In The News: eMarketer Wearables Forecast

I was recently interviewed by eMarketer about wearables in 2017 and how they are trending for marketers as they evaluated the future forecast of wearables.

The full report is available to eMarketer PRO subscribers.

My summarized commentary is that most of the client demand I have experienced over the past few years has been web and mobile centric.

Over the years I have focused on the intersection of wearables, and the data that’s created and how that can refine a more personalized experience. But the reality is that most wearables are simple extensions of a mobile device and that limits their value to marketers.

Most of the wearable based programs I have been a part of were focused more on the data created as well as actionable notifications but interest has shifted significantly towards conversational experiences such as chatbots and voice based systems.

The full report is available to eMarketer PRO subscribers.

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MWC 2017 – Data Design Speaking Recap

What a great show! Mobile World Congress is when the tech world converges on Barcelona, Spain to discuss the ever expanding domain of mobile. I was excited to attend this years event for three reasons: speaking engagement, conducting tours for media and live streaming on behalf of Epsilon. This post will focus on a comprehensive recap of my panel discussion and pre-session approach.

SPEAKING – I had the opportunity to speak at the Modern Marketing Summit event at Mobile World Congress with the CMO of Aston Martin. The main topic was discussing where he could place bets on emerging tech in the near future. I wanted to put more rigor around the discussion and spent time ahead of the session diving into our proprietary data assets to uncover hidden truths about Aston Martin drivers as the basis for recommendations on where to invest for the future.

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One of the teams I lead is called Data Design. We take unstructured data from a given category such as automotive and apply machine learning to process conversation among owners and map key perceptions, occasions and attributes as well as personality. Machine learning directs our quantitative research and then we overlay some of the worlds largest proprietary data assets to map category perceptions and behavior among Aston Martin drivers.

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This approach proved impactful as the foundation based on data design allowed for differentiation of opinion through insights that allowed a more seamless transition to discuss the intersection of emerging technology and new behavioral signals that will continue to empower consumers.

I begin mapping future state strategy through the lens of Connection, Cognition & Immersion. 

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CONNECTION – Trends and technology that connect us, this can include voice based and conversational experiences such as chatbots. Here are previous posts on Connection.

COGNITION – All facets of artificial intelligence such as Machine Learning, Deep Learning, Neural Networks. Here is a previous post on AI.

IMMERSION – Full sensing and immersive experiences, Virtual, Augmented, Mixed, Merged reality, all of these will have an impact in the near future, and possibly shift entertainment from the back seat to the front. Here are previous Immersion posts

Once I outlined each of the components of the Connection, Cognition & Immersion framework I then recommended that he first begin by laying a foundational data designed strategy to prepare for the pending intelligence revolution.

The Intelligence Revolution will incorporate both reactive and predictive elements in anticipation of the rise of the Proxy Web & System based journeys. All of this is built on a foundation of data + decisioning and will transcend individual technologies.

Here is additional context about the four components of the intelligence revolution:

REACTIVE DATA SETS – Today most consumer centric marketing is based on reactive data. For this panel I began with machine learning based AI to map the psychographics of the Aston Martin user.

PREDICTIVE – Next you will see the rise of predictive algorithms and API’s. This is where you see the combination of reactive datasets and regression analysis and modeling to build towards predictive experiences.

PROXY WEB – This is essential for the most important point to consider which will be the time very soon when the consumer may not be at the center of marketing. The Proxy web is where bots or other intelligent systems will drive predictive discovery driven by vertical and horizontal algorithms. Where the bots become the new DSP’s and IOT based sensors and intelligent environments become the new DMP’s.

SYSTEM BASED JOURNEYS – That will lead to a new type of consumer journey, except this time it is the addition of system based journeys that provide both predictive elements, but also overlay situational awareness across an intelligent environment.

More detail to come on the topic of the Intelligence revolution in a future post.

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LIVE: MWC 2017 Trend Recap

Here is a video recap shot live from the floor of Mobile World Congress 2017 in Barcelona.

The video outlines emerging technology and trends tied to Connection, Cognition and Immersion and touches on key territories such as:

  • Evolution of Conversational Experiences
  • Artificial intelligence and Advancements in Smart Assistants
  • New Types of Interfaces Beyond Mobile
  • The rise of 5G
  • Convergence of Artificial Intelligence and Virtual Reality

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In The News: Ad Age Data Design & Alexa

I was recently interviewed by Ad Age discussing the efforts of my data design team and our work with Amazon and the Alexa Skills Kit.

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When I first joined the Epsilon agency team I wanted to bridge traditional brand planning, strategy and data science to uniquely assess all of our data sources and build recommendations that leverage the right data to assist planning, strategy development and data-driven insights to support strategy and creative.

Now the agency data design group is comprised of 3 core components: 1) Mapping the data landscape 2) Storytelling through data 3) Consulting & training. My goal with this team is align intelligence from the data, regardless of source, that will inform how we communicate and message with consumers as technology and behaviors evolve and most importantly drive performance.

There are three primary areas of focus for the team:

1) Proprietary data sources & methodologies e.g. Leveraging Epsilon’s structured data

2) Unstructured data sources & methodologies e.g. Finding previously invisible insights by applying machine learning & artificial intelligence to unstructured category data

3) New data sources & methodologies e.g. Uncover new types of data sets that we call affective datasets and how it will impact and reshape how we connect across the consumer journey

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Unstructured and New Data sources combined with Epsilon’s proprietary data began to accelerate our processing and analysis capabilities to uncover consumer truths with unstructured data to further fuel our agency’s strategic storytelling and data driven creative leading to an evolution of brand planning.

For the past 12 months my data design team has focused on aligning emerging artificial intelligence systems and algorithms with our structured data assets to combine all of the following elements.

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Data Design is the bridge between planning and bleeding edge tools like cognitive computing, artificial intelligence and natural language processing. Ad Age highlighted our approach with Amazon and how we leverage machine learning on amazon.com down to the product SKU level to further inform communication and engagement strategy as well as our team being one of the early adopters of the Alexa Skills Kit (ASK).

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Here is an example of data design concepts in action.

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7 Ways AI will Enhance Marketing

For the past 12 months, my Epsilon team and I have focused on multiple facets of artificial intelligence (AI) with data as the primary fuel that powers key insights. We have leveraged machine learning, natural language processing, predictive APIs, and neural networks to uncover consumer truths that previously would have taken weeks or months to uncover.Having the opportunity to work with comprehensive, boundless proprietary data assets is incredibly exciting. In addition to fueling strategy work, it also drives emotional connections with consumers, bonding them to brands in meaningful ways. It is the future of marketing.Now past the experimentation phase, I can say confidently that AI will be a key driver of technology growth over the next decade and will significantly impact consumer marketing. Initial predictions show the market for AI-driven products and services will jump from $36 billion in 2020 to $127 billion by 2025*. (*Source: BofA Merrill Lynch Global Research Estimates — 2017 the year ahead: artificial Intelligence; The rise of the machines.)Most AI we work with today is categorized as Artificial Narrow Intelligence (ANI). This means that the AI is extremely adept at executing specific tasks.

Right now, there are seven subsets of artificial intelligence, outlined below. Brand marketers can better uncover insights, connect with consumers, and redefine customer experiences using this innovative technology.

Machine learning (ML)

ML uses human coded computer algorithms based on mathematical models. Probability models then make assumptions and/or predictions about similar data sets.

Currently, machine learning can be leveraged as a service to accelerate sentiment analysis and domain-specific insights. It also serves as a foundational element for identifying consumer behavior based on occasions, perceptions, and attributes to construct themes and trends from unstructured data which represents the thoughts, behaviors, and preferences of consumers taken directly from their online activities.

In 2017 and beyond, I expect more third-party providers will offer ML as a cloud service brands and agencies can leverage to transform products and services into smart objects, able to predict needs and preferences.

Machine learning solutions have allowed my team to align our proprietary structured data assets with unstructured data to combine the best of both worlds. This began to accelerate our processing and analysis capabilities to uncover consumer truths within unstructured data to further fuel our agency’s strategic storytelling.

Cognitive computing

Cognitive computing builds on machine learning using large data sets.

The goal is to create automated IT systems that can solve problems without human intervention. Marketing centric cognitive computing solutions can consist of a single, all-encompassing solution, or be comprised of multiple services that build and scale applications over time.

From a marketing application perspective, cognitive computing-based solutions range from customer experience enhancing chatbots to closed loop systems for tracking media performance.

Bank of America recently launched the Erica bot using AI, cognitive messaging, and predictive analytics to further influence consumers’ ability to create better money habits.

Cognitive computing will be key to unlocking the potential of conversational experiences. As ecosystems continue to rise, many of the 30,000 chatbots on Facebook Messenger are powered by AI services.

Facebook’s own M virtual assistant housed within Messenger will soon come out of beta testing and will incorporate cognitive suggestions based on content of a conversation users are having. The goal is to make Messenger-based interactions more convenient, enabling users to access services without leaving the conversational thread within Messenger.

Speech recognition and natural language processing (NLP)

NLP refers to intelligent systems able to understand written and spoken language just like humans, along with reasoning and context, eventually producing speech and writing. NLP plays an essential role in the creation of conversational experiences.

Voice-based experiences, such as Alexa’s voice services (AVS), will become pervasive over the next few years. It is projected that by 2020, 30 percent of web browsing sessions will happen without a screen.* (*Source: Gartner analysts at Symposium/ITxpo 2016.)

The core of the AVS experience is a combination of automated speech recognition, natural language processing, and a cloud-based AI that comprise a voice-based user experience.

As with most artificial intelligence entities, learning new skills is how personalized and contextual experiences will be created. With Alexa, it is possible to “teach” new conversational elements and interactions through developing skills.

Here is an example from Domino’s pizza that allows consumers to order pizza directly through Alexa voice services.

Alexa skill development is one of the quickest ways for brands to connect with the rapidly growing audience that calls upon Alexa to empower their daily lives.

Fitbit is another brand leveraging Alexa-based skills to extend brand engagement. Traditionally Fitbit users depend on an app to visualize their data. With the Fitbit Alexa skill users can get a quick update on the stats that matter the most without the need of a screen.

Deep learning

Deep learning builds on machine learning using neural networks. Neural networks are statistical models directly inspired by, and partially modeled on, biological neural networks such as the human brain. The use of neural networks is what differentiates deep learning from cognitive computing.

Deep learning is currently redefining Google’s approach to search, and search engine optimization (SEO) will never be the same. Previously, Google search results were based on algorithms defined by a strict set of rules and SEO was based on regression models that looked at past behavior to adjust a given strategy.

With the introduction of RankBrain, Google’s machine learning technology, in 2016, search algorithms are now enhanced with artificial intelligence. Google is now processing roughly 15 percent of daily queries by mixing the core algorithms based on each search type.

The system is adept at analyzing words and phrases that make up a search query. It also decides what additional words and phrases carry similar meaning.

Expect the percentage of search queries handled by AI to significantly increase. Marketers will need to rethink site architecture, content, and the signals being sent via backlinks as the systems continue to learn on a query-by-query basis.

Predictive application programming interfaces (APIs)

A predictive API uses AI to provide access to predictive models, or expose access to an ability to learn and create new models.

Fortune 500 company USAA is analyzing thousands of factors to match broad patterns of customer behavior through its intelligent virtual assistant Nina.

As we shift from consumers using technology to technology enhancing consumers, predictive APIs will play a key role in providing recommendations, enhancing customer service, and providing real-time analytics without in-house data scientists. This is key to unlocking new forms of value exchanges with consumers in a hyperconnected world.

Image and object recognition

Image recognition finds patterns in visually represented data, pictures, and objects. Facebook and Google are two organizations focused on AI research and solutions in this area.

As image recognition is extended into video and live broadcasts, it will redefine contextual relevance, categorization, and automation of content distribution.

Combined with the advancement of cameras, image recognition and machine learning are transforming the way we process data, including much more than just attitudes and behaviors.

Brand marketers can now leverage images, facial expressions, body gestures, and data collected from IOT-enabled devices to understand the triggers behind behavior and build experiences that anticipate their customer’s needs. This requires brand marketers to transform their data strategy to expand beyond first- and third-party data to also incorporate unstructured datasets that capture affect and unconscious data inputs.

Snap’s pending patent on object recognition is potentially game changing. A recent patent application shows its desire to built object recognition into snaps that can enhance recommended and sponsored filters most likely powered by an AI-based system. This showcases how any object can be aligned with creating immediate context with a consumer and brand.

Olay launched an AI-powered Skin Advisor that ingested user generated photos and provided recommendations for suitable products.

Dynamic experience generation

AI-based systems not only have the ability to parse through large data sets and offer predictive solutions, but also can drive the creation of dynamic experiences. AI will become a powerful tool for creating vs. analysis.

Many startups are leveraing AI APIs to create intelligent solutions. The Grid (https://thegrid.io) is leveraging AI to automate web design with Molly. Molly analyzes design decisions and creates new web experiences.

Eventually, AI will be a key driver of creating augmented reality experiences. Dynamic experience generation through AI will recreate physics, recognizing gestures and movements that can generate new consumer experiences.

Below, Mark Zuckerberg discusses the future of AR/VR at Facebook’s F8 conference.

The various subsets of artificial intelligence will continue to be interconnected, redefining how we approach connecting with consumers. AI makes it possible to know the consumer better than ever before. If approached correctly, with the right mix of AI subsets leveraged, companies will see their business grow.

This is a repost of my recent iMedia cover story.

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In The News: iMedia 7 Ways AI Enhances Marketing Cover Story

This morning my new article 7 ways artificial intelligence will enhance marketing was the cover story for iMedia Connection.

The article reviews seven subsets of artificial intelligence from machine learning, cognitive computing, natural language processing, deep learning, predictive API’s, object recognition and dynamic content generation and how brand marketers can better uncover insights, connect with consumers, and redefine customer experiences using this innovative technology.

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In The News: Entrepreneur.com & AI

I recently sat down with Jeffrey Hayzlett of C-suite TV for the first episode of season 7 for Executive Perspectives live.

He recently wrote a piece for Entrepreneur.com outlining 5 business trends that will take off in 2017. Jeffrey referenced our conversation regarding automation of conversational experiences through artificial intelligence.

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The infusion of voice-based technology into consumer products, and the ways in which brands are shifting from social media to social messaging strategies were the subject I addressed with Epsilon Chief Digital Officer Tom Edwards, during a recent interview. Edwards told me how “disruption is the new normal” and how chatbots are the next thing chief marketing officers will have to deal with as technologies keep evolving.

For more insight from the discussion here is a link to the full interview.

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Trends To Watch in 2017

Technology is now essential to our daily lives. Accessibility and empowerment has transformed how we connect and communicate. This has led to new forms of user interaction that will usher in the business models of the future.

2017 will be comprised of new types of conversational experiences to connect with consumers. It will see the continued evolution of artificial intelligence and connected systems as well as the rapid rise of third-party ecosystems supporting virtual, augmented and mixed reality.

The following trend deck outlines the evolution of marketing in 2017 through the consumer centric filters of connection, cognition and immersion and is now available for download.

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  • CONNECTION – Trends that reimagine how we connect, enable and empower consumers.
    • Examples include: Simplified Conversational Experiences, Pervasive Voice-Based Interfaces, Search and Retrieval to 1:1 Prediction, Affective Datasets and eSports

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  • COGNITION – Trends where machine based intelligence will disrupt and redefine data assets and how we work.
    • Examples include: Machine Learning as a Service, Centaur Intelligence, Blockchain & AI

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  • IMMERSION – Trends that align technology and presence to evoke emotion, entertain and power commerce.
    • Examples include: Democratization of VR, VR Commerce, Social VR, (Re)Mixed Reality

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  • ZONE OF CONVERGENCE – Trends that align elements of connection, cognition and immersion that will redefine consumer engagement.
    • Examples include: Cars as the next Mobile Platform, Holographic Computing, Ambient Computing.

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How we consume and interact via digital channels is about to be absorbed and redefined. We believe that 2017 will begin the convergence of connection, cognition and immersion toward an ambient computing future built on new data types that will simplify complex tasks and predict need states vs reacting.

Download the 2017 Trend Predictions Today!

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C-Suite TV Discussion – Disruption, UX, The Future

This week I had the pleasure of joining the C-Suite TV team at their San Francisco event and was interviewed by Jeffrey Hayzlett. It was a fun discussion as he asked me about the shift from social media to social messaging, strategies to make the shift, voice based experiences, disruption, galactic cannibalism, trends and the future of connecting with consumers.

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Below is a recap of my key talking points for each question.

(C-Suite TV – JH) As we’re on the verge of a transformational moment in marketing with the shift from social media to social messaging, how are marketers making this shift?

(Tom Edwards – TE) Over the past 5-10 years we as marketers have focused primarily on the open web + social media. Earlier this year social messaging passed social media in terms of monthly active users. Consumers are ready for conversational experiences. Part of the reason for the appeal is that it is seen as safe, comfortable and intimate.

I spent most of this year researching, writing and educating our brand partners about what this shift can mean for their business. We conducted proprietary research on what consumers want from conversational experiences that led to an ebook on the topic.

Social Shift Toward Messaging

As we dug into consumer expectations around conversational experiences, our research found that they want experiences that are convenient and support local experiences, there is openness to pay within social messaging and an expectation that it will connect physical and digital elements such as in store coupons and discounts, there is also a willingness to interact with intelligent systems.  Research also shows that 60% of millennials would prefer talking to a chatbot vs. talking to a human when it comes to resolving questions about online shopping.

From a marketing perspective there has been a significant amount of experimentation trying to create the ideal experience. With Apple, Facebook, LINE, Kik, Skype and more providing tools and services that will allow others through 3d party SDKs & API’s to create an ecosystem. Their hope is to become the central portal in order to empower consumers and drive commerce. Facebook doesn’t own the hardware or the operating system, so they are invested in keeping people in the messenger experience.

Some experiences are trying to further personify the brand, others are about creating utility or a sense of intimacy with the brand. The goal is to create a real-time experience that is centralized in one conversational thread.

The key will be creating experiences that are not disruptive but are actually attentive to the current and future needs of the consumer. The ideal experiences will be built around the premise of simplification + prediction. It’s not about a deeper personal connection like a friend, but to be able to anticipate, predict and enhance a consumers experience.

This is where we see the idea of CONNECTION + COGNITION coming together.

(JH) What processes and strategies do you need in place to make this shift effective?

(TE) I recommend an approach that is based on five core factors of Simplification, Data Design, Prediction, Ambient Design & Physical to Digital.

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1 – (SIMPLIFICATION) The key is to reduce complexity in consumers lives and create experiences that are ownable by the brand’s domain. Mine customer data for most commonly asked questions and expand from there with use cases focused on enhancing and simplifying experiences.

2 – (DATA DESIGN) Have a strategy not just to capture data but how to use it. Define the role of unstructured data in refining the experience. Consider what new data points are being integrated to inform future prediction. How are you making the data actionable? On my team we now have a data design team that sits between traditional brand planning + digital strategy. This is the intersection of Big Data + Design Thinking. They own the tools, assets and data sources and understand how to craft a data driven narrative.

3 – (PREDICTION) Anticipate consumer needs is key for the future of conversational experiences. Messenger experiences are not designed to be like Google search, at least not yet. Google is working towards the ideal intersection between search & retrieval vs. predictive. But again a combination of data, predictive analytics built on working data is the entry point towards truly predictive experiences. (cognitive will accelerate this)

4 – (AMBIENT DESIGN) The future of computing is tied to ambient experiences, or how your environment interacts with you. It is critical to approach designing conversational and voice based UX differently.

5 – (PHYSICAL TO DIGITAL) One of the other elements is the rise of conversational commerce. There is a concerted effort to closely align physical & digital shopping experiences as a means to enhance the customer experience. Our research shows there is an expectation from consumers to have local experiences connect to digital through conversational experiences.

(JH) Let’s talk about some newer technologies, how does voice based technology play into this shift to a conversational user experience?

(TE) I am a strong believer in the fact that voice based experiences and artificial intelligence systems will become pervasive in our everyday lives. The core of the experience is a combination of automated speech recognition, natural language processing and a cloud based AI that comprise a voice based user experience.

I am very intrigued by the possibility of the ability to create context through voice services such as Amazon Alexa Voice Services & the recently launched Google Home. Voice based experiences will play a key role during this time as our interactions with connected systems and the rise of micro services as a primary mechanism to navigate a hyper connected world will become the new normal.

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I strongly believe that we will begin to see a convergence over the next few years where elements that enable connection such as social messaging and voice based conversational user experiences combined with cognitive computing (AI) and immersive experiences such as holographic computing will become interconnected and will redefine how we approach connecting with consumers.

We will begin to see services such as Alexa Voice Services quickly proliferate throughout 3rd party devices from in home IOT systems to connected vehicles and “skills” will become a key component for how we navigate beyond screens. Estimates already show over 28 billion connected devices by 2019.

(JH) We hear you say that “disruption is the new normal” what do you mean by that?

(TE) Digital disruption has been at the center of major consumer shifts over the past 10 years. Disruption is now the new normal. The Premise is change is constant and experimentation is critical and how you integrate trends into your existing business is key.

The acceleration of technology has led to the rapid empowerment of the consumer. What organizations have to consider is that with each iteration of technology and consumer empowerment new types of interactions will lead to the need to rethink the business models of today.

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This has a significant impact on the C-suite as the pressure on CMO’s to be creative thinkers, intelligent around data, domains and disciplines as well as mitigation of risk, pressure to innovate, find and retain talent and try to be as agile as possible. Combined with the pace of new interaction models there is a lack of strategy to deal with the shifts in a meaningful way as the focus is on short term stability.

This is why it’s important to build a plan with a foundational approach to data and understand what domains the brand can own and where in the new interaction types there are opportunities to redefine business models. This is why I have chosen Connection, Cognition and Immersion as the pillars of how brands can map to the new interaction types of the near future.

(JH) I heard you say we’re on the verge of galactic cannibalism can you explain what this means for marketers and how can marketers stay ahead of the game?

(TE) I have spoken a lot recently about how disruption is the new normal. I recently heard someone compare the last five years as a “supernova” of disruption in terms of the intensity and velocity of change.

With the rise of artificial intelligence, conversational & ambient experiences, connected systems and mixed reality on the horizon we are moving well beyond a supernova and are now on the verge of galactic cannibalism.

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Galactic cannibalism is when one galaxy collides with another and there is a subsequent absorption of parts of one into the other. From a consumer marketing standpoint how we consume and interact via digital channels is about to be absorbed and redefined through new advancements in connection, cognition & immersion.

The key point to surviving and thriving is to have a comprehensive data strategy as data assets will serve as the fuel of this shift. Regardless of which galaxies collide a thorough understanding of data, content, experiences and outcomes is a marketing foundation for the future.

Also, it is important to understand how data will evolve. Currently the focus is on 1st part & 3rd party data. But in the emerging world think of the data created by connected systems as well as new forms of real time sentiment data, such as your eyes in a VR experience or facial recognition in a retail setting. These will require a comprehensive data design effort to craft content, experiences and drive outcomes as a marketing foundation for the future.

Ultimately we will have to acknowledge that the relationship between consumers and technology will fundamentally change from consumers operating technology to technology operating for consumers through data.

(JH) How do you apply the trends of today to the business models of the future?

(TE) The first step is to be aware of what is happening. Analysts such as Gartner and Forrester are evaluating and publishing their rankings of where technology is going. One of my favorites is the Gartner Hype Cycle.

One of my responsibilities with Epsilon is I lead the innovation practice for the agency business. We have designed an approach that is consumer centric, data driven, iterative and allows our brand partners to scale emerging technologies and integrate trends into tangible solutions that drive business outcomes. The practice is comprised of four distinct elements that span research, workshops, experimentation and transformation.

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Regarding research & trends, we leverage Epsilon’s proprietary data and analytics, first and third party research, emerging companies and established partner networks to research, curate and educate on the latest trends and how it can apply to our clients business.

Our approach is as follows:

Our team identifies a new tech/emerging tech…

1. Track Product/Technology Announcement

2. Measure Velocity of coverage & discussion

3. Conduct Initial analysis & POV outlining potential value/impact

4. Explore outcome impacts & role of tech in consumer journey

5. Map vertical specific use cases

6. Educate internal teams & external clients

7. Identify early vendor partners and alpha/beta opportunities

8. Conduct Project based experiments

9. Capture & package project based success

10. Build business value case for horizon consideration

Once you have identified your trends its helpful to begin to filter across key macro trend territories, in this case I am exploring trends that reach across

Connection, Cognition & Immersion

(JH) What’s really resonating with consumers right now? What should marketers be paying attention too?

(TE) Anonymous personalization through dynamic content, targeted video content, Personalized, connecting the consumer experience across digital to physical & 1:1 messaging that is authentic, provides value and is contextually relevant is key.

Human attention is now a scarce commodity. Attention is a resource – and we only have so much to give. The key to experience design is built around data, content & channels or experiences.

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I like to start with data, it can be 1st party or secondary data sources, but I look for attitudinal, behavioral in addition to standard demographic. Transactional data can also be a key element and consistency of message is key.

(JH) What is the future of connecting with consumers?

(TE) I strongly believe that we will begin to see a convergence over the next few years where elements that enable connection such as social messaging and voice based conversational user experiences combined with cognitive computing (AI) and immersive experiences such as holographic computing will become interconnected and will redefine how we approach connecting with consumers.

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The key will be to create data designed experiences that empower consumers.

Here is a link to the full video interview kicking off season 7.

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Virtual Reality Experiences Are Evolving

I have closely monitored the state of virtual reality for the past few years. From product announcements, beta tests and insider access to hardware and experiences. VR can be a powerful, emotion evoking medium and one that has captured the interest of mainstream media.

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I wanted to test the experience beyond short stylized sessions and review the potential for enhancing live event experiences as well as the integration of commerce, context and the opportunity for content distribution and brand impact.

I recently live streamed the University of Oklahoma vs. Ohio State CFB game via Fox Sports VR app. It was a good experience and one that really pushed the limits of comfort due to length of the session and the hardwares capacity.

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Having the ability to control various camera angles and a pervasive stats bar was a good enhancement to the experience and provided additional context to the on-field action.

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Digital overlays of commentators and in-game recaps also gave the feel that this was an enhanced experience and highlights the potential to create points of distribution/engagement within a virtual session.

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The most impressive aspect was the use of contextual hotspots in the VR experience to control the various commands to shift the camera. By simply focusing my gaze I was able to shift through menu options in a very frictionless way.

Stare at the orange circles to change the camera view

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It’s this in-session capability that has me incredibly excited about the potential of the medium to transcend simple entertainment and have implications on brand impact & conversion potential by connecting commerce in addition to evoking emotion and presence.

There were a few hiccups as the experience would occasionally freeze, the device overheated numerous times and also requires wi-fi, but overall it was a very positive experience and one I would gladly engage with again.

While this experience was app based, I was incredibly excited about the recent announcement from the Oculus team announcing the ReactVR framework that will allow our team to create Web VR experiences in a virtual browser codenamed “Carmel”

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This will reduce the dependency on app based experiences and opens up possibilities for creating experiences that don’t require a traditional download.

Having a web type user experience within VR where the transition from topic to topic is seamless vs. stopping, launching an app, navigating to the right content and initiating the experience can open up new opportunities to increase dwell time and create a better UX.

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This framework will enable rapid and portable deployment of experiences combined with the consumer benefit of shifting from various content types across device types such as VR, mobile, traditional web .

This combined with the data created across browsing sessions provides a key foundational element to create connections with consumers within immersive virtual reality experiences.

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Tom Edwards Innovation To Reality

In The News: Luxury Daily & Seasonal Retail

I was recently asked by the team at Luxury Daily to elaborate on a proprietary Epsilon research initiative tied to how likely consumers are to shop in-stores vs. online for the 2016 holiday season.

Findings show that 87% of shoppers are “very likely” or “somewhat likely” to purchase at brick and mortar stores this year, with 55% of shoppers “very likely” or “somewhat likely” to look at a product online and then go to a store to buy.

Conversely, 76% of shoppers are “very likely” or “somewhat likely” to purchase online this holiday season, with 54% of shoppers “very likely” or “somewhat likely” to look in store for a product and go online to find the best deal. These findings further signify the importance of personalizing communications both online and offline and creating a seamless customer journey across marketing channels.

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With this as a baseline, I was asked by Luxury Daily to outline the key findings and impact for luxury retailers.

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Luxury Daily also asked how luxury retailers and retailers in general should respond.

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Voice Based UI Best Practices

Over the past year I have focused research efforts on the shift towards conversational experiences and what consumers expect. The research has been covered by Adweek and it’s fascinating how open consumers are to engaging and adopting these experiences as long as they are easy to use and are convenient.

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One flavor of conversational experiences is tied to voice based user experiences. I recently visited Amazon HQ in Seattle and wrote about my experience with the newly formed Amazon Alexa partner team and the rise of voice based user experiences.

Since this article published I have seen client interest and demand for voice based concepts and skill creation rise as our brand partners see the potential of voice based systems.

Here is a slide from a recent client presentation. Almost every meeting over the past few months has included discussions around voice based UI.

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I strongly believe that we will begin to see a convergence over the next few years where elements that enable connection such as social messaging and voice based conversational user experiences combined with cognitive computing (AI) and immersive experiences such as holographic computing will become interconnected and will redefine how we approach connecting with consumers.

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Voice based experiences will play a key role during this time as our interactions with connected systems and the rise of micro services as a primary mechanism to navigate a hyper connected world will become the new normal.

We will begin to see services such as Alexa Voice Services quickly proliferate throughout 3rd party devices from in home IOT systems to connected vehicles and “skills” will become a key component for how we navigate beyond screens. Estimates already show over 28 billion connected devices by 2019.

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Developing voice based experiences differs greatly from visually driven experiences. Visual experiences provide immediate context and cues to the end user that can guide the user and enhance the experience.

Here are 5 emerging voice UI design patterns the Amazon team and I discussed and subsequent best practices and points to consider when designing voice based skills.

  1. Infinitely Wide Top Level UI

With a mobile user experience, users have the benefit of visual cues that can guide their actions within a given experience. Be it a hamburger menu or on-screen prompts. With Voice based UI the top level of the UI is infinitely wide. Here are a few best practices for building solutions to beyond infinity wide top level.

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Don’t assume users know what to do – It’s important the first time a voice skill is initiated to provide additional detail and tell the user about their what options they have for interacting with your experience.

Expect the Unexpected – Unlike visual interfaces there is no way to limit what users can say in speech interaction. It’s important to plan for reasonable things users might say that are not supported and handle intelligently.

2) Definitive Choices – The key to successful Voice UI design is to make the next consumer action clear. Consumers will not always say what they want so it is incredibly important to map intent beyond the normal function of a skill. An example is how a consumer may end a session. They may utter done, quit, etc… and the skill needs to provide clear action for how to end the session. Here are additional points to consider.

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Make it clear that the user needs to respond – Ask the user a question vs. simply making a statement.

Clearly present the options – Prompts are very important, especially if the question set is an either/or vs. yes/no.

Keep it Brief – Speech is linear and time based. Users cannot skim spoken content like visual content. Quick decisions are key, so voice based prompts should be short, clear and concise.

Avoid too many choices – Make sure choices are clearly stated and do not present more than three choices at a time, avoid repetitive words.

Use Confirmation Selectively – Avoid dialogs that create too many confirmations, but confirm actions of high consequence.

3) Automatic Learning

One of the areas I am most excited about over the next few years is the intersection of artificial intelligence and the ability to apply machine learning and other higher level algorithms to create more personalized experiences. For Voice based UI it is important to understand how sessions can persist over time.

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Obtain one piece of information at a time – Users may not always give all of the information required in a single step. Ask for missing information step by step and focus on a progressive profiling strategy vs. lead capture.

Develop for Time Lapse – It is possible to create skills that allow for sessions to persist with end users. This can be hours or days. This can allow more data to be collected across sessions.

Personalize Over Time – As sessions persist and users interact with skills it is possible to further personalize the experience over time based on previous interactions.

4) Proactive Explanation

With traditional visual design a user can open a web page or a mobile app and the information design shows you what to do. With voice you don’t have a page so having the ability to clearly articulate definitive choices in addition to providing proactive explanations such as tutorials or help are critically important to reduce user frustration.

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Offer help for Complex Skills – If a skill does more than three functions, it is important to not overload a single prompt to the user. Present the most important information first, along with the option of a help session.

Make sure users know they are in the right place – In speech only interactions, users do not have the benefit of visuals to orient themselves. Using “landmarks” tells users that Alexa heard them correctly, orients them in the interaction and helps to instill trust.

Use Re-Promptiong to Provide Guidance – Offer a re-prompt if an error is triggered. This should include guidance on next steps

Offer a way out if the user gets stuck – Add instructions into the help session. “ You can also stop, if you’re done”.

Don’t blame the user – Errors will happen. Do not place blame on the user when errors happen.

5) Natural Dialog

Research shows that people are “voice activated” and we respond to voice technologies as we respond to actual people. This makes the crafting of voice based narratives incredibly important as the dialog needs to be natural, consumable and written for the ear not the eye. Here are a few key points to consider for enhancing natural dialog within a skill.

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Present information in consumable pieces – Humans only retain a small amount of information that they hear, only present what is absolutely required in order to keep the interaction as short as possible.

Longer lists need to be broken out into three to five items and ask the user if they want to continue after presented with each chunk.

Write for the Ear, not the Eye – The prompts written for voice-forward experiences will be heard, not read, so it’s important to write them for spoken conversation. Pay attention to punctuation.

Avoid Technical & Legal Jargon – Be honest with the user, but don’t use technical jargon that the user won’t understand or that does not sound natural. Add legal disclaimers to the Alexa app for users to read and process.

Rely on the text, not stress and intonation – Use words to effectively convey information. It is not possible to control the stress and intonation of the speech. You can add breaks but cannot change elements such as pitch, range, rate, duration and volume.

Clarify Specialized Abbreviations and Symbols – If an abbreviation such as a phone number or chemical compound is somewhat specialized, ensure to test the text-to-speech conversion to see if additional steps need to be made.

One final takeaway RE: the Alexa voice based system is the proximity to transaction and list creation via Amazon’s core services. This combined with 6 years of development tied to Alexa Voice Services and the rising partner ecosystem are all signals towards the convergence of connection, cognition and immersion.

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The Medium Is the Message

This week Adweek published our quantitative research infographic about consumer behavioral shifts tied to social messaging and the types of experiences they are interested in engaging with in both the print and online edition.

Look for this week’s issue of Adweek. Our research is on page 13.

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With apps like Facebook Messenger, WhatsApp and Snapchat vying with conventional SMS to be the preferred texting method, the line between social media and texting is more blurred than ever. And brands have a real chance to capitalize on this, according to a newly released study by Dallas-based marketing group Epsilon.

“We are on the verge of a transformational moment, as consumer behavior is dictating a shift towards intimacy of sharing content and experiences versus public sharing,” said Epsilon chief digital officer of agency business Tom Edwards. “Messaging apps now boast more active users than social networks, and this shift from social media to social messaging will redefine how we, as marketers, will approach connecting with consumers.”

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IIeX 2016 Machine Learning + AI = Data Driven Creative

Yesterday I had the privilege to speak at the Insight Innovation eXchange or IIeX North America 2016 discussing our approach to getting data driven creative via Machine Learning and artificial intelligence.

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This presentation was a joint effort between my Epsilon team and one of our strategic partners Oculus360. I work closely with Raju Kattumenu, the founder of Oculus360 and we have engaged on numerous initiatives over the past year.

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This has allowed us to leverage the power and reach across public domains leveraging their technology combined with our proprietary data assets to validate consumer truths or find new connections based on occasions, attributes, perception & demand signals.

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The technology is a combination of natural language processing, an artificial intelligence neural network and machine learning systems that combine to unlock various themes & trends associated with demand signals created by consumers.

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The key to this approach is that instead of starting macro across all facets of the web or social conversation, this approach looks at specific domains and can go incredibly deep down to the product sku level.

We then take the results from this approach and combine it with our connection planning process and data assets to unlock consumer truths that will define our approach to creative and strategic territories. It truly is an approach where data fuels creativity.

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This approach of combining machine learning + AI with Epsilon’s data assets allows us to truly identify contextual moments to create personalized experiences.

Context is key as this informs whether we should use storytelling vs. storymaking moments. We then align moments with personalized elements of the story based on our data findings and use cross device identity to create personalized story delivery at scale.

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I also discussed how we have realigned our approach to planning with data science to inform creative territories & strategic themes as well as how this approach supports innovation initiatives by informing and validating consumer readiness when it comes to emerging storytelling mediums.

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We then showed an example based on the mini-van category. Traditionally mini-van advertising has stayed very close to the “family” approach to connecting.

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We wanted to either validate the approach or find new consumer truths based on all the factors outlined above. What we found was very interesting as key attributes and occasions began to surface that outlined new demand signals that could be used to shift perception.

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This also allows us to take a look across brands and see which brands align with specific occasions which can lead to differentiation among competitors.

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We can also look at specific features associated with each of the brands to identify new territories or areas to focus on driving awareness, engagement or advocacy.

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In order to maximize contextual connections with consumers it is important to not only have qualitative data tied to consumer insights. It is also critical to leverage the power of machine learning and artificial intelligence combined with strong data assets to unlock demand signals that can fuel the creative process.

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Why Microsoft Bought Linkedin

News broke this morning outlining Microsoft’s intention to purchase Linkedin for $26.2 billion dollars. Many outlets are reporting the purchase, but not many are discussing the advantages and benefits that Microsoft may gain by the acquisition.

Here are 6 territories that may be bolstered by Microsoft’s acquisition:

Professional Data – The acquisition of Linkedin offers almost immediate access to professional profile data that Microsoft could leverage and integrate into Microsoft Office products, specifically Office 365.

By merging the 433 million members with 1.2 billion office users, Microsoft can quickly build integrations between professional profile data and their product set.

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B2B Marketing Reach – With 433 million members (128 million in the US) Microsoft just picked up one of the premier B2B advertising players that instantly gives them global reach to further extend advertising solutions as well as Microsoft products and services.

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Search – Microsoft has dabbled with social search with social integrations into Bing over the past few years. Also their failed launch of So.cl in 2012 was designed to research the potential integration of social and search. By picking up Linkedin they also gain the growing content engine that is highly optimized for organic discovery within traditional search channels.

Here is an example of my latest Linkedin Post that is also the #1 result for Data fueling Creative.

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Extending Social Capabilities – Microsoft has also been a minority player previously investing $256 million dollars in Facebook. They  recently launched a joint underwater cable initiative to further boost cloud service capabilities for both organizations.

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With a strategic partnership with one of the largest B2C marketing entities and now picking up the premier B2B platform, Microsoft is positioning itself to remain relevant through diversifying their assets, strategic partnerships and leveraging the content created from Linkedin as well as it’s global reach and subscription based member model to further deliver products, services and create new streams of revenue.

Extending Productivity Solutions – Microsoft has been laser focused on building subscription based productivity solutions over the past 5 years. This includes unified communications solutions yammer and lync as well as products like Office 365, OneDrive and OneNote.

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By acquiring Linkedin they will have direct access to various users across company type and could potentially box out competitive products and solutions and focus on exclusively positioning their products and services to the 433 million global users.

Cortana – There is speculation that Cortana is being positioned as one of the first virtual assistant/artificial intelligence systems being built specifically for the enterprise. The acquisition of Linkedin could be a viable platform to educate, identify and sell through the service in addition to leveraging professional profile data, content and conversations happening within Linkedin Groups to further refine offerings.

cortana

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