Liz Miller

Vice President & Principal Analyst Constellation Research

About Liz Miller: Liz Miller is Vice President and Principal Analyst at Constellation, focused on the org-wide team sport known as customer experience. While covering CX as an enterprise strategy, Miller spends time zeroing in on the functional demands of Marketing and Service and the evolving role of the Chief Marketing Officer, the rise of the Chief Experience Officer, the evolution of customer engagement, and the rising requirement for a new security posture that accounts for the threat to brand trust in this age of AI. With over 30 years of marketing experience, Miller offers strategic guidance on the leadership, business transformation, and technology requirements to deliver on today’s CX strategies. She has worked with global marketing organizations to transform…...

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Salesforce recently conducted a survey of over eight thousand marketers from around the globe representing all shapes and sizes of organizations. Overall, the message was pretty darn positive: Growth IS the agenda and marketing DOES play a substantial role in turning growth strategies into tangible, measurable reality.

The study—click here to download—tracks with much of what I’ve seen in the past year. Some 90% of the Salesforce study respondents agree that 2020 upped the ante with digital engagement and three-quarters of marketers now work…and collaborate…from anywhere. For CMOs, who in the face of unprecedented change managed to weather the storm, taking a break is NOT on the agenda as 70% indicate that they plan to continue to redefine success to match company goals.

It should come as no surprise that the only thing outpacing the rise of digital channels is the rise of data sources. With 78% of marketers indicating that their customer engagements are data-driven, this data surge should be expected. Even attitudes and definitions of metrics changed due to the pandemic with 78% of marketers indicating that they have changed or reprioritized their metrics in the past year, with the big shifts in prioritization of customer acquisition costs (+26%) and content engagement (+23%) while revenue growth remains the top metric being tracked.

So why the title of this blog…why lay down the hint that things might not be awesome? Don’t get me wrong, the story told through the State of Marketing report is incredibly positive and shares what I believe is a true and honest story of just how far Marketing has come, especially through the dumpster fire of a pandemic year like 2020. We deserve to have a state of marketing that is optimistic.

But a journalist didn’t once dub me the “Debbie Downer of Marketing” for no reason.

At first glance, there is nothing really that notable about the list of Marketer’s top priorities or their challenges. Similar to their top two priorities in 2020, marketers are prioritizing innovation and engaging with customers…with their top two challenges being engaging with customers and innovating. Yes…in that order…on both counts. Now, thanks to Salesforce providing access to the survey’s data via Tableau, I decided to take a dive into these findings…because if I am being honest, I got suspicious about this whole innovation is a top priority point.

What I found was that for the CMO, innovation doesn’t actually reign supreme. Instead, the priority (and the biggest challenge) is engaging with customers in real time and creative cohesive cross-channel journeys in the second priority spot. This tracks for me as CMOs are keenly aware that as customers have embraced digital channels so too have they embraced the expectation that their digital experiences should occur in the channel of their choice in their definition of real-time. It also tracks with marketing’s understanding that while they can imagine any number of journeys…it is the customer that is wholly in charge of their own experiences. And THAT, ladies and gentlemen, is what keeps the CMO up at night.

So, WHO is sweating innovation? Based on the data…marketing managers. Innovation stands at the top of the priority AND challenge chart…and what subsequently pushes innovation to the top of the overarching marketing data. This isn’t just innovation for innovation’s sake. Marketing managers are pushing boundaries and looking to innovate in order to achieve their biggest priorities and solve their greatest challenges. They are looking to solve the problem of HOW we engage in real time and HOW we orchestrate cross-channel journeys. All good, right? CMOs are looking long-term at how we craft the strategies, marketing managers are innovating to turn strategies into results.

All sunny in the state of marketing once more. So why do I keep bringing up cloudy skies? CMOs might not be setting marketing managers up for long-term success.

When asked to rate employee training teams receive, 47% of CMOs rate training as excellent…41% of marketing managers agree. Not a wide swath to be sure…but shouldn’t the recipients of the training be more enthused than the leader signing off on it? When you dig into what training is being offered, CMOs say that content marketing (47%), creativity (46%), data analytics (45%), communication (43%) and collaboration (41%) top the list. Managers shuffle the deck a bit, but for the most part agree: communication (48%), creativity (43%), content marketing (43%), collaboration (39%) and data analytics (37%).

Here’s where I get concerned…remember how marketing managers said their key priority and their top challenge was innovating…and remember how it was that innovation that could solve everyone’s big concern over real time customer engagement and cross channel journey orchestration. So why is it that campaign strategy (36%) and digital proficiency (34%) are, at best, in the middle of the pack for what marketing managers say their employers offer by way of training and support. Critical leadership skills like emotional intelligence, agility and adaptability and even resiliency rank far lower…and in an age of data dependence and digital innovation skills like data science and coding are near last.

In fact, the bottom three training opportunities listed by CMOs mirror the bottom three opportunities listed by marketing managers: data science (29%), coding (23%) and resiliency (22%).

Why are we training marketers to be successful in the year 2005 when our goals, priorities and challenges are distinctly SO 2025?

This isn’t to say that marketing skills like content marketing, creativity and communications aren’t important. We need to start upskilling based on what our teams, especially our managers and the functional teams on the ground fighting the good fight, are trying to solve…we need to train and educate so they can meet their own needs and expectations. They expect to be successful and to thrive. They WANT to innovate. So how are we helping that next generation thrive?

If there is a big ah-hah moment for me from this year’s State of Marketing report it is this: there is real cause to celebrate the resilience and fortitude of marketing, but the sun sets eventually. If we expect our digital tomorrow to be better than the dumpster fire we just survived, we need to start training teams to BE the marketers of tomorrow. Let’s start training for innovation, agility and resilience. Yes, let’s make sure content and creativity are still pumping through the veins of marketing, but let’s also remove the limitations of what a marketer can and can’t do. YES! A marketer can code. It IS possible. YES! A marketer can do more than just read a visualized data set…in fact, a marketer CAN pick up data science skills. And yes, in order to fulfill on that promise of humanizing marketing and engaging with each individual customer with empathy and contextual understanding, upskilling and uplifting marketers with emotional intelligence should be on the agenda right along with communication and collaboration.

We’ve all embraced marketing’s role as growth driver. Now, let’s get marketers ready for what comes next.

Andy Thurai

Vice President and Principal Analyst Constellation Research

About Andy Thurai Andy Thurai is an accomplished IT executive, strategist, advisor, enterprise architect and evangelist with more than 25 years of experience in executive, technical, and architectural leadership positions at companies such as IBM, Intel, BMC, Nortel, and Oracle. Andy has written more than 100 articles on emerging technology topics for publications such as Forbes, The New Stack, AI World, VentureBeat, DevOps.com, GigaOm and Wired. Andy’s fields of interest and expertise include AIOps, ITOps, Observability, Artificial Intelligence, Machine Learning, Cloud, Edge, and other enterprise software. His strength is selling technology to the CxO audience with a value proposition rather than the usual technology sales pitch. Find more details and samples of Andy’s work on his…...

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In digital economy, you must move fast to survive. Not in six-month release cycles. But moving with fast release cycles, continuous releases, a mature CI/CD pipeline is only a portion of the solution. If you continue to break your systems at a faster rate but are unable to fix them faster as well, you are setting up for unplanned disasters that will hurt your business sooner than later.

I recently did a podcast with my buddy Mike Kavis, Chief Cloud Architect at Deloitte discussing some of these areas of concern.

To achieve this, the DevOps culture, agile development, CI/CD pipeline, and microservices are in full swing at most digital powerhouses. I recently wrote about the digital powerhouse release cycles on how many changes they make per day. The classic microservice architecture from Netflix from a few years ago claims they have close to 800+ microservices (at that time). Netflix, Uber, and most other digital giants claim to make thousands of "daily production changes." Sometimes multiple changes to the same service. That is the power of agile development. "Fix fast and fail fast" is the mantra of successful digital houses where they can be very nimble and provide the changes the customers want, sometimes by making multiple changes to the same service. The canary, blue-green, and rolling deployments give power to the developers and DevOps teams to figure out how to get the functions and features fast to the consumers.

However, this can be a nightmare for centralized Ops teams. As I discussed in my previous article, per Gene Kim in his The Visible Ops Handbook, 80% of unplanned outages are due to ill-planned changes. Distributed systems produce a ton of noise. If anyone critical microservice or underlying infrastructure component goes down it is not uncommon for IT monitoring and observability systems to produce tens of thousands of alerts. It is very common in many digital-native companies the Ops teams get drowned in alerts and often are "alert fatigued." The noise to signal ratio is very high in these environments.

After looking at the processes are multiple large customer situations, I have to say the "fail fast" or development cycle, has matured enough, but the "find fast and fix fast" cultures of Ops teams are still not mature enough. Using yesteryears tools, processes, and skills to fight the modern war is the most dangerous thing any organization can do and yet it is very commonplace with today's IT teams. Most of them seem to band-aid something until something major breaks.

War/Incident collaboration rooms are broken

Given the virtual nature we are operating in during the pandemic, most enterprises have successfully adopted virtual incident collaboration rooms instead of physical war rooms. A good thing about the physical rooms is that you can physically see how many are in the room, and who is appropriate and figure out someone important is missing. This will help reduce the incident collaboration rooms to the right size quickly before they can deep dive into the issue.

With virtual incident collaboration rooms, everyone who is tagged with a remote association to any critical service will be automatically invited to a virtual incident room (eg. Slack channel) and everyone starts to guess what went wrong. Not only too many cooks but most of those engineers, developers, system admins who would be doing something else productive instead. Sadly, as one high-powered executive told me in confidence, they established a "Mean Time to Innocence" to reduce crowd in those situations. In other words, invite everyone you can think of, and if they can prove it is not their work that is offending then they can leave the room. 

Find what is broken and fix it fast

I have written numerous articles on this topic. You need to first figure out if what happened is really an incident. All notifications/alerts/anomalies are not necessarily incidents. An incident is defined as "Something that affects the quality of service delivered." If it is an unplanned incident, you also need to figure out if it is causing problems to any user. You also should have a mechanism to figure out how many high-profile customers are affected vs random users which need to happen before the customer knows the incident happened so you can fix it.

AI/ML systems, Observability systems, AIOps, and proper Incident Management systems, if set up properly, can help a lot in this area. Those are some of my coverage areas that I am researching here at Constellation. If you have an offering in this space, please reach out to us to brief us. I would love to find out what you do and include you in my research report.

Keep in mind in the digital economy you need to fail fast and recover fast as well. If you just keep failing without finding and fixing things faster your business will fail permanently soon enough. It is not about how hard you fall that matters, but how fast you get back up that matters more.

I am currently a research VP and Principal Analyst at Constellation Research a silicon valley research firm. My coverage areas include AI, ML, AIOps, DataOps, ModelOps, MLOps, CloudOps, Observability, etc. Contact me if you would like to brief me about your company or you need content/research work.

Steve Wilson

Former Vice President and Principal Analyst Constellation Research

Steve Wilson is former VP and Principal Analyst at Constellation Research, leading the business theme Digital Safety and Privacy. His coverage includes digital identity, data protection, data privacy, cryptography, and trust. His advisory services to CIOs, CISOs, CPOs and IT architects include identity product strategy, security practice benchmarking, Privacy by Design (PbD), privacy engineering and Privacy [or Data Protection] Impact Assessments (PIA, DPIA). Coverage Areas: -  Identity management, frameworks & governance-  Digital identity technologies-  Privacy by Design -  Big Data; “Big Privacy”-  Identity & privacy innovation Previous experience: Wilson has worked in ICT innovation, research, development and analysis for over 25 years. With double…...

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My presentation to this year's Identiverse, SWILSON Why Isnt Identity Easy HANDOUTS

From the beginning of e-commerce, we have tended to complicate "digital identity". Its relationship with “real” identity has never been clear and loosely defined metaphorical efforts like “electronic passports” have never fixed liability. The Anglophone (Five Eyes) countries have no tradition of National ID; occasional proposals have been roundly rejected by the public, which has poisoned most of the discourse of identity capability building. Private sector initiatives in banking and technology sectors (e.g. Identrus and Infocard) came and went. British and American efforts at grand public-private federations attracted very few Relying Parties (despite the urgency of better identity) and spawned no commercially sustainable identity businesses. Scandinavia and the Baltics have seemed successful with multi-purpose digital IDs but these are backed by specific legislation. A few free market identity frameworks remain in development in Australia and Canada. Progress has been disappointing and their futures remain uncertain.

The hottest developments in digital identity today are not about identity! Instead,Verifiable Credentials are digitally signed data structures which convey details of the credential issuers and other conditions specific to different use cases. Verifiable credentials are bound to cryptographic keys controlled by the credential holders, so they can't be copied, spoofed or counterfeited. Fresh verifiable credential standards are being developed that update earlier PKI certificates. Multiple credentials and identifiers can be conveniently carried in personal data wallets or data carriers, which ideally feature secure elements to house the all-important private keys.

In digital life and work, we need to show things about ourselves, typically discrete pieces of important data, backed up by metadata that proves origin, Ts&Cs, regulatory commitments, consent and so on, depending on context. If we generalise from credit cards ― including terminal, data carriers, standardised contracts and service providers ― we could build truly global infostructure for verifying everything we routinely need to know. 

In conclusion, we in the industry have made digital identity hard by solving for the wrong problem! Personal human identity is always going to be rich, relative and analog but the challenges in the digital domain boil down to trustable data. We know how to solve for data reliability, by blending cryptography and governance. Our industry has been evolving and shifting focus from identity through attributes to arrive now at Verifiable Credentials. Let’s keep up the good work, let’s be clear about where actual identity problems lie, and use our tools to build infostructure for verifiable data across cyberspace and the digital economy. 

The post Why isn’t identity easy? appeared first on Lockstep.

Liz Miller

Vice President & Principal Analyst Constellation Research

About Liz Miller: Liz Miller is Vice President and Principal Analyst at Constellation, focused on the org-wide team sport known as customer experience. While covering CX as an enterprise strategy, Miller spends time zeroing in on the functional demands of Marketing and Service and the evolving role of the Chief Marketing Officer, the rise of the Chief Experience Officer, the evolution of customer engagement, and the rising requirement for a new security posture that accounts for the threat to brand trust in this age of AI. With over 30 years of marketing experience, Miller offers strategic guidance on the leadership, business transformation, and technology requirements to deliver on today’s CX strategies. She has worked with global marketing organizations to transform…...

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It is officially summer and the shopping spree continues. Some are saying this latest trip to the Billion-Dollar-Mall is set to upend markets…and yes, that’s the short-term news for those following the customer feedback charts. I’m more inclined to see a bigger shake up beyond that as new and interesting moves across multiple players could be signaling a bigger win. But more on that in a bit. Let’s get to the meat of it: Last week’s late announcement has Qualtrics scooping up feedback and analytics darling Clarabridge for a cool $1.1 billion in stock.

Qualtrics has been on a streak since spinning out of SAP in summer 2020. By January 2021, the experience intelligence firm had crushed expectations on an IPO…paid off debt…and still managed to leave some acquisition bucks burning a hole in their pockets. In Clarabridge, Qualtrics has a worthwhile expansion of customer feedback and voice aggregation capabilities that they need to fully realize the vision of being the ultimate engine for experience decision-making and engagement optimization.

Clarabridge has made a name for itself as an AI-powerhouse taking natural language processing to new levels, turning customer service and call center interactions into the highest of high-fidelity signals informing and molding customer engagements. With the capacity to analyze ALL interactions from human to bot, the Clarabridge solution unifies customer interactions into a single analytics pane including attributes that include scores on effort made by the customer, emotion and sentiment, and a tally of topics covered over time. Now just imagine, for a second, where else Qualtrics can point all that AI and NLP power. Did I hear someone say enterprise wide unstructured data perhaps?

The beauty of this move is it takes the direct feedback customers provide through Qualtrics interactions with the direct dialogue customers are having with any agent, be them human or AI.

OK…so let’s address the big elephant in my post. That’s right…I can’t with calling either platform an “experience management” solution as I am 100% in the “customers are and will remain the only source of managing their own experiences” camp. But…I will say that when it comes to customer AND experience intelligence, Qualtrics is racing to the top of that hill. But they are NOT alone. With the Customerville pickup by IFS, you have Qualtrics running up the experience side of customer mountain while IFS races up via customer service, field service, enterprise asset management (EAM) and even ERP lanes. That doesn’t even start to address what competitors like Medalia and InMoment are cooking up.

So now I’m sitting here looking around at players like Invoca, SupportLogic and UserTesting and just…well…wondering. Remember how last week with the Zoom/Five9 acquisition news I said a reckoning was coming? Waves are being made…in crazy directions and it couldn’t happen at a better time when CX juggernauts across Marketing Automation and Sales Engagement are starting down an evolutionary path we are just starting to decipher.

But here is my off the wall hot take: The biggest winners in this just might be SAP...and SAP’s CDP and CX portfolio customers.

WUT? Has she lost it? Well yes, but that is a totally separate blog post. It is easy to forget…but don’t…Qualtrics is still owned by SAP (or more specifically, SAP is still the majority shareholder) and SAP customers have been bathing in the CX messaging of Qualtrics as a critical inbound connection to customer voice that needs to be ingested into SAP’s CDP.

Words like “native” and “out of the box” integrations have been core to the SAP/Qualtrics CX decision velocity story for some time now. So now…with Clarabridge…turn on the fire hose SAP CDP customers! It takes customer voice programs to a new level with AI powered analysis of natural language, connected to a persistent, unified and harmonized customer record that now feeds all that joy BACK into a system of engagement that spans sales, service, marketing and commerce. Suddenly asking about an NPS score looks even more outdated as customers can start asking, no really, why did LIZ walk away from that last experience putting out maximum effort for minimal reward…and what do we do next to flip that?

Liz Miller

Vice President & Principal Analyst Constellation Research

About Liz Miller: Liz Miller is Vice President and Principal Analyst at Constellation, focused on the org-wide team sport known as customer experience. While covering CX as an enterprise strategy, Miller spends time zeroing in on the functional demands of Marketing and Service and the evolving role of the Chief Marketing Officer, the rise of the Chief Experience Officer, the evolution of customer engagement, and the rising requirement for a new security posture that accounts for the threat to brand trust in this age of AI. With over 30 years of marketing experience, Miller offers strategic guidance on the leadership, business transformation, and technology requirements to deliver on today’s CX strategies. She has worked with global marketing organizations to transform…...

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For a first trip to the Billion-Dollar-Baby Mall, Zoom made quite the purchase with their $14.7 billion deal for cloud contact center software player Five9. The obvious conversations about this deal center around Zoom’s explosive COVID-fueled growth that needed someplace to crash. Sure, Zoom grew, by their own estimates, 326% in 2020, and that steep climb was going to slow. Acquisition felt like the obvious answer for anyone watching. Sorry…that’s the boring story.

Let’s establish a timeline…

April 2021 Zoom announces the Zoom Apps Fund. It’s a fund to jumpstart the growth of the Zoom ecosystem of apps. Everybody and their momma has an ecosystem and a fund or “ventures”. But look past Zoom’s whole these apps are an “important component in building the future of video communications” bit. Instead turn your eye to a new line that has crept into almost every corporate communication positioning Zoom as “core to how customers meet, communication and collaborate.”

Core to how customers meet, communicate and collaborate.

May 2021 Zoom announces Zoom Event Platform for Virtual Experiences. This one flew past a lot of folks. The new capabilities combined customers, communication, collaboration and, in the case of events, commercialization. With the new event platform, events can be ticketed, with controlled access and billing in one portal, and brings a new integrated networking module for attendee connection along with back-end tracking across everything from registration to revenue.

Core to how customers meet, communicate and collaborate.

June 2021 Zoom launches Zoom Phone Appliances, representing a move into hardware were Zoom tech meets hardware from big names like Poly and Yealink so bring video and voice calling to an all-in-one desk phone. And yes…thanks to that Zoom rooms tech…this slicer and dicer even does whiteboards.

June 2021 Zoom dipped a toe into the buying pond with the pickup of Kites GmbH with a global cross-language interaction solution to ramp up Zoom’s machine translation capabilities. So now, not only is Zoom going to core to how customers meet, communicate and collaborate…they can take it all global…with a fancy new phone.

Core to how ANY customer meets, communicates and collaborates…anywhere.

So now…let’s talk Five9. First it helps to understand that Five9 isn’t your average cloud center software kit. It too saw explosive growth in 2020 as brands across both B2B and B2C markets had to send their front line of customer engagement and experience home. Call center agents didn't just start working at home, they needed to be able to connect and engage with a customer caller that was also in the same motion of uncertainty and flux.

Five9’s solution is underpinned with AI tools that turn everything into smarter things…smart dialing, smarter self-service, smart routing, virtual agents, virtual assistants…basically everything smarter that employees and customers crave to make life (and work life) just a little bit easier. The cloud solution is also untethered to a single communications channel allowing a customer to choose not just when, but also where they need to or want to engage from mobile to messaging.

Dig a bit deeper into the portfolio and you start to see a common tread…it isn’t just about how call center employees could connect and, in essence, collaborate on problem solving and question resolution with a customer, but their platform could enable employees to connect and collaborate with other employees…and suddenly Five9 isn’t “just” a call center tool but part of a larger human capitol management story...and dare I say a larger enterprise communication and collaboration story.

Dare I say it…it starts to sound like solutions that are core to how people (customers, employees, families, whoever) meet, communicate and collaborate.

So now I have to ask myself…what DOES Zoom want to be when it grows up? All signs point to leaving folks like Ring Central and even Cisco in the dust for something higher up the chain and even more broad in the realm of customer experience. And they might just make it. For most platform players in the wild and bizarre world called “Customer Experience” where everyone from surveys to emails are claiming the title of “customer experience platform,” the foundation of most of these solutions is still some Kuato-like vestige of a CRM solution, feeding off of its host waiting for Quaid to arrive.

But…what happens to CX when the center of gravity leaves the familiar trappings of CRM and takes up residence in the land of communication and service? What happens when the center point for a CX platform is literally the center point for communication with any customer or any employee? My obvious questions are not what networking, router or VoiP system Zoom is eying next…but rather what CDP, omnichannel engagement solution, DXP, marketing automation or even sales engagement system could Zoom be eyeing next.

Sure, Zoom started as the “better and sassier” video conference to Cisco. But there is something bigger at play in the opportunity…something bigger than skaing up a stale market and a stale industry. It is the chance to unexpectedly reshape it all and drive analysts like me INSANE as we grapple with new acronyms to segment this new space. This Five9 pickup hints at just how big and bold Zoom CEO Eric Yuan can go. At least to me, this is just the opening salvo.

In the end, this is how I'd summarize this acquisition: Together, Zoom and Five9 dare to be core to how customers and employees meet, communicate and collaborate.

R "Ray" Wang

Principal Analyst and Founder Constellation Research

R “Ray” Wang is the CEO of Silicon Valley-based Constellation Research Inc. He co-hosts DisrupTV, a weekly enterprise tech and leadership webcast that averages 50,000 views per episode and blogs at www.raywang.org. His ground-breaking best-selling book on digital transformation, Disrupting Digital Business, was published by Harvard Business Review Press in 2015. Ray's new book about Digital Giants and the future of business, titled, Everybody Wants to Rule The World was released in July 2021. Wang is well-quoted and frequently interviewed by media outlets such as the Wall Street Journal, Fox Business, CNBC, Yahoo Finance, Cheddar, and Bloomberg. Short Bio R “Ray” Wang (pronounced WAHNG) is the Founder, Chairman, and Principal Analyst of Silicon Valley-based Constellation…...

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THE AGE OF BIG TECH REGULATIONS HAS ARRIVED

Governments across the world seek to rein in the digital giants for political, economic, and societal rationale. While most digital giants have not flaunted the law, the public perception of their enormous size, massive scale, and unfair competitive advantage drive political motivations to check the power of big tech ahead of any economic or societal costs.

The recent five anti-trust legislation proposed by the House Democrats and the House Republicans Anti-trust agenda reflect the growing bi-partisan sentiment to reign in digital giants. Further, China’s crack down on its digital giants such as Alibaba’s Alipay and Didi highlight both the threat digital giants pose to the power structure of the CCP China government and the populist sentiment that government must do something to protect their citizens. And the recent global minimum tax deal endorsed by the G7 seeks to cut out loopholes that digital giants have effectively used to reduce their tax burdens.

Consequently, in the age of big tech regulations, both built-from-the-ground-up digital giants and joint venture digital giants will experience a high level of scrutiny for potential marketplace abuses. In highly regulated markets such as the EU, market dominance is defined as having more than 39.7% market share. But while the percentage thresholds for what constitutes market dominance may change, how dominance is defined will play a significant role in identifying digital giants that have the power to abuse their market position.

LOOKING FOR ANTI-COMPETITIVE PRACTICES

As we saw in the battle for mobile operating systems with Google Android versus Apple iOS, market share alone does not necessarily convey market dominance. Apple with less than 20 percent adoption versus Google’s 80 percent market share has managed to drive more profits than Google with a more attractive ecosystem. In the future, market dominance might be defined as the percentage of paid users, or percentage of total transactions, or percentage of personal data controlled, or percentage of economic value created.

Once a digital giant is deemed a dominant company, regulators and politicians seeking to create a more fair playing field should look out for these anti-competitive practices:

1. Forced upsell or cross-sell (Tying). When a company requires that the purchase of one product or service be made with the sale of another to restrict consumer choice. For instance, you want to purchase a video game and you are forced to buy the augmented reality headset with it whether you need it or not.
2. Bundling. Similar to forced upsell or cross-sell, when a supplier will only sell products that are put into a combined package and will not sell the individual item. For example, you are required to purchase an extended digital warranty for each digital product you buy.
3. Collusion and price fixing. When competitors work together to pre-determine and agree to either set, increase, or lower prices to impact the market. Imagine every digital mortgage broker got together to agree that they will charge no commission below 2.5 percent. In this case, fixing the floor in pricing would be a form of collusion.
4. Exclusive dealing. When a customer must purchase a majority or all of a particular type of good or service from a company and is excluded from purchasing from its competitors. One example would be when a hospital is forced to buy only one brand of hardware to run a type of healthcare software, even though the software could run perfectly on any device.
5. Exclusive rebates. Plans or loyalty programs that force a customer to purchase the majority or all their goods or services from one company and prevents them from purchasing from a competing one in order to receive a discount. An example of an exclusive rebate would be if one vendor provides rebates and volume discounts only if the customer makes all their purchase exclusively through that vendor.
6. Margin squeezing. When an integrated firm sells a product that is an essential input at a downstream rival for a similar price as the integrated firms’ finished product in order to hamper the rivals’ ability to survive or compete. For instance, a software vendor that resells its component code to competitors as well as builds its own software on the same code, decides to increase the price of the component code it charges competitors but charges its own internal teams less.
7. Predatory pricing. When a dominant entity reduces prices that create market side losses in order to force competitors out of a market. For example, a digital giant offers free shipping and returns for purchases at a loss to increase the cost of business for a competitor.
8. Price discrimination. When some market participants are arbitrarily charged higher prices unrelated to the actual costs of supplying, creating, or distributing the service or good. Charging small businesses one price for a product and large enterprises a higher price without a regard for how much volume they order could be considered a price discrimination violation.
9. Refusal to provide IP. When a dominant firm refuses to license critical intellectual property to potential competitors. An example would be if a critical security technology is banned for use in a competitor’s product, leaving them vulnerable to security attacks.
10. Refusal to supply. Similar to the refusal to provide IP, when a dominant firm refuses to supply limiting access to a competitor with a good or service to eliminate competition.  

ENCOURAGING INNOVATION THROUGH ANTI-TRUST LAWS

One of the negative consequences of a duopoly market for consumers is that they block competitors from gaining critical mass. In the course of a challenger’s lifecycle, leading digital giants will try to partner, acquire, or otherwise threaten it with retaliatory measures. The result? Each value chain will be left with only a couple of digital giants and very small players in niche markets.

In order to encourage competition, governments must enforce anti-trust laws that ensure a free-market system and corporations must respect these laws. In the US, three pieces of legislation form the core of our antitrust laws. The Sherman Anti-Trust Act sets rules to prevent restraint of trade or the conspiracy to restrain trade. Fines for violating these rules include up to $100 million for organizations and $1 million for individuals with up to 10 years of imprisonment. The Clayton Antitrust act regulates mergers and acquisitions, pricing, discounts, and other unfair practices that reduce competition and enable the creation of monopolies. The Federal Trade Commission Act bans all unfair or deceptive acts or practices and unfair methods of competition.  

In the US the Federal Trade Commission (FTC) plays a significant role in supporting free and open markets through competition. The creation, adoption, and enforcement of these rigorous anti-trust rules allows for vigorous competition on the merits of a company’s offerings. Anti-trust rules often remove the impediments to economic opportunity and powers economic growth. Without these laws, consumers face limited access to products and services and would pay higher prices for goods and services. Some of the common anti-trust rules involve the prevention of bid rigging, market allocation, mergers and acquisitions, and price fixing.

PROTECTING DIGITAL GIANTS FROM OVER-REGULATION

The balance between over-regulation and no regulation is delicate. To achieve it, regulatory bodies have to engage in a cost-benefit analysis. Most regulation is designed to protect the consumer and the smaller competitors. But regulation must also consider the benefits that come from a duopoly market: the stable creation of a new market, increase in the number of jobs, and market efficiencies gained for the consumer. New markets create and expand new categories for spending and for hiring. New types of jobs are created along with new opportunities for both the new market and its ancillary ecosystem. Market efficiencies include cheaper pricing, easier access, and more choices for customers.

In some markets, the minimum efficient scale for a given product, service, or experience is one or two per market—or even per planet. At that point these entities may emerge as regulated duopolies like Airbus and Boeing. They both sell planes, everyone can board them at an airport, and few passengers care what type of plane they are boarding. These factors should be taken into account when considering regulations of digital duopolies. 

A key guideline to keep regulation in check is to put the burden of proof on governments to show how an organization’s actions or behaviors harm consumers in a market as opposed to measuring how a policy change may improve competition. For example, dominant streaming services built on membership and advertising revenue may end up creating new models that disrupt traditional cable, satellite, and movie theater distribution. The net result is that consumers will pay less per view, content creators and consumers will avoid massive distribution fees, and more money will go back to the content creator. These benefits could outweigh the fact that there are only two streaming players with a dominant market share, and that more expensive, traditional competitors are being disrupted in the market.

The successful balance between growth and regulation will require a deft hand and smart regulators. The massive influence of digital giants on politics, society, and the economy require the smartest and most skilled professionals to ensure that policies not only address the policy needs of today, but also builds in a futurist view of the impact today’s policies may have for generations to come.

My book, "Everybody Wants to Rule the World," talks about what needs to be done to regulate big tech while balancing the costs and benefits. Get the book on pre-order now and receive the first 3 chapters today: https://amzn.to/3uR9Q9I

Your POV

How will we balance innovation with regulation?  What's required for free and fair markets?

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Dion Hinchcliffe

Vice President and Principal Analyst Constellation Research

Title: About Dion Hinchcliffe Dion Hinchcliffe is an internationally recognized business strategist, bestselling author, enterprise architect, industry analyst, and noted keynote speaker. He is widely regarded as one of the most influential figures in digital strategy, the future of work, and enterprise IT. He works with the leadership teams of large enterprises as well as software vendors to raise the bar for the art-of-the-possible in their digital capabilities. He is currently Vice President and Principal Analyst at Constellation Research. Dion is also currently an executive fellow at the Tuck School of Business Center for Digital Strategies. He is a globally recognized industry expert on the topics of digital transformation, digital workplace, enterprise collaboration, API…...

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DataStax famously has its roots in the 2008 open source release of the Apache Cassandra “NoSQL” database, which itself brought global scale database capabilities to companies seeking to overcome the growing limitations of their traditional relational databases. Though founded two years later in 2010 to support enterprise customers, the company has increasingly become a key player in how businesses think about managing data in the cloud, as well as how they hedge the risk of lock-in with large commercial cloud vendors.

Cassandra itself, and therefore DataStax, is a Java-based product that makes for easy uptake and management in IT shops because most such organizations have Java skills, which remain widely available. At its heart, DataStax is aiming at companies that have the classic problem of coping with large scale data in the cloud, along with high geographic dispersion of said data. The Home Depot, for example, uses DataStax to connect its logistics, delivery, supply chain, customers, digital channels, and associates. With Cassandra and DataStax, the home improvement retail giant successfully launched curbside pickup quickly. Datastax’s key strength is in making distributed data straightforward and workable for any business.

On its face, DataStax is to Cassandra what RedHat is to Linux:  A strategic offering that makes it easy to really bet on the product. The company  provides a multicloud-ready, serverless database-as-a-service named Astra DB so that organizations can just use it as a service with little to no provisioning. It also provides commercial support for Cassandra and an enterprise-optimized version for on premises deployments known as DataStax Enterprise.The company recently launched a new data streaming-as-a-service offering called Astra Streaming that’s built on Apache Pulsar to take advantage of that major trend as well. The offerings are fully cloud-native, run in Kubernetes, and they generally play quite well within an assembled modern cloud IT stack that IT needs now to be as future-ready and future-proof as possible.

Perhaps the single most important aspect to understand about DataStax is its vast ability to easily scale data either outside or within the confines of a large commercial cloud. The underlying technology, Cassandra, can easily handle Internet services the size of Facebook after all, which is where it originally came from. Organizations can build on and wield DataStax as their core operational database, assured that they can grow the largest business possible on it. And perhaps most significantly, all without being locked into Amazon Web Services (AWS), Azure, or Google Cloud various data storage offerings.

An Agile Cloud of Data for the Future

The digital world is still in its infancy and data growth is rapidly outpacing growth of compute speed, network speed, and storage. Managing truly vast amounts of data and feeding it through highly analytical and artificially intelligent systems to extract insights and value is becoming the top objective of just about every organization today and in coming years. Consequently, selecting the best database is a truly strategic decision today. The pernicious effects of forces like data gravity, which makes it harder to move from cloud to cloud as data volume increases, means the choice of the right database is crucial.

I’ve had a chance to talk with executives at DataStax over the last few weeks to understand their strategy and also so I can explain it to CIOs and other IT executives or digital teams. The company has its eye closely on where the industry is headed. They bring both true elasticity of database, high performance, cloud-native support, and the ability, when used appropriately, to substantially reduce the risks of data gravity and commercial cloud lock-in. DataStax also understands that the cloud is steadily moving towards models for radical ease-of-consumption, with serverless models for just about everything. The company also appreciates the painful lessons of the 1980s and 1990s, and that putting all the eggs of IT in one basket isn’t wise. This is core to their offering, and as is helping companies avoid the generation after that, where commercial SQL databases like Oracle and its near-predatory pricing also dominated. These are eras that most companies do not wish to return to as they migrate to the cloud. In short, my analysis is that DataStax is at present one of the clearest routes to ensure a move to the cloud doesn’t end up like these previous journeys.

Ultimately, DataStax provides the industry with a model for enterprise data that offers a high degree of both choice and sustainability agility for companies moving to the cloud. They enable CIOs to craft a best-of-breed IT multicloud-ready stack from the data on up that has genuine long-term legs with repeated proven capabilities within the Fortune 100. The company itself is healthy and growing. It recently received funding led by Goldman Sachs.

In the end, data is the only truly irreplaceable asset that organizations have, but it still tends to be underused and under leveraged in most organizations, in part due to over-reliance on schema-heavy, harder-to-access, and more difficult to consume traditional databases. Having a strategic cloud data capability that is both nimble, consumable, scalable, sustainable, and IaaS-neutral must be a key objective today for IT. Making the right choice unlocks the most value, helps achieve successful digital transformation, and increases innovation, while preserving the most flexibility and options among cloud vendors.

Doug Henschen

Former Vice President and Principal Analyst Constellation Research

Doug Henschen is former Vice President and Principal Analyst where he focused on data-driven decision making. Henschen’s Data-to-Decisions research examines how organizations employ data analysis to reimagine their business models and gain a deeper understanding of their customers. Henschen's research acknowledges the fact that innovative applications of data analysis requires a multi-disciplinary approach starting with information and orchestration technologies, continuing through business intelligence, data-visualization, and analytics, and moving into NoSQL and big-data analysis, third-party data enrichment, and decision-management technologies. Insight-driven business models are of interest to the entire C-suite, but most particularly chief executive officers, chief digital officers,…...

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Google Cloud’s Dataplex, Datastream and Vertex AI announcements point to a well-rounded platform.

The star performers in baseball are known as five-tool players, meaning they hit for average, hit for power, and excel at base-running, throwing and fielding. Think Hank Aaron, Willie Mays and Ken Griffey, Jr. The five-tool equivalents in data excel at data integration, data platforms, data governance, analytics and data science.

Enterprises scouting for star-caliber vendors have certainly had their heads turned by Google Cloud on the strength of its data platforms, with BigQuery being a standout, and its data science capabilities, leading with TensorFlow. (Indeed, Major League Baseball itself is a Google customer that uses BigQuery, among other services). But Google has been akin to an up-and-coming baseball star like Fernando Tatis, Jr. or Vladimir Guerrero, Jr.: It’s clear that both are going to be superstars based on their prodigious hitting, but Tatis needs to work on his fielding while Guerrero is just average when it comes to running the bases. These players need time to mature and develop all five tools.

So it goes with Google Cloud, which is maturing into a five-tool data platform. During the Google Data Cloud Summit last month, it became clear that the pace of maturation is accelerating, with three crucial services announced: Dataplex, Datastream and Vertex AI. These services will help to fill out an integrated, end-to-end platform for data engineers, data scientists, developers, data analysts and business users (see slide below).

Google Cloud is filling out an integrated data platform aimed at a broad spectrum of users.

Google describes Dataplex, now in preview, as an “intelligent data fabric.” We’ve seen fabrics (also known as data virtualization and data federation) before. What is now TIBCO Data Virtualization, for example, was founded as Composite Software in the mid-2000s. Microsoft SQL Server PolyBase and Teradata Query Grid are two other examples. IBM announced an all-new fabric offering, called AutoSQL, at the IBM Think event last month.

The idea with data fabrics is to virtualize access to data, with queries reaching out to myriad, distributed sources without having to move or copy that information into a centralized data warehouse. Fabrics increasingly extend across data lakes and data science environments.

The “intelligent” part of Dataplex promises “automatic data discovery, metadata harvesting… and data quality with built-in AI.” Google is also touting centralized security and governance capabilities, including “data policy management, monitoring and auditing for data authorization, retention and classification.”

It’s pretty clear that Dataplex, which is in private preview, is combining data virtualization, which I would put in the data integration camp, with the data governance role, addressed elsewhere by metadata management and governance offerings such as independent Collibra, IBM Watson Knowledge Catalog and (also in preview) Microsoft Azure Purview.

Given Google’s multi-cloud efforts with Google Anthos and BigQuery Omni (which now extends BigQuery data access to AWS and Azure), Dataplex will surely extend beyond Google Cloud, but we’ll have to wait to see what’s available at launch and what comes later. Google has stated that support for other data sources is coming “soon.”

Datastream, a second big announcement at last month’s Google Data Cloud Summit, is a change data capture (CDC) and replication service, now in preview, that will support low-latency requirements including real-time analytics, heterogeneous database synchronization and event-driven architectures. Squarely in the data integration camp, CDC technology is also not new, with long-standing market leaders being Oracle GoldenGate and Qlik Data Streaming (CDC) (formerly Attunity). Nonetheless, the company says its offering takes a different approach by offering a serverless service that automatically scales while replicating and synchronizing data with minimal latency. It integrates with services including BigQuery, Cloud Spanner, Dataflow and Data Fusion.

Vertex AI has been enhanced with new services to ease the production deployment of AI and ML models.

The third notable announcement last month was Vertex AI, (formerly “Unified AI Platform”) announced at Google I/O. Though this platform for model builders is not entirely new, it has many new components (shown above), including a feature store, pipeline capabilities and model monitoring capabilities. This builds on Google’s already strong AI capabilities by rounding out the tools needed to get models into production more quickly.

In addition to the new integration, governance and data science tools detailed above, Google also announced a preview Analytics Hub service that will provide a collaborative library for curating analytic assets and sharing and monetizing data. So here again, Google is building on core strengths like BigQuery and rounding out the portfolio to be a complete data player. I’m looking forward to an increasingly competitive public cloud playoff season that will extend over the months and years to come.

The thermometer outside says it’s 90 degrees, but as I sit gently cooking at my desk, the real heat these days is in the sales tech market. The last four weeks have seen four major funding announcements in what I’ve broadly called the B2B seller enablement space. The amounts raised range from $80 million to $250 million with valuations from several hundred million to several billion dollars.

Don’t let the stupefying numbers (and temperatures) fool you—these companies are hot for good reason. Though none of the four are direct competitors (yet), they all address some of the fundamental challenges of selling effectively, each with its own particular focus and specialisms. They also fill one essential gap that has existed in traditional CRM systems for the past two decades: automating data capture and updates. This simple yet powerful ability to liberate sellers from administrative work is the single unifying factor among every vendor in this category, including the four companies here. It’s also the foundation of all the other capabilities that help improve the ways companies sell.

Here are the big announcements in order of recency:

Introhive Dials in Relationship Intelligence

On June 16, Introhive announced $100 million in Series C funding, led by PSG and including several existing investors. That’s a substantial increase from previous funding rounds totaling $40 million. Introhive, founded in 2012, has developed its offerings around the needs of businesses that build long-term relationships with their clients—think consultancies, law firms, recruitment companies, and, increasingly, financial services and technology companies. For these businesses, building customer relationships is often the job of partners and principals, not necessarily sales teams.

What distinguishes Introhive’s offerings in the market, aside from a clear understanding of how relationship-driven businesses operate, are relationship mapping and an almost obsessive focus on data quality. The company’s automated data capture uses machine learning to populate CRM systems with the timing and nature of customer interactions. At the same time, the system uses that data to build and score relationship maps across organizations, while also identifying important insights about customer accounts.

Introhive also has a specific offering around data cleansing, using AI to incorporate both internal and external data sources to validate data in CRM. The emphasis on data quality has substantial impact on the accuracy and reliability of the analysis Inrohive provides. This spans account intelligence, relationship maps, coaching opportunities, and pipeline analysis.

Gong’s Conversational AI Drives Revenue Intelligence

Gong announced $250 million (the largest in our assortment here) in Series E funding on June 3. The round was led by Franklin Templeton along with numerous other existing investors. This brings the company’s total funding so far to $584 million and values Gong at $7.25 billion.

Founded in 2015, Gong’s claim to fame is using natural language processing (NLP) to understand and assess sales calls and communications. In addition to automated data capture and CRM updates from email, chat, phone, and video calls, Gong uses NLP to analyze the substance of those conversations. By identifying and extracting key words, Gong filters insights into deal intelligence, people intelligence, and market intelligence.

Deal intelligence provides sellers with a clear view into how opportunities are trending and what actions are most likely to close deals. People intelligence gives sales managers and leaders insight into what the most effective sellers are doing and when, as well as identifying where individuals may need coaching, training, or additional support. Market intelligence highlights trends across opportunities like key competitors, emerging trends, and the most effective value propositions.

Outreach Ups the Ante on Remote Selling

On June 2, one day before Gong, Outreach announced $200 million in—wait for it—Series G funding, increasing the company’s valuation to $4.2 billion and total funding to $489 million. This latest round was led by Premji Invest and Steadfast Capital Ventures, with additional investors participating.

Outreach’s founders initially developed the company’s technology when they were running a previous startup and realized their biggest challenge was identifying and pursuing customer leads with limited manpower. They needed to make sales but with a small staff, couldn’t afford to waste time on low-value admin tasks or pursing apparent prospects that weren’t really interested.

To make the best use of what time and resources were available, they used machine learning to capture data from email exchanges and leveraged calendar plugins to automate meeting scheduling. From there, Outreach, founded in 2014, began to focus on developing automated cadences to maintain communication with prospects, gauge their level of interest, and focus on those most likely to close. Initially, the company’s bread and butter was supporting inside sales teams responsible for opportunity identification and qualification. With the pandemic-driven move to remote sales for all kinds of sellers, Outreach has expanded the scope of sales constituents it serves.

Dooly Does It

News about Dooly’s somewhat stealthy $80 million Series B funding round came out on May 20. The round, hot on the heels of Series A funding, was led by Spark Capital with participation by several other investors. According to Tech Crunch, this round, which brings total funding to $100 million, values the company at $300 million. Dooly was founded in 2016.

Dooly brings a straightforward yet extremely powerful offering to the seller enablement market: automated note taking and data syncing across a wide range of applications, including CRM. Through integrations with videoconference platforms, collaboration tools, email, calendar, document stores, and even other seller enablement tools, Dooly uses NLP to identify relevant keywords. This allows users and ops teams alike to build playbooks, connect useful information to keywords, and surface relevant supporting documents at the moment they’re needed.

The flexibility and extensibility of Dooly have broad application across customer-facing teams. By focusing on capturing insights and synchronizing them across multiple systems, Dooly removes a significant admin burden while improving transparency and coordination.

There’s a Big Waterfront to Play In

Looking across these four announcements, what strikes me most is the tremendous potential these companies (and others in this space) have to fundamentally change the way we work, starting with the way we sell. All these technologies are focused on making the job of selling easier and the experience of buyers better as a result. That’s a big reason why the people using each of them seem to be such big fans.

And, fascinatingly, it’s not uncommon to see two or three of the vendors here happily coexisting with a single customer. I wouldn’t be at all surprised to hear of all four of them being used in the same business. At some point growth, expansion, and eventual market consolidation will draw starker competitive lines between them. For now though, the diversity of approaches to tackling the challenges of B2B selling is a good thing. It means plenty of options for companies trying to find the right solutions to match the way they work—and the way they want to in future.

When you consider how much of the economy is comprised of companies that sell to other businesses, it’s easy to see just how big the opportunity really is. Every company has to sell, and everyone wants to do it better. Just wait until marketing is brought into the fold. What we’ve seen so far is still just a drop in the bucket.

On that note, time to go for a swim to cool off…

For more information and detailed discussion of the seller enablement market, see “B2B Relationship Selling in the Virtual Age: New Seller Enablement Tools Facilitate Old-School Fundamentals,” by yours truly.