4 Trends Marketers Should Watch At Mobile World Congress

Marketing Cloud

A recent global survey of more than 4,000 consumers showed that 92% of millennials considered the smartphone to be their primary device. Even when those in the 70+ category were asked, 67% answered the same.

Whatever demographic, brands have to engage with users that are not only mobile-first, but also increasingly mobile-only, particularly in countries like China and India.

As much limelight as device makers and telecoms get at Mobile World Congress, marketing and advertising are becoming focal areas, as well. This year, Feb 22-25 in Barcelona, we see tracks dedicated to everything from mobile analytics to ad blocking.

Here are some of the big trends:

Location-Based Marketing Means More Than Ads 

Beacon technology came out to great fanfare when it was introduced around 2003. Since then, it’s gotten a bad rep; personalized ads and discounts can be effective, but they are one of many possible use cases. Having access to contextual data allows brands to be more creative.

For example, a clothing retailer could install a large display in their store, which changes depending on who’s walking by it. Shopper A might see a cocktail dress; shopper B might see a pair of shoes. Or, an app could enable shoppers to take pictures of clothing and accessories on those around them and suggest similar items in the store.

These user cases already exist, either in practice or demo form. They enable brands to blend physical and digital, identifying the specific experiences that provide value for their audience. In the above survey, 67% say they would use their smartphones in conjunction with physical shopping sometimes or often.

Internet of Things: Close, But Not Quite 

IOT lays out the possibility of an interesting future, one where everything is connected but invisible. Even though the experiences will be transformational, most of the ideas are still pies in the sky.

Much of the technology needed to enable the Internet of Things is already available. For brand marketers, it’s not a matter of capabilities, but elimination and curation. Having the possibility of putting your app on a wearable doesn’t mean you should; for some brands, it makes a lot of sense. For others, it’s pointless.

Bringing your brand into IOT requires that you accept that the first few tries will likely be failures. Similar to mobile, iteration is the new innovation here. Marketers should deliver the minimum viable experience and run a series of experiments; see how users respond and hone in on the hero features.

Mobile Analytics: Human Intuition, Informed by Data 

Analytics is an example of technology being in front of what consumers think they want, or expect. We’ve evolved from data visualization all the way to artificial intelligence and predictive capabilities. As commentators postulate on the possibility of a machine takeover, the human touch will be the most important factor.

The risk with mobile analytics is lack of subjectivity. If customer Andy’s daughter helps her father order all of his clothing online, an algorithm might tag Andy as a 19-year-old female millennial. Consumers are only one bad experience away from deleting you off their phones.

Air on the safe side; humans and technology are meant to work in concert. Good data should inform your best intuition and when you’re wrong, be humble enough to take another look at the numbers and make the changes.

Ad Blocking is Giving Brands Good Feedback 

The expansion of ad blockers from desktop to mobile was accelerated with the introduction of Safari on iOS 9. Consumers embraced the change because it provided a better experience. Some ads have become so obnoxious (and resource draining), that the trade-off for free content no longer sticks.

For publishers, this is a form of user feedback. Consumers are taking more ownership of their browsing experience and every ad blocker install is a vote for change. If bad ad experiences are causing users to flee, a good ad experience can help decelerate the trend.

There are some guiding principles: (1) Balance ads and content (2) Enure security risks are mitigated; an ad–induced virus guarantees you’ve lost the customer; (3) Optimize ads for speed and lessen the impact on computing resources. (4) Ask for feedback and see what’s working.

This article was originally published on Media Post.

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Dynamic Tag Management and the User Experience

Marketing Cloud

When Adobe acquired Satellite in 2013 and rebranded the Tag Management System as Dynamic Tag Management, we stated that DTM has the capability to truly revolutionize the way marketers tag their web properties and deliver personalized experiences to consumers. Internally, we called out three specific reasons for adding DTM as a no charge, added value feature to the Adobe Marketing Cloud family of solutions:

  • Increase the rate of digital marketing adoption
  • Solve the industry problem of tag management with an industry-wide solution
  • Elevating the conversation to more than just tag management

As part of those mandates, I like to provide real-life use cases as well as commentary from DTM developers, which might help you in managing the implementation of DTM and governing the data gathered by this fantastic solution. With that in mind, take a look at our conversation with Michael Helbling, analytics practice lead at Search Discovery (the creators of Satellite), who sat down to discuss our three reasons to offer DTM and more. We talked about the work his team has done with clients before and after the Satellite acquisition, and what Dynamic Tag Management has meant to customers.

Before we talk about the DTM solution, can you tell us briefly about your role at Search Discovery and your experience with DTM?

As analytics practice lead, I am responsible for our analytics solution and [its development] team. This includes our go-to-market strategy, client delivery, and team development. I have been using Adobe DTM (formerly Satellite) for just over three years. I was fortunate enough to lead the first ever implementation of Adobe Analytics for a client using what is now Adobe DTM. Our team uses the tool on an almost daily basis, working with clients to deploy and manage their [native] analytics solutions as well as other digital marketing activities through Adobe DTM. It is amazing to see in such short time what has been able to be accomplished leveraging this platform.

Let’s walk through the three key points called out in John Mellor’s original DTM launch post, and get your perspective on how DTM has addressed those points with your clients.  

1. Increase the rate of digital marketing adoption

This is the fundamental use case of Adobe DTM. It has always been at its core a mechanism for digital organizations to streamline deployment and usage of digital measurement and marketing technologies. Our clients consistently get speed and efficiency from using DTM. This frees us up to help them focus on data they can trust, the ability to quickly refine that data, and the ability to use the data in ever more creative ways. In a world where becoming more data driven is a necessity

2. Solve the industry problem of tag management with an industry solution

Adobe DTM is unique in its ability to exist in the context of an organization like Adobe and still be able to easily handle any tag and any pixel from from any vendor. At Search Discovery, we have had the opportunity implement and manage Adobe DTM for more clients than anyone else, and we have yet to find a tag or measurement solution that cannot be deployed by Adobe DTM. It is truly a universal solution meant to address any need in any context.

3. Elevate the conversation to more than just tag management

I have long maintained that putting a tag on a webpage is a fairly mundane activity. Many organizations developed systems for managing this aspect of marketing technology long before tag management was a thing. But one thing that DTM does better than any other solution is promote and provide a bridge for real collaboration between marketing and IT. The best and most successful digital organizations are the ones who are solving that problem. For large and small enterprises this can take the shape of governance and making sure there is a well-defined path for how technologies become integrated with the digital experience. In Addition, DTM provides the ability to iterate more quickly and take advantage of the segmentation and personalization features providing a much more rapid growth and response to increased customer understanding. Every client we engage with at Search Discovery we are attempting to move beyond the tags to help solve the problems of becoming more data driven. Adobe DTM is an awesome tool because it makes the deployment of tools and technologies an easily solved aspect of the underlying problem set.

Given your experiences with DTM how much time/money/heartache have clients saved using DTM?

It is incalculable. In some cases, deploying Adobe Analytics went from a painful six-month back-and-forth process to a well-defined three-week process.  Even more encouraging for marketers is not just how much money you will save, but how DTM can dramatically increase the value of your digital experiences. Things like real time segmentation, ease of data integration between tools, and the ability to deploy tests and customized experiences rapidly. What we are really excited about is how our clients are using Adobe DTM to grow their businesses. Over 40 percent year over year in one case. Adobe DTM is an enablement technology. It starts the engine, and savvy technologists and marketers are finding ways to hit the gas pedal in extraordinary ways.

Looking back over all the time you have worked with TMS systems in the past, is the market where it should be in the understanding and maturity levels with Tag Management?

Given that the concept of tag management as a stand-alone solution is less than eight years old, the adoption and maturity rate is astounding. That being said, I am never content to say that our work here is done. There are organizations that will always be out on the cutting edge, and there are those that will wait until the solution set is more proven and stable. If I were to place TMS on the Gartner hype cycle, I would say that in this very short time we have put tag management on the “slope of enlightenment”. At Search Discovery we believe that the appropriate use of data will fundamentally transform an organization.  Our passion is to assist our clients in that transformation, and Adobe DTM has been a great vehicle for that purpose.

Are there some more challenging uses cases that you’ve encountered that DTM has been instrumental in solving?

Adobe DTM was unique in the space for recognizing that the most valuable measurement often happens within the interactions on the page and not necessarily the traversal of them. Adobe DTM led the way in building a very robust event tracking capability. This makes Adobe DTM an ideal solution for handling the frameworks of the modern web like Angular, Backbone, etc…

Beyond mobile applications (Read here for a better understanding of the challenges faced by all tag management vendors) the better question might be is there a use case that DTM hasn’t been instrumental in solving? There has literally never been a time when we have had to go back to a client and say; sorry this just isn’t possible with the tool. If you are reading this, and you have heard that before we need to talk.

As we look back over the last few years at the amazing success of Dynamic Tag Management, a key piece in the Adobe Core Services offering, it is special to be a part of a process and solution that is being used by nearly 3,000 companies and drives more than 2 Billion Adobe Analytics transactions every day.   More than just these great adoption numbers is how DTM and the rest of the Adobe Marketing Cloud have helped companies make great strides in governance, efficiency, and improve that data collection at the first millisecond of interaction with the users in order to deliver the right personalized message to drive conversions.

Additional Resources

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5 Ways CRM Data Benefits Your Marketing Strategy

Marketing Cloud

There seem to be a lot of misconceptions in marketing around CRM, or customer relationship management systems. Many think a CRM system is just a technology to manage sales leads or just a database of sales contacts. It’s actually both, and when integrated with marketing automation, it can be much more of an integral part of your sales and marketing strategy. Here are five ways incorporating a CRM system benefits you

1. Increased Awareness

One of the main functions of a CRM system is to provide visibility of where leads are in the funnel, as well as raising awareness of sales and marketing activities. Your CRM can alert your sales team to upcoming marketing initiatives, such as an upcoming email campaign or marketing event. Even more than that, it can alert sales team members to important actions your customers have taken. If they have registered for an upcoming webinar, your sales team might want to send them personalized reminders to attend. Alternately, your team may only want to reach out with a phone call if the customer attended. Whatever your outreach strategy is, it cannot happen properly without a well-maintained CRM.

2. Enables Automated Alerts

To make the system even more seamless, it is possible to create triggers and alerts within your CRM. These ensure the appropriate team member can be notified every time a particular action happens. For instance, if you want someone who subscribes to your newsletter to receive a touch-base call one week later to see how he or she is enjoying it, you can create automated alerts that notify the appropriate team member to make that call. This type of functionality helps ensure that the wealth of information inside your CRM becomes actionable. The benefit is increased visibility into leads across both sales and marketing, which can accelerate the sales cycle.

3. Ensures Consistent Messaging

In addition to being able to reach out to customers at appropriate intervals, a CRM also provides you with the input you need to ensure your messaging is consistent. If someone already subscribes to your newsletter, there is no need to continue inviting them to do so. If they have begun regularly attending your webinars, it is somewhat of a faux pas for your sales team to call inviting them to attend. Knowing which messaging works for which clients based on their past and current behaviors is important. Without this ability, you can end up sending your customers mixed messages. The more targeted your content is, the more value that content will be and the more likely a lead will engage.

4. Provides Holistic Customer Insights

Once your sales and marketing teams are accustomed to entering accurate and useful data into a CRM, they can start to acquire a more robust understanding of your customer. Sure, maybe a customer attended your webinar. However, when the sales team followed up, they found out the customer hated the webinar and never wants to attend anything like it again. This kind of insight can help all future engagements with the client, as you can turn off the indicators that might invite them to similar types of events. This insight provides us with the context that simple behavioral data — the act of attending a webinar — does not offer. As a result, a CRM can increase engagement and accelerate sales cycles.

5. Increases Customer Engagement

Once you have the elements above in place, you should begin to see increased engagement from your customers. You may be wondering why that is. Simply put, you have begun listening to and understanding them through the data you have compiled in your CRM system. This makes them more likely to receive the types of messages that will resonate best with them, which in turn leads to increased engagement. Increased engagement then leads to increased likelihood of conversion, which leads to customer loyalty, future spend, becoming a customer advocate, and so on.

Synchronizing your data between CRM and marketing automation will help you optimize customer insights. While it can take time to create a shared repository of data between sales and marketing, you’ll gain the ability to understand your customer’s actions and preferences better than ever before.

If you take the time to make this transition now, you will have the added benefit of being ready for whatever technological advances are coming in the future. Ultimately, a well-organized CRM system offers your organization a wealth of benefits both now and in the future.

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How Do I Choose the Right Content for Content Amplification?

Marketing Cloud

With today’s focus on customer experience, smart brands are looking for ways to boost content marketing strategies for stronger relationships with potential customers. Yet time and money spent creating in-depth, well-articulated content is just the beginning. The best content in the world is meaningless if no one is paying attention to it.

The days of using ad-hoc tactics to promote content are over, and savvy brands are employing content amplification strategies to place valuable information in front of the right people at the right time. Moving your content from publication to distribution seamlessly requires a plan. What does it look like, and how do you choose the right content for amplification?

Content Amplification Explained

With tons of amazing content available today, businesses looking to differentiate are pursuing content amplification to get their messages in front of the right people. That means sharing content beyond the initial publishing source and in some cases marrying it with social advertising for increased reach and engagement. Blogs, articles, infographics, web pages and other content assets that have already been published are placed strategically onto a variety of social media sites and other high-traffic networks, improving impact and reach. Bottom line? Content amplification done well puts your best content in front of the customers you want to reach.

Choosing the Best Content to Amplify

Your challenge is to boost valuable content that will have the most impact on business goals. So how do you choose the right content to amplify? Keep in mind while consumption metrics like social shares are important, making the right selection requires looking a little deeper to reveal underlying reasons why content is being shared in the first place. Is it funny? Is it making a major business announcement? Determining why content performs well and then mapping those insights back to business goals is a first step in choosing which content to amplify.

Without identifying the “why” behind a successful piece of content, you could be putting money into something that’s not actually achieving any real purpose – besides getting a laugh, for instance. Supporting content that furthers brand messaging and resonates with your audience is key. Find content that performs well organically, but has meaning. Then promote it beyond organic reach through paid campaigns.

Social advertising can help build your audience with a goal to expand your reach to potential customers who haven’t necessarily experienced your brand. Keeping content tied to brand messaging with a clear call to action (CTA) is critical. Whether it’s a whitepaper to download, a video to learn more about the business or a blog to read, content needs to be meaningful to those that consume it while at the same time providing information about your business.

Assess Content Performance

Data is essential to marketing success, and the right performance indicators can help you maximize amplification efforts. Use these indicators to recognize content worthy of amplification:

  • Time Spent on Page – A key metric for understanding the behavior of people who come into contact with your content, time spent on page helps identify what readers find useful. Particularly with long form content, a lengthy amount of time spent on the page assumes people are reading it all the way through as opposed to sharing quickly or browsing and dropping off. Amplifying valuable content is the goal, and time spent on page is a key metric.
  • Page Views – Another great consumption metric, page views helps you measure reach, offering a baseline of sorts for comparing the performance of different types of content and identifying trends over time.
  • Social Shares – Social proof indicators like shares and comments serve as evidence that content is valuable and people like it, but shouldn’t be the end all be all to your success metrics.

Effective Content Amplification

Defining performance goals at the beginning of a content amplification strategy makes it easier to promote to identified metrics. Besides, this is also where accountability lies. With social advertising, the ad type often is defined by the goal. With Twitter for example, it’s possible to design an ad that reflects tweet engagements, website clicks, conversions, video views or app downloads. Setting the right performance goals from the start helps align your amplification strategy with intended outcomes.

Clicks on an image are not the same as website clicks, and having clear performance goals defined ahead of time can clarify these outcomes. Without the right goals defined, a tweet could perform well but may not deliver the success you’re looking for, whether it’s link clicks, engagement, etc. Without context, it’s difficult to determine performance, even if the numbers look great.


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More Than Getting to “Buy:” Optimization in the Retail Industry

Marketing Cloud

Christi2The retail industry has a unique opportunity when it comes to testing, optimization, and personalization. On every retailer’s mind right now are brick-and-click considerations, the upcoming holiday season, mobile and social trends, and the Internet of Things, and retailers are constantly expanding and evolving their strategies to gain greater consumer engagement and boost conversions. Christi Terjesen, a principal consultant with Adobe Target Consulting, chatted with four Adobe retail optimization experts on the trends and best practices they’re seeing in the field—and what to expect in the future.

What are the biggest opportunities or challenges in the retail industry right now?

Amy_Lam_Nov_2015Amy Lam, Digital Optimization Consultant: It seems people think that, for the retail industry, mobile is the greatest opportunity. We’ve all heard so much about mobile and being in the era of mobile—and I get it. We know the mobile audience is growing in general and for retailers. But I’m not convinced the retail space is really using mobile effectively. I always recommend seeking data to show if prospects are really buying on mobile phones or just researching.

JessieDoeckJessie Doecke, Digital Optimization Consultant: Retailers must invest in the data they own and really understand the customer and noncustomer behavior that is device agnostic versus device specific. I think it’s critical to understand that data evangelism and visibility across the organization is the foundation of a successful optimization program. It’s not just about communicating wins—it’s about identifying real starting points and benchmarks to understand the big opportunities to test, and to continue to understand how those tests are moving the needle in the long term.

Richard OtoRichard Oto, Digital Optimization Consultant: One of the challenges we see a lot of the time is that companies are trying to dictate or force how consumers act with their mobile app. But we can’t force those assumptions on our customers. We need to allow them through testing and optimization to determine what activities are most relevant to them on their mobile devices.


Amy: And where, exactly, is mobile in terms of all of the customer touch points? Where does mobile sit? And where do ALL touch points sit?

Richard: Mobile spans vertical and horizontal; it touches multiple channels and teams. Companies need to identify ownership between marketing, product, IT, etc. It’s important to identify ownership of the various portions of the site so that they’re able to create and execute on a strategy.

Jessie: The biggest challenge I’ve seen is the wealth of data retailers have that they may not be fully utilizing, to target and serve relevant content, and support user needs and functions across devices and touchpoints. This could be for a number of reasons, whether from constraints related to development resources, solutions owned, limitations with data warehousing or a lack of strategic alignment across business units and teams. The opportunity to leverage this data to increase conversion and drive customer loyalty is limitless but there must be a general consensus for the strategic vision across departments and resources to support this opportunity.

So it’s about understanding how your website and how your app are being used by customers, possibly in conjunction?

Amy: It’s not just about your website for acquisition purposes. Say a customer goes into a store and is looking for a trench coat. One way she can shop this retailer is on its website. Maybe she does research before to see the latest trench coat colors. Then, when she gets to the store, she really likes the green coat, so a salesperson comes over and uses the store’s app to find her size. There are so many different touch points ultimately influencing the customer’s purchase. It’s not just about the website or mobile app. And, yes, there are plenty of opportunities, but also plenty of challenges. As a retail executive I would be trying to think about how to make all of these pieces fit together and make the entire experience consistent and cohesive and, at the same time, a fantastic experience. I want the customer to not just make this purchase but to come back and buy shoes, too, for example.

And before going too far you can test to see if your hypotheses are correct?

Amy: Right.

Richard: So backing up to the question of the biggest opportunities and challenges, I’d say data availability is both an opportunity and a challenge. There’s more and more data available for customers—second party, third party, different platforms. My clients struggle with how to identify what’s needed, get it into their systems, and make sense of it to scale personalization programs. What I see with mobile is that people are so focused on what we can do and they get into these fringe use cases, focusing on very hard data integrations. This really bogs us down and prevents us from effectively using our time. But we need to increase velocity, too. Time is our most scarce resource. Every time we aren’t running tests or campaigns we’re not learning and not identifying future opportunities. So going back to the biggest challenge, I’d say strategizing a long-term plan then focusing on scalability.

How can retailers do that? Is it setting clear direction to the people on their teams—what they should go out and look for, for example? What can retailers do here?

Richard: I would find the data sources that are readily available and perhaps even built-in. Very simply, Target and Analytics detect geolocation, previous site activity, current site behavior. Start there. Some sources are easier to get in and some are harder. It’s crawl/walk/run. Don’t start more complicated then you have to.

Matt-LowdenMatt Lowden, Digital Optimization Consultant: I keep coming back to personalization. With mobile, everything has to be data driven and, second, I think everything needs to be loyalty focused which relies heavily on convenience. I think about the best mobile experiences I’ve had and the brands I purchase from. No one wants to browse around and shop forever on their phone. Those sites that I’m loyal to I have a profile with, they know what I like and when I’m ready to go in and purchase something they know who I am, they offer it up, they have my credit card on file or use Apple Touch ID so I can pay fast and I’m out. Brand loyalty, personalization and streamlining the mobile process—those are three things that, if you can focus on and build out, you’re going to have a great mobile experience.

Amy: Look at the data aspect, too. You really have to know your consumers, too. If you have the data but can’t interpret it and get to the core insights on what resonates with your audience, then you aren’t really tapping into the resources available to you. Tap analysis help if you need more support combing through the data.

I agree. It’s not enough to just know customers are 24–45-year-old females. You have to know how often they shop and why, for example. Are they looking for suggestions or just want the jeans they need right now? Are they here to browse the latest styles?

Amy: My question is always why? Why do they shop with your brand? Because of familiarity? Because they know you have the right cut of jeans, for example, that fits your body type? Is it something else?

Are there ways to get there besides just asking?

Amy: I always go back to the qualitative studies like UX studies, surveys, and product reviews. What I’ve seen be very successful is the coupling of qualitative and quantitative. I think the quantitative is a mixture of observing what actually happens that, perhaps, consumers can’t quite articulate in the qualitative studies and, of course, testing. It’s sometimes a challenge to find the resource or build the skill set to get to those insights marketers need.

Matt: There’s also marrying the in-store and mobile experience—what Amy’s saying informs that in a lot of ways. We’re seeing businesses go out of business because of the mobile effect—people shopping on their mobile phone while they’re at the store. Customers are showrooming with Amazon and other lower cost providers. I think, Amy, what you’re getting at is quantitative/qualitative—why are customers loyal to you? Why would they appreciate being in the store versus shopping online? Maybe it’s being able to try things on, for example. But then it’s using mobile to drive there. We’ve tested using brand loyalty and discounts and things like that and, more and more, the successes are with mobile.

Jessie: This requires that a retailer step out of the shoes of a retailer and into the shoes of their customer. What makes their brand or product different from the customer’s perspective? Have you tried to shop your own site, app or store? If so, what could have been better about your experience? Now put your retailer shoes back on and ask yourself (and your team)—what are we doing to better position the primary reason why our customers shop with us and what are we doing to make their experience better? Now take a good look at your demand data to see how this translates to site, app and store behavior, and your shipped data to see where further opportunity lies to take advantage of channel affinities, product purchasing combinations and subsequent purchasing trends. Taking these steps should give you quite a bit of insight to pinpoint both bigger opportunities as well as low-hanging fruit.

So organizationally we need to break down the silos because our customers aren’t buying in silos—and maybe they never were.

Matt: I agree. One example I read recently was about a “virtual dressing room” and consumers could be in a dressing room with an article of clothing in a particular size—if they need a different size it was complicated. You had to change back into your clothes, find a new size, lose your dressing room—it was annoying. With this mobile app you could request a new size or color and have it brought to you in your dressing room. That’s a perfect example of marrying in-store and mobile to drive loyalty. Marketers should be thinking how to complement other channels.

Amy: If you have a retail store it’s a huge advantage. People are coming and interacting with products in your store. They’ve already gone to your store—they already have an interest. Capitalize on that!

Matt: Yes—and there are so many opportunities to do this. Brands are building apps with geolocation targeting. That’s so out of the box these days. There’s also beacons and opportunities to push special notifications to people near your store. It’s just more breaking down of silos.

I also think there’s a real relationship between online and brick and mortar. There’s the notion that if I order online and it doesn’t fit I can take it to a store and swap out instantly. Or if one doesn’t have a size and the other does, perfect. That’s a complementary relationship.

Matt: I see it more and more. I shop online and at checkout have the option to have it delivered in a few days or pick it up at the store near me.

Right—there could be a mixture of in-store and online happening all of the time, with the same customer. Add mobile and there’s a new dimension entirely.

Amy: I love what you said—it doesn’t have to be competitive. Often when I work with retail clients they don’t see it that way—it feels competitive. But it shouldn’t be. I see so many testing examples that involve online interactions but, ultimately, yield valuable information that the stores could benefit from. That gives every platform a boost.

Jessie: The benefit from integrating online and brick and mortar fulfillment options goes both ways. For example, shipping windows around the holidays are definitely a seasonal concern for most retailers to keep up with, and it’s becoming more common for companies to use retail stores as a ship-to-store delivery option or as a secondary warehouse of sorts to backfill primary distribution center bottlenecks. At the same time, brick and mortar can utilize online as a secondary method of fulfillment when their own inventory is cleared out. The result is that the retailer collects additional sales and both channels benefit. The problem is that the adoption of these opportunities can delayed for a number of avoidable reasons that really just equate to the perception that each channel is competing with the other. For example, who gets the credit for the sale for each scenario, how should commission be structured for brick and mortar fulfillments, or even just concerns related to product sell-through and replenishment. These shouldn’t be blockers to expand the avenues a customer has to purchase. Getting the brand and the product to the customer is what matters because it’s what acquires and retains loyalty, and ultimately keeps a company in business.

Amy: So how can one brand look at all of these channels and connect them to the same customer? I ordered on the site, picked up in-store—and picked up something else—and then accessed the brand’s app a few days later. If I were a retailer I would love to have that level of information and, from there, have it inform my personalization strategy.

Matt: And that goes back to brand loyalty. We’re working on solutions that will marry a profile across all devices. If you can convey the value of becoming a member of that brand site or community, then people will authenticate. You’re ID’ing yourself and it makes it easier for brands to convert you. Brand loyalty isn’t the only way, but it’s a good process and it’s very powerful.

Amy: Brand loyalty is nothing new for retail brands. But how it’s translated now is different. Now they say, “oh, we know this segment has specific ways to interact with our brand,” and can go from there. I can see this evolving even more fully in the future.

Agreed, brand loyalty now includes ease of use across the different channels of customer interaction and through customer experience optimization and personalization retailers can help maximize that loyalty.

Thanks to Christi for moderating this roundtable and to the team for lending their insights and strategic thinking. The retail industry is definitely unique in the digital marketing and optimization landscape, setting trends for the other verticals to follow. We’ll continue to tackle some of the shifts and growth opportunities in the industry in the coming weeks and months.

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Smashing Through the Conversion Rate Optimization Glass Ceiling

Marketing Cloud

Last week I touched on what I believe should be digital marketers’ key priorities for 2016: conversion rate optimization (CRO), content personalization, and the mobile app universe. These are, hands down, the most pivotal topics right now and the ones that could yield the greatest impact on your business no matter what you do. Get it right and you’ll be in a prime position to knock it out of the park this year. Let yourself and your business grow stagnant or, even, plateau and you’ll wind up no better off in 12 months—or, worse, you’ll lose out to some of your competitors who prioritized pushing the envelope in 2016.

The first area to dig into? Conversion rate optimization. It’s good to start here because, In many ways, CRO is a foundational piece of content personalization and mobile apps, the other two game changers this year. Think about it: if you break digital marketing down to its most basic components, what have you got? An end goal of making the most of customer journeys and experiences.

The interesting thing about CRO is that it’s been around forever. When weren’t you trying to convert customers? But that doesn’t mean the conversation hasn’t grown and evolved. If you’re still playing in the old CRO sandbox you’ve probably leveled off or, even, seen your successes taper. I wouldn’t be surprised if, as a result of waning successes, you’ve moved on to other initiatives.

But we need to reset the conversation. We need to redefine what it means to “convert” someone. And we need to make sure that you, your brand and marketers everywhere recognize the new CRO path to success, and the multiple platforms, touch points, and considerations it entails. Here’s where to start.

Being Truly Data Driven

Adobe’s latest Digital Optimization Survey showed a clear split between the top 20 percent of successful conversion companies and the remaining 80 percent: the highest performers align testing with decision making. “The survey results,” the report explains, “show that companies who shift to a culture that embraces optimization to make decisions increase conversion 100 percent.” One hundred percent.

That shouldn’t be a surprise to anyone who’s elbow-deep in optimization. Today’s leaders are the ones who are using data religiously. They know what their audience and its segments look like right now, in real time. And, equally importantly, these marketers and brands embrace that even their most valuable consumer segments could change, shift and evolve overnight, even.

But for digital marketers on the optimization forefront, this isn’t a cause for concern—they’re deeply data-driven and, no matter how the consumer landscape looks in a few months, weeks or hours, even, they’ll be ready to pull in new profiles, drill down on the latest metrics and unearth the most valuable segments at that moment in time. It might seem intuitive enough but, surprisingly, nearly half of companies don’t have any real plans in place to scale their data-driven marketing initiatives.

To do this well brands need a companion to all that data. Today’s CRO relies on this vital data being woven into the DNA of your brand, as well as through various organizational niches. From my end I see the massive differences in those brands who have data companions and those who don’t. Companies that tap Adobe Target versus Target and Adobe Analytics have very different experiences because the latter has a companion to the data. By bringing together Target and Analytics you can choose from rich segments and slice and dice to your CRO delight—people who spend X dollars perform this way, while those who spend Y engage this way. It’s multidimensional, it’s highly actionable and it’s always at your fingertips. Integrating a data companion gives you the flexibility to reach up and out, to be nimble, to automate, to segment even more deeply. It’s having the data and using it—and doing it all in real-time, with incredible impact and efficacy. It’s the ultimate one plus one equals three. CRO ceiling smashed.

Here’s the challenge many organizations face, though: they’ve got the data and, maybe, they’ve even got the analytics machine raring to go. But then the magic happens after the fact, or by a team that doesn’t have the keys to the proverbial kingdom. By having key pieces, people or next steps too far removed from the conversion epicenter, you’re missing the mark—or, minimally, not making the most out of the data you’ve got. Gartner estimates, “85 percent of Fortune 500 organisations will be unable to exploit Big Data for competitive advantage.” As Forbes explains, that “means only 15 percent will be…using Big Data and analytics to uncover new insights and deliver a sharper competitive edge.” It’s, simply, not good enough—remember, CRO falls in the all-important need-to-have bucket, and that means Big Data jumps in right alongside. Not just having but actually using for the greater good . ..yours and your consumers’.

Dodge the Blind Experiment Trap

If you aren’t tapping into data effectively, blind experimentation is likely an issue holding back your CRO—and that’s a major misstep. Saying you “do CRO” but blindly poking around in a testing tool just isn’t good enough in this new conversion world order. Think about your own testing and experimentation efforts. Are you utilizing the numbers, being smart and strategic, and launching every test eyes wide open? Or is there some level of blind guessing and experimentation still happening? Guess now, analyze later won’t hold water when it comes to driving conversion value.

Adobe Target has taken great strides in this area and, now, is able to test elements within your entire campaign. Based on options that emerge from the rich data you’re already collecting, Target can pull in metrics from other solutions as well as critical success benchmarks to both test and deliver optimized experiences. Maybe it’s digging into fall out rates at one stage of the journey and conversion rates in another and identifying ways to do more of what’s working and ease up on what’s not—and, more importantly, unearthing the gems from those experiences that can inform other consumer touch points along the way. It’s a unique approach that turns valuable insights into actionable information and, with it, improves CRO—and, even better, it mitigates risk in a big way.

Stop Siloing

Adobe’s view of the customer and his journey is simple, holistic and looks at interactions as continuation of one ongoing conversation that starts with the first touch. By taking this approach we’re able to optimize a series of successful experiences that shepherd customers through the journeys we want them to take. Remember, conversion isn’t just the path from A to B—instead, it’s something marketers and brands need to observe across multiple engagement modalities, in most cases, to get a truly clear picture. If you aren’t thinking about CRO through this kind of a lens then you’re still stuck in yesterday’s definition of “conversion” and, as a result, you’re likely smacking your head against the CRO ceiling.

This is definitely an optimal approach to improving CRO and one that it’s essential to benchmark your brand against. Are you taking this same 360 view of the customer, or are you focused on the touch points and individual moments in time, and optimizing accordingly? If it’s the latter remember this: consumers don’t care about your channels, how they accessed your brand or the device they were using this time or that time. They see your brand—Brand X—as one experience in their minds. And, more importantly, they see it as an experience they can jump into and out of as needed. Ignore cross-channel movement or silo her experiences and you’ll no doubt curb your CRO efforts—if you don’t recognize her when she pops up somewhere else and can’t keep the positive momentum from your last engagement, she’ll likely abandon in favor of a brand that sticks with her through every twist and turn.

The industry has, effectively, re-benchmarked itself when it comes to CRO, and we’re coming up against seemingly sky high hurdles as result—hurdles that, in most cases, have left the industry a bit paralyzed. But that doesn’t mean we’re done with CRO. Far from it, in fact. Getting over this hurdle, though, isn’t going to be about fighting our way through—the brands that will ultimately be successful in the CRO game are those that can take a good, hard look at what can be done to shift, realign and keeping pushing ahead. They’re the brands that know CRO is a need-to-have, not a nice-to-have. They’re the brands that can be data-driven, acknowledge the conversion journey everywhere it takes place. And they’re the brands that can redefine what “conversion” means even when it doesn’t fit in the neat, clean little box we’ve assigned to CRO. Decide where you fall and get ready to dive in. We’ll be there to sprint right alongside you, every step of the way.

The post Smashing Through the Conversion Rate Optimization Glass Ceiling appeared first on Digital Marketing Blog by Adobe.

Quick Guide: Personalization and Optimization Sessions at Adobe Summit

Marketing Cloud

It’s hard to believe, but Adobe Summit—The Digital Marketing Conference is just around the corner. We’ve been working hard to create a great Personalization & Optimization track for attendees.

One of the challenging things about owning a track at Summit is trying to cover all the interesting topics we’ve been exploring with customers over the year and all the great customer stories that we want to share. One of the challenging things about being an attendee is working out how to best spend your time at the event and which sessions to attend. Consider this your quick guide to the topics, sessions and fantastic organizations sharing their stories at Adobe Summit 2016 in Las Vegas.

A Look at the Personalization & Optimization Track Main Focus Areas

This year our sessions focus on three main areas that we keep hearing customers express interest in or challenges with:

  • How to get started with optimization and build an ongoing, sustainable program
  • How automation and algorithms can reveal deeper insights and help you focus on strategy
  • How to stay ahead of the curve with the switch to mobile—mobile personalization and optimization

New this year, we also have Personalization & Optimization sessions geared toward specific verticals: B2B, Financial Services, High-tech, Retail, and Travel and Hospitality; I’ll indicate when a particular speaker is from one of those areas. And we’ll have a couple of sessions that are information-filled, great networking opportunities and downright fun; I’ll highlight those at the end.

Based on those three main topic areas and our vertical-specific sessions, here’s my personal guide to choosing sessions in the Personalization & Optimization track to get the information you need at Adobe Summit this year:

Getting Started and Building a Sustainable Optimization Program

Digital marketers often get stuck simply knowing where to start with optimization. They invest a lot in the tools to launch their program, but then don’t get the return on investment (ROI) that they expected or take a long time to realize that ROI. These sessions help you get started and let you see what you can be using in today’s highly approachable, but very powerful Adobe Target.

Recommended Sessions

S912 Site personalization: Where do I start?

S913: Perspectives on personalization from financial services leaders (Financial Services)

S905: Adobe Target: Redesigned for powerful optimization and marketer control

Once organizations do get started with optimization, many find it challenging to mature their program. That goes well beyond simply having the right technology; it requires the right people, processes and governance. A key tactic to an effective program is developing a personalization roadmap that outlines how testing will support the organization’s business goals. These sessions will give you great ideas for how to mature your program.

Recommended Sessions

S907: Clearing Hurdles for Optimization Success

S911: Make your vision reality: Building your personalization roadmap (High-tech and B2B)

S915: Driving personalization and testing at Macy’s (Retail)

S916: Building the case for optimization: Lessons from financial services pros (Financial Services)

Some organizations have stopped experiencing the big wins they saw early on and want to breathe new life into their optimization programs. This session offers some tried and true, and in some cases traditional, marketing tactics that you can apply in the digital marketing sphere to get that positive momentum going again with your program.

Recommended Session

S904: Test results flat? Bust through plateaus with customer-centric optimization 

Still others want to learn how to deliver the customer an end-to-end, cross-channel experience or about new, innovative, even cutting-edge approaches to optimization. These sessions show what’s possible with Adobe Target and other solutions and core services in Adobe Marketing Cloud, and highlights customers who are embracing what’s possible.

Recommended Sessions

S902: End-to-end offer management with Adobe Marketing Cloud

S903: Holistic experience optimization at The Home Depot

S917: VMware: Using deep personalization to fill the sales pipeline (High-tech and B2B)

Using Automation and Algorithms for Deeper Insights and a More Strategic Approach

Many digital marketers want to take their optimization efforts to a new, higher level by applying data science and using automation and algorithms in their personalization and optimization work. These sessions discuss why automation, algorithms and data science are where personalization and optimization are headed.

Recommended Sessions

S906: Because you’ve got bigger fish to fry than button color

S909: Unleash your inner data scientist with Adobe Target

Staying Ahead of the Curve with the Switch to Mobile—Mobile Personalization and Optimization

In almost all industries, more visitors and customers are connecting with companies via smartphones—particularly those in the millennial generation. The features unique to mobile devices open up completely new, exciting opportunities for digital marketers to deliver more relevant experiences and offers. The first session shows innovative thinking about how to tap into mobile unique capabilities for personalization and optimization in travel and hospitality industry. The other session gives you data and insights about millennials, including why a mobile focus is important if you want to resonate with them.

Recommended Sessions

S914: The personalization journey: What happens before and while you’re in Las Vegas (Travel and Hospitality)

S908: Marketing to the 77 million millennials

Last, but Certainly not Least

These last two sessions don’t quite fit into the last three categories, but they’re iterations on two of our most popular sessions from last year. If you want to get your questions answered, meet others working in personalization and optimization, or just see what others are doing with optimization at their company, these are must-attend sessions. See this blog post for more detail on the WhichTestWon competition* and how to enter—it’s not too late!

S901: Personalization & Optimization Workshop 2016: 2 hrs of ideas & inspiration

S910: Step right up and guess the test winner: WhichTestWon’s Adobe Target Awards

Don’t Forget the Hands-on Labs!

Be sure to look through the Hands-on Labs. There are a ton of labs focused on Personalization & Optimization that you may want to sign up for, too!

Please let me know on Twitter @jamiebrighton what you think of the sessions and if you have any questions.

I look forward to seeing you at Adobe Summit 2016 in Las Vegas next month!

* Entries for competition close February 19, 2016. Enter the competition here.

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Personalized Email Follow-up: How Do You Create the Right Message?

Marketing Cloud

Marketing technology enables us to target, create and adapt messages to consumer preferences and behaviors. We’re in the era of personalization, but not everyone is playing. We’ve got data—business intelligence—and tools to do the heavy lifting, so now is the time to make email messaging a personalized experience.

Why is it important? The bottom line is personalized messages get a better response. Customers feel noticed and appreciated when an email seems built just for them.

However, personalization has to be done correctly to be effective. Just inserting a name field there, a location field there, won’t work. Consumers see through that. You’ve got to give them more.

Personalization Is Still a Challenge

Marketers are still struggling with personalizing email campaigns for several reasons. Many might know where they want to be—that is, more intuitive with messaging, delivery, retargeting, etc.—but aren’t there yet because they don’t know where to start. Maybe they don’t have the resources, their data is a mess or they’re having difficulty understanding what it means. Some might not even have access to data at all!

But if you’re not personalizing, you’re going to spend a lot of time managing marketing fatigue and customer fallout. Most marketers know that it’s more effective and cheaper to retain and drive revenue from existing, loyal customers than to acquire and convert new customers. Personalization allows email marketers to develop this loyalty and in turn, more revenue with less effort.

Brands Doing Personalization Right

During my time at Adobe, I’ve come across some great personalized emails. Here are three examples of brands that are getting it right.

Creativity Leads to Conversion

Within two hours of a visitor abandoning a cart on a certain childrens retailer’s site, they send out a follow-up email with a simple message: Did you forget something? The message comes with a really nice visual and a clear call to action. It reads, “Don’t forget about your cart. We noticed you left some items in your cart, because you probably got sidetracked with a phone call or even a unicorn sighting. If you have any questions about your order, feel free to contact our customer service department. View your cart.”

Why it’s great: They aren’t devaluing their brand by saying, “You forgot to check out, here’s 20% off.” That kind of email diminishes the return on investment. Some brands feel they need to offer a lower price to get visitors to come back. The truth is customers might buy if we just give them a little nudge. In this case, the consumer may have had every intention of converting but as a busy parent, they likely got distracted during the checkout process. This email assists with the conversion by providing helpful customer service.  Bonus: They’re witty, creative copy also helps strengthen the overall image of the brand.

Cross-channel personalization builds relationships  

My next example is from an online retailer that offers a monthly subscription service for razor refills and supplies. In this example, they personalized an email by analyzing social data. A relative of mine left a comment on the brand’s Facebook page about how much he loved the razors, but that he received way too many, and now has a surplus supply. Within four days of writing that comment, he got an email that read, “Too many blades? Get your razors delivered every other month if that’s what you need.”

Why it’s great: The club proactively sent him this message knowing that it’s going to make less money, but might create a more loyal customer. Bonus: He’s a relative newbie to social media, and LOVED that they took time to not only leave a response under his Facebook comment, but also sent him the email letting him know he could update his delivery preferences. He now recommends the service to all his peers!

Offline to online personalization to advance loyalty

One of my favorite fashion retailers does a great job of matching in-store purchases to their email subscribers. In this case, I bought a bunch of petite dresses at one of their brick-and-mortar stores. A few days later, I received an email with a nice visual of a petite model and some petite size options. The message felt like it was created just for me. It read, “Looking for petite sizes? We got you.”

Why it’s great: The email was meant to reinforce the point that the company suspected I was a petite shopper based on my instore purchases. It was a simple reminder there was an entire online shop with way more petite options. This type of message keeps the brand top of mind for me, providing a connection that will keep me coming back. Bonus: Again, in this case, there was no need to push a discount.

For marketers who haven’t moved their email marketing campaigns to a more personalized approach, you can look to these examples for guidance. Remember, personalization creates loyal customers.

The post Personalized Email Follow-up: How Do You Create the Right Message? appeared first on Digital Marketing Blog by Adobe.

A Look into Adobe’s Digital Marketing Collaboration with Universities

Marketing Cloud

The talent and game-changing data science research coming out of academia never ceases to amaze me. There’s such a tremendous spirit of curiosity and exploration in faculty and students, and we encourage our research team for Adobe Marketing Cloud to embrace this spirit. When we launched Adobe’s first ever Adobe Digital Marketing Research Awards back in June 2014, this was the heart of the idea. By exchanging ideas and research between Adobe and universities, we knew we could uncover incredible advances in data science, and that we could push the boundaries of how data science is used in digital marketing.

Adobe sits on a wealth of data with Adobe Marketing Cloud. Adobe Marketing Cloud powers 41 trillion transactions and 4.1 trillion rich media requests for our customers, annually that includes two-thirds of the top Fortune 50 brands. This presents a tremendous opportunity to develop theoretical and empirical solutions to problems in marketing that can improve consumer experiences.

Adobe’s annual Data Science Symposium at our San Jose campus is an opportunity for academic researchers to learn about our Digital Marketing business. Professors also present research proposals for the Adobe Digital Marketing Research Awards, which provide up to $50,000 in funding support from Adobe. Research institutions including the likes of UC Berkeley, Stanford, Massachusetts Institute of Technology (MIT), and Northeastern University participate at the Symposium.

The academic institutions we work with benefit from the ability to bring together conceptual ideas with real, industry problems and data. Here are a few projects from past recipients of our Adobe Digital Marketing Research Awards:

  • UC Santa Cruz Professor Lise Getoor’s cross-device graph-based entity resolution research, which was awarded a grant in August 2014. The research matched users across devices and platforms by understanding contextual features or signals (e.g. location, login info) across the different platforms, and developing scalable algorithms to perform the matching. Dr. Geetor’s research enhanced personalization performance by 10-15 percent, suggesting that the ability to match users across their various devices would provide brands with better targeting and insights into consumer behavior.
  • Professor Ramesh Johari from Stanford and his team, Adobe Research Award grant recipients in August 2014, hypothesized that predictive modeling – or building correlation insights from existing data – isn’t sufficient to determine the value of potential interventions on individual’s purchase decisions. So take for example a marketer sending a digital coupon to a customer. It’s not simply about sending a coupon; it’s about how much more likely the individual is to convert with the coupon. Dr. Johari combined machine learning and causal inference techniques, so in this case, it is not about simply measuring how many people who received a coupon made a purchase but rather what influence did the coupon have on the individuals that led them to make a purchase to evaluate the impact of interventions to individuals. This is especially important when optimizing ad spend across multiple channels, where the goal is to maximize the ‘bang-per-buck’ matching specific marketing content with particular customers.
  • Professor Anindya Ghose from New York University and his team won a grant in February 2015. They proposed a new mobile advertising strategy leveraging information from mobile phones on consumers’ offline activities. The research offered insights into how businesses can leverage both consumer mobile in-app and offline physical behaviors to better understand and influence customer preferences.
  • Rutgers University’s Professor “Muthu” Muthukrishnan won a grant in August 2015. Professor Muthu has an advertising background, having previously worked at Google. His project examined issues with analytics, in particular detecting anomalies (e.g. a sudden drop in people of certain demographics visiting a page or a sudden increase in clicks from a specific region) and offering insights into the cause of change, especially when the data is large in size and the number of possible explanations are numerous. The goal of his research was to develop algorithmic solutions to circumvent these challenges.

Students from Professor Getoor’s UC Santa Cruz program and Professor Johari’s curriculum at Stanford have interned at Adobe. We’re always on the lookout for both undergraduate and graduate level interns to work with our product and operational teams, as well as with our Adobe Research organization. In addition to the Adobe Digital Marketing Research Awards, we offer grants to universities to continue our work with interns and their professors with students returning to school following a successful internship.

I’m excited to share that on May 26 2016, we’ll host our third Data Science Symposium at our Adobe San Jose campus. Stay tuned for a look into the inventive ideas and research discussed and presented at this year’s Adobe Data Science Symposium.

Adobe will also award academic institutions with research grants up to $50,000 for data science projects in the areas of digital marketing in February and August. If you’d like to submit a proposal for the Adobe Digital Marketing Research Awards, submission details can be found here.

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Digital Marketing 101: DMP Dictionary

Marketing Cloud

A data management platform (DMP) is an important part of an organization’s marketing strategy. We often talk about the lingo surrounding a DMP without diving in and explaining every term. Here I’ve outlined some of the basic concepts to help you build a foundation of understanding around data management platforms.

DMP: A DMP, or data management platform is a tool used to consolidate the disperse data sets of a company across first, second, third-party channels. It manages the segmentation and identity definition of user to then provide cohesive audience targeting across all of the various channels where you might be engaging with a consumer.

Forrester Research defined a DMP as “a unified technology platform that intakes disparate first-, second-, and third-party datasets, provides normalization and segmentation on that data, and allows a user to push the resulting segmentation into live interactive channel environments.”

In other words, it pulls data from a bunch of different, potentially unrelated sources and allows organizations to define specific audience segments to which they can provide distinct marketing experiences.

Why is a DMP important?

A successfully implemented DMP is critical to the definition of a cohesive core dataset and enables different marketing teams to draw from it. This will ensure that end consumers have consistent and repeatable experiences across a multitude of various marketing channels. Without a DMP, communications sent to your end consumers through different channels — such as social, display, direct mail, and email, among others — become fragmented due to the varying degrees of personalization or segmentation needed to create a more unified experience.

1st, 2nd, & 3rd party data

Three types of data can be fed into a DMP: first-, second-, and third-party data. To develop a successful DMP, it is important to understand when each type of data should be utilized and what benefits each can offer to your organization.

1st Party Data: First-party data is proprietary data that has been captured by your company. This could be through channels such as onsite analytics audience information, the capture of various web behaviors in relation to specific experiences, or any offline first-party data such as customer-relationship management (CRM) data or data from a brick-and-mortar store.

Why do you care?

This is your most important asset, as it allows you to build a strong foundation from the vetted information that you have access to about your consumers that helps to establish a truthful baseline. In addition to traditional first-party data types, it is also important to consider more unique types of first-party data — such as survey information, media performance, or data that is not collected directly from traditional channels — as these information sources can provide valuable insights during the definition of that baseline.

Once you have a strong grasp of what this first-party data looks like, you can pull in second- and third-party data to supplement your understanding of the customer base. It is also important that you are aware of the potential benefits and shortcomings of using other people’s data in your DMP. Generally, second-party data — a partner’s first-party data — is more reliable than third-party data.

2nd Party Data: Essentially, second-party data is a partner’s first-party data.

Why do you care?

Second-party data may be the greatest untapped resource in many DMPs today. Oftentimes, businesses already have broad contracts in place with existing copartners, allowing for the transfer and use of co-marketing and co-branding initiatives. Many times, those second-party data repositories are readily accessed and can be used to take a full inventory of partners and all their available datasets. Marketers can use second-party data to begin identifying really unique datasets that are meaningful to their businesses and much more defined and tailored to the consumers they want to attract than some of the more commoditized third-party data.

Once you have established a solid customer base from your first-party data — and expanded your understanding of that base using second-party data available to you through partnerships or other directly shared customer data — it is time to take a step back and objectively define gaps in your data foundation. Are you missing specific demographic data or other types of information that could supplement your understanding of your broader customer base? Here, you can determine the best place to plug in third-party data to fill those specific areas where you lack enough of this data foundation.

3rd Party Data: Any data that you can get your hands on, that isn’t first- or second-party data, can be called third-party data. Third-party data is data that is gathered by businesses that typically sell customer data to other business, that is used to supplement gaps in first- and second-party data.

One example of this type of data supplementation is prospecting initiative. When marketers are trying to find new customers who have never made purchases from them or their partners or visited their websites, there is no first- or second-party data available for those users. At this point, they can leverage third-party datasets to fill in the gaps and help to better define those audiences.

Why do you care?

Be aware of the potential downfalls of relying too heavily on third-party data. This information is mined by businesses that sell customer data to other businesses, and it may not be as reliable as first- and second-party data. Third-party data has become somewhat commoditized over the years, meaning that multiple businesses and industries have access to the same datasets. Relying too heavily on data that is not specific to your industry or customer base can mislead your overall marketing strategy or dilute the insights developed through your DMP.

DMP Strategy

Many businesspeople who understand the value of implementing a DMP — and what types of data can be integrated with it — wonder to what level the DMP should be used to define their overall marketing strategy or how they properly govern and operate a DMP. A DMP should not be used to define your strategy; the DMP is a tool to help you achieve your strategy. Building a comprehensive strategy is less about having a super-skillful data scientist who can run all sorts of algorithms and more about interacting with different groups that are working with data in one way or another and bringing all those ideas together to collectively define a single strategy for an organization.

It is very challenging to incorporate all of the different requirements and use cases for each of the different groups utilizing the DMP within your organization, but that is how you really set a successful strategy. Once you have determined your strategy, and all those different groups are in agreement regarding what type of strategy it is, you can bring in the data scientists or algorithmic tools or Big Data analysis to capitalize on the scientific analysis of information; however, the analytics should not define the data strategy.

The strategy should be defined across all the different parts of the organization that are working with data. Strategy is defined at the management level to identify what the different groups are doing and how these groups must work with data at different levels. From here, you can build a comprehensive strategy, and then use the DMP to actually execute that strategy, combining all the data to unify the message across the different channels.

In the end, that is the true value of the DMP. It consolidates datasets. It manages identity at the master’s level, pulls first-, second-, and third-party data — both online and offline — into the system, and effectively creates segments and subsegments of your audience that accurately reflect your customer base across a broad range of channels. The much more challenging aspect of a DMP strategy is determining what datasets you need to put into the DMPs. Which audiences should be prioritized across all those different marketing channels, and how will they impact existing marketing initiatives? These are the business decisions to be made as part of the strategy, as opposed to the technical decisions that can be made by the DMP.

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