Summit 2016: Mobile App Lifecycle Announcement


Marketing Cloud

The mobile transformation happening with consumers and industries is currently in a second phase. The first phase was focused on presence; brands needed to put an app out and optimize for mobile Web. This happened quickly and users began migrating over.

The latest data from Adobe Digital Index shows that in the retail, travel & hospitality, media & entertainment and the automotive industry, the top 20 brands saw over 35% of traffic coming from smartphones.

Phase two will be focused on great experiences, the biggest hurdle facing brands today. The industry has gotten pretty sophisticated when it comes to desktop Web, but a lot of work is left to be done on mobile. You only have to look at the latest retention stats to see why.

The Adobe Mobile App Lifecycle is our approach to the kind of foundation that enables a solid mobile strategy. Each pillar is covered by a solution in Adobe Marketing Cloud, and we are able to comprehensively address all the needs that a marketer has today. As digital transformation continues to upend everything around us, we can help brands create beautiful content in Creative Cloud and deliver great experiences with Marketing Cloud.

Adobe Mobile App Lifecycle

At Summit, we’ve announced major updates across the Adobe Mobile App Lifecycle. Here’s a snapshot of what’s new:

Create Beautiful Apps: 

  • Apache Cordova Integration in Adobe Experience Manager Mobile: We unveiled a new product at Mobile World Congress that allows brands to make and manage beautiful apps, called Adobe Experience Manager Mobile. Deeper Cordova integration helps customers build mobile-app extensions to create richer app experiences. We’ve also announced that several new technology partners are extending their support of Adobe Experience Manager to include mobile.

Build An Audience: 

  • Capturing a TV Audience Across Screens: As consumers are adopting alternative ways to watch traditional TV across connected screens and devices (while even bypassing cable and satellite TV packages), Adobe Primetime OTT, enabled by Adobe Marketing Cloud, will extend the solution to help TV Networks and pay-TVE providers deliver more personalized TV and ad experiences directly to consumers – when and where they want to watch TV content. Integration with Adobe Marketing Cloud will enable brands to target outreach to specific audience segments and optimize to convert audiences into paying subscribers.

 Act With Good Data:

  • Data Science Enhancements: Advanced analytics have long been kept in the domain of data scientists, with marketers on the outside looking in. Adobe is delivering a wide array of algorithms laser-focused on marketer’s needs and helping brands drive exceptional consumer experiences. On top of over 40 existing data science capabilities across Adobe Marketing Cloud, we’ve announced several ones: Virtual Analyst will help marketers surface buried, real-time insights they may have missed; Smart Tags use image recognition technology to help teams easily search, manage, measure and optimize assets across devices.
  • Introducing Adobe Certified Metrics and comScore Partnership: Consumers are increasingly comfortable with getting television content across mobile and connected devices; in some cases, they demand it. Measurement in a digital world is not on par with the standards seen in traditional television, and comScore and Adobe are joining forces to address this issue. We’ve introduced Adobe Certified Metrics as part of this, standardized digital census data built on the Adobe platform. This partnership will deliver comprehensive measurement of content and ads, allowing the industry to deliver more consistent and relevant user experiences, while better monetizing these channels.
  • A single data source for faster optimization: Enhanced integration between Adobe Analytics and Adobe Target for mobile app engagement allows you to act on insights quickly. By selecting Analytics as the data source for optimization reporting, mobile marketers and mobile analysts can collaborate with confidence in the data, and dig deep for engagement opportunities. Automatically share audiences for testing and targeting activities, and set them to optimize for out-of-box mobile lifecycle metrics, custom metrics, or any Analytics success metric that matters to your app strategy.

Deliver Relevant Experiences:  

  • Deliver Better User Navigation with Deep Links: Introduced at Mobile World Congress, this new capability within Adobe Marketing Cloud allows mobile teams to define the right paths in the user experience. When we look at TV content across devices for instance, media companies can now land their users directly on the content itself, as opposed to a home page or otherwise. The fewer steps there are for users, the more they’ll find the experience enjoyable. Leveraging Adobe Mobile Core Services, Marketers can visually construct decision trees and easily define the right path.
  • Personalization at Scale with Adobe Marketing Cloud Device Co-Op: With the various devices that consumers own, it’s difficult for brands to identify people across various touch points. The new Adobe Marketing Cloud Device Co-op is a collaborative effort amongst the world’s most reputable brands, which will help transition the industry to people-based marketing and deliver highly personalized and relevant experiences to consumers as they move from one device to another – while ensuring the highest level of privacy and transparency.
  • Mobile Video Recommendation Engine: For TV Networks and pay-TV providers to capitalize on the migration of television content across devices, they need the right tools to engage audiences with great experiences. As part of our data science capabilities within Adobe Primetime and Adobe Target, media companies can now deliver personalized video recommendations based on deep contextual insights and granular video consumption insights. It goes beyond existing methods of tracking viewing history and purchases within closed environments, looking at contextual insights such as how and what video content a viewer has watched.

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Smart Tags Use Machine Learning to Bring Your Images Back to Life


Marketing Cloud

Walk into any organization — I am sure in 100 percent of them — and somewhere you will find a hard drive full of images about which no one knows. These are files with less-than-illuminating names such as 1.jpg, 2.jpg, and so on. Someone in the past was in a hurry and did not take the time to name the files properly or to tag them with keywords. Without tags, these images cannot be searched, making this collection a veritable black hole of dead images. If you cannot find them, you cannot use them.

Machine Learning to the Rescue
I do not blame people for skipping on metadata. Properly tagging metadata can be tedious without the right planning or tools. But it still has to be done. Without metadata or tags, our images, videos, and rich media can be lost, ending up as useless bits on a disk.

Now we can use machine-learning algorithms to help with the onerous task of adding metadata to images. Image-recognition algorithms are getting better all the time, and in a recent report, Microsoft reported an error rate slightly lower than that of humans for a large set of test images.

These reports have some people panicking that machines are taking over, but it is not like that at all. At an airport recently, I checked in on my phone, completed a security check at a computer, checked my bags by myself, badged in, and did not see anybody until I got to the plane. I did everything by machine. Machines take care of certain jobs so we can do more important ones. Far from being a job killer, we now can perform strategic and high-level tasks instead of standing there checking bags.

It is the same in marketing. In a future world, machine learning can aid the process, but it does not replace full metadata management by a skilled human librarian. Humans definitely have a place: some things that will stump a computer — such as identifying cars by year, make, and model — are still obvious to people.  BUT computers will not complain about having to add metadata, they will not try to avoid it, and they will work just as hard on the 100,000th image as on the first one.

Content Intelligence Can Add Value
If we run that hard drive of mystery images through a machine algorithm, they become discoverable. Marketers can find and use them again, eliminating the need to create or buy more. The images have really come back to life. This is instant return on investment.

Adobe is leveraging this technology. Smart Tags (Beta) was showcased as a sneak peek at last year’s Summit and will be released at this year’s Adobe Summit; this innovation leverages deep-learning technology to tag images automatically with useful metadata, allowing easy image discovery by marketers.

The technology can automatically tag images with keywords based on photo type (macro, portrait, etc.), popular activities (running, skying, hiking), certain emotions (smiling, crying), popular objects (car, road, people), animals, popular locations, primary colors, and more.

Adobe Experience Manager Assets User Interface

Smart Tags automatically tags images with useful keywords, allowing for easy image discovery by marketers.

Machines can help with images that are already in your digital asset-management system. These algorithms may add tags, not originally thought of, to previously tagged images to make them more discoverable, increasing their value across the organization.

Another area of value is Asset Insights: unique to Adobe Experience Manager, customers can now gain immediate insights into how specific assets are performing and use that information to optimize their investments in creative that drives marketing campaigns.

You can read more about data-science capabilities in our products here.

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From Barcelona to Las Vegas – Driving mobile analytics conversations across the globe

Marketing Cloud

We’re quickly approaching a time of unprecedented customer demand for brands to make the most of their mobile app experiences. Nearly two-thirds of Americans have smartphones and globally, and there are over 2.6 billion smart phone subscriptions. By 2020, there will be over 6 billion with another 3 billion subscriptions for devices like tablets and electronics in our cars, offices, and homes, let alone a gargantuan number for IoT based devices or “things” .

Gone are the days when a mobile app was little more than a static version of a company’s website oriented for a smartphone. Today’s users demand rich, personalized, contextually relevant, and real time app experiences or they will be happy to uninstall it and move on to another app of competing capabilities. Developing and successfully marketing – and more importantly monetizing – mobile apps today requires a holistic understanding of the underlying user analytics and companies are realizing that these insights should be an integral component of their overall data-driven digital marketing strategy.

This year’s Mobile World Congress (MWC) in Barcelona looked nothing like a few years ago when the exhibits were all about mobile phones and a few general app services. In addition to the connected cars, virtual reality demos, and countless Internet-of-Things (IoT) applications, I wasn;t surprised to see a continued trend for last 3-4 years – an exploding number of vendors showing off great solutions for specific areas of the app marketing lifecycle (Adobe likes to think of it as Build-Measure-Evolve-Test-Grow). Over the last several years of attending this truly world-class (and “world-scale”) event, I have seen a dramatic growth in the attendees and exhibitors at Hall 8 and 8.1 of the Fira Gran Via. It’s the Northern-most hall with a primary (if not sole) focus on mobile apps and related solutions

Adobe engaged in educating customers about how to think about mobile apps as part of a multi-channel strategy and how to deploy solutions that address all stages of the “customer journey.” Marketers need a deep understanding of end-to-end components of the customer journey through every touch-point.

Over time traditional digital marketers are realizing the power of analytics in providing visibility into their customers’ journey (to ultimately understand their experience), irrespective of which channel and device (or a combination thereof) they might be using to access (and transact with) their brand.

Adobe is bringing that energy from Barcelona to Las Vegas this week with Adobe Summit 2016 being held this year in Las Vegas, Nevada. One of the 2016 Summit’s nine tracks is devoted to comprehensive Mobile Engagement strategies, with over 30 presentations designed to help those involved with app development manage their digital transformation from one of fragmented parts to a unified foundation.

In addition, four of Summit 2016’s sessions in particular are designed to help marketers and other decision makers understand the pivotal role that mobile analytics plays for effective mobile app marketing and engagement. Moos of these sessions include some great customers and very relevant content for marketers at all levels and across all industries.

S411 – Mobile App Analytics: The key to a successful omni-channel strategy

Mobile might be central to the customer journey, but often it doesn’t get treated like it’s central to your organization’s strategy. In this session, you will dive into issues often overlooked by organizations scrambling to implement a mobile app strategy and see how Redbox is looking at this.

S412 – Bridging the gap between mobile app and web: Tools for the digital analyst

The secret to a happy union of mobile and analytics teams is a healthy understanding of each other’s needs around unifying data collection and access, while preserving individual charters. In this session, you will learn how to break down these walls to unify reporting and optimization strategies across your mobile app and web platforms.

S413 – Adobe is not only the mobile analytics leader, it’s also a client 

We think the Adobe Marketing Cloud provides a best-in-class solution for mobile insights and app engagement. In this session you will see how Adobe’s own Creative Cloud team harnesses these features to grow its business and how you can do the same.

S710 – National Australia Bank: Moving from mobile analytics to engagement

Measurement of mobile apps is a clear priority for companies that serve mobile-first customers.  However, how can you leverage data and insights to improve mobile engagement?  In this session, we learn what has worked for NAB (National Australia Bank) to advance their relationship with mobile customers.

We hope you will join us for some insightful discussions for organizations of all sizes, led by Adobe experts, partners, and leading brands, to provide you with insights about how to develop that “Mobile First” mindset today and to future-proof your efforts for tomorrow.

See you there!

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Adobe Summit: Know Before You Go

Marketing Cloud

We’re all excited for the biggest Adobe Summit yet. You’re going to have a great experience, and we have lots of resources to help you do just that.

Here’s a quick look into some interesting, behind the scene, facts about Adobe Summit that will get you excited for the week, and help you prepare your shortlist of everything you’ll need.

Venetian/Palazzo is the 2nd Largest Hotel in the World

The Venetian and The Palazzo together offer over 7,000 rooms on 53 floors, making their hotel offering the 2nd largest hotel in the world. Summit has grown so big, it’s only fitting that we take the event somewhere worthy of our 10,000 guests.

You’ll Measure your Walking in Miles Instead of Cubicles

Because this is our first year in Las Vegas, we don’t have any stats on the actual distance you should anticipate walking. However, you can rest assured that it will be farther than from the elevator to your desk.

With great space, comes the need for great walking shoes. You won’t be hiking Mount Fuji, but you’ll want stylish shoes that are comfortable to get you through an entire day. You’ll also want a water bottle to stay hydrated.

You’ll be in 75 Degree Weather or Warmer

If you’ve been to past Summit’s in Utah, you’re probably thinking snowcapped mountains and a chilly breeze. This year, however, Las Vegas has been above 75 degrees consistently for several weeks.

While the hotels are connected, and you can access all your sessions under one air-conditioned roof, there will be opportunities to peak your head outside to see the sun.

Adobe Bash will be OUTSIDE this year in the LINQ parking lot. With multiple entertainment options at Bash alone, we’ve taken the best of the Las Vegas entertainment genres and created the perfect evening. There is going to be live entertainment from a world-famous band, action sports with Motocross, fireworks, a DJ, tons of free food and drinks, and everything Vegas has to offer you in one spot. Summit Bash is going to be something you won’t want to miss.

So if you think the Las Vegas weather isn’t warm enough for you, or you get cold in well air-conditioned spaces, consider bringing a jacket. For the rest of you traveling from area’s still holding onto winter, consider dusting off some of your lighter summer clothing. Dress for Summit is Business Casual.

You’ll Hear from 3 Celebrities, and Many Noteworthy Speakers

From the main stage alone we’ve got a world-famous line-up. George Clooney, Donny Osmond and Abby Wambach will catch your attention for sure. While this might not be the time to get an autograph for your little girl, this is a perfect time to have some note-taking material ready.

For those of you who take notes on your phone or mobile device, you’ll have free Wi-Fi, accessible without a password. Just remember your phone is going to be working as hard as you are. Don’t get caught with a dead battery. Power stations and outlets often get claimed quickly. Consider packing an extra power source and an additional power cord to charge your devices when you can.

There will be 100s Prizes and Giveaways

Keep your phone close by your side to enter and win an iPad Pro, celebrity signatures, and much more. You’ll find surveys with prizes on the mobile app, after Summit sessions, as well as at Bash, the Community Pavilion and other areas around Summit.

Download the Summit app now, and get up-to-the-minute announcements, access and updates to your Summit session agenda, view conference maps, and connect with other attendees.

The Lost and Found Will Grow

Americans lose an average of $5,591 over a lifetime by forgetting things and then not checking the lost and found. For things like coat check, lost and found, support and general information on-site, visit the registration area at Summit.

It is Impossible To See Everything At Summit

Summit is so big, that it is nearly impossible to attend every session and hear every speaker. However, there are a few things you don’t want to miss:

Vertical industry mixer: It’s one thing to sit in a room learning alongside other people in analytics, but it’s a whole different experience to talk with other analytic specialists in your vertical. Don’t miss this opportunity to meet and network.
Wed 3:30-5:00pm at the Community Pavilion

Community Pavilion: This open area is not just our 106 sponsors, we’ve upgraded the experience to engage you in a connected world experience. Get your golf swing analyzed or take a seat at the sports bar, visit the community park or get a massage, experience some new tech or have an artist sketch your profile, and much more.
Tuesday: 11:30-5:30pm, 6:30-8:30pm
Wednesday: 12:30-5:30pm
Thursday: 10:30-3:00pm

Stay connected to the Adobe Summit experience by following the conversation with our Summit 2016 Social Media Channels:

Twitter | Facebook | LinkedIn | Adobe Conversations Blog

For more details on registration and more, please look for the Know Before You Go email in your inbox. See you at Summit!

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Quick Guide: Social Media Marketing Sessions at Summit

Marketing Cloud

We’re only days away from Adobe Summit! And for those of you working in social media we have several sessions for you to enjoy. These sessions will focus on measuring social success, and best practices for optimizing your social efforts.

Session 418: Measuring content performance in a multichannel world

You spend a lot of time and resources creating social content, but are you seeing the desired ROI? As social content marketing budgets continue to increase, so does the pressure to produce greater results. Marketers need to move beyond simply collecting large amounts of data and begin refining measurements to gather more actionable insights. With the proper tools and strategy, you can capture the right data at the right time to optimize content performance.

Session 203: Advertising on Facebook and Instagram with programmatic precision

As social networks converge with mobile and are set to take 20% of U.S. digital ad spend by 2017, understanding the customer journey across devices and channels is more important than ever. Facebook is transforming the digital advertising ecosystem, enabling marketers to innovate and prove business value.

Session 825: Centralized content workflows: Breaking down the walls around social content

Consumers interact with your brand on many different channels, and they expect a consistent, engaging experience. However, this expectation is difficult for brands to deliver on when internal marketing teams are siloed and unable to collaborate across channels. Forward-thinking companies are making an organizational shift toward convergence, with a focus on building efficient workflows for creating, delivering, measuring and optimizing their cross-channel content.

Consider this your quick guide to all things social at Adobe Summit. See you soon in Vegas!

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5 Steps to Analyst Success

Marketing Cloud

All around us we are surrounded by information and data. In fact there is so much information bombarding us each day that there is even information about recovering from information overload. With terms like Big Data, Data Scientist, Machine Learning, and others dominating every corporate conversation its not hard to see that sometimes there might be slip ups in analysis or understanding of this information. This can cause issues like what we have seen with recent interpretation of Uber data

As a current social research lead at Adobe and a former Godfather of the Adobe Digital Index team that produced thought leadership for outlets like Wall Street Journal, CNBC, New York Times, and Forbes I decided I would put together a short list of ways to ensure the best insights are created from the mountains of data that we now have access to.

  1. Have an intimate knowledge of the data you analyze – when I first started analyzing Adobe marketing cloud data, I attended every training possible about the products that were producing the data. I talked with engineers, sales people, even customers to understand better how they used the products and implemented them. This knowledge helped me to know what data was available to analyze, how to identify if data was not correct or needed cleaning, and most importantly create a working relationship with the guardians of the internal data.
  2. Learn statistics – You don’t need to be able to create complex models, write code, use R, or be able to predict the next economic down fall to be a great analyst. A basis understanding of means, averages, outliers, histograms, standard deviations, and other statistical terms will go a long way in helping you to create a true trend free of outliers from a large data set. You can go the formal route through online degree like a masters in stats from my alma matter Utah or through free routes on Coursera
  3. Be curious – Adobe has an unmatched data set with the marketing cloud, so I have a great playground to learn about trends across all industries. However, I was only able to succeed in analysis because of my curiosity for knowledge through data. Over the last 4 years among other things I have predicted movie success with social buzz, analyzed Brazilian sentiment around the World Cup, shown that broadcasters still rule the content game in social, found what were the hot knew items in IoT, and which Super Bowl ad was the best based on six points of social data. These ideas were all cultivated by my curiosity for proving points with data.
  4. Always question results – Even after cleaning, averaging, and removing outliers you should still always question your results. Make sure it passes the sniff test and compare to other historical results if available. Also, if possible, ask colleagues to do a peer review of your work to ensure that you feel confident and comfortable with what you share internally or externally
  5. Find your passion – Social data is my passion and it took me about 2 years to figure that out. I was able to analyze other data just fine, but social really got me excited. Everyone will be different and it can take time to find what you truly enjoy. Once you find that passion follow it and examine it as much as you can. You will find that when you are working on something you have passion for that it will be the most natural path to success in being an analyst.

This list is by no means comprehensive, but can at least provide a glimpse into ways to produce meaningful insights from data. Curiosity and passion are the too that really can’t be taught. You will have to look inside yourself to get an understanding of what truly drives you to finding results in data.

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Introducing the Adobe Digital Economy Project: Harnessing Big Data to Reveal New Economic Trends


Marketing Cloud

Our team is pleased to announce the launch of a new initiative, the Adobe Digital Economy Project. The project’s core goal is to add insight to current economic discussions based on dynamic, responsive data about the digital economy. The Adobe Digital Index, a group of data scientists and researchers within Adobe, publishes research on digital marketing and the economic landscape based on anonymous data aggregated from thousands of websites worldwide. With this latest project, we are focused on shedding light on an increasingly large driver of the economy—online spending.

Exploring the Digital Economy Project

The Digital Economy Project has three key components:

  • Digital Price Index (DPI): The Digital Price Index looks at inflation through the lens of digital commerce. It is based on massive aggregate and anonymized data sourced through the Adobe Marketing Cloud. Our first iteration, comprised of electronics and grocery products, includes data from 8 billion website visits and 1.4 million products sold online between January 2014 and January 2016. The methodology, discussed in more depth below, implements the gold standard of price indices: the Fisher Ideal Price Index. This implementation is made possible due to the unique capability of Adobe Marketing Cloud to amass huge amounts of data where the quantity of products sold is available, in addition to sale price.
  • Digital Housing Index (DHI): The Digital Housing Index looks at trends in the housing market based on online behaviors. The initial DHI is based on an analysis of aggregated data from 2 billion visits to U.S. housing search websites between December 2014 and December 2015.
  • Job Seeking Index (JSI): The Job Seeking Index enhances insights into national employment data, based on digital job search behaviors. The initial JSI is based on analysis of data aggregated by Adobe Marketing Cloud from 1 billion visits to U.S. employment-search websites and top employer career pages from December 2014 through December 2016. The JSI is a significant index given the fact that Adobe Marketing Cloud currently powers 20 of the top 30 U.S. employers.

The data set for each index is updated daily and is based on transactions processed, and behavior measured, through the Adobe Marketing Cloud. Future findings, as well as additional product categories, will be released regularly. All data remains fully anonymous and confidential and is analyzed only in aggregate.

Ensuring Methodological Integrity

Quantifying the digital economy is challenging and Adobe recognizes an opportunity to add another perspective to the existing conversations on inflation and the economy. Consequently, ensuring the methodological integrity of our data was an overarching objective. We worked with two of the leading economists in the United States to create the indices. Our goals in collaborating with them were to take into consideration as many factors as possible, to ensure methodological soundness and to provide a deeper level of insight into digital transactions than is currently publicly available.

The experts we worked with are Dr. Austan Goolsbee and Dr. Pete Klenow, who recognize the potential found in the vast dataset Adobe possesses. Dr. Goolsbee is the Robert P. Gwinn Professor of Economics at The University of Chicago’s Booth School of Business. He served as President Obama’s Chairman of the Council of Economic Advisers. Dr. Klenow is a Professor in the Department of Economics at Stanford University. He has served as both a Senior Economist and Visiting Scholar at the Federal Reserve Bank and he is a member of the editorial boards of publications such as Econometrica, American Economic Review and the Quarterly Review of Economics.

A Closer Look at the Digital Price Index

Let’s explore how the Adobe Digital Economy Project will be valuable by taking a closer look at the Digital Price Index. Currently, the most frequently cited source of economic data on inflation is the U. S. Bureau of Labor Statistics Consumer Price Index (CPI), which is the standard for measuring inflation. The CPI methodology is based on a finite data set comprised of approximately 83,000 products. The list of products—and their respective weights within the CPI—is obtained through consumer surveys administered every four years for each product category. Then, each month, Bureau of Labor Statistics research assistants visit retail outlets to manually record the current prices for those products, which is generally a handful of products in each outlet.

When the Adobe Digital Economy Project team set out to develop the Digital Price Index, our goal was to leverage, in-depth, Big Data on both product categories and quantities sold through online channels, as tracked through the Adobe Marketing Cloud. The Fisher Ideal Price Index is considered the gold standard for calculating inflation. Nonetheless, the index has been largely aspirational as it requires measurement of the quantity sold of each product in every time period, instead of through surveys administered once every four years. This data has been difficult to capture consistently—and at the immense scale needed—in an efficient, affordable way. Now, with the accuracy and massive data-gathering capabilities of Adobe Marketing Cloud, we are able to aggregate that data efficiently and accurately. Today, we track 1.2 million products across categories like electronics and groceries. Due to the dynamic nature and direct measurement of this data we are able to accurately and speedily identify pricing trends, inflation and more.

The Digital Price Index also allows us to responsively track rapidly shifting consumer preferences. In the category of electronics, for example, we estimate that 80% of online spending goes toward products that have been in existence for less than 12 months. Even in the category of groceries, 16% of monthly online spend goes to products that have been on virtual shelves for less than a year. In other words, the capability of DPI to do daily data collection and updates enables us to track changes closer to the timeframe in which they are happening. These insights can help drive business and public policy decisions.

The DPI Index can also demonstrate how prices shift during specific time periods. Consider trend data from the category of computers. Between January 2015 and January 2016 the Adobe DPI shows cumulative deflation of 13.07%. Yet, for the same period, the CPI has reported cumulative deflation of 7.09%. In a closer look at month-over-month price changes in the November and December timeframes each year, the DPI is able to show price decreases informed by Black Friday, Cyber Monday and other holiday-related promotions. As seen in the graph below, the DPI highlights trends that, previously, went undetected: A trend toward deeper holiday season discounts, year-over-year, is reflected. With its dynamic data, Adobe can pinpoint discreet, seasonal price fluctuations to better identify both macro and micro trends.

ADI

There are caveats to note about the Adobe Digital Economy Project: It is intended as an addition to existing economic data sources, not a replacement. And while the Project’s indices incorporate billions of data points, that information represents only one very specific slice of the economy: digital transactions. In specific categories, such as groceries, digital transactions represent a very small but rapidly growing segment of the market. The customers who purchase these products online tend to skew affluent and urban so they cannot be taken to represent a median demographic. However, in the proper context, our aim is that the Digital Economy Project bring additional insights about the online economy to the collective knowledge base.

Moving forward, the Adobe Digital Index team will periodically release findings from the Project. We also anticipate expanding the indices further by, for example, developing additional categories for the DPI.

To stay updated on the latest developments, please check back at the Adobe Blogs and follow us on Twitter.

Luiz Maykot, Tyler White, Data Scientists, Adobe Digital Index

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Beyond Attribution: Insights into the Customer Journey

Marketing Cloud

Before the Internet, it was impossible for brands to understand what the customer’s journey to conversion entailed. We could not follow people around and observe what billboards they viewed, which people they talked to, or how they used the Yellow Pages to find service providers. In fact, if we had tried to accomplish that type of research, we would likely have been viewed as crazy and thrown in jail.

Now that the technology has made reams of data about our customers’ behaviors commonplace, brands are hyper-focused on analyzing customer journeys to understand how they can optimize their ad spend to increase the bottom line. They are collecting data on everything from call centers to email to social to offline sales.

These brands are spending tons and tons of time and money trying to track marketing attribution. While attribution still cannot incorporate all of this customer data, we are getting there. At least now you will only be viewed as kind of crazy for trying to take action on it. And although there is plenty of actionable information that comes from developing an attribution model that is right for you, it is important for you to look beyond basic marketing-attribution reporting to truly understand what your customer’s journey looks like.

Understanding the Customer Journey

Since we, as marketers, now receive an unbelievable amount of data, it can give us great insight into what the customer’s journey looks like. In the past, this was something that required a data scientist (or ten) to even try to accomplish — and that did not usually work out too well. However, now we have the ability to give a unified view of the customer and push that into the everyday workflows of marketers and analysts. This ability to democratize data allows users who do not have a statistics background to gain a better understanding of how customers interact with their brands.

It can also be important to have digital analysts who act as data storytellers. They play an important role in translating data about the customer journey in a way that is actionable for marketers. This role is so important because it helps people at every level of the organization to understand that there is more to using data than determining whether you have met key performance indicators (KPIs). Data can instead help us to understand how — and why — our customers are interacting with our brands in certain ways.

Go Beyond Reporting

Instead of seeing attribution-modeling results from a static report that might tell you to invest more in a specific display campaign, dig deeper to try to uncover the reasons why this display campaign might be more impactful. Overlay different audience segments to see if this holds true — or your higher-value customers versus your newer customers. Analyze deeper to see the different paths that a customer took to convert (or not convert). Understand the drivers and characteristics of these results to create brand new audience segments.

By using the advanced attribution features of Adobe Analytics, users can go beyond static reporting to start driving more customer-journey analyses. Attribution is a great tool to make your marketing more effective, but it is also only the beginning. Since higher sales and lower churn are things all brands hope for, it is high time that all brands start understanding what their customers’ journeys truly look like and what it is their customers truly value.

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Defining Machine Learning, Predictive Analytics, and Data Science — Without the Mumbo Jumbo

Marketing Cloud

If you walk into any conference room in the world, it is likely you will hear people talking about “opening the kimono” in a “play for transparency” so they can “dig deep into Big Data.” You may walk away thinking that what you just heard did not make any sense. Honestly, it is entirely possible that what you heard did not actually make any sense. Often, people oversimplify things, use too many buzzwords, or simply do not understand the material well enough to explain it without using a whole lot of mumbo jumbo. That is why we want to level set and explain the difference between data science, machine learning, and predictive analytics in terms that anyone can understand.

Data Science

Let us start at the beginning with data science. Data science is the broad umbrella under which all other types of analysis fit. Data cleansing, manipulation, and the selection of the type of analysis that needs to be done are all key pieces of the data-science foundation. Without these foundational items being accomplished, your data analysis will never truly be accurate.

Communication and domain knowledge are crucial traits found in data scientists. Data scientists need to understand how the underlying data is created, the business objectives and goals, the applications of the data and the predictions, and how to interpret the data through data storytelling and engaging visualizations. This is why it is important to not just hire a data scientist but to hire the data scientist that is right for your brand.

Predictive Analytics

At its core, predictive analytics uses statistics to either estimate what behavior a customer is likely to exhibit or to forecast future outcomes of the business. You may hear people say that predictive analytics are always probabilistic in nature, because they tell us what the probability is of something happening. Predictive analytics help us to understand what is likely to happen in the future based on what has happened in the past. While this may seem like some type of new-age voodoo, predictive analytics have been used for years. For instance, your credit score is calculated using predictive analytics. Based on a predetermined predictive analytics model that includes data about how you have behaved in the past, your credit score predicts how creditworthy you are likely to be in the future.

Machine Learning

When you are dealing with analytics that have to process truly Big Data — like terabytes or petabytes of data — it is unreasonable to expect a human or an unparalleled, unscaled technology to do it. Not even if you have the best data scientist in all the land. This is where it makes sense to bring in machines to help process and analyze mass quantities of data.

From there, these tools can also address the “learning” piece of machine learning. Once you can see what you think is going to happen, and you begin to receive feedback on what actually did happen, your model can update and become even better at predicting which customers might take which actions. This means that predictive analytics — when dynamic — drive machine learning so that your model is constantly becoming more and more accurate.

These analytics tools are used every day in ways that can help your brand better understand and connect with your target audience. To do that, though, it is important for everyone in the room to understand exactly what you are talking about when you discuss various analysis techniques. Having everyone on the same page can save tons of time, money, and headaches.

If you are interested in bringing your team up to speed on various analytics tools, you can learn more about machine learning, correcting predictive-analytics mistakes, and more on my blog.

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Do Not Let Your Mobile App End up in the Wasteland: 10 Best Practices

Marketing Cloud

We are all guilty of it: as soon as we have a free moment to ourselves, we pull out our phones to check in. Even parents of young children are pulling out their phones when faced with tantrums. There is something so helpful about having entertainment at the tips of our fingers. But with this ease of access comes competition. There is always a new app to try, a new game to play, a new video to watch. How are average consumers to choose which apps they use most often?

In this day and age, mobile apps are considered part of most brand experiences. However, having an app is not an end in itself. If your app does not reflect your brand or have a purpose, users can download it, become unimpressed, and never use the app again.

So, when you are crafting your mobile-app strategy, it is important to understand how you can get your users to not only download the app, but also come back to it again and again. Users who are regularly engaged are much more likely to take the next step in the conversion process, become brand advocates, and engage with your brand in other mediums. So, how do you get people to engage regularly with your mobile app? Here are ten things you can do to make your mobile app more engaging:

  1. Have a Purpose — If your app is created off the cuff, it is entirely possible that there is no real reason for users to engage. As a result, the first rule of engagement is to make sure that you give consumers a reason to engage. It seems simple enough, but many apps fail to serve a purpose in their users’ lives.
  2. Understand Analytics — It is so crucial to understand how your app is performing. Analytics can help drive your optimization and targeting strategies as well as encourage users to reengage.
  3. Conversion Plan — There are many ways that apps can convince users to convert. Whatever the goal — whether to encourage social sharing, drive actual purchases, or teach users to use your product in a new way — there are many ways to measure conversion on a mobile app. Understanding what your conversion goals are is the foundation for creating a conversion plan that helps users engage regularly with your app.
  4. Test Regularly — Once your app has been built, you can begin testing versions to see which improvements make it easier for users to engage and encourage them to come back regularly and remain in-app longer. Just because the app has been built does not mean that has to be the last version of your app; mobile apps can constantly be iterated to make the app as engaging as possible.
  5. Deep Linking — Whatever users click on in your app should take them to the same product, service, blog post, or information in your browser. Users should never feel as though they have been taken “out” of the path that they were on. Instead, give them a consistent brand experience across platforms and channels to increase the ease of use to the point that users come back regularly because your user experience is so much better than that of your competitors.
  6. Push Notifications — If you do not have a push-notification strategy, it can be incredibly beneficial to develop one. Many brands are pushing weekly newsletters but are not also trying to bring users back to their app by using weekly push notifications with the same goals in mind. If you have an existing strategy, it is worthwhile to test and optimize it. Without testing whether your push notification is relevant to your audience, there is no guarantee that you will be able to use notifications to draw your users back to your app consistently.
  7. Targeted Advertising — If your advertising options do not match your target audience, it can be a turn off to your end users. In fact, if they are wildly inappropriate, users may decide not to come back at all.
  8. Gamification — If you have ever thought, “I just need to beat one more level of this game,” then you are familiar with gamification. Making something fun, giving users a goal to beat, can encourage them to regularly return to your app. Candy Crush is an excellent example of this, but it also extends to games like Farmville and beyond. Some loyalty programs implement gamification strategies; if you start looking, you will notice gamification everywhere. This is an excellent strategy for getting users to engage regularly with your mobile app.
  9. Social-Sharing Convenience — Being able to share updates on social media is a great feature for any app. But more than just being able to share updates, it needs to be simple to share updates as well. If it is difficult, it is unlikely users will engage. In a world where time becomes more and more precious, customers will not likely go over the top to try sharing your message for you.
  10. Use Offers — If you want people to return to your app, it can be worthwhile to develop loyalty programs or use offers to entice users to reengage. This needs to be a strategy that is well thought out, as offers that are incorrectly targeted will not just leave a bad taste in users’ mouths, they can prevent users from opening the app again in the future.

We see many brands with teams that do not really own mobile. Someone is tasked with developing an app, he or she creates an app without really planning a true mobile-app strategy, and then the app sits unused by anyone for months or years. Instead, if you develop your mobile app with a strong engagement strategy from the get-go, you can encourage the type of engagement that will lead to increased conversion rates down the line.

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