly fall back into their old, carefree data sharing ways. It’s probably worth noting that Facebook was already uniquely distrusted compared with Google and Amazon, both by consumers and small business.

We do know that most have been following the Cambridge Analytica story in particular. But, to their credit, they also recognize that what they post on Facebook is public even if they don’t necessarily understand just how much tracking really takes place.

Sure enough, it seems that few Facebook users actually plan to close their account and, more broadly, there’s little support for government regulation of social media.

Indeed, most consumers are generally comfortable with sharing personal information so long as they know how it will be used. 

Surveys do show that EU consumers say they’ll exercise their privacy rights under GDPR, but it’s reasonable to wonder how many will follow through. After all, they’re notably lax on other cybersecurity issues such as changing default passwords on home networks.

But this doesn’t mean that Facebook and similar firms are home free. Consumers are smart enough to distrust recommendations from smart speakers, as indeed they should be.
They’re also not terribly enthusiastic about ads on smart speakers or, indeed, about personalization in general.
On the other hand, of course, many studies do show that consumers expect personalized experience, although there’s some reason to suspect marketers overestimate its importance compared with other aspects of the customer experience.

This matters because personalized experiences are the main public justification that marketers give for gathering personal data – so consumers who increase the value they place on privacy could quickly reach a tipping point where privacy outweighs the benefits of personalization. That could radically shift how much data marketers collect and what they can do with it. Given the dire consequences that would have for today’s marketing ecosystem, everyone involved must do as much as possible to make sharing data genuinely safe and worthwhile.

Friday, April 27, 2018

What I Learned at the Customer Data Platform Workshop

I ran a four hour workshop on Customer Data Platforms this week at the MarTech Conference in San Jose.* The attendees were a mix of marketers and technologists from brands, agencies, and vendor companies. We had surveyed them in advance and found, not surprisingly, goals ranging from understanding CDP market trends to optimizing data loads for technical performance. The agenda was correspondingly varied and I like to think that everyone learned something useful.  Based on attendee comments and my own observations, here’s what I myself learned.

- CDP is a vague category. This was voiced with some frustration at the end of the workshop, when several people said they had hoped to come away with a clear picture of what is and isn’t a CDP, but found instead that CDP systems differ widely. In the context of the workshop, I actually considered this to be a positive result: one of the main points I tried to get across was that CDPs have very different features and picking the right one requires you to first understand your own needs and then look carefully at which systems have the features needed to meet them.  Complaining about it is like going to a workshop on car buying and discovering that automobiles differ widely: if you didn't understand that before, you couldn’t possibly have made a sound choice. The variety may seem overwhelming but once you recognize it exists, you’re ready to take the next step of figuring out how to find the capabilities that match your needs.

- People want CDP-specific use cases. I knew in advance that people want to understand CDP use cases. This has become a very common question in the past year and the CDP Institute Library includes many papers on the topic. My personal problem has been that CDPs are like bacon: they make everything better. This made it seem silly to list use cases, because the list would include pretty much any marketing project that involves data. What I learned from the workshop is people are really looking for use cases that only become possible with a CDP. That’s a much different and more specific question: What can I do with a CDP that can’t do without one?

We discussed the answers as a group at the end of the workshop and the main conclusion was CDP makes possible many cross-channel activities that are otherwise impossible because cross-channel data isn't unified.  This isn’t exactly news – unified customer data is the whole point of a CDP – but it’s still good to focus specifically on the use cases that unification makes possible.

On reflection, I’d add the CDP also exposes data that’s otherwise trapped in source systems or not collected at all. This could be information from a single channel, so it’s distinct from the cross-channel use case. Our workshop group didn’t mention this one, so I’ll have to stress it more in the future.

The group also didn’t list the operational efficiencies of a CDP as unique benefits. That’s interesting because so much of our discussion stressed the lower cost, faster deployment, and lower risk of CDP compared with other solutions. Apparently that’s either not credible or not important. I’ll speculate that the technicians didn’t believe it and the marketing people didn’t really care. But of course that’s utterly unsupported stereotyping. (Speaking of stereotyping, I’m pretty sure the technical people sat in the back rows and the marketers talked a lot more during the small group discussions.  Next time I'll make them wear labels so I know for sure.)

- Marketers don’t care about technical details. Ok, that's really unfair stereotyping so let's change it to “some marketers”.  But it’s definitely fact-based: one of marketers complained as we started to drill into the technical parts and several others agreed. I pushed back a bit, arguing that you can’t make a sound system selection without looking at technical differences. I think I was polite about it, but have strong feelings on the subject: lack of research into specific product capabilities is by far the biggest reason people end up unhappy with a software purchase. (Yes, I have research to back that up.)

I suppose the counter-argument is what really matters are the functional differences and not the technical methods used to accomplish them. My counter-counter-argument would be the technical methods matter because they determine how efficiently a system executes those functions and how easily it can extend them. Architecture is destiny, as it were.  In my mind, the argument ends there and I win but maybe there’s more to be said for the other position. (If case you’re wondering, I did speed through the technical parts after that objection, and talked more about use cases instead. Squeaky wheels get the grease. And there was a later part of the agenda that circled back to technical questions anyway.)

So, that’s what I learned during the workshop. As you might imagine, preparing it forced me to think through several topics that I’ve been addressing casually. I’m most pleased with having clarified the relationships among strategy, marketing programs, use cases, resources, and requirements. The image below summarizes these: as you see, strategy drives marketing programs which drive resource needs**, while marketing programs drive use cases which drive system requirements. Those are two sets of objects that I usually discuss separately, so I’m happy to finally connect them. Plus, I think it’s a cute picture. Enjoy.



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* I'll likely be repeating it elsewhere over the next few months.  Let me know if you're interested in attending.

** The flow can also run the other way: available resources determine what marketing programs you can run which determine what strategy makes the most sense.