Digital Influence Mapping Project

How Deep Learning May Change Marketing

Listening to Hugo Larochelle, researcher at Google Brain, talk about the relationship between artificial intelligence, deep learning and the, apparently, much-maligned neural networks, two things become clear. First he is super smart. Like PhD+ smart. Like unattainably smart. The second is that Canada is where all the neat AI and deep learning breakthroughs happened – speech recognition that actually works, image recognition and more.

When I challenged him jokingly on the Canadian thing, I was expecting a light-hearted response like the character Chekhov in the original Star Trek series who always claimed Russia came up with everything – “It was inwented by a leetle old lady in St. Petersburg.”

Hugo is serious and backs up his claim about the Canadian heritage via smart folks like Geoffrey Hinton and others (see a great story from MIT Technology Review on Hinton and Deep learning here ) Then Hugo gave us a “deep learning” demo-for-dummies. It was almost impenetrable. What he took for obvious and self-evident gave me a headache. Still, it left me with a clear sense that deep learning and AI will radically change many aspects of marketing someday.

 

What is Deep Learning

With all apologies to Hugo, my simplified take is that deep learning is computers using human brain-like neural networks to find or apply meaning to data. Here’s how Bernard Marr (@BernardMarr ) puts it:

“…it’s probably most helpful to think of Deep Learning as the cutting-edge of the cutting-edge. ML (machine learning) takes some of the core ideas of AI and focuses them on solving real-world problems with neural networks designed to mimic our own decision-making. Deep Learning focuses even more narrowly on a subset of ML tools and techniques, and applies them to solving just about any problem which requires “thought” – human or artificial.”

 

Four Ways Deep Learning May Change Marketing

Pulling meaning from quantitative and qualitative customer research

Think about the last quantitative survey you did and the effort to derive insights and meaning from it. What a laborious process. There’s all the mechanical procedures and strategic choices that go into creating the test instrument and then administering it. At the end of the day, humans review that data and assign meaning to it.

Deep learning and AI may not only be able to sort through the data to more insightful and defensible insights, it may be able to detect better inputs than self-reported responses. Hershey did this via Affectiva with their smile-detector – technology that reads and analyzes human emotion from a single expression, in this case a smile.  AI or AI-like image recognition played a role here to better understand the nature of the smile delivered.

 

Understanding customer intent more precisely

Think about how we use search engine optimization to understand intent and then deliver something valuable. By sorting through keywords, phrases and the complete questions people now type into Google, we can draw conclusions about what the person is trying to accomplish. Pretty crude and straightforward.

With deep learning and big data sources from search engines, social media and where people go online next, it may be possible to better understand (infer?) what people are trying to accomplish. Marketers can then be more effective at serving their needs. How to accomplish this and stay on the better side of privacy is key as is the potential misuse of this hypothetical knowledge.

Deep learning would be seeking “patterns within patterns” of data over time. Rather than being able to recognize visual or auditory patterns, this might give us a decipherable view of an elongated customer journey. What happens over the course of 4 months, 8 months or two years as someone approaches buying a new house, car or, for that matter, insurance? Deep learning may finally make the complex and long buyer journey into a navigable course where marketers can reliably be more useful to shoppers at different points along that journey. 

 

Preference recommendation systems

We all experience preference recommendations today. Amazon product recommendations, Spotify’s related artists, publishers suggestions of related content are examples of recommendations fueled in part by AI.

“Like Flipboard, other publishers around the world are tapping into AI to improve their content recommendations. Some 60% of the 184 publishers in the Reuters Institute poll said they are using AI to improve content recommendations. Significant numbers were also using it to automate workflows and to target ads. (Flipboard, too, uses AI for ad targeting.)” (see more)

Current systems seem to be blunt instruments. How often do you take a Netflix movie recommendation? Still, they are terrific discovery “engines.” I have discovered plenty of music artists via iTunes recommendations.  If I am in a ‘discovery’ mood – willing to click around a bunch – this can be a much better alternative to randomly wading into the haystack of online music.

Deep learning may provide ever-more precise recommendations as multiple data sources combine together on individual users (blinded, of course). Browsing history, demographics, geolocation, past shopping history, content choices, other users’ behavior – may all be combined in some way that provides ever-better recommendations via constant learning.

Deeper knowledge will also lead to more personalized messaging about recommendations. Product choices can be presented with just the right headline that hits on the concerns of that individual. (image from Adelyn Zhou's great presentation)

 

 

Fuel effectiveness and efficiency in account based marketing

The two super-powers of account based marketing (ABM) is reaching the individuals from a particular company or organization and delivering personalized messaging that drives action.

A third super-power is finding ‘look-a-likes’ based upon the original prospect list and a ton of relevant data.

Deep learning may allow marketers to analyze and growing data set of the users from a particular account/company, understand their individual intent and deliver the right messages and content that meets that person’s need. This goes beyond wedging the company name into the banner ad as a nod to personalization. Of course, these messages and the sequencing of content would all be informed by what causes a prospect to convert.

 

Final word

How much of any of these applications are fueled by artificial intelligence, writ-large, versus machine learning versus the particular capabilities of deep learning? I don’t really know. I would have to ask Hugo Larochelle and I wasn’t quick enough to put that question together when I saw him.

AI, ML, and DL will change marketing. Time to learn.  

 

 AI resources:

AI Can Drive New Insights to Drive SEO 

Is AI in Marketing Overhyped

Deep Learning at Affectiva 

10 Ways Machine Learning is Revolutionizing Marketing 

AI, Machine Learning and Their Application for Growth 

What Marketers Can Expect from AI in 2018 

AI - Closer to Relevance at Scale 

 

Eight Principles and Voices of Agile Marketing

Agile marketing is still being defined. The rules are being written and tested as we speak. As such, I am not sure I buy into a dogmatic application of the software version of “agile” with its Scrum masters and 6-member team size limits. We are borrowing from the evolution in the production management and software development worlds. The aim is to make marketing more responsive, iterative and more impactful. “Agile” is a way of working that produces work that can be released, tested, and optimized. This is different for marketing. Sure, marketing has been tested for decades but not usually out in digital channels with the benefit of immediate feedback. 

Here are some principles from smart voices in the world of agile that will define this new operating model:

1. Embrace adaptive planning and continuous improvements (from Meta Karagianni at Sirius Decisions)

I have been obsessed with strategy. Following strategy comes a great plan. Part of the innovation of 'agile' is respecting that plans change. When your strategy and plan are so rigid, they cannot change nimbly as you learn via the execution of the plan, you will likely waste a lot of effort. While I still believe a great strategy does wonders to align a team, the plan that shakes out of that is just a start. setting processes that allow for continuous improvement are important in the age of the connected customer. 

2. Testing has become the quintessential data-driven marketing process: running controlled experiments to determine what resonates best with prospects and customers. (from Scott Brinker at ChiefMartec)

Learning how to test discrete marketing elements quickly and cheaply in-market is more important than old-school testing (although that does have it's place). We can test the demand for a new product just by buying some cheap advertising on Facebook. We can A/B test different ad creative or landing pages to figure out which actually drives the most response. Agile marketing requires skills at testing, reading results  and adjusting on-the-fly.  

3. Agile marketing methodologies encourage cross-silo teams to come together on projects quickly and easily and to dynamically reconfigure as needed from cycle to cycle. (from Scott Brinker at ChiefMartec)

Assembling small-ish, unusual teams brings the diversity of brains needed to create interesting work fast. Creating easy ways to bring those teams together so they know what to do and how to work with each other is worth the effort. Training teams in agile methods helps as routines like daily stand-ups, demos and others are new to most marketing folks. 

4. “Our highest priority is to satisfy the customer through early and continuous delivery of marketing that solves problems” (from the Agile Marketing Manifesto)

Greater customer-centricity is on everyone's minds these days. Since agile methods drive us to test our hypothesis via actual customer behaviors, it can improve our knowledge of the customers and what he/she wants. Thinking about marketing as something that aims to solve customer problems is a good thing, better than "messaging" or simply "selling" when someone is ready to buy. 

5. Learning, through the build-measure-learn feedback loop, is the primary measure of progress (from the Agile Marketing Manifesto)

I appreciate that there is a thing called the "Agile Marketing Manifesto." To some extent it's just us marketers being marketers and wrapping our idea in a "manifesto" package to associate these thoughts with it's software development predecessor. The Manifesto has some strong ideas. Following the build-measure-learn feedback loop makes great sense. And making it an end unto itself also makes sense except that I still believe my alma mater's  truth, "we sell or else." Marketing sells, period. This new emphasis on learning is just how we do it in the age of the connected customer. 

6. Empower teams with decision-making and accountability. Marketing is regularly hampered by internal approval processes (from Barre Hardy at CMO.com/Adobe)

How many marketers have worked at brands where the "work" must be seen by the CEO, never mind the CMO? Sometimes that is right-minded. In this day and age of quick, iterative work, we need to empower the small marketing team to fully execute and learn fast. With the right team leadership, the risks can be minimized. 

7. Bring the agency in-house. Internal agencies can work much more closely with cross-functional marketing teams to enable the company to own the performance data associated with campaigns (from Barre Hardy at CMO.com/Adobe)

The agency world is being turned on its head. Working on the brand side, I love the smart agencies that I work with. That being said, we have pulled all of the strategy work and even much of the operational marketing work internally. And the data. No way could we outsource all that it takes to source our data feeds and feed it into a reliable reporting framework and dashboard. Some things you just need to keep close to make agility work. 

8. Work (and prioritize) according to aligned business priorities (from Veronica Jarski at MarketingProfs and CMG Partners)

Marketing has always needed to be aligned to business priorities except, perhaps, when marketing simply supports "brand." Business priorities always have a commercial goal - growth, profitability, increased customer value, innovation and more. The days of pure brand initiatives are waning. More and more marketing tries to drive a concrete commercial outcome while establishing brand via experience. Agile methods can help retain alignment with business as priorities shift quarter-to-quarter.  The days of monolithic marketing campaigns extending out for a year or more are numbered. 

 

 (image thanks to Kim Seiter Dog Agility) 

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CES 2018: Four Wishes for the Future

I am just back from CES 2018 and found myself trying to sort through that experience of hobnobbing with 184K of my closest friends. What did I see or experience that really mattered to me? There are plenty of great recaps of what was shown and what happened at CES 2018. One of my favorites is the CNET CES 2018 hub. When we attend, I always appreciate the briefing that CNET’s Brian Cooley does for our team. He’s a great analyst and guide.

So while I could talk about the neat bits and bobs in the Smart Home category like Kohler’s Alexa-powered mirror or Vivint’s increasingly big booth; or Samsung’s 146” snap tech TV; or the autonomous Lyft ride; I am going to think ahead towards some simple wishes.

The event is exhilarating and tiring, and I prefer to surrender to optimism and look ahead to what might be.

 

Here are my 4 wishes coming out of CES 2018:

Big Vision Like Ford’s Living Street Gets Rewarded by Wall Street

“If you can change the street you can change the world” said Jim Hackett, CEO of Ford during the main keynote at CES 2018 (watch it here).

The vision is about restoring cities and a shared sense of belonging sacrificed by tech starting with the advent of the highway ‘operating system’ if not the automobile, itself. We need to harness tech to improve lives and restore a sense of community.

The Living Street vision combines car and infrastructure IoT. It includes the Transportation Mobility Cloud (TMC) – an open and collaborative platform; Cellular Vehicle to Everything (CV to X) – a partnership with Qualcomm to leverage the direct communications of 700K vehicles on the road; and self-driving business model(s) – establishing an API-led approach being tested with the Postmates delivery service, Dominoes and Lyft.

Jim delivered an inspiring and aspirational message at a show dominated by gadget geeks. A tech-rendered view of a new urban utopia seemed to spin off the architect’s CAD system onto a ribbon of video screens behind him that were reminiscent of the very roadways that need a re-think. (all thanks to Alex McDowell, production designer extraordinaire.)

Mr. Hackett cited physicists and ethicists as his close friends and influences. He made it clear that he thinks about some heady stuff.

I was inspired. I appreciated that he had ‘purpose’ at the heart of the thinking – craft or restore our vital cities towards vibrant and healthy communities. Ford partners with other great brands who are deeply expert in what they do. That type of brand collaboration provides a competitive edge and also telegraphs a healthy humility that Ford cannot figure this out on their own.

If Jim Hackett, CEO of Ford does not show off some commercially appetizing vehicles at the follow-on event, the North American International Auto Show, he may not have a long enough tenure at Ford to see The Living Street actually come to life.

He must sell cars and trucks today to hold onto investor confidence. I hope that the Ford stock retains value and grows. I am a customer. I hope Wall Street rewards the vision and that Mr. Hackett continues with strong vehicle sales now to fund this future vision. 

 

The Smart Home and AI Lead to an Anticipatory Environment

Smart Home tech was everywhere. There were more sensors of every variety, cameras combined with light bulbs and robots, and applications against more and more use cases from showers to kitchens to litter boxes.

Often demos of these products began with the opening of an app on smart phone. Increasingly it began with a voice-command to either Alexa or Hey Google. The possibilities and modality in the apps was impressive. Still, after the third swipe or button-click to turn something on in the home or the awkward voice command, “Alexa, open the blah, blah, blah skill...,” I just get a little tired.

The tech hobbyists have the patience to establish “scenes” which bundle several actions together. Blurt out, “Alexa, night time,” and you could dim lights, lock the front door, turn the room temperature down and more.

But I want that to all happen automatically when I walk in the door - because I have done it before, it’s Tuesday night, and it’s what I like. We need the tech to anticipate us and drop the cognitive load to zero – or as close to zero as possible. I want control and simplicity and not necessarily in that order. 

By combining artificial intelligence and the machine learning within it, smart tech can teach itself what experience to manifest based upon my behavior, not twelve button clicks in an app.

Brain Cooley (@briancooley) mentioned ViaRoom, an AI-powered hub-of-hubs meant to learn your habits. I expect Google, Apple and Amazon, at least, to offer their own versions of this intelligence going forward.

Technology that accurately anticipates needs will be a leap forward.

 

Marketing Becomes True Customer Experience

CES is not a marketing show. The marketing “hub” at Tech South was particularly scattered and anemic this year. Still, the event is great for brand marketers. We want to get glimpses of innovation in consumer’s lives, talk with smart people who are working to bring those innovations to market, learn from others what may be next, discover new potential channels or how consumers are or will be spending their time, and more.

Still, some marketers are just trying to understand where to put their ads on a smart fridge or a dual screen smart phone.

Interruptive advertising may really be in its last legs. Joe Marchese (@joemarchese) from Fox developed a POV that we ought to be planning marketing around a fixed asset – people’s available attention. His Attention Rate Card is a way to scale, buy and sell access to customers. He takes an old idea – the attention economy – and breathes new life through the practical lens of how we purchase media. In this model, we can buy access but we must earn the attention by delivering real value to the customer/prospect. We earn that attention by being genuinely relevant and useful to people, not finding new ways to wedge in ad messages.

I love marketing. But it’s time for it to become “customer experience” where everything we do to sell the right product or service at the right time to the right customer becomes an authentic value to that customer. Either we reminded them of a product when they were truly shopping, or the brand provides a service and becomes relevant or we help them accomplish something important.

If we accept a broad view of ‘customer experience’ as our relationship starting before we even know that customer through acquisition and loyalty and ahead to losing that customer and winning them back, then marketing needs to become that big view of customer experience.

It’s a semantic change. I get it. But the line between marketing and customer experience needs to go away. And we are more apt to see customer experience as being in service to the customer and, therefore, all about delivering value. That’s what marketing needs to be going forward.

 

AI-powered Virtual Agents Become the New Interface 

Judging by posters and billboards around Vegas, it was easy to see that the battle is on between Hey Google and Amazon’s Alexa to become the dominant voice interface or agent inside of everything. Alexa seems to have a bit of a momentary advantage, yet most of the bets I heard were on Google to win.

But voice is only part of the story. CNET’s Brian Cooley (@briancooley ‏) showed a slide on virtual agent dominance beyond voice and Google owned the lion’s share of that pie chart. Next up is virtual agent plus artificial intelligence.

Whether it’s the spoken question or the typed phrase or the submitted image, the new ability to have machines learn your intent and give you the most useful answer could change how many interfaces are designed going forward.

Think about Web sites. Most are designed with three basic interfaces: navigation, browse and search. Users can try to click through a navigation hierarchy to get to something they need. They can browse pages to discover something relevant. Finally, they can use the site search to find something they need.

Site search is the closest interface to AI agents in a chat format. Most brand sites are organized around products and search results reflect that. If you are not familiar with what a product is called, your search will be frustrating. Never mind that most brands under invest in the quality of their site search.    

Imagine a robust AI chat interface where you can type in the question you are trying to answer (or speak it into the microphone) and immediately get an answer and relevant link to the best content. Web sites become an AI chat window plus a beautiful way to browse. Find something specific quickly or simply browse for ideas and inspiration. That’s it.

No more big, spidery Web sites. No more product manuals. No more keyword search. Perhaps.

Here's another interesting POV on the interface topic: Why Google A.I. is the last user interface (Computerworld – Mike Elgan, @MikeElgan )

 

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Crash Course in AI for Marketing: 4 Videos

 

Continuing down the “roadmap of exploration” on how artificial intelligence and machine learning may impact marketing, I have discovered 4 videos which serve as a good foundation for thinking about the opportunity. These videos provide 4 important concepts for me as a marketer:

• Which applications of AI in marketing could I focus on first
• What are the right questions to pose when framing an AI-for-marketing challenge
• How does machine learning work and what is an easy way to talk about it
• How does a marketing/tech geek think about AI and machine learning

 

 

A.I. for Marketing & Growth - Where do I start?

This 5:02 video from Growth Tribe maps AI application to marketing and business along a maturity curve. That curve outlines which applications are more ready or more accessible for marketers from “must haves” to “nice to haves.” The simple rating system will be different for different businesses and marketers, and it’s a simple way to think about the potential behind AI in marketing. I particularly like David Arnoux’s (@darnocks ) rapid, no-nonsense approach to explain all of the topics from Growth Tribe.

Must Haves:

• Predictive Analytics
• Clustering/Customization

Should Haves:

• Recommendation Engines
• Natural Language Processing

Nice To Haves:

• Psychographic Personas
• Image Recognition

 

 

AI for Marketing & Growth #1 - Predictive Analytics in Marketing

Specifically focused on the needs of the marketer, David quickly (3:16) outlines AI’s application to use cases like focusing on leads with the highest ROI and which offer to recommend when and to which customer. Most usefully, the video outlines how to think about an AI challenge via 3 simple questions:

• Which questions am I trying to ask
• Which metrics am I trying to forecast
• Which future behavior am I trying to predict  

 

 

The 7 Steps of Machine Learning 

This 10:00 video from Google Cloud and @YufengG (Yufeng Guo) outlines the basic steps needed to get to machine-based predictions. This is foundational knowledge meant to help non-tech geeks understand the concepts and have a productive conversation with tech and data teams.

The 7 steps include:

1. Gathering Data
2. Preparing that Data
3. Choosing a Model
4. Training
5. Evaluation
6. Hyperparameter Tuning
7. Prediction

 

 

Machine Learning in Marketing from the Conductor event, C3 2017 

In 32:10, Dharmesh Shah, CTO at Hubspot (@dharmesh) offers a way to think about Machine learning in marketing. He quickly answers the question of what is the difference between data-powered and machine learning-powered marketing.  His concept of “Autonomous, Self-driving, Marketing Automation” is simple and powerful. He grounds the talk in real marketing use cases like smart lead routing (sending the right lead to the right salesperson) and persona development. He covers some useful basics like the difference between unsupervised machine learning vs. supervised machine learning and makes a great point that success will be about data not the algorithm. He also offers a glimpse of his sandbox for chatbots which he sees as the future of Web sites (growthbot.org).

 

 

How AI and Machine Learning May Apply to Marketing

Most of the talk about current use of artificial intelligence (AI) in marketing cites what the 4 Horsemen are doing or likely doing. Google, Facebook, Apple and Amazon have digital, data and automation at the heart of their businesses. They have the skills and the culture to make the application of machine learning and artificial intelligence a core competency.

Meanwhile, many marketers still struggle just to get their customer data source in order never mind speculating on how AI might improve the customer experience and/or the profitability of these customers. The hype curve of AI creates this nervous energy for marketers. To not do anything in AI seems wrong. On the other hand, to leap in expecting it to solve big, hairy 2018 problems also seems naïve.

I would recommend creating a simple ‘road map of exploration.’ Andy Betts (@andybetts1) has a useful post and diagram (above) counselling CMO’s to start planning in 2018. For once, it’s okay to start learning and exploring vs. jumping into action. I have a ‘bias-for-action’ like most marketers. We want to learn by doing. In this case, I want to pick and choose the pilots and proof-of-concepts (PoCs) while not derailing my marketing and customer service operations who already have a pretty full agenda next year. I will start by defining use cases where AI may have a positive effect on marketing.

 

Five Use Cases for AI in Marketing

Show the right, next call-to-action – Are people looking for a home-plus-valuables insurance quote? Trying to get answers about coverages in the weeks leading to an insurance need? Winterizing their home before jetting off to Florida for the season? These are pretty simple states but often hard to detect amongst the unknown visitors to your digital properties. Knowing the next right action to suggest and guide them is hard.

Propensity modeling used to be the answer. Defined as “a statistical scorecard that is used to predict the behaviour of your customer or prospect base,” propensity modeling works best when you know a bunch about the person. Think rich customer databases vs. a few Web clicks from strangers on your Web site.

Would you rather have a “scorecard” or a really smart robot (i.e. AI)? Imagine paying attention to the patterns of visitors to your site and all of the content they consume. Imagine if you could reliably predict/understand what they are trying to accomplish and you were able to deliver just the right calls-to-action on their screen. No more junking up their view with every possible choice they may consider. No more agonizing over Web site navigation models. With AI, you could understand what they are after and just give it to them.

 

Identify more accurate and actionable “look-a-likes” – Finding more prospects that look like your most valued customers and then selling them your product is generally a good thing. Most of the social networks have offered look-a-like audiences for a few years now. And given their facility with data and AI, these models will get better and better (and be worth more and more to advertisers).

As brands build their own audience pools for advertising, we need to find ways to use machine-learning and AI to identify more precise matches for our most valued customer. Just finding people in the same demographic or even the same interests as your current customer base isn’t enough. What if you could find more or less perfect matches for your top 20% most valued customers? And what if you could overcome the problem of “diminishing audiences” (when your target is so narrow you cannot cost effectively market to them) and engage them with just the right offers? AI could make that possible.

 

Automate market research and performance insights – We need a steady flow of timely insights about our customers (and prospects) and the performance of our marketing efforts. Currently, this process is so manual my bones ache thinking about it. If I think about all of the effort we are spending just automating a dashboard –a visualization of performance data, I have to laugh.

I want my performance AI to find patterns I would never recognize and draw insightful connections that help me market today and tomorrow.

When will my little machine-learning robot sift through all of the online panel data on a particular group of customer-types and reveal something I didn’t know to ask it for?

 

AI-generated content - I am less interested in teaching a robot to create a compelling article or video, than using AI to generate relevant content at a scale that is prohibitively expensive otherwise.

Let’s say you serve the small business market with a solution that lots of different business types could use. But small businesses want to buy a solution made for their business-type. If they are a dry cleaner they want a solution provider for dry cleaners. If they are a dog groomer or an art supply store, same thing. How can a solution provider create content for hundreds of small business types?  

Discovering how AI can “learn” your existing content and then assemble industry-specific content to create something of value and relevance to the dog groomers and art supply store owners is the trick.

 

Solve customer problems conversationally – AI-driven chatbots are the most popular customer experience application judging by the number of companies offering chatbot solutions. Still, they remain in their infancy.

Get a computer to consume a “corpus” or body of data, teach it some lessons and “walla!” you have a way to quickly get personalized answers for customers and cut down on the overhead to deliver said answers.  This is the type of solution that can serve both customers and prospects and will take sustained iteration and use to make very valuable.

These are just a few of the use cases on my road map of exploration in AI and machine learning. What’s on yours?

 

Good resources:

3 Ways AI Will Affect Marketing - Smart Insights

The CMO’s guide to AI’s marketing impact for 2018 - MarTech Today

How Will Artificial Intelligence Impact Digital Marketing in 2018? – NextWeb

8 Ways Intelligent Marketers Use Artificial Intelligence – Content Marketing Institute

10 Ways to Use Chatbots for Marketing and Sales – Entrepreneur

 

 

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Why Agile Marketing is New and Important

I have seen a lot of “new and improved” marketing POVs –guerrilla marketing, disruptive marketing, social media marketing, “Marketing 4.0”, “Growth Hacker Marketing,” content marketing, performance marketing and more. Some are onto something. Social media marketing was a true shift that really started around 2004 with the publishing empowerment of the individual. It gave marketers a way to make sense of changing customer behaviors and the shift in attention that undermined the effectiveness of marketing-as-usual. Some of these new marketing concepts won’t take hold in any big way but may successfully sell a book or two.

Agile marketing will be a significant shift in how marketers run their teams. It is as much about how we develop high-performing marketing as it is a response to changes in customer behavior. Agile marketing offers a way to apply the best of account planning and performance marketing to a discipline that can no longer sustain the stratified, agency teams of the eighties.  It is a way to work smarter, cheaper and better. Yes, all three.

 

Account Planners Gave us Customer Insights

Account planning introduced the notion that deep customer knowledge – from psychology to where and how people spend their time – could add intelligence and effectiveness to the unknowns of marketing. That model saw the rise of the “planners” in marketing agencies, first in London, and soon across the world. These were the guys and gals who ingested customer research and insights to design marketing programs that, hopefully, produced results. Planners came in many shapes and sizes – account planner, communications planner, brand planner, “connections planners.” Born in 1965 in London and Australia, brought to the US by Jay Chiat in 1982, the planners most often were the voice of the customer in marketing.  They had ways of mining insights from quantitative and qualitative research which often included anthropological excursions that looked as much like deep undercover assignments as anything. They were thorough.

The future of planners and the bigger agencies they sit within is in question. Not because they aren’t good or relevant. More likely it’s because they have only one piece of the puzzle – moment-in-time customer insight.

 

Performance Marketing Brings Real-Time Instrumentation

When customers shifted to digital shopping, buying and influence, performance marketing was born. Suddenly we had actual data behind customer behaviors. Direct marketers discovered they could tweak and optimize their marketing to drive up effectiveness and drive down marketing cost (e.g. cost-per-click) based upon what the buyer actually did. This real-time instrumentation was taken to extremes by the ‘bottom-of-funnel” ecommerce marketers who only cared for an efficient cost-per-purchase. 

Performance marketing seemed to overcome the age old ‘Wanamaker Problem’ of determining whether marketing was producing a result or not. It favored a ‘last click’ analysis which doesn’t reflect the complexity of the buyer journey – all those soft touches in the weeks of research leading to a purchase. More recent improvements in tracking a buyers experience across devices and even online and offline touchpoints may strengthen the richness of performance marketing. This may give a view of what content and experiences provide an “assist” to a sale. That is if we can weight these touchpoints in a way that reflects how the actual customer weights them.

Performance marketing-thinking drives us to get marketing materials into market faster to see how they will perform. We don’t want to overinvest in those assets as we fully expect to optimize – drop, add, change them – based upon actual behavior.

 

Software Development Popularized “Agile”

Meanwhile, software development had evolved from the careful, planned approach that mimicked factory work – moving the process along an assembly line – to one that was more nimble, more responsive to feedback and ultimately relied on teams to be more “agile.” The long development process of traditional software tended to veer away from user needs either because the research phase was so removed in time for the release of the software or, more likely, no research in the world did a good enough job of anticipating how customers would actually interact with software applications once relased. Best to get a ‘pretty good’ version of the software done and out quickly by a multidisciplinary team. Agile teams work in sprints with small teams achieving incremental progress towards and on top of a ‘minimum viable product.’ Get that MVP in hands of actual users and see what resonates.  (Get more on the history of agile development from Gary Police)

 

What is Agile Marketing?

Agile Marketing combines lessons from the quick, collaborative approach of agile software development with the reliance on insights from the planners and the use of response data in performance marketing to create a way to plan and execute marketing that is fast, responsive, and measured.

Here’s a definition: Agile marketing assembles small teams that represent makers and planners and equips them with customer insights to work collaboratively in short sprints to develop marketing content, tools, and plans that are tested and optimized for effectiveness and efficiency.

Here are a few more:

“At its core, Agile marketing is a tactical marketing approach in which teams identify and focus their collective efforts on high value projects, complete those projects cooperatively, measure their impact, and then continuously and incrementally improve the results over time” from the Workfront Blog and Andrea Fryrear

 

“Agile, in the marketing context, means using data and analytics to continuously source promising opportunities or solutions to problems in real time, deploying tests quickly, evaluating the results, and rapidly iterating. At scale, a high-functioning agile marketing organization can run hundreds of campaigns simultaneously and multiple new ideas every week.” From McKinsey Insights and David Edelman, Jason Heller, and Steven Spittaels

 

“A mindset and methodology that transforms culture and operations so you can execute more efficiently, champion the customer, and achieve better performance through a data-driven iterative approach.” From CMG and Russ Lange.

 

Is Agile a Strategic or Tactical Approach?

These definitions of agile marketing don’t preclude the value of big, pivotal insights about customers that can inform strategy. Still, we cannot build cathedral-like marketing programs that are carefully crafted prior to ever seeing the light of day.

Agile marketing may be a new way of being more customer-centered when behaviors and channels are changing more quickly than the last half of the prior century.

Agile may be a better way to develop marketing strategy and to execute once you have a strategy. The choice to work in a more nimble, responsive way could be its own strategic choice to remain relevant to customers. The concept of agile emerged from an operational mindset – how to make software development better – better result, more efficient.   It’s a leap to apply new operating methods for software to contemporary marketing. Still, something has to change. The over-architected marketing strategies of yesterday that required a whole ecosystem of marketing agencies to plan and execute will disappear. Those agencies are fast-evolving as they look to better ways to deliver value to the brands and companies they once worked for.

Internal marketing teams need ways to cut costs of marketing as that marketing is now being evaluated as a revenue-driver and not simply as brand-building.  As marketing gets more technical and data driven, we need collaboration methods that bring creative, data-geeks, UX wizards and storytellers together.

Agile marketing methods may just be the way forward.   

 

(image from Twin Cities Obedience training Club) 

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Hacking the Marketing Insight

True customer insights are gold for marketers. They serve as the key to unlock relevance and drive important behaviors. They are not new to marketing yet remain as elusive and misunderstood as ever. In our fast-paced, performance marketing world where we figure we can just test our way to relevance, true insight seems superfluous

Whether you are developing a product, the marketing for that product, or, hopefully both, having some valuable insight into the needs and wants of your customers or the salespeople who sell your product, can make all of the difference as to whether your product actually sells. If your product or service doesn’t capture their attention in pretty short order, it may just flow past them like their daily newsfeed. 

What is an insight?

It’s not a statistic. (like the Facebook Cards used in the illustration above)

It is not a simple observation.

An insight is a deep, penetrating truth about a customer – their beliefs, behaviors, needs and wants – that reveals an understanding that can be used in more effective marketing.

There are related definitions out there including these:

“A deep ‘truth’ about the customer based on their behaviour, experiences, beliefs, needs or desires, that is relevant to the task or issue and ‘rings bells’ with target people. ” Elena Ozeritskaya 

"An insight is a disturbance in discourse." A good insight creates a whole new way of thinking. Dove's Campaign for Real Beauty did this — it allowed expression of something that previously was inexpressible.” From Think with Google: Andy Davidson, Head of UK Practice at the global insight and brand consultancy Flamingo

“There are different types of creatives, and I've come to the opinion that you're either a creationist or an evolutionist. Creationists get the insight and then craft a perfectly formed concept. Evolutionists — especially in digital — use insights that come from data and our creative work evolves over time. In creationism, there is a sense that the insight is written in stone and can't be changed. For evolutionists on the other hand, the insight is more mercurial and flexible. Often creationists and evolutionists can come to a fairly similar place, but the insights come from very different methodology.” From Think with Google: Caitlin Ryan, Group Executive Creative Director for the advertising agency Karmarama

For small business people in the US, I know that 43% say wearing many hats is most challenging part of their job. That’s a data point.

SBOs will turn to family, friends as “informal advisors” to help understand and make complex, hard, decisions. That’s an observation.

Small business people need help being enough of an expert in many things with just enough information to supplement their own radar and make “pretty good” decisions to advance their business. They want quickly verifiable, expert guidance to build their confidence that they know what they are doing. They need help they can ingest quickly – speaking in simple business terms, not arcane, technical language – and verify via their personal/professional connections or through Google. This is an insight, or at least, the beginnings of one.

I can do something with that as a marketer. It can tell me what to engage them with and how. It points the way where I can be of-service to them in a rational and emotional way. I pretty much just spit-balled that insight. But I stand by it. I can verify it via more research if I feel it’s necessary. Call it a hypothesis, call it hacking the insight, either way it gets me to something I as a marketer can build on beyond just data.

Hacking the Insight

I love research folks. I love planners. The insights they have generated in my years in marketing have been impressive. The traditional method for getting to insights takes time, money and often specialism.  It’s hard to want to skimp on research yet in marketing today, we move pretty fast and there is more pressure for ‘lean marketing.’  

Lean marketing is a made up concept. Due to digital marketing where we can get instant feedback on marketing and then optimize, there is less demand to build a cathedral of a marketing plan ahead of time. That doesn’t mean we don’t need insights. They tell us where to start.

One thing it means is that we need researchers and marketers to collaborate to uncover those insights. It’s not fair to rely on the researchers to do it alone. That’s sort of where planners came in. Good marketers are part planners. They can now link up with researchers to find useful insights faster. Planners are fast becoming an anachronism carried into other strategic positions as the British-influenced agency model of the nineteen eighties finally sunsets. Today, we need to combine the specialism of the modern researcher and the marketing strategist to deliver the actionable insights we need.

 

Here’s a recipe for hacking the insight:

Step One: Curate existing primary and secondary research that answers the simple questions:

How do prospects research and buy your product/service? What are their pain points and needs as it relates to those products and services and the role they provide in their lives? How has this changed due to new digital behaviors and technologies? And so on.

If the researchers believe there is a critical mass of existing research then move on to Step Two. If not, commission some targeted additional research to fill the gap.

Step Two: Have researchers and marketers workshop the insights

Take the curated research into a room with 1-2 researchers and marketers and have them whiteboard insights driven by that research and their cumulative experience with both customer and product. Don’t be afraid to headline insights you’re not sure the data supports. We can call these ‘insight hypotheses.’

Step Three: Do targeted research against the insight hypotheses to fill gaps

Chances are, the existing research you had in-house wasn’t enough. Once you have a sense of where the insights might be headed, qualitative or quantitative research can be a terrific boost to corroborate or refute your hypothesis. Even interviewing 3-4 customers can be hugely revealing.

Step Four: Share your insights with everyone working on the product and/or marketing

We all want our work to be more customer-driven. Solid insights can really help but only if you get them into marketers hands to apply. When you deliver them, show examples of how those insights can influence:

• Content
• Marketing messages
• Calls-to-action
• Tone and character
• Journeys and moments

 

Hacking, agile and design-thinking

The enduring need to understand and be empathetic to our customers’ lives is getting new life from the ‘design-thinking’ community. The need to be more collaborative and iterative in our work is being popularized by the agile-anything movement. The direct-response nature of digital is changing how we get research (“hacking” vs. cathedral-building) but not the critical value of insights that help us connect at a deeper level with our customers and find authentic ways to be valuable to them as they live their lives.

More

Jonathan Dalton, CEO of Thrive, has a particularly good set of posts on Insights starting with "What is Insight? The 5 Principles of Insight Definition" 

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3 Steps to Plan Content Marketing for Enterprise Brands

A lot has been written about the basics of good content marketing - from gathering customer insights to defining what the brand can talk about to understanding the impact on business. At a big, enterprise brand, the challenge that many consultants overlook is how you get the existing organization to efficiently adopt content marketing practices. Every company is different. Every culture is different. As I head off to Content Marketing World this week, I want to focus on the lessons learned from marketers actually applying content marketing in their enterprise-level companies. Often it’s not the fundamentals of content marketing that remain allusive, it’s how to make it work at Travelers, Xerox, GE and more.

In the interest of sharing my own experience – remember, results may vary - here are 3 key steps to enable content marketing across multiple business units in an enterprise brand. Far from perfect, these are, nonetheless, steps that seem to help rally people around common tools and processes.

 

 

Define Your Narrative Territories

Combine customer-centricity, brand-building and storytelling to effectively focus what you brand or business unit can talk about. Simple, right? In practice, it takes a framework and collaborative work to help a business unit focus their message in an impactful way. A narrative platform does just that.

Here’s what it is:

“A Narrative Platform is a message platform and a brand position rolled into one simple model. By focusing what a brand cares about and saying it consistently again and again, we can earn a position in customers’ minds. The Narrative Platform is built upon customer insight and reflects what customers would find compelling not just what our brand-building wizards think it should be.  It's brand positioning just from the customers POV.”

A lot goes into this including customer insights. What are customers’ needs and pain points in relation to your category? What are the purchase drivers that cause them to select your brand over another?

Also, what is your brand position and core value proposition?

The actual deliverable for a narrative platform is pretty straightforward. Picture 3-4 short descriptions of territories with one summary statement. For those with a public relations background, this will remind you of the message platform.

Tools: Narrative Platform

Process: workshop or collaborative iteration + marketing writer

Resources:

Narrative Platforms are the Brand-building Tool for the Content Age 

 

 

Map Topics to the Buyer Journey and Narrative Territories

If the Narrative Platform helps you focus on what you will say or create content around, mapping topics to the buyer journey adds context. What is your customer trying to get done at any point in the journey? Their needs will be very different if they are trying to prep their teenager to drive then if they are comparing insurance providers for auto insurance.

A ton has been written around buyer journeys. They can take many forms some quite detailed. I would recommend a simplified view that represents core phases of what a typical buyer goes through from very early stages of a journey through moments of being a customer. Here’s a way to think about the buyer journey in a simplified way for business. A B2B buyer journey might include these phases:

Discovery – they may discover your brand when they are trying to solve business problems related to your category. This could be well before they are ready to shop or purchase a solution.

Consider – when they begin to define the solution and even start shopping, they may engage if you help towards making good decisions.

Evaluate – ready to buy, what does the customer need to know that will help them select your brand over others?

Purchase – immediately after purchase, what telegraphs that they have made the right choice.

Experience – as a customer, how will they interact with the brand from billing and customer service to actually getting additional value as a customer.

Renewal – for some product categories like insurance, customers have a choice to buy again or renew. What are their needs during this moment or phase?

 

Tools: Buyer Journey Template

Process: collaborative iteration + marketing strategist/writer

Resources:

Examples of Buyer Journey Templates – Google 

How to Create Content for Every Stage of the Buyer's Journey – Hubspot  

10 most interesting examples of Customer Journey Maps – Uxeria

How to Map Content to the Buyer's Journey & the Marketer's Funnel - Hubspot

 

 

Define a Seed Plan for Content

One of the steps we have wrestled with is how much content is planned up front (yearly? quarterly?) vs. how much is developed organically and iteratively on a daily and weekly basis. As marketers, we want to ensure all of the content we create supports that sweet spot between customer and business goals. That takes planning and creating useful tools like the Narrative Platform and a Content Plan anchored in the Buyer Journey.

But tactical content – articles, videos, visuals on specific topics that will resonate with users – isn’t quite so neat and predictable. Story ideas don’t always pan out in the research phase. A good idea in a headline and abstract can sometimes fall apart in execution.

We are learning that our content plan is more like a “seed plan” that has topics and some actual content titles. It’s a place to start. It is also a good plan for those items like videos and interactives that require more lead time and investment.

Reserving time and resources to pursue related content stories that come out of evolving priorities or insights from performance data can be helpful. A marketer might get a new priority - to help promote insurance to the legal sector or to try and bundle a few insurance covers in a new way. We might see that content on ‘business continuity’ is outperforming other small business content. In each case, we need to respond to these needs and not be slavish to “the plan.”    

To ensure our content plan is strategic and that it aims to drive valuable business actions, we do need a plan of what content to create. We simply need to leave room in the plan for content that wasn’t foreseen and responds to new needs from both customer and the business.

Tools: Content Plan Template

Process: collaborative iteration + content strategist/writer

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6+ Promising Sessions at Content Marketing World 2017

Content marketing remains a critical strategy for brands eager to earn the attention and interest of customers – ones they already have and those they seek to attract. It’s different than advertising messages but is just as high-tech and data-driven.

Since content sits at the heart of a lot of the marketing that I plan, I am heading off to Content Marketing World on September 5^th – 8^th in Cleveland  (home of Bonin Bough's Cleveland Hustles) to learn from many of the smart people attending and speaking. I will have my own session on how we use data-driven, integrated content marketing to drive business impact. I plan to share what we have learned putting content marketing to work in a large enterprise.

If you go, connect with me via Twitter – @jbell99 . I would love to compare notes on enterprise-level content marketing. Here are some of the sessions I am looking forward to (I hope I can get to most!):

 

The Messaging Science behind Customer Acquisition and Customer Renewal Messaging

Sounds like I will get a good dose of sales ‘behavioral economics.’ And Tim Riesterer (@TRiesterer ) appears to be a very smart guy in this space.

 

Content ROI – How Marketers Demonstrate Value to the Brand and the Boss (a panel)

Connecting the business value for content marketing is not as simple as ‘how much did it sell.’ While that is important, I am looking forward to hearing what this panel including Jenifer Walsh/GE (@jlansky) and Laura Cameron/Key Bank (@lcameron80) have to say in terms of communicating value within an organization.

 

Driving Content Marketing Success in Your Organization: Sales, Product and Global-Regional Collaboration

This session is marked for the “Beginner” yet, even still, I am guessing that Jillian Hillard/Electrolux (@jillianhillard) will offer some good tips on how she engages others like product people in content marketing.

 

Machine-Assisted Narrative: How to Transform and Scale Your B2B Content with Artificial Intelligence

Okay, I know it’s early days yet for applying machine learning and AI to content but we are doing it now on the customer service side and I am keen to see how Paul Roetzer (@paulroetzer) sees the immediate future.

 

Time to Leave the Lead-Gated PDF Behind: How More Engaging Content Can Transform Your Lead Gen and Accelerate Growth

This may sound a little tactical but I am hoping that Aaron Dun (@ajdun) can deliver some insights that get us beyond the “whitepaper.”

Also eager to hear:

• Matthew Glick/Marriott (@matthewglick123)  – these guys do some interesting things
• Matt Heinz (@HeinzMarketing) – I hear this company is smart in this space
• Scott Monty/Brain +Trust Partners (@scottmonty)  – always good to connect with Scott
• Lee Odden/Top Rank Marketing (@leeodden) – a very smart consultant

 

Here’s my session on September 6 at 11:20am:

Under the Hood: Deconstructing Content Marketing the Travelers Way

Travelers publishes hundreds of articles, videos and visuals to engage consumers and business leaders at different points along their buyer journey. This fuel for integrated marketing programs attracts customers before they are even ready to shop for insurance. This session will cover building belief in data-driven content, integrating an editorial team inside marketing, and how we pulled it all together inside the Travelers Engagement Center – a new approach to digital marketing.

 I hope to see you in Cleveland.

(Thanks to Cleveland Leadership Center for the image of The Sixth City) 

What Does a Post-Digital Marketing Organization Look Like?

The words “digital,” “mobile,” and “social” each describe changing behaviors and technology that affect how we make decisions, buy things and live our lives. Marketers must put extra energy behind each to learn and master how to use these technologies, channels and customer insights and behaviors to win, service and retain customers.

Digital Leads a Path to the Customer Journey  

Enlightened marketers hire specialists in these new areas to strengthen their use of new platforms to deliver messages and “engage” with customers and stakeholders. They provide training and invest in new technologies to improve skills and outcomes.

Then you end up with some sort of digital marketing department(s) that sit alongside more traditional functional marketing groups: media, creative, analytics. The tension is good for a while. Both groups – digital and traditional – learn from each other.

Ultimately, marketing leaders conclude that people’s lives have changed so much in many countries around the world that distinguishing between digital and non-digital is not as helpful as trying to understand the holistic, complex, ever-changing customer journey that describes what people do across their lives and over time to get to a purchase decision.

You end up wanting a “post-digital marketing organization.”

There are a series of beliefs, principles and a view on an operating model that both gauge whether a marketing organization is ready to start down this path and indicate what it takes to succeed.

Beliefs

Customer journey moments: Today’s digital, mobile, social, online, offline customer journey has many touchpoints and influences over time and micro-moments full of opportunity.

Old marketing would tell you that reach and frequency matters, old digital marketing would tell you that optimizing for last click matters. Neither focus reflects the true, messy world of customer decision-making that can stretch out across all sorts of online and offline touchpoints over weeks or months or longer.

Look at GFK’s summary of the auto insurance journey – one of the simpler insurance journeys out there. Now think about a large manufacturing company purchasing/renewing their commercial property and casualty insurance. What are the moments that drive them to or away from renewal? How does that play out over the course of 1-3 year renewal cycles?  Understanding that journey in its entirety with all of its variables and the weighting of influence is hard, potentially too hard. Mapping that journey to understand segments and moments where brands can have an impact is critical.

We used to just think in terms of “moments of truth” which was often interpreted to be those important events between a brand and customer that makes all of the difference in the world. For insurance that would be the claim experience.

But there are other moments that matter and set the tone of the relationship or present opportunities for brands to be of greater service to people.

David Edelman at McKinsey and Lisa Gevelber at Google outline the importance of “micro-moments:”

“Brands can identify micro-moments by recognizing times when someone has a particular type of need. Someone may need to learn something, somebody may need to get something done, or someone may need to buy something. It's about creating the content or tools to enable people to accomplish whatever they want in that particular moment.”

 

Deliver more value: Brands need to provide increasing value to customers over time to meet their needs and earn their business.

It’s not enough to make a static product and deliver it to your distribution channel. Business customers and consumers expect more and more. These expectations are established by our interactions with other brands across all parts of our life. Amazon, Uber, OpenTable and Trunk Club can set the expectations for the customers of a B2B electronics firm. Call it the “unified customer experience expectation.” 

Shar VonBoskirk and her colleagues at Forrester have coined the phrase, “be human, be helpful, be handy.” Brands need to shift their marketing focus from advertising and message delivery to being customer obsessed and delivering more value. Ideally, that value would increase over time. The longer I am a customer, the more value I reap from the relationship. 

 

Customer insights and needs: Marketers must constantly work to stay close to the customer and understand their emotional and rational needs and influences.

Forrester stresses the phrase “customer obsessed” over the weaker “customer-centered.” They are right to do so. Companies who say they are merely customer-centered may fall into the trap of doing lip service and approaching this quality as a static achievement. Customer obsession is a way of being and is never done.

Having a powerful mandate and organization to mine customer insights and drive their application across the enterprise is critical to walking the walk of customer obsession. Going beyond traditional methods of quantitative and qualitative research to include ethnographies, site visits and other close-contact research is critical.

 

Collaborative, agile process and teams: It’s more important to work across disciplines, iterate, learn and optimize than craft a “big bang” marketing campaign. Operate accordingly.

Skills, process and tools matter more than organizational structure. Too many big companies agonize over reporting and organization structures. The new marketing organization must have clear roles – that can be played by many people; a variety of new specialisms that can be assembled into teams; and a few commonly understood tools that make it easy to work in quickly assembled or transient teams. Agile means work quickly and adapt. Focus energy on what helps that happen.

 

Principles

Always learning; always curious – we will never know enough about our customers and how to be of-use to them so we are always seeking. We condition ourselves to an ongoing effort to learn and gain insight.

Data-driven; data-facile – we focus on using data to gain insight, instrument our work and tell true stories about the impact of what we are doing as marketers.

Empathetic to a fault – we care about the challenges our customers and our salesforce faces. That empathy ensures we stay ‘customer-obsessed.’

 

Operating Model

Shar VanBoskirk and Sheryl Pattek at Forrester both have insightful views of the post digital organization. Think of post digital marketing as an operating system. We focus on how we work together quickly and effectively.

We do that by having shared:

• Beliefs
• Principles
• Goals
• Tools
• Framework for working

“Framework for working” is a better approach to improving how we work together than proposing another organization model. Organization models are tough to upend. By outlining the roles and skills needed and then outlining how teams form and work quickly together it’s possible to align contributors in a post digital marketing organization.

Sheryl Pattek makes a good case for the need to move away from a channel-centered organization model to one that is customer-centered (see her preso here). She has a sketch of what that organization might look like. Rather than an org model, however, I read this as a ‘framework for working.’ I can also see the wisdom on adjusting it to your own company’s reality.

 

Here’s a ‘framework for working:'

• Customer segment marketing strategy leads: these folks run a team serving particular customers – small business, consumers, etc… They take responsibility for holding deep customer knowledge and for being the steward of the strategy – how to play & win. 
• Marketing CoEs: from content marketing to social media marketing to insights & analytics to advertising media, each of the CoE’s represents a highly technical specialism. Trained to integrate with each other, this collection of CoE’s builds defensible strength in their particular area and attracts talent to the organization.
• Channel Managers: Our Web sites, email marketing, social media channels are all precious customer touchpoints and must be managed with the customer, the businesses and the brand in mind.  
• Marketing Operations: The new ‘ops center’ can have responsibility in four areas: performance measurement, process and workflows, marketing technology management, marketing data management. This group serves the entire marketing organization and has its eye on making the function ever more effective and efficient.

Are you working towards a post digital marketing organization? If so, how are you making it work?  

Additional resources: 

• What it takes to Win in a Post-Digital World - Forrester Blog Post 
• Thriving in a Post-Digital World - Forrester Report 
• The Marketing Team Structures Report - TFM Insights 

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