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A version of this purr-fect article originally appeared in The Drum on Feb. 13, 2023, a few days after Super Bowl LVII aired. A picture of my photogenic muse Jerry appeared at the end (as it does below).

While some people say the Super Bowl was a close game, it really wasn’t. Dogs totally dominated cats in the USA Today AdMeter poll.

The Farmer’s Dog came in first with a time-travel tail – uh, tale – that showed just how good dogs are at nuzzling our emotions. Amazon’s bad-dog-turned-angel saga took third.

And where were all the spokescats? Not feline the love. One provided a whisker of comic relief in a Google Pixel ad, where a sour puss pointedly removes a dog from a photo with AI. Probably out of jealously.

It turns out, there’s a good reason for the double-standard. Cats and dogs evoke different emotions in people and can be used to inspire specific actions in marketing.

• Dog actors actually inspire us to make connections, take risks, and share our personal space
• Cat actors put us in mind to purr-chase more insurance, protect our homes and families, and prep for doomsday

So says a first-of-its-kind study which tries to quantify the impact of cat and dog talent on consumer behavior.

Dogs Say YOLO, Cats Say YOWL

Half of U.S. households have a dog and one-third have a cat – a number that continues to grow. One in five households even found a new furry friend to rescue them during lockdown.

And we are big spenders, not just on our pets. Pet owners tend to be more affluent, healthier, more confident, even better-looking (meow).

Pets appear often in entertainment, from Puss in Boots to every perfect-family-with-an-SUV TV spot, especially if it’s in the snow (cue adorable baby Bernese mountain dog). But the impact of our four-footed friends on our attitudes and behaviors hasn’t really been clawed over until recently.

The current study – a collaboration among universities in the U.S. and Hong Kong – wasn’t yet another meme about cat-people vs dog-people. It showed that dogs and cats actually evoke a chain of emotions in most consumers that is both different and predictable. They prime the message pump.

For decades now, many researchers have adopted an idea called regulatory focus theory, which claims there are two basic consumer mindsets:

• Promotion – focusing on gains, success, YOLO, being all that we can be
• Prevention – focusing on safety, preserving what we have, personal security, avoiding risks

Now we consumers aren’t all one or the other – except in the case of some fussy outliers – but have a mindset that can be shifted by social cues and marketing messages … which brings us to pets.

”This stream of research suggests that a promotion-oriented eagerness system better captures dogs’ temperaments and behavioral characteristics, whereas a prevention-focused cautious system better describes cats’ temperaments and behavioral characteristics.”

In fact, advertisers already intuited the study’s findings before it appeared. (And they exhibit a subtle anti-cat bias, which cats will remember when they take over the world.)

Cats are often used in dark and dyspeptic scenarios:

• Wells Fargo demonstrating “suspicious activity” on cards, pushing alerts
• Sainsbury’s (U.K.) Mog the Cat, disappointed by an empty dinner bowl at Christmas, warning us to shop early
• That alarming All-State ad where Mayhem cat-thropomorphizes from human to feline while his home decomposes around him

Meanwhile, of course, dogs tag along with kids in the sunshine and spread nothing but golden light and joy:

• Wells Fargo, this time with Regina King and a golden retriever promoting a cash-back rewards card
• Subaru Ascent … which featured no fewer than seven adorable goldens outside a condo sign-posted “The Barkeleys” and … I rest my case.

Cats, Fight Plaque!

The researchers got their human test subjects primed with dog (or cat) questions and images, putting them into the promotion (or prevention) mindspace. Then they asked them if they would buy toothpaste that would “freshen breath” (or “fight plaque”).

Not surprisingly, the dog-primed promotion-focused pack preferred the fresh-breath feature. The cat-primed prevention-focused pride wanted to take a swipe at that plaque.

Other scenarios found that the dog-primed pack was significantly more likely to:

• Participate in a lottery

• Buy stocks (vs funds)

• Buy vitamins that made wellness (vs prevention) claims

On the other paw, the cat-primed group was more likely to:

• Stay away from high-flying but risky stocks

• Put a higher value on preventative health services

• Spend more for products with prevention claims

The experiments controlled for factors like personal pet ownership, preferences and even mood. So again, it’s not just more cat-people-are-shy propaganda. Rather, it’s evidence that there is some stereotypical behavior in animals that triggers semi-unconscious associations in people. These associations in turn nudge consumers into a particular general mindset, which can bolster certain messages.

So now we have some guidelines for our feline- and canine-themed campaigns. That’s something to howl (or meow) about.

If you didn’t know, for the past 18 months or so I’ve been hosting a podcast with the inimitable Jill Royce on the topic of ad-tech history. It’s called #PaleoAdTech and we’ve been blessed with a roster of ad-tech titans, from the pinballing pioneers of the dot-com days — now-forgotten blazers like AllAdvantage, AdAuction and FlyCast; and well-remembered disrupters like DoubleClick and Advertising.com — to the makers of a more recent past, like AppNexus and MediaMath.

Wondering where ad servers, DSPs, DMPs, SSPs and all the other Ps came from? Join us as we regularly offer 30-minute chats with fascinating founders, co-founders and otherwise intriguing entities. Find it:

• At this dedicated website riven with illustrations, links and brain-blowing insights
• At Apple Podcasts
• At Spotify
• Via the RSS feed, if you like

Taylor Swift has a way of breaking things: records, superlatives, hearts, and even – when she committed the previously inconceivable magic of occupying all ten spots on the Billboard Top 10 with tracks from her 10th album Midnights – herself:

She also broke Ticketmaster, apparently startled by demand for the 2.5 million tickets available for her 52-city ‘The Eras’ tour, her first since 2018.

“It’s a function of Taylor Swift,” said the CEO of the largest shareholder in Live Nation/Ticketmaster’s on CNBC. “We had 14 million people hit the site, including bots….” Even non-humans love Swift.

What’s her secret? After Midnight dropped at, of course, midnight on October 21st, Swift became the most-streamed artist with the most-streamed album in a day on Spotify, breaking records set by her own Red (Taylor’s Version) and 2020’s folklore.

By now, it’s clear Taylor Swift’s only rival is herself.

“Taylor Swift is nearly unimpeachable as a human, role model and brand,” Aaron Kwittken, Chief Executive of the PRophet, told The Drum recently.

As a brand – setting aside her artistry for a moment – Taylor Swift is a global phenomenon. Capital One, Target, Starbucks, Keds, CoverGirl, Diet Coke, Apple, Comcast, American Greetings – just a partial list of partners who have contributed to her estimated $400 million net worth in recent years.

Make no mistake; she’s a marketing engine. And it turns out brand Taylor Swift has a definite playbook, refined over her fifteen-year career. She still has a lot to teach marketers.

1. Be an Anti-Brand

The first single from the 13-song Midnights was called “Anti-Hero,” which Swift claims is about her “insecurities.” (Remember that number 13: it’s important.) In many ways, Taylor Swift is an Anti-Brand.

Traditional branding calls for a definite identity, promise and voice. It requires research-driven lines in the “brand space.” But Taylor Swift doesn’t have these things – she’s more of a “Blank Space” on which any of us, no matter how different, can see anything we need to see, especially ourselves.

Earlier this month, Midnights sponsor Capital One revealed two spots for the World Series called “Multiple Taylors,” featuring versions of Swift from 1989, Speak Now and others. It recalled the cryptic video for her song “Look What You Made Me Do,” from Reputation, unleashed at the 2017 MTV Video Music Awards, which featured fifteen versions of Swift, from the Red ringmaster to the stunned victim of Kanye’s notorious trophy-snatching.

She dared to ask us: “Who is the real Taylor Swift?” And the answer: We all are, pick the one you want.

She’s an oddly malleable brand, ideally suited to an age of creators, remixes and memes. It makes sense that there are multiple versions of two of her albums, with at least four more to come. Another celebrity, Ryan Adams, famously rerecorded her entire 1989 himself.

And then there are the lookalikes: it’s possible to become TikTok famous just for looking a little bit like Swift. And the oddly Teflonish quality: famous people who seem to want to feud with Swift somehow end up fading away (like Katy Perry) or on stage at one of her shows singing a duet (like Hayley Kiyoko), best friends forever.

Sociologist Emile Durkheim talked about totems as supernatural objects within which tribes can see themselves. Brands like Taylor Swift are totems for the age of TikTok.

2. Make Your Fans Do Work

It’s not easy being a fan of Taylor Swift; just ask us. Between buying $75 pajamas at her Official Store, waiting on virtual lines that break, and pre-ordering 13 copies of the expanded 20-song Midnights (3am Edition), there’s barely time to decipher all the clues she’s left in her TikToks, lyrics and Insta captions.

Mainstream fans might not know it, but Swift has long embedded Baroque ciphers into her marketing materials. She does this to encourage social media action, conversation, digital engagement – and of course to repay our attention.

Swift’s code-work started early. Her first album, Taylor Swift, released in 2006 when she was 16, featured liner notes with random capital letters, embedding messages like “Date Nice Boys.” She told the Washington Post: “That’s how it started, and my fans and I have since descended into color coding, numerology, word searches, elaborate hints, and Easter eggs.”

Examples abound – so many, in fact, that at least one commentator has ranted that “people treat Taylor Swift’s albums like they’re the damn Da Vinci code!”

Many of these Easter eggs are simply rewards for the faithful, references to outfits and props from previous albums. In the video for “Anti-Hero,” a stand-in breaks a guitar from the Speak Now tour, and a character wears a dress from Fearless. Others are aimed at completists: there are four versions of the vinyl album cover for Midnights that can be tiled to build a clock.

In her more Gothic Reputation phase, Swift packed the video for her first single with references to Mean Girls, her “Out of the Woods” video, a dollar bill she won in a notorious lawsuit, snakes and tea referring to various Kardashians, and so on.

It’s all harmless fun but can get hyperbolic in an overwired age. Swift’s fans often work harder than required, locating clues that aren’t actually there. Last September, the NFL made the mistake of issuing an announcement at midnight. Immediately, Swift’s conspiracy-minded cadre built a widely-reported rumor that Swift herself was going to be the half-time show at the Super Bowl because – well, of course – Taylor Swift owns midnight.

The announcement had nothing to do with Swift. Sometimes midnight is just midnight. (Rhianna is doing the half-time show.)

There’s a sociological theory that the successful cults are those that make their adherents work harder. Brand Taylor Swift is annealed by all the work we put into it.

3. Master the Art of Suspense

On October 7, thirteen days before Midnight‘s release, Swift started posting videos on TikTok under the title “Midnights mayhem with me.” The singer pulled titles from a bingo cage at random, announcing them and providing backstories. At the same time, Spotify co-branded billboards appeared in New York City and London with enigmatic snippets of song lyrics.

As the Drum’s Audrey Kemp wrote recently, these tactics were part of the masterful rollout of Midnights.

Swift has always made the most of withholding and releasing facts most prized by fans: release dates, album and song titles, co-stars. Last year, for Fearless (Taylor’s Version), she combined suspense with her penchant for puzzles, tweeting a video of a vault filled with scrambled letters. These were unscrambled by the intrepid to reveal the names of collaborators Phoebe Bridgers, Chris Stapleton and Ed Sheeran, and song titles such as “All Too Well.”

For 2019’s Lover, Swift provided both a Monday and a Saturday version of the mystery. She admitted the video for “ME!” contained the (unknown) title of her next album, but fans rejected “Lover” because it was too obvious, appearing in huge pink neon letters on the top of a building. The album was called Lover.

Then some sharp-eyed owners of her official calendar noticed a butterfly stamp on April 13 (there’s 13 again), and thirteen days later, Lover‘s first single debuted.

This kind of suspense makes her releases more poignant. Combined with a sense of scarcity, carefully cultivated through the ticket-buying (or not-buying) process, it puts Swiftys into a state of near-continual brandemonium around these key launch windows.

So brands, be like Taylor: malleable and flexible, demanding in a way that rewards close attention, and above all unpredictable. Taylor Swift is in show business, of course, but now so is every brand.

Note: a version of this article originally appeared in The Drum on November 23, 2022.

Elon Musk does not have a love-hate attitude toward advertising: he hates it. At least, that’s what he said – on Twitter, of course – back in 2019: “I hate advertising.”

This may be a curious attitude for a new media mogul whose most recent acquisition – that same Twitter – is almost entirely ad-supported.

But it turns out that Musk is not alone. The history of major ad platforms is littered with righteous founders who did not like the business they now own. In fact, it’s difficult to find a founder who expressed any fondness for ads, let alone ad tech.

But when revenues are required, attitudes change; call it a pivot to reality.

Here – in alphabetical order – are the origin attitudes of the great modern ad businesses. What’s the lesson? We change as we grow? Maybe. Or maybe, like Musk, we all need to learn a little respect.

Amazon

“Advertising is the price you pay for having an unremarkable product or service.”

– Jeff Bezos, founder (2009)

Apple

“If a business [i.e., advertising] is built on misleading users, on data exploitation, on choices that are no choices at all, then it does not deserve our praise. It deserves reform.”

– Tim Cook, CEO (2021)

Facebook (now Meta)

“I say it’s time to start making money from theFacebook but Mark [Zuckerberg] doesn’t want advertising. Who’s right?”

– Eduardo Saverin, co-founder (2004), quoted inThe Social Network

Google (now Alphabet)

“… [W]e expect that advertising funded search engines will be inherently biased towards the advertisers and away from the needs of consumers.”

– Sergey Brin and Larry Page, co-founders (1998)

Instagram

“If we were to just build a product for advertisers, we would have no consumers.”

– Kevin Systrom, co-founder (2012)

LinkedIn

“Silcon Valley is not particularly good at marketing.”

– Reid Hoffman, co-founder (2021)

Netflix

“We want to be the safe respite where you can explore, get stimulated, have fun, enjoy, relax — and have none of the controversy around exploiting users with advertising.”

– Reed Hastings, co-founder (2020)

Oculus (now Meta)

“It’s not clear right now that advertising is the right model for virtual reality anyway.”

– Palmer Luckey, co-founder (2015)

SnapChat

“I got an ad this morning for something I was thinking about buying yesterday, and it’s really annoying.”

– Evan Spiegel, co-founder (2015)

WhatsApp (now Meta)

“Advertising has us chasing cars and clothes, working jobs we hate so we can buy shit we don’t need.”

– Jan Koum, co-founder (2014) [channeling Fight Club]

Yahoo

“We are probably the last people in the world that want to do this [i.e., advertising], but it will be tastefully done, and that will keep it free to the users, like TV.”

– Jerry Yang, co-founder (1995), quoted in Inside Yahoo by Karen Angel

Note: a version of this piece originally appeared in The Drum on Nov. 22, 2022

This article first appeared in The Drum on Oct. 11, 2022

Without appropriate cultural relevance, data analysis and distributed resources and knowledge, centers of excellence can undermine global success, writes Salesforce’s Martin Kihn as part of The Drum’s Globalization Deep Dive.

/ Leon Seibert

Many of us remember where we were during the great chopstick scandal of 2018, when a storied luxury fashion maison launched three highly-produced videos on YouTube in China to support an upcoming show.

In them, models tried to eat traditional Italian food like cannoli and pizza using chopsticks, with predictable results: a hot mess for both the utensils and the brand, which faced a chorus of complaints from Chinese consumers on Weibo and other platforms, claiming cultural tone-deafness.

The brand quickly pulled the videos, canceled the show and has since lost share in the Chinese market. Part of the problem was a lack of localization in global brand messaging – or what one study of social marketing fails politely called “inadequate research.” The brand had a world-class marketing team, but it was back in Milan, the company’s de facto ‘center of excellence’ (CoE).

During a time of cultural sensitivity, global marketers must balance the imperative to build out such centers with a growing need for in-market nuance. There are new forces facing global marketers that call into question the conventional rush to build centers of excellence across almost every functional discipline.

It turns out, excellence may increasingly be found at the edge – not the center.

Four horsemen of the CoE-pocalypse

There is much logic and some evidence that CoEs can add value. Firms such as Gartner have long championed CoEs for marketing functions such as analytics and data science. They generally define a CoE as a discrete cadre of coordinated professionals with specific, uncommon expertise, who cross-reference ideas, disseminate practices and templates and function as a skilled resources for dispersed global operations.

So compelling is the impulse to the CoE model that it is difficult to find any doubters. Consultancies such as McKinsey routinely recommend establishing a CoE for advanced functions. For example, a recent McKinsey report on automation says: “A center of excellence is vital both as a source of expertise and to define priorities.” Meanwhile, the US Army has at least 15 CoEs for functions from missile defense to human resources.

Global marketers have taken the advice and adopted CoEs. A Gartner survey indicated that two-thirds of enterprise marketers already had an analytics CoE five years ago – yet this year, 26% of CMOs identified analytics as an ongoing capability gap. The same research revealed global marketers had a lot of swagger about their ’operational excellence’ (only 15% cited as a gap), due in part to CoEs.

Yet as the chopstick incident implies, not all wisdom can be centralized. And there are a number of rising forces that point toward the need for global marketers to question the march toward CoEs.

The four horsemen of the CoE-pocalypse are:

Cultural relevance: Local consumers require local nuance – and will take to social media if it’s missing.

Data bias: AI and machine learning models can inherit bias from data collection and processing methods, both of which can have a cultural dimension that is only now being recognized.

Knowledge resources: Many formerly ‘specialized’ disciplines – including reporting and campaign automation – are more common, with widespread learning resources.

Distributed workforce: More dispersed and hybrid employment models undermine some of the CoEs’ neo-Xerox Park ‘skunkworks’ premise.

To CoE or not to CoE?

How is a marketer to assess whether or not a CoE makes sense for a particular situation? As an ex-consultant, I’d be surprised if I didn’t propose a solution in the form of 2×2 framework.

CoEs are supposed to support: (1) availability of specialized skills; and (2) processes that can be run globally rather than locally. So by implication the axes of our 2×2 are:

Skill level: specialized v unspecialized

How hard are the skills to find in most global markets? If they’re rare and uncommon, or less rare in some regions than others, a CoE may be in order. As marketing teams get more sophisticated over time, fewer skills may fall into this area. (According to Gartner, the hardest marketing skills to find in the current environment are data and analytics, customer experience management and marketing technology; the easiest is social marketing).

Cultural proximity: embedded v not embedded in local culture

Is the function something that requires an awareness of how actual human beings talk, think and work in a specific context or not?

Another way to evaluate this requirement is in symbolic terms: How much does the function use global symbols, such as numbers, versus more culturally loaded symbols like words and images? If it’s mostly about numbers, a CoE could work – and if not, it may be time to reevaluate.

So the CoE is most useful for marketing challenges related to data modeling and predictions, such as next-best-action and -experience – and for data operations and automation projects that can be standardized across regions. It is less useful for developing creative artifacts for specific regions and building media plans.

Let’s apply the framework to our original example. We see the capabilities required are video production and creative development, skills that are both locally available and deeply embedded in the culture – so, not amenable to the CoE treatment. On the other hand, were that same brand to implement a marketing automation system, it would be entirely reasonable to spin up a CoE for that.

As we go forth into our new world of global marketing, we should take care to discriminate non-human processes from very human communications and recognize that both standardization and globalization have their limits.

Martin Kihn is senior vice-president of strategy at Salesforce Marketing Cloud. For more on what marketers and their partners need to do to succeed on a global level, check out The Drum’s Globalization Deep Dive.

This article first appeared in The Drum US on August 31, 2022

We’re all under the influence.

Influencer marketing is the fastest-growing paid channel this year, after connected television (CTV), resilient even in the face of recession. As companies plateau their use of social media, 75% of US marketers plan to invest in influencers this year – up from 66% in 2020, according to eMarketer.

And it’s not about products-for-posts anymore – it’s big business. Global marketers spent about $14bn on influencers last year, including media. B-listers such as Joanna Gaines and Addison Rae enjoy multi-figure deals, while real-life stars including footballer Cristiano Ronaldo get an estimated $500,000 per post. And there are thousands of creators in niches from travel to beauty to – of course – cats who are paid an average of $100 per 10,000 followers per meow.

In a world where 50 million people call themselves ‘creators,’ there are a lot of options for brands to partner their way into feeds, tweets and videos. Influencers can provide creative content, access to elusive audiences, higher engagement and compelling social proof.

But there’s a problem. Brands using influencers, surveyed by the Association of National Advertisers (ANA) in 2020, admitted their top challenge was measurement. The situation is no better now. How do you know if you’re getting a worthwhile return-on-influencer (ROIn)?

Channels are not created equal

Measuring the impact of an influencer program is notoriously sketchy. It’s an emerging channel without industry standards. Although the Media Rating Council (MRC) has established guidelines for paid social measurement, most of the value of influencers comes from organic engagement – all those likes, shares and comments from followers and friends of friends that turn a snippet of video into cultural cachet.

Challenges with measuring ROIn include:

1. Data collection: Brands without API access to influencer accounts rely on methods such as emailed screenshots for metrics
2. Reach: It is difficult (read: impossible) to deduplicate audiences across platforms
3. Engagement: Different platforms present different options (where TikTok garners likes, Pinterest culls clicks) and define ‘engagement’ in different ways
4. Consistency: Agency partners often use proprietary roll-up metrics that can be opaque

Earlier this summer, the ANA released the first ‘Influencer Marketing Measurement Guidelines,’ taking a step toward standardizing organic measurement. Developed by the Influencer Marketing Advisory Board – formed in 2020 with reps from brands such as Puma and Target – it was based on meetings with 25 agencies and the eight major platforms (Facebook, Instagram, LinkedIn, Pinterest, Snapchat, TikTok, Twitter and YouTube).

Brands that have been there will tell you that working with influencers is special – more like hiring an improv troupe than deploying a bot. Companies like control, but creativity is part of influencers‘ charm. So it makes sense to start by asking them how they measure success. A beauty star such as Huda Kattan might value video engagement, while a photo influencer such as Murad Osmann might care more about shares.

Most brands measure ROIn based on ‘engagement,’ a blunt sum of actions divided by exposures, aggregated across all the platforms in the campaign. But this method assumes every creator aims for the same responses, and it ignores the platforms‘ real inconsistencies.

Many roads to the rainbow

Using basic discipline, the hard-working marketer with an influencer program wants some combination of three KPIs:

1. Awareness: This is driven by reach and frequency, generally available for each platform in isolation, but not across platforms; video views are usually counted here
2. Engagements: These are measured interactions with the influencers‘ content, including likes and shares – often expressed as an ‘engagement rate’ (ER) or engagements per reach
3. Conversions: Often the ultimate goal, this is likely undercounted and based on direct clicks through to the brand’s commerce site or other destination

Now, the ANA performs a public service in teasing out the vagaries of the platforms‘ self-reported metrics. Anyone who’s spent time parsing reports from social networks will appreciate this effort. Key differences among the platforms‘ influencer reporting include:

1. Facebook and Instagram: For Meta-owned platforms, ER is total engagements divided by impressions, not including video views
2. TikTok: ER is total engagements divided by video views, excluding replays
3. YouTube: ER is the same as TikTok; however, TikTok counts any video that’s started as a view, while YouTube only counts a view after 30 seconds or 100% for its short-form ‘Shorts‘
4. Twitter: Twitter is similar to Meta, but quote-tweet counts aren’t available via the API
5. LinkedIn: ER does not include video views, which are counted after two seconds with 50% viewable
6. Snapchat: Interestingly, Snap doesn‘t yet provide organic influencer reporting

Understanding the components of the platforms‘ reports unlocks comparisons. Obviously, an autoplay video view on Twitter isn‘t as meaningful as a video view on YouTube, and a retweet on Twitter is not exactly equivalent to a pin on Pinterest.

For awareness and conversion measurement, reach by platform and direct attribution are useful. They aren‘t perfect, since the former misses duplicates and the latter indirect attribution (ie people saw the content and converted later, or offline). But they‘re reasonable baselines.

The problem comes with the most important influencer metric: engagement rate. How can it be improved?

Worth the weight

The answer is by weighting the different components of engagement. Intuitively, we know that a like isn‘t the same as a share or a comment. It‘s easy to like a post – you just tap the heart, right? But sharing to your network is a kind of endorsement, and a comment – with the right sentiment – indicates more visceral involvement.

A principle I used when measuring the impact of social media for brands was one I took from the self-help guru John Bradshaw: “We give time to those things that we love.” Simple enough. Extending it to social platforms, I‘d argue that actions that take more time and effort should count more toward ROIn.

For example, the marketer can create a consistent weighting factor for different actions based on the time they take to complete. Say it takes a second to commit to and tap a like. Even a short, positive comment takes at least five seconds. And a share with a comment might take longer. Typical viewer patterns should be considered, and they will vary considerably based on the influencer and type of campaign.

The ultimate ROIn plan might include breakouts for awareness and conversion, and an approach to ER that considers weighting actions by their level of effort. (The ANA guidelines don‘t address weighting.) Of course, a detailed formula requires access to the platforms‘ API and permission from the influencer. Art, science and some social engineering are required.

But that’s what puts the ‘sure’ in measurement.

Martin Kihn is senior vice-president of strategy, marketing cloud at Salesforce.