7 ways to personalize TV


Marketing Cloud

When TV viewers go to their favorite screen to watch a TV show, they want something good right there in front of them. They want personalized TV.

In our guide, Television Gets Personal, we share proof that consumers want personalized TV and cover several ways that media companies can successfully deliver it, helping you envision a TV experience that’s intuitive, intelligent, and interactive.

Of course, personalized TV wouldn’t be possible without data and technology. Media companies need data to understand viewers’ taste preferences. And, they need technology to infuse those preferences into an experience that delights the viewer.

If you’re a broadcaster, cable network or operator looking to infuse more personalization features into your TV service, the following seven ways are a good place to start.

1. User data – Get the most accurate and complete data on your users by keeping information such as their name, age, gender, location, and previously shared preferences in a customer database. The more accurate and complete this data is, the better it can inform your segmentation. Then, you can anonymize the data and use it for segmentation with a data management platform such as Adobe Audience Manager.

2. Session context – With each viewing session, you can capture more data, which will lead to better personalization. Capture the browser type, device type, IP address, and time zone. This data can feed into a personalization algorithm that can recommend different content to the same user based on whether he or she is on a mobile device or a PC. Or, based on whether he or she is watching in the morning or watching at night.

3. Third-party data – Data from external providers can be used to further understand your users or your content. For example, you can purchase data about the products your audience buys or the types of websites that they visit. You’ll also want to purchase content metadata so that you can make personalization decisions based on the genres, subgenres, cast, awards, year of release, and user ratings of shows that your users have watched.

4. Segmentation – You can use segmentation to orchestrate different types of personalization experiences for different segments of users. Segments can be generated based on behavioral attributes about your audience such as how frequently they visit your service or what type of content they most frequently watch. Segments can also be generated based on contextual attributes you know about your visitors such as device, time of day they most frequently visit, or geo location. To drive the most engagement from your audience, you can drop each viewer into an experience that’s proven to work with other people in their segment.

5. A/B testing – A/B testing lets you test your hypotheses about how your data can be used to improve personalization. For example, you may have a hunch that viewers who browse sporting websites are more likely to respond to recommended sports content. You can test this hunch by exposing a control audience to your existing personalization algorithm, which doesn’t consider sports browsing data. At the same time, you expose a test audience to a new personalization algorithm, which does consider sports browsing data. If the test audience outperforms the control audience on one or more metrics that you care about, such as viewing time, then the new algorithm is a success.

6. Algorithms – Algorithms make up the decision engine for personalization features. Once an algorithm has been programmed to know what data to consider and how to consider it, then it can make personalization decisions on the fly for every viewer of a personalized TV service. You don’t have to be able to develop algorithms in order to personalize a TV service. Solutions like Adobe Primetime recommendations include built-in algorithms that you can use.

7. Automated optimization – Optimization technology makes personalized TV smarter over time. For example, Primetime recommendations automatically conducts A/B testing to continuously improve the decisions that it makes regarding video recommendations and visual layouts.

These seven data sources and technology capabilities put personalization within reach of any TV service. In fact, many media companies already have the data they need to do personalization well. Others can get the data they need.

If you’re embarking on implementing more personalized TV services into your brand, we’d love to hear from you.

The post 7 ways to personalize TV appeared first on Digital Marketing Blog by Adobe.

Remember This: B2B Customers Are Consumers, Too


Marketing Cloud

Deliver the Digital Experiences They Expect or Kiss’em Good-bye

Manufacturers in today’s global marketplace need to embrace digital solutions in order to optimize the online experiences they deliver to their customers. Maxim Integrated, a semiconductor manufacturer, realized that their website was failing to deliver to prospective B2B customers, who were logging onto, and quickly bouncing away from the company’s legacy website because they could not easily find what they needed. Chances are, the elusive B2B buyer — who orders lunch on Foodler, books a plane ticket on Expedia over lunch, and catches an Uber ride back to the office — will move on to a competitor who makes the online experience easier.

The analog days of cold calling and pre-sales schmoozing are long gone. Digital technology is facilitating a new matchmaking paradigm. Today, buyers will find you — if you’ve got the digital infrastructure in place to be discovered. Once prospects enter your online ecosystem, they begin to build a relationship with your brand. In the digital world, making that connection requires you to align your content with what a buyer needs, from the first moment they make contact with your company.

B2B customers are consumers too, with an added twist — they need to produce and deliver results for their companies as fast as possible. No one can afford to wait. Maxim Integrated learned that manufacturers can better serve their customers by creating a user-friendly digital experience that delivers spot-on information at exactly the right moment.

Why are digital experiences so important?

The future of manufacturing is digital. Some experts call this movement Industry 4.0, while others refer to it as the emergence of an experience business transition, in which a companies invest in technology capable of connecting content and data with behavioral, engagement, and predictive analytics.

Becoming an experience business is about more than increased efficiency. It’s about competitiveness in today’s marketplace. Success in marketing, sales, and support depends on how well you engage with your customers. Your message has to resonate in a business environment filled with an ever-changing choice of products and technologies. Customer experience is one of the most important ways in which companies can both differentiate themselves and close sales deals.

Customer experiences matter, and B2B customers are simply consumers playing a different role in a different context. In fact, according to a recent survey, 80 percent of B2B companies say that their customer’s expectations are higher because of what they experience as consumers. This means that manufacturers need to prioritize customer engagement during the B2B sales processes, across multiple distribution channels, and on whatever device the buyer prefers to use. The bottom line is that competing in the digital economy requires delivering information to prospects and customers when and where they want it.

How one company went digital

It used to be agonizing to scour Maxim Integrated’s website for information and specs on their products, which number more than 9,000. Search was slow, and instead of focusing on better content delivery solutions, Maxim Integrated’s IT department spent inordinate amounts of time fixing problems on an outdated system that could not scale or connect easily with other software systems. The process was time-consuming and ineffective.

The semiconductor manufacturer solved the problem by leveraging a digital foundation that combined digital asset management (DAM), customer relationship management (CRM), and enterprise resource planning (ERP) into one system. Says Robert Reneau, the company’s director of digital marketing, “Now we can transform the online experiences we offer our customers and partners, and deliver content faster.”

That’s the name of the game these days — respond at the speed of light, and deliver a consistently good user experience. “Our previous approach typically involved costly and difficult-to-maintain workflows,” says Reneau. “But now, we are integrating responsive design into our processes to publish content once and deliver it across any device. We have created a digital communications platform that makes our customer’s navigational experience simple and easy.”

The past is prologue

Evolution is not always easy. For some manufacturers, moving from legacy systems to a completely digital model requires letting go of processes that are deeply ingrained in the company’s operating ethos. However, companies like Maxim Integrated understand that legacy systems just don’t have the technological horsepower to drive content velocity, or to connect with prospects and customers in real time.

If your company is still relying on technology that represents the way you’ve “always done it,” it’s time to rethink your strategy. Legacy CRM solutions, for instance, lack the ability to process and deliver personalized digital assets on demand. To move forward, you need to understand your options. In order to build a digital foundation, it’s important to know what solutions are available, how to apply them, and how to integrate them with your existing IT infrastructure.

Moreover, you need a digital platform that can be customized. Something that works for one customer might not work for another. Delivering the right content at the right time requires an understanding of how your customers identify, research, select, and purchase products. You also need state-of-the-art analytics tools that will facilitate tracking user activity, modeling how purchasing decisions are made, and predicting what users are looking for at various crossroads on your website.

Implementing a digital solution

The first step a manufacturer needs to take in moving toward a fully digital content management platform is to develop an understanding of how technology can deliver better customer experiences, lower costs, and, ultimately, boost the bottom line. Maxim recognized the advantages of combining its DAM, CRM, and ERP systems to form one, well-oiled machine. So they implemented a fully extensible digital platform, and customized it to meet their specific needs. Here are five steps that any company can use as a starting point for developing and implementing a digital content platform:

1. Create a cross-functional team. Great results depend on multiple parts of the company — including marketing, sales, operations, IT, support, customer service, and legal — working together to develop a strategic plan.

2. Focus on understanding your customer’s journey and experience. Obtain a clear idea about what customers want from your company, and how to deliver the online experiences they expect. Mining website analytics and focus groups with customers can help sharpen your team’s focus.

3. Establish benchmarks for results. Don’t try to achieve everything at once. Develop a strategic plan for building and implementing a digital foundation that can be tested and tweaked as you move forward. This will require an accurate understanding of the capabilities of your DAM, CRM, and ERP systems. As the system is rolled-out, monitor user engagement and results closely in order to determine how best to optimize the platform to meet both company goals and customer expectations.

4. Leverage an existing framework. For most manufacturing companies, customizing a digital framework is a more cost-effective approach than trying to re-invent the wheel. Your platform should be unified, easy to use, and capable of integrating with other systems. It is essential that you start with a scalable platform that can integrate easily with your company’s core tools, workflows, and data sets. Finally, consider security, as well as a cloud-based infrastructure that provides complete redundancy to prevent any downtime.

5. Consider your ROI. Return on investment matters, so crunch the numbers and consider how the new system will reduce costs while increasing sales.

For manufacturing companies that are serious about a digital transformation, moving to a platform that facilitates faster content delivery on virtually any device is usually an easy decision. The combination of cost savings and improved customer engagement means higher conversions and a clear path toward increased sales.

Transform your manufacturing business with digital experiences, and read about more best practices for managing digital experiences or read more in our #manufacturing series.

The post Remember This: B2B Customers Are Consumers, Too appeared first on Digital Marketing Blog by Adobe.

Experience Chains: Linking Great Experiences Across Companies

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Imagine flying into San Francisco International and having a driver ready to pick you up and deliver you directly to your hotel. There, the concierge greets you and hands you the key card to your room. Or better yet, an app on your phone directs you to your room and unlocks your hotel door. And, all of these actions are enacted without your initiation. You may think this is an experience for the elite, but this “experience chain” — where multiple brands collaborate to provide a singular experience — is getting closer to reality for all of us.

From a customer’s perspective, a travel excursion like the one mentioned above is a single experience. But in today’s on-demand economy, a single business can’t deliver such an end-to end experience for a consumer outside of its core business.

How do brands work together to deliver a unified and seamless experience rather than multiple, possibly disjointed, but hopefully related, experiences?

As I go from place to place or site to site or app to app on my phone, once I leave the context of the brand I was interacting with, I’m basically breaking whatever experience I was having and starting a new one. That’s where an “experience chain” is needed. The idea is that two or more related businesses (an airline, ground transportation, and hotel, as in the example above) work together to create a seamless experience for their joint customers, which in turn helps all three companies succeed.

For airlines, on-demand cars, and hotels to collaborate on an experience chain, they need to find a way to share information that allows them to deliver an exceptional experience throughout their customer’s entire trip. Instead of ordering a car when you get off your plane and then finding out the closest driver is 10 minutes away, imagine that as soon as the plane is at the gate, the airline shares that information with a car service, so that by the time you walk out to the curb, your car is pulling in to greet you. The hotel and car service also exchange information about where your hotel booking is (so the car knows where to take you) and when you will arrive (so your room is ready for you).

How is this possible? It takes sharing the right data at the right time — and having entire organizations from multiple businesses eager to help.

Get C-Level Support for Information Sharing
As companies commit to true collaboration, there are so many exciting ideas that can come to fruition, including experiences that go beyond what a single brand can deliver. But it will take the willingness and capability of one business (like American Airlines) to share their data with another (like Uber and then Marriott) so that the customer’s positive, even delightful experience can continue seamlessly from one brand to the next.

Sharing data, first throughout a single organization — whether from calendars, social media, purchases, or surveys — requires buy-in that starts at the top and then moves down into the other layers. Perhaps the product design team is getting negative feedback on why money transfers take five days, so they need to share information and data back and forth with the financial team to brainstorm creative ways to change the process and facilitate better user experiences. Or, the legal department needs information on how to keep the customer in mind when developing their terms of service to ensure they don’t stand in the way of a positive customer experience. This collaborative focus on the customer throughout an organization is key for making an experience business work.

The next major step to develop experience chains is to have C-level executives buy into the sharing of data among partnering companies. Data security is always of utmost concern, but experience businesses need to be willing to trust their partners. They should implement and insist upon rigorous controls, as well as develop ethics and standards that protect the type of information needed to keep experience chains going.

We already have dozens of customers subscribed to data “co-ops,” designed to help them create better analytics and experiences for their own businesses. These companies already have the mentality and CEO support to share data that will help them deliver better experiences.

Use AI, But Don’t Neglect the Human Touch Just Yet
Technology also plays a valuable role in creating experience chains. Today, artificial intelligence is used to look at a customer’s history and then provide current options based on what he/she is likely to need or do. Where we expect it to become extremely valuable is in predicting what consumers want and delivering it without them having to ask. This kind of preemptive decision making is the golden ticket we’re all working toward — and we’re getting closer every day.

For example, smart home technologies such as Amazon Alexa and Google Home are listening to us and learning about our preferences at different times of day and are starting to make decisions for us (kind of creepy, I know). If my smart refrigerator orders fruit and I leave an apple in the fruit bin too long, then it will decide to order fewer apples the next time. Or if my home assistant recognized from my schedule that I had been in back-to-back meetings all day, it could know to play relaxing music when I arrive home.

You might recall the Tesla-Dunkin’ Donuts-Visa experience chain we shared at the Adobe Summit last year — your Tesla gets a text about a nearby Dunkin’ Donuts, automatically orders a coffee for you, and it’s ready and paid for through your Visa account when you arrive, so you just grab it and go. As long as experience businesses commit to true collaboration, AI can help create many similar and fulfilling experiences.

This being said, I don’t believe we should automate everything just yet. We aren’t to the point yet where AI can make the right decisions that take into account my emotional state or my history as a consumer of any particular product. Additionally, the human touch is still needed, in most cases, to turn a potentially negative experience into a positive one. Interacting with an automated machine doesn’t often make me feel better about a product or service. That only happens when I get a human on the phone and can feel my problem being solved.

Experience businesses that are eager to operate in an experience economy will succeed as they help each other through experience chains. Learning how to structure your organization — as well as work with other brands and even competitors — will help deliver fluid, compelling, and personalized experiences that create an emotional connection between the customer and the brand, resulting in long-lasting loyalty. It’s a win-win-win for all.

Read more ideas about the future of experience business from our #AdobeTT participants.

The post Experience Chains: Linking Great Experiences Across Companies appeared first on Digital Marketing Blog by Adobe.

Retailers: Adopt Artificial Intelligence Now for Personalized and Relevant Experiences


Marketing Cloud

When something changes in the customer landscape, Walmart knows. And they know just how to react.

“Walmart has a massive inventory with millions of products,” says John Bates, senior product manager for data science and predictive marketing solutions at Adobe. “And they adjust that inventory to better align with certain types of products, depending on what’s happening in real time.”

For example, if a hurricane is in the weather forecast, Walmart will shift its inventory to have the things they know from past experience their customers will want to buy — extra grocery staples, bottled water, sandbags, wet/dry vacuums, chainsaws, and generators. Simultaneously, merchandise that is less likely to sell in this weather — again, according to Walmart’s data — is taken off the shelves.

“This strategy provides sufficient inventory for the most-needed items on any given day and minimizes the shelf time of all products — satisfying both customer and retailer needs,” says John.

Ensuring a relevant experience for customers, whether they’re heading to a store or shopping online, is achieved by leveraging the power of artificial intelligence (AI), including machine learning and predictive analytics, to deliver personalized experiences at scale.

AI Helps Deliver What Customers Want
Not surprisingly, retail and ecommerce have always been central to the personalization and optimization conversation. From Amazon’s recommendations — which drive 30 percent of its revenue — to targeted email outreach and push alerts promoting complementary products, the most optimization-focused retailers have always pushed the experience envelope, fueling people’s desire for more relevance at all touchpoints.

Delivering relevance on those touchpoints, though, is where some retailers start to lose their footing. “Taking that next step is a big leap,” says Kevin Lindsay, director of product marketing for Adobe Target. “It’s a leap of faith in terms of how much you can bite off. How much is actually doable today and what benefits can you get from incorporating AI into developing these tactics today?”

But delivering personalized experiences at every touchpoint isn’t something customers just want, it’s what they expect. More than half of consumers want a “totally personalized experience,” and three in five are happy to have interests and behaviors shared if it means a more personalized journey with a retailer. However, 42 percent of retailers say they know too little to effectively engage key segments.

Even a Little AI Can Help Deliver the Right Experience
Working with AI, predictive analytics, and machine learning perhaps seems out of reach for many retailers, however, as Kevin mentioned, it’s not an all-or-none proposition. Retailers that take a phased approach to implementing and applying the insights they gain from AI are the ones that are already benefiting. Think about how you can start applying AI to help you in each of these areas.

Invest in the right technology stack. Because many retailers haven’t made the leap of faith to invest in the right technology stack that delivers relevance at scale, the experiences they deliver are more likely to miss the customer experience mark. From ecommerce experiences to connected store associates to post-sales communications, without the machine anticipating next steps by acting on predictive analytics, retailers can’t effectively and efficiently map out the customer journey — and, naturally, can’t act on those critical cues and moments in time. Start by taking inventory of the data your organization has access to and how it is integrated for a complete view of your customers.

Surface customer needs. Retailers also aren’t able to leverage key data points and real-time actions to deliver relevance beyond what’s right in front of them. “There are plenty of other applications that come along with machine learning,” John adds. “ Discoverability of content in search is a good example. By leveraging machine learning and predictive analytics, brands can look beyond what customers are searching for and start connecting the dots on what they likely want — it’s cross-selling at scale, matching customers to specific products or content that will nudge them towards more conversions and greater lifetime values.”

ASOS.com, a British online fashion and beauty store, uses AI to uncover and solve issues specific to online retailers — helping customers find the right size and minimizing returns. By analyzing which items customers keep, in which sizes, versus the items and sizes that get returned most often, ASOS is able to use machine learning to recommend appropriate sizes for individual customers regardless of the brand or fit of specific items of clothing. As a result, returns of ill-fitting clothing are minimized, the customer experience is improved, and ASOS reduces its costs.

Produce relevant cross-channel interactions. When machine learning and predictive analysis do take the wheel, cross-channel customer interactions become increasingly relevant to customers on an individual level. And that surprises and delights those consumers at every turn, and all but ensures they keep coming back for more. Says John, “The impact is very straightforward. Machine learning and predictive analytics increase the likelihood a customer will convert — or, even decreases the likelihood an undesirable outcome will occur. That could be something like low retention for a subscription service.”

Gather more data. Retailers should act on every opportunity to gather data. “Every single point of interaction that a consumer has with a retailer is another dot. It is another piece of data that helps to make up the picture,” explains Kevin. The picture you create with data ultimately will feed machine learning and predictive analysis for retailers. Brands like The Home Depot and Ikea are good examples of companies moving on this data, as they’re using beacon technology to understand the physical journeys and pathways that people take within a large mass merchant store. And the data that emerges provides an interesting insight into how they should be merchandising their products.

Incorporating AI is a shift that’s happening daily but, for most retailers, isn’t quite there — yet. “The ability to say, ‘OK, here is everything we’re learning,’ and then ask how we can act upon it right now to provide a customer with a much more relevant experience — I would say that is the piece that is not very mature yet even among bigger retailers,” says Kevin. “You can probably count on two hands the number of big retail companies out there that have the data, resources, and ability to build machine learning systems for the benefit of personalization.” Start small, but start, and you’ll be at the top of the pack when it comes to delivering personal and relevant experiences across your customer base.

The Future of AI in Retail Experiences
The technology powering artificial intelligence is quickly growing and evolving. “There’s a lot more we’ll see,” John says. “More intelligent systems with cognitive analytics — systems that go beyond serving up insights to actually make recommendations and decisions based on those insights, and then constantly learn to make better decisions.”

Investments in AI at Adobe are consolidated under a single framework with Adobe Sensei. Sensei will unify AI components along with trillions of data and content points to create unparalleled experiences. In Adobe Target, a new experience decision engine dubbed One-Click Personalization is now in beta and enables marketers to test different web page layouts and activate the process with a single click. After that, the machine takes over, working through several hundreds of thousands of visits and interactions with the website to determine the ideal layout — the one that drives the most conversions.”

And that’s just the beginning. Take steps now to incorporate the power of AI in your efforts to drive personalized and relevant experiences to each of your customers.

For more insights on how retailers are adopting new technologies for more personal customer experiences, read more from our digital marketing retail series.

And, download our white paper to learn why retailers that use experiences stand out.

The post Retailers: Adopt Artificial Intelligence Now for Personalized and Relevant Experiences appeared first on Digital Marketing Blog by Adobe.

Manufacturers: Stop Drowning in Your Own Content

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Marketing Cloud

Digital Asset Management (DAM) Cuts Costs, Speeds Workflows, and Saves Time

Zebra Technologies has solved a tremendously difficult problem that many manufacturing companies share — the organization of thousands of digital assets into one, easily accessible system. Zebra, which makes mobile printers and computing devices, needed a digital filing cabinet capable of managing everything from product specs and images to catalog entries and sales slicks. What’s more, all of those assets had to be readily available in different languages, and for various markets, customer segments, and device formats.

To bring order to the chaos, Zebra implemented a digital asset management (DAM) system — one that would enable the company to find and deliver personalized customer content, on demand. Now, distributors and sales reps have ready access to the materials required for product marketing and promotion. The end result is greater efficiency in content delivery, lower costs, and higher ROI.

The Content Flood
Implementing a DAM solution helps manufacturers align content to product marketing and customer-targeting needs. This is particularly important when it comes to delivering content with pinpoint accuracy, at precisely the right customer touchpoint.

The ROI rationale for better content management is clear. In just a few years, buyers have become five times more dependent on digital information when making a purchasing decision. They also interact with an average of 10.4 pieces of content before buying. Moreover, according to IDC, 71 percent of marketers create more than 10 times the amount of content than they did in the past.

The challenge is to make it easy for customers to find the information they need. The solution is digital asset management. DAM organizes assets in a way that enables the content to find the customer, instead of expecting the customer to search for content. Buyers no longer have to forage for information. The asset management system anticipates where the customer is on their buying journey, and automatically serves up the correctly-targeted content.

As an added bonus, better asset management improves overall business processes and efficiency, which are two important goals for helping manufacturers compete in the global marketplace.

Why an Integrated Platform is a DAM Good Solution
Digital asset management is far more than just a database of assets. A good DAM system facilitates customized user experiences, automates tools for everyday content management tasks, and optimizes your capability to work at any scale you need:

  • Deliver a personalized experience. The most important aspect of implementing a DAM solution is to help deliver an experience that delights customers and partners, using any combination of display devices. The system automatically adjusts for variables, such as language, pricing, regulatory restrictions, and/or branding. This enables manufacturers to customize the user experience with special product websites, custom portals for distributors, product manuals, and even personalized after-sales support.

At DuPont, the Crop Protection division formerly produced a 400-page book once a year to provide customers with information about the company’s chemical agricultural products. It was a one-size-fits-all information solution. Today, DuPont uses a DAM tool to manage all of its assets online, including delivery of that annual print piece in an e-book format. Now, farmers can also use a mobile app that mines Dupont’s database for information on the specific needs of their crops and potential threats to their harvest. This translates into a more cost-effective, tailor-made solution for reaching customers in their localized languages, wherever they are located.

  • Automate time-consuming tasks.  Another advantage of a DAM platform is that you can control how digital assets are used, and for what purpose. If you need to modify an asset, you change the repository copy so everyone has access to the most recent version at the same time. Everything passes through any set of reviews and/or authorizations you define. Different items can have different authorization paths so, for instance, the person who reviews marketing material for use in France isn’t seeing product manuals meant for the Singapore market. Furthermore, the system helps to ensure that nothing gets released until it has all the necessary authorizations.

For DuPont, the DAM system tracks labels and safety sheets generated for farmers who buy the company’s insect, weed, and pest control products. When customer information is changed, the DAM program drives automatic updates that can be used to customize future interactions with any given buyer. By automating the delivery and updates of buyer data sheets, DuPont saved one million dollars a year, and reduced the time it takes to get materials into the hands of its customers by 50 percent.

  • Create workflows at scale. Also, with the right DAM platform, you can update, approve, and deploy content as fast as needed, on any scale, without creating a drag on performance. Managing content and assets then becomes all about quality, efficiency, and velocity.

A case in point is Maxim Integrated, a manufacturer that designs and sells semiconductor-based solutions for automobiles, medical devices, and consumer electronics. Digital asset management enabled the company to implement a powerful search tool that makes information on over 9,000 products readily available to its customers. Currently, instead of constantly combing through digital assets, Maxim’s staff can more efficiently and effectively focus on adding new capabilities, and on improving the information delivered to end users. Using a content management system also makes it easy to make updates without relying on IT. Plus, the company’s DAM solution interfaces with Maxim’s overall content management platform, and scales as needed

  • Ease of integration. Another advantage of implementing a scalable DAM system is that it integrates easily with other IT solutions. For instance, when Zebra acquired the enterprise solutions unit of Motorola, it doubled its digital assets to 130,000. There was no need to create a new website for former Motorola customers because Zebra was able to repurpose templates from its DAM system in order to leverage its existing website at a fraction of the cost of building a new, customized site.

A Top-Line Growth Investment
Digital asset management addresses the need for manufacturers to improve both content marketing and the speed at which new information is created and deployed. Your investment in a DAM system is an investment in supporting sales conversions and top-line growth. Moreover, by extending content across channels in ways that can scale as necessary, a DAM solution also facilitates better engagement, response rates, conversion, brand consistency, and, ultimately, customer satisfaction. It’s a win for the company, for the customer, and for your budget.

For more information on how you can begin to implement digital asset management at your manufacturing company, explore the following links:
Adobe Experience Manager (AEM) solutions for manufacturers
Learn more about the benefits of AEM

The post Manufacturers: Stop Drowning in Your Own Content appeared first on Digital Marketing Blog by Adobe.

Introducing Adobe Advertising Academy


Marketing Cloud

Once controversial, the adoption of automated, data-driven buying of advertising is now so mainstream it is often taken for granted. Over 70 percent of digital video ad budgets and over 80 percent of display ads are forecasted to be bought through automated channels this year. Traditional TV advertising bought through automated software is expected to eclipse $3 billion in 2017, and double in 2018 to $6 billion.

Given the rapid rate of change, the skillsets required for modern media planning, buying and execution are much different today than they were even five years ago. Even creative jobs — traditionally the bastion of designers and art directors — are becoming more data-driven according to Adobe Digital Insight’s latest Advertising Report, which found that nearly one-third (32 percent) of creative job listings require data and technology skills.

As a result, it’s becoming mission-critical for marketers to adapt, train, and cultivate the next generation of advertising talent — particularly as industry hiring is expected to outpace the labor market overall. Every role — from CEO down to an entry-level media planner — now demands new expertise, and marketers need a partner that is committed to helping them succeed in a fluid industry.

To that end, Adobe Advertising Cloud is proud today to announce the launch of Adobe Advertising Academy.

Adobe Advertising Academy is an immersive, free training program that provides marketers with both certified technical training as well as a broader strategic understanding of industry developments and current events that are necessary to excel in today’s evolving market.

Adobe Advertising Academy pushes the boundaries of traditional, platform-specific training programs by utilizing insights from all of Adobe. New courses on creative strategy, sophisticated ROI analysis, hiring and presentation skills are designed to arm marketers to succeed in a broader context.

Adobe Advertising Academy is associated with Adobe Digital Learning Services, Experience Cloud learning programs. Adobe Advertising Academy builds on an earlier, award-winning program launched at TubeMogul, which Adobe acquired in December of 2016. At launch, Adobe Advertising Academy has already trained over 1,000 marketers across North America, EMEA and APAC including Adidas, BRP, Clorox, Heineken, L’Oréal and Walmart.

Clients that successfully completed Adobe Advertising Academy’s inaugural session include Diageo, The Prosper Group and Universal Music Group.

“While we’re incredibly proud of our industry-leading platform, we’re even more proud of our client services and learning and development teams that have armed our clients with the knowledge they need to succeed,” said Brett Wilson, VP, GM of Adobe Advertising Cloud. “Adobe Advertising Academy builds on that legacy by offering a rigorous program taught by experts covering the whole industry — all in a setting that encourages sharing best-practices with industry peers.”

“Adobe Advertising Academy is the gold standard in digital marketing education programs,” said Andrew Finnan, director of accounts, The Prosper Group. “The overview of current market trends and the ability to network with other leading advertisers yielded valuable insights that will drive real results for our clients.”

Enrollment in Adobe Advertising Academy will be included in the new client activation process at no additional cost for qualified customers. In addition to the hands-on product training and industry overview, Adobe Advertising Academy’s other new curriculum includes:

  • Social 201 – Optimizing for branding or performance
  • Display 201 – Optimizing for branding or performance
  • Getting the Most Out Of Your Data
  • Vertical-custom tracks for clients with experience in the following industries: Retail, Finance, Auto, CPG, Entertainment and Health/Pharmaceutical

Post-graduation, Adobe Advertising Academy also offers opportunities for continued enrichment. These include:

  • Product and industry sessions via web conference to accommodate busy schedules
  • Invitations to stream Ad-Nauseum, a guest speaker series with top industry experts
  • Annual certification renewal via online exams

Michelle Chen is Head of Training, Adobe Advertising Cloud

The post Introducing Adobe Advertising Academy appeared first on Digital Marketing Blog by Adobe.

Strengthening Ties with Developers

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Marketing Cloud

A vital and vigorous online community is an essential part of the way Microsoft interacts with developers and IT professionals. But with only 800 technical authors, it was tough for Microsoft to respond to more than 90 million readers who use Microsoft portals for resources, discussions, and support.

Recognizing that an engaged audience of such as size is valuable to the brand, Microsoft is moving the 5 million articles on its MSDN, TechNet, VisualStudio.com, and Docs.Microsoft.com web portals to a new content site, Docs.Microsoft.com. The site uses Adobe Livefyre in Adobe Experience Manager, part of Adobe Marketing Cloud, to help article owners manage and publish content, and respond quickly to readers who provide feedback.

“To keep our brand strong, we need to support our community through good experiences and high engagement. Customers expect an interactive experience, to be listened to, and that their concerns are addressed in a timely manner. Livefyre gives us the tools to make our content better and improve customer satisfaction,” says Gigel Avram, principal data science manager at Microsoft.

Since implementing Livefyre, Microsoft has seen improved article ratings of up to 30 percent. It’s also improved and accelerated the ability of authors to respond to recommendations and corrections, which makes readers feel more engaged and improves the overall quality of content.

Learn more about how Microsoft is cultivating online communities and strengthening ties with developers using LiveFyre, part of Adobe Experience Manager.

The post Strengthening Ties with Developers appeared first on Digital Marketing Blog by Adobe.

Adobe Launches Adobe Advertising Cloud TV for Personalized TV Advertising


Marketing Cloud

Native integration with Adobe Analytics Cloud enables audience-based linear TV planning and buying with first-party data.

For the better half of a century, both advertisers and broadcasters alike enjoyed the security of knowing that TV was the unquestioned champion of media, the most effective and reliable way to deliver a message to millions.

But the rapid fragmentation in consumer attention — accelerated by the spread of high-speed broadband internet, smartphones and social media — means that TV advertising isn’t as effective as it once was. A typical buy achieving 200 gross rating points (GRPs) reaches 25 percent fewer people today than it would 20 years ago. This reach atrophy – combined with the efficiencies gained from leveraging data to amplify effectiveness across digital channels – has left traditional TV buyers looking for a way to regain their lost reach, and do it in a way that goes beyond basic age and gender demographics.

Which is exactly why Adobe Advertising Cloud, part of the new Adobe Experience Cloud, is thrilled to announce the launch of Adobe Advertising Cloud TV, the industry’s first automated software for linear television ad buying that incorporates first-party data.

“Adobe Advertising Cloud TV is leading the charge for more automation and data-driven targeting in traditional TV advertising,” said Brett Wilson, vice president and general manager, Adobe Advertising Cloud. “This solution builds on TubeMogul’s legacy product with new firsts, including a native integration with Adobe Analytics Cloud for targeting using a brand’s first-party data and cross-screen capabilities that bridge the gap between TV and digital formats.”

The ability to use data to reach a strategic audience — mothers who are in market for an automobile as opposed to Females 25-49, for example — has been a hallmark of data-driven television for years. Now, powered by Adobe Advertising Cloud’s seamless integration with Adobe Analytics Cloud, marketers can finally use their own first-party data segments to inform strategic targeting across linear television. And thanks to Adobe Advertising Cloud Search — Advertising Cloud’s search advertising solution — marketers can now plan and buy linear TV against audience segments that have already demonstrated intent through online searches.


Any marketer can plug their own data into Advertising Cloud’s demand-side platform; advertisers do not need to be pre-existing Analytics Cloud clients in order to use their digital first-party data for traditional TV. Advertising Cloud’s open approach means marketers can activate data from any DMP, and even more importantly, take those learnings with them post-campaign.

No first-party data? No problem! Adobe’s data-driven approach to TV buying means advertisers can easily determine whether a past or present TV buy is effective and whether a new approach is needed to reach a specific audience. Notably, Advertising Cloud’s exclusive access to TV manufacturer data provides minute-by-minute insights as to what content a viewer is consuming on their TV, enabling marketers to index consumers based on their viewing history and build a TV plan to reach that audience. This data is collected in a privacy-safe manner from consumers that have opted-in to an enhanced advertising experience.

But our data offering goes well beyond just TV manufacturer data. Our extensive data partnerships are seamlessly integrated into Advertising Cloud TV, providing advertisers with access to:

  • Integrated strategic audience targeting, buying and reporting with a market-leading MRI partnership
  • Minute-by-minute viewing data from Nielsen AMRLD
  • Strategically target specific households with set-top box (addressable) data

The solution seems perfectly timed: Programmatic TV advertising is forecasted to grow 206 percent this year, eclipsing $2.16 billion, and double in 2018 to $4.4 billion. As investment expands and new entrants make the space more competitive, what separates Advertising Cloud TV from the pack?

“Not only is Advertising Cloud TV the most comprehensive platform available, but our unique position as an independent technology provider is conquering barriers to scale the market opportunity,” said Brett Wilson, VP and GM of Adobe Advertising Cloud. “The fact that we don’t own or markup media means that we’re not out there competing for upfront dollars or steering spend toward preferred partners. That earns trust, both on the supply-side in gaining access to exclusive inventory from TV networks and on the buy-side by offering advertisers a platform aligned with their incentives.”

Clients are similarly upbeat. “With TV playing a significant role in Sparkling Ice’s media mix this year, as seen in our recent integrated marketing campaign Be Not Bland™, we wanted to leverage a platform that would help us navigate through the noise and get smarter with our offline strategy,” says Brian Kuz, Chief Marketing Officer of Talking Rain. “Adobe Advertising Cloud TV best positioned us for success by targeting our mass audience efficiently and effectively, while giving us the capability to measure and optimize our first national TV campaign.”

Brought to you from Adobe Experience Cloud’s Facebook page, watch Phil Cowlishaw, Head of Special Operations Consulting, Adobe Advertising Cloud, discuss Advertising Cloud TV and the benefits for marketers.

Brett Wilson is GM & VP, Adobe Advertising Cloud

The post Adobe Launches Adobe Advertising Cloud TV for Personalized TV Advertising appeared first on Digital Marketing Blog by Adobe.