email personalization: increase opens, clicks, and

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EMAIL PERSONALIZATION: INCREASE OPENS, CLICKS, AND REVENUE WITH THE RIGHT STRATEGIES AND TECHNOLOGIES SPRING 2015

A PRACTITIONER GUIDE Updated November 30, 2015 • Andrew Jones

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Contents

03

Introduction

09

Maturity benchmarking

21 27 36 38

» Email personalization is extremely effective » What to expect from this report » Marketers are using personalization

» Measuring email personalization maturity » Segmentation » Data: understanding customer identity

» Email marketers face challenges » Data and customer identity

» Content: what is being personalized, exactly » Speed: processing and send time

Technology: comparing options » Email service providers » Marketing automation

» Machine learning

Strategies and tactics » Use cases: low hanging fruit to expert tactics

Conclusion Appendix » User survey details » Vendor survey details

» What does the future hold?

Introduction EMAIL PERSONALIZATION IS EXTREMELY EFFECTIVE Email is the marketing ROI leader and the preferred channel for customers to receive information from brands. Yet email is seeing a decline in click rates because people have less time and patience. Silverpop has found that more than 50% of people unsubscribe from email lists because the content is irrelevant, too frequent, or both. Personalized emails counter this trend. In a survey of 257 email marketers, the vast majority reported increased open rates and click-through rates (CTR) by employing some form of email personalization. This includes even the most basic personalization tactics:

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Greater relevance from email personalization also reduces unsubscribe rates. AgilOne has found that unsubscribes result in an average loss of 60% of future lifetime value (LTV). The unsubscribe rate also affects your sender reputation score — which affects your overall email deliverability — so lowering the number of unsubscribes is another critical metric. And email personalization increases revenue even more than opens and CTR. Experian Marketing Services has found that subscribers who receive personalized content have not only higher opens and CTR, but a 6x increase in transactions. Personalization vendor Rich Relevance has found that while average customer email clickthrough rate is 2.5 times higher using personalization compared with non-personalized emails, revenue is an average 5.7 times higher. In short, email personalization has tremendous ROI.

WHAT TO EXPECT FROM THIS REPORT Email personalization can get complex, involving a wide scope of data, content, and technology. But lack of information can be the greatest challenge of all — many marketers simply aren’t aware of the scope of possibilities. Fortunately, getting started with email personalization is easy and there’s plenty of low hanging fruit. Just personalizing an email with a name can have a demonstrable impact on open rates, for example:

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In this report you will learn key challenges, benchmarks and what your peers are doing, strategies and tactics, and best practices for email personalization. You will also learn how to increase the maturity of your email personalization efforts incrementally, not just through one-off tactics. This report includes survey data from 506 marketers using personalization across multiple channels, 256 marketers using email personalization specifically, and 33 vendors providing some form of email personalization capabilities. We also interviewed 14 vendors and email experts. Further details about survey respondents are in the appendix.

MARKETERS ARE USING PERSONALIZATION We found in our previous report, Marketing Personalization: Maximizing Relevance And Revenue that email is the channel most commonly personalized. In a survey of 506 marketers using personalization, four in five marketers reported personalizing emails.

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But most marketers are employing only experimental or unsophisticated efforts, like dynamic fields to insert a name. Even these efforts can yield impressive results, but without advancing to more mature efforts, most marketers are leaving money on the table. According to CampaignMonitor, an email service provider that focuses on SMBs, agencies, and departments within larger organizations, “[2016] is the year of personalization.” Everything is about “targeting, hyper-targeting, personalization, and relevancy.” We heard a consistent message from nearly all marketers and vendors that 2016 is the year of relevance, hyper-targeting, and personalization.

EMAIL MARKETERS FACE CHALLENGES Email marketers are tasked with not only maintaining but also increasing relevance at a time when consumers are bombarded with more messages than ever, increasingly filtering and unsubscribing from emails. Given that task, and effectiveness of personalization, it’s no surprise that marketers cite it as the number one priority for the coming years. Yet marketers face a number of challenges.

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Kristin Naragon, director of email marketing at Adobe Campaign, says that one of the hardest parts about implementing new strategies is changing the behaviors and mindset of email marketers: “It is the largest hurdle to clear,” she says. Mindset can be an especially high hurdle because marketers often fear making changes, says Angela Sanfilippo, chief evangelist at AgilOne. “Everything is about hitting numbers and there’s fear about not marketing as opposed to over-marketing.” Better targeting might lead to reaching fewer prospects, which can be a scary proposition. Another reason changing behaviors can be challenging is simply lack of resources or time. For example, Rip Curl has only five people managing all of their email campaigns, from layout to design to execution, which leaves little time to try new things. Technology is a related challenge. “Vendors have to make it easier to integrate, coordinate data, and experiment,” acknowledges Kraig Swensrud, the CMO Campaign Monitor, which Rip Curl’s team uses to manage its campaigns. “As vendors we are delivering new sophisticated capabilities, but we have to make them easier to use to make it valuable.”

DATA AND CUSTOMER IDENTITY Understanding the customer is the basis of personalization. Many companies already have the data they need, but they often aren’t connecting the dots yet. Lytics CEO James McDermott says, “I have not talked to anyone who is not thinking about changing their email system… but no matter how many times you switch, the problem isn’t in the tool, it’s in the data.”

Many companies already have the data, but aren’t connecting the dots yet.

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There are a number of different technologies available, and choosing the right tool certainly does matter, but its true that personalization efforts rely upon a foundation of data. Many brands don’t necessarily know who they’re talking to or who their best customers are, says Yesmail’s Ivy Shtereva. “Many companies aren’t sure if Peggy, who is 30 and has no kids, is a better customer than Anne, who is 45 with two kids in college; you can get this data from preference centers, purchase history (and data mining for what they are purchasing), or from a third party and append it.” To collect and unify the right data can be a daunting challenge. Data structure, storage, and sanitization (cleaning and de-duplicating) are elements of a complex topic on its own. For in-depth analysis, see our related report, Identity And Marketing: Capturing, Unifying, And Using Customer Data To Drive Revenue Growth.

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Maturity benchmarking We’ve looked at ROI of email personalization in the beginning of this report. In this section we’ll discuss maturity across factors like segmentation, tactics, and technology, including benchmarks to see how you stack up compared with your peers. This section addresses the following questions: •

How advanced are my peers with regard to email personalization?

•

What approaches or methods are being used to personalize email?

•

What content types are being personalized?

•

How many segments are being typically being targeted?

•

Are marketers able to send personalized emails in real-time or is there lag time for data processing?

•

What technologies are most relevant?

We look at specific tactics associated with different degrees of maturity in the section on Strategies and Tactics.

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MEASURING EMAIL PERSONALIZATION MATURITY The maturity of email personalization is best measured in degrees of segmentation, content personalized, and speed of execution. Progression in each of these categories is not always linear, but certain elements are more commonly associated with specific levels of maturity. EMAIL PERSONALIZATION MATURITY FRAMEWORK

Segmentation

Content

1. NOVICE

2. COMPETENT

3. PROFICIENT

Preference center

Demographic

Dynamic behavioral

segmentation

segmentation

segmentation

Dynamic field insertion

Subject lines and media (images, video, attachments)

4. EXPERT Individualization; based on profiles, preferences, and behaviors

Products (individual

Subject, text, media,

recommendations)

sender details

Within 10 minutes

Real-time

Within a day (if Speed

using data for

Within an hour

segmentation at all)

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In a survey of 33 vendors providing a broad range of email personalization capabilities, over half ranked their customers as either “Competent” or “Novice.” Because these vendors include a majority of marketing automation and cross-channel personalization vendors, this skews toward more advanced.

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Adobe similarly looks at three email marketing personas: classic, dynamic, and contextual email marketers. In part, these speak to organizational and executive support, but also their capabilities: 1. Classic: some basic strategies, such as emailing lapsed customers and possibly some dynamic fields (like name). 2. Dynamic: automated retargeting, coordination with other channels, and capturing customer feedback 3. Contextual: real-time and contextually relevant According to a study Adobe conducted, over half (54%) are “classic.” About a third are dynamic (32%) and only about one in seven are contextual (14%). Although estimates vary, the consensus is that the majority of email marketers are early in their personalization efforts and few are advanced.

SEGMENTATION When it comes to segmentation, there are only a few options (assuming any segmentation at all is being done): 1. First, a spreadsheet-based approach that is manual, slow, and tedious. This is associated with traditional email service providers (ESPs), although many now provide at least limited options for segmentation. 2. Second, a rules-based approach often associated with marketing automation, where marketers can set conditions to trigger specific engagements. This approach is still manual but automates redundancy and can remove the need for spreadsheets. 3. The third option is a machine learning approach, which can create more segments based on more data and criteria than a marketer ever could. (More details on machine learning in the section on technology.)

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We asked specifically about the latter two to see how many email marketers using personalization were using rules-based segmentation compared with a machine learning approach. It turns out a greater number than we expected are using machine learning, which enables greater segmentation than creating rules.

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We also asked how many segments email marketers were personalizing their email for, on average. Although about half are targeting fewer than 10 segments, a surprising number are targeting many more. And one in ten said they were personalizing at the individual level.

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DATA: UNDERSTANDING CUSTOMER IDENTITY Of course, segmentation is based on data, and a wide variety of data types are being used. Segmentation with traditional ESPs, which would have depended on excel sheets from campaign managers, might have been based largely on customer preference. Now, though, marketers (and technology vendors) are getting more sophisticated with relational data. Segmentation can be based not only preferences, but transaction history, web and mobile behavior, product inventory, and others.

We found that engagement history is least commonly used as the primary data source for email personalization, whether it was transactional or engagement with another department. This is particularly noteworthy, because we’ve previously found that most companies know little more about customers than transactional history. It turns out that companies that have more customer data tend to rely data sources other than engagement history for personalization.

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A preference center is a simple way to capture preferences for very basic segmentation, but beyond that profile details (including demographics) tend to be used most commonly, by 44% of marketers employing email personalization. Behavioral data, most often from web and mobile activity, is one of the most valuable data sources, because it provides real-time insight into a prospect’s interest and intent. After all, clicks on email are far fewer than interactions on a website or mobile app. Graham Young, director solutions consulting at Experian Marketing roughly estimates that 10% or fewer are using web behaviors for personalization now, but says that those few who do see tremendous lift. He expects this number to crease dramatically in 2016.

Behavioral data is one of the most valuable data sources.

Although we have also found that fewer marketers use behavioral data overall, over a third of marketers using email personalization are using behavioral data as the primary data type for those personalization efforts.

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What about specific data points? When it comes to specific data points being used for email personalization, it’s not just about using a customer’s name. Segmentation by demographics, geography, social profile, time of day, and a variety of others are commonly used data points.

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CONTENT: WHAT IS BEING PERSONALIZED, EXACTLY When it comes to content, there are only so many options for what goes into an email. But little of that content is being personalized by marketers today. Text, and specifically a name, is most commonly personalized with dynamic tags that grab the details from a CRM system. Media can be personalized by segment using similar tags, but is less frequently done. After all, creating different content takes time, energy, and money. And even though companies may already have a lot of content they could more effectively leverage, associating specific media with different segments remains a manual and tedious process in most cases. Companies using a recommendation engine can, however, effectively personalize products to a much greater degree. This requires some degree of machine learning, most often offered by web and “omnichannel” personalization vendors. Sender details like the name and profile photo can also be changed for different segments. Again, this remains a mostly manual process, though.

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Although subject lines might be considered in the same bucket as other text, advancements in artificial intelligence make it possible to personalize subject lines to a much greater degree. Persado uses artificial intelligence and machine learning to evaluate and construct short text, including email subject lines. The company’s technology helps create copy that is more persuasive without having to create multiple variations and A/B test. And although time does not fall under the category of content, when an email is sent can also have a significant impact on email engagement rates. Some marketing automation vendors help marketers optimize send time, and still others like AudiencePoint enable marketers to customize the send time of every single email.

SPEED: PROCESSING AND SEND TIME Speed matters. Interest has a half-life, and getting in front of a consumer within a limited time frame is often the difference between winning or losing a customer. Charles Nichols, VP of product strategy at SAP Hybris says that after 12 hours, 70% of interest is gone. As a result, both behavioral data (which indicates what a prospect is interested in in real time), and the time it takes to process and use data, play increasingly important roles in email personalization.

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The good news is that email marketers are getting faster. It used to take days to transfer data from a data warehouse, process it, and then use it in an email campaign. Today 42% of email marketers report they can deliver personalized email in real-time, with fewer than 10% saying it takes longer than a few hours.

Many marketing tools today have cloud-based databases, with open APIs and data connectors. This makes it possible to connect and move data like never before. As companies have better access to view and use customer data, we expect the number of email marketers able to send personalized emails in real-time to double in the next two years.

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Technology: comparing options Personalization is about relevance at scale, and reaching different degrees of scale (or segmentation) requires different types of technology. For most marketers looking to personalize emails, marketing automation, which enables rules-based segmentation, will be the best fit. But there’s more to it than that. It’s certainly still possible to use ESPs, especially with additional third-party vendors. And for marketers that require a much greater degree of personalization, machine-learning options are essential.

EMAIL SERVICE PROVIDERS Traditional ESPs are email-centric, able to track clicks and opens, but don’t have listening capabilities to track and make use of on-site behaviors. Marketing automation vendors, by contrast, typically enable marketers to track and incorporate behaviors from the website and other channels. ESPs are also oriented toward a mass email approach. By contrast, marketing automation platforms use triggers along the customer journey, making communications more targeted and relevant. In a way, ESPs actually have less incentive to increase efficiency too, since they traditionally charge by volume. Traditional ESPs remain relevant for many marketers, especially retailers who may fear not hitting everyone every time. But as traditional “batch and blast” email marketing faces diminishing returns, it will be difficult to continue using email as a blunt instrument. In short, marketing automation makes email (and other channels) more efficient — and as a result email marketers must evolve or face extinction.

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To be fair, many ESPs have been adding more automation capabilities to address markets’ needs. For example, ExactTarget bought Pardot (before being acquired by Salesforce), StrongMail added campaign and cross-channel management features and rebranded as StrongView (recently acquired by HGGC), and MailChimp continues to add automation capabilities:

It is possible to use third-party tools to make ESPs more efficient through better segmentation and send more targeted emails. Many of RichRelevance’s biggest customers use Cheetahmail, ExactTarget, and Responsys, for example. (RichRelevance is an omnichannel personalization tool across web, mobile and in-store.) However, for most marketers looking to advance their personalization capabilities it will make increasing sense to move to a marketing automation platform that offers better data management, segmentation, and rules capabilities in a single platform.

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MARKETING AUTOMATION While marketers using traditional ESPs have had to segment stale lists, and have been unable to quickly target dynamic segments like web abandons, marketing automation offers a number of real-time targeting and automation capabilities. For more on marketing automation, including vendor details and segmentation, see Marketing Automation: How To Make The Right Buying Decision (The First Time). Marketing automation platforms can store personally identifiable information (PII) for each individual, with segmentation and data management built right on top, in order to facilitate the design of single or multi-channel, multi-wave campaigns. As a result, email marketers don’t have to ask for data, because they already have at least most of what they need within marketing automation. With marketing automation, the focus also moves from email volume to efficiency. For example, if you can tell that someone has a high likelihood to opt out of email, you may want to instead target them on another channel and not send an email until later. That speaks to both the need to coordinate across channels and the imperative not to use email as a blunt instrument.

The focus also moves from email volume to efficiency.

Marketing automation, campaign management, or journey builder tools help marketers be more efficient with rules and automated workflows. These tools are all about encoding a series of customer paths based on the best data available at that time. Marketing automation is much more efficient than traditional email marketing — enabling marketers to reach much greater scale and relevancy — but also has limitations. It can get complex quickly and can require a lot of people: analysts to develop segmentation, designers to configure templates, and marketers to execute campaigns. Ultimately, there’s a bottleneck around how many tests you can run or how many flows you can create.

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For companies with fewer than a few hundred thousand emails or with relatively few segments, marketing automation and campaign management tools are most often best for email personalization. For companies in this bucket, there are also options to add predictive lead scoring and segmentation that can increase targeting and personalization at scale. Predictive lead scoring can also make campaigns more effective, by focusing on the most qualified leads. Mintigo, which was started by ex Israeli defense forces to find signals on the web that might represent terrorist threats against Israel, now uses its technology to find prospects and understand which are most likely to convert. 6Sense, EverString, and Lattice Engines are others that provide predictive capabilities. Half of the email marketers we surveyed doing some form of personalization are using predictive modeling or scoring. And of the vendors we surveyed, 22 of 33 said they offered some form of predictive capabilities.

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There’s a reason marketing automation adoption is growing. It enable marketers to reach customers at the right time (timers, triggers), in the right context (channel), with the right message (fields and segments). And just as ESPs have made efforts to add automation capabilities and move upstream, some marketing automation vendors have been adding predictive and machine-learning capabilities to enable marketers to reach greater scale. Marketo acquired Insightera at the end of 2013, for example, in order to add web personalization and machine learning capabilities.

MACHINE LEARNING Machine learning approaches enable marketers to forego much of the design, testing, analysis, and optimization that would otherwise be required in traditional campaign management. Machine learning means decision trees can go much deeper than humans could, enabling far greater segmentation or individualization, which in turn offers greater ROI. Ultimately, machine learning requires fewer people, but provides greater granularity at a greater scale. A variety of vendors are using machine learning to make email (and cross-channel) marketing more efficient. A number of these were previously focused on web personalization, such as Certona and RichRelevance, but are now applying behavioral data (combined with other first-party data sources) and recommendation engines to make email more relevant. Other vendors, like SailThru and Boomtrain, straddle campaign management and web personalization while applying machine learning for greater greater personalization reach. Amplero, which sells a machine learning, “self-learning personalization” tool focused on maximizing retention and LTV, provides marketers machine-learning capabilities to layer on top of their existing email marketing or campaign management tools. This enables marketers to create much deeper and more accurate segments than is possible with a manual approach.

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And still others focus on much more specific elements of personalization, like Persado (subject lines) and AudiencePoint (email send time), mentioned previously. For the most part, only brands with over half a million records and with greater segmentation needs should look at machine learning options. Companies with fewer records are unlikely to find it worth the investment to do additional segmentation. And, according to Amplero, anything below 6-700k records starts to become difficult in terms of statistical significance. Aside from a minimum number of records to make an investment in machine learning worthwhile, a few industries are particularly relevant, including retail, publishers, hospitality, travel, mobile gaming, and technology. These industries typically have a higher variety of products, segment types, or customer attributes.

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Strategies and tactics Marketers use personalization for a variety of reasons beyond simply increasing opens and clicks. Different objectives and use cases entail different tactics, some easier and some harder.

USE CASES: LOW HANGING FRUIT TO EXPERT TACTICS YesMail has found that about 30% of email marketers are not personalizing at all. For those who are employing email personalization, though, a number of specific tactics are commonly associated with different levels of maturity. Here is a snapshot overview of tactics related to each level: EMAIL PERSONALIZATION TACTICS 1. NOVICE Personalized greetings, subject lines Onboarding/welcome campaigns A/B testing (subject line, message, promotion, etc.)

2. COMPETENT Trigger-based actions

3. PROFICIENT

4. EXPERT

Dynamic content can be

Attribute-based

adjusted until or at time

clustering for better

of open

segmentation

Lifecycle campaigns

Time-based

(abandoned cart, post-

replenishment

purchase, etc.)

campaigns

Targeting segments like

Product

Individual subject line

VIPs, store proximity, etc.

recommendations

personalization

Real-time, cross-channel behavioral triggers

Novice Dynamic fields and names For companies with a way to associate names and email addresses, it’s table stakes to use dynamic field insertion and use those names. It’s not necessary to use them all the time, but the majority of marketers employing email personalization are using a (first, last, or full) name at least some of the time. Campaign Monitor has found that just using a name increases open rates by 26%.

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Dynamic fields or templates can be used for content well beyond customer name or text, although name is most common. Basic segmentation Limited segmentation is easily attainable with basic demographic attributes like age, gender, date of birth, or location. Campaign Monitor says that even limited segmentation based on limited data increases open rates by an average factor of 10x. For example, when Rip Curl introduced new wetsuits for women, they targeted a campaign by gender (women) and location (in the northern hemisphere). More marketers than ever adopted this kind of segmentation in 2015. Preference Center For larger brands in particular, a preference center is easy to implement and provides valuable data quickly and easily, directly via the customer (meaning data quality is good). Based on preference center data, marketers can easily perform basic segmentation, as well as implement welcome and onboarding campaigns.

ABOVE: A PREFERENCE CENTER CAN ASK FOR PROFILE DETAILS, NOT JUST EMAIL PREFERENCES

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Welcome or onboarding campaigns Welcome or onboarding campaigns are another basic tactic. Once a prospect opts into your email list (whether by subscribing, downloading a white paper, purchasing, etc.), this type of campaign welcomes them and can begin a series of engagements. Welcome campaigns are very effective but still not very common. It can take a dozen or more touches before delivering a Sales Qualified Lead (SQL) or conversion, and automating engagement with relevant engagement increases leads and sales. A/B Testing A/B testing has become a relatively basic capability. Many vendors provide an engagement meter to see how engaged people are with email to see how often to send them, and which are working best. A/B testing is a simple way to optimize engagement. Marketers can only run so many tests manually (which is why machine learning can be so valuable), but it’s easy to compare two different subject lines, promotional offers, product offerings, etc. and optimize accordingly. Competent Triggers Triggered-based actions, like retargeting someone who abandoned their cart, are relatively simple to implement. Those emails have an open rate 5x normal, says Ivy Shtereva, director of marketing at Yes Lifecycle Marketing. Devang Sachdev, director of product marketing at RichRelevance agrees that abandoned cart and other trigger-based campaigns can be very effective. But, he says, “While it’s one of the more common use cases, the maturity and adoption is still relatively low.” A lot of marketers have anxieties about triggers. “Many email marketers are reluctant to implement triggers unless they’re perfect,” says Shtereva. “They don’t have to be perfect, and they will have to be changed over time, but marketers are not aware of how incredibly helpful triggers are.” She cites an example where only 3.5% of a customer’s audience is reached by using triggers, but they generate 9% of revenue and 12% of website visits. Triggers are easy to set up and good candidates for testing.

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Lifecycle campaigns Lifecycle campaigns in particular can be good trigger-based campaigns. Not only the aforementioned welcome campaign or abandoned cart retargeting, but also post purchase thanks and upsell and, later, reactivation. Birthday and anniversary campaigns Birthday and anniversary campaigns are very easy to implement and, for retailers especially, get in front of a prospect when they have an especially high propensity to buy. “When brands send a ‘happy birthday, here’s 20% off ‘message, people very often buy,” says YesMail’s Shtereva. Birthdays have almost double the open rate and CTR compared with standard campaigns, and account for about 13% of trigger-based revenue. Anniversary campaigns are similar, but involve just the brand and customer, making it even more unique than a birthday, when others might also email you. Despite their success rate and the relative ease with which they can be set up, few are using birthday and anniversary campaigns today. Proficient Dynamic, time-based content Today’s marketers can dynamically assemble content as an email is opened, rather than when it’s sent. For example, if an email for a promotion is sent at 9am, it sells out by 10am, and then a customer opens the email 11am, then rather than have the customer get annoyed with a waste of time, a new message can be created in places of the original. Many marketing automation tools enable marketers to programmatically change the message this way. For example, Autopilot will look for the right code to inject based on the time its opened, rather than forcing marketers to send static content.

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Rules-based segmentation and content Segmentation efforts today remains mostly manual. Fewer than a third of big brands are not doing intelligent or dynamic segmentation, by creating rules or actions to segment, according to Sachdev. But even for those that are, many of those segments are served static content. Only about 15% of marketers are using both rules-based segmentation as well as dynamic content. Timers and replenishment campaigns By understanding when customers will need to refill, repurchase, or renew a product or service, marketers can set and forget time-based campaigns to follow up at the right time. This type of campaign can be for makeup, pet food, car service, and insurance, all the way to renewing a multi-million dollar contract. Campaign Monitor says this kind of tactic has resulted in a 70% open rate increase and 150% higher close of revenue. Product recommendations Companies with a commerce element can connect their ecommerce or CRM platforms with their email marketing or automation platform. Data from the former can be used to enrich the email database, but also to automate campaigns for relevant products based on real-time product interest. For example, Birchbox uses real-time purchase data that now flows directly into its email database. As a result, the company can set up automated campaigns for relevant products to individual customers.

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Expert Attribute-based clustering Most (web or omnichannel) personalization vendors are based on recommendation engine technology. This approach can be very valuable, especially for recommending specific products, articles, or services. However, customer attribute clustering can better segment prospects and customers as individuals. Moosejaw, an online retailer of outdoor clothing and gear with nearly $100 million in annual revenue used to be heavily dependent on discounts. After testing different discount levels for different segments, the company increased email revenues by 122% in a year, with more total orders and a higher average order value (AOV). Moosejaw did this with AgilOne’s Predictive Clusters. Others with similar attribute-based clustering include Salesforce’s Predictive Decisions and Amplero. Real-time, cross-channel behavioral triggers Marketers able to use data from across all significant customer touchpoints are best equipped to engage, support, or convert customers when they are most receptive. Web behavioral data is a critical part, but using mobile app data, or data from interactions with other departments like sales or customer service is also valuable to most marketers. Most marketing automation and email personalization vendors have integrations or APIs to facilitate bi-directional data transfer with a variety of other tools. Advanced marketers are able to use data from across channels to be more relevant and more selective about which channel is used to engage the customer.

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Individual targeting and personalization Some elements of email can be individualized more easily than others. Name and other unique customer details, like birthday, are obvious and easy to use. Others are harder to use and may require additional technology investment. Location from a mobile device can be used to determine proximity to a store or competitor’s store and trigger a one-off email. Some marketing automation tools have open time analysis and customization options. Marketers who want to send emails at exactly the most relevant time for every single individual, AudiencePoint has demonstrated ROI. Persado’s subject line personalization capabilities provide higher open and click through rates than manually creating and optimizing them.

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WHAT DOES THE FUTURE HOLD? We asked practitioners and vendors what they expect to grow in 2016. Here’s what we heard. Triggers Marketers are recognizing the value of using triggers to automate engagement and increase relevance. As marketing automation adoption in particular grows — which enables a variety of trigger-based engagement — using them will become standard practice. For more, see our report on Marketing Automation. Onboarding and lifecycle campaigns As triggers are increasingly adopted, onboarding and lifecycle campaigns will quickly increase in prevalence. These are low hanging fruit, with high returns on minimal investment. Mobile and location Location, especially on mobile, will be big in the coming year. That includes conditions based on location, like weather or proximity to a store. For example, if it’s hot there, offering a coupon for ice cream. This is important as mobile engagement continues to increase. Cross-channel Although email remains dominant, “it is still used as a sledgehammer by many,” says Autopilot’s CMO Guy Marion. Marketers are getting savvier about better targeting in email, but also using in-app messaging or ad retargeting as more precision tools.

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Behavioral data Email targeting and personalization is largely based on historical data today, yet behavioral data from web and mobile in particular provides valuable customer insight that can make email more timely and relevant. Several web personalization vendors in particular, like Reflektion, Monetate, RichRelevance, Certona, and others are now leveraging their real-time behavioral data and moving into email personalization. Predictive Predictive analytics extend the degree to which marketers can segment and target customers by automatically surfacing and segmenting prospects and customers based on values like propensity to buy or churn.

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Conclusion Email marketers are seeing massive lift in their KPIs using personalization, increasing open rate, click-through rate, and revenue, as well as lowering unsubscribe rate. Yet email marketers face challenges, with limited resources and often a lack of knowledge about options. Getting started isn’t hard. Use the Email Personalization Maturity Framework to evaluate where you are today. Use it to make your business case, if necessary, and then guide your investment of time, resources, and technology based on which priorities are highest for your marketing efforts. EMAIL PERSONALIZATION MATURITY FRAMEWORK

Segmentation

Content

1. NOVICE

2. COMPETENT

3. PROFICIENT

Preference center

Demographic

Dynamic behavioral

segmentation

segmentation

segmentation

Dynamic field insertion

Subject lines and media (images, video, attachments)

4. EXPERT Individualization; based on profiles, preferences, and behaviors

Products (individual

Subject, text, media,

recommendations)

sender details

Within 10 minutes

Real-time

Within a day (if Speed

using data for

Within an hour

segmentation at all)

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The options of tactics also depend on where you fall on the maturity spectrum and what technology you implement. EMAIL PERSONALIZATION TACTICS 1. NOVICE Personalized greetings, subject lines Onboarding/welcome campaigns A/B testing (subject line, message, promotion, etc.)

2. COMPETENT Trigger-based actions

3. PROFICIENT

4. EXPERT

Dynamic content can be

Attribute-based

adjusted until or at time

clustering for better

of open

segmentation

Lifecycle campaigns

Time-based

(abandoned cart, post-

replenishment

purchase, etc.)

campaigns

Targeting segments like

Product

Individual subject line

VIPs, store proximity, etc.

recommendations

personalization

Real-time, cross-channel behavioral triggers

For more on specific vendor categories, see our reports on marketing automation and web (increasingly “omnichannel”) personalization.

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Appendix USER SURVEY DETAILS This report contains user data from two surveys. The first is a survey of 506 marketers using some form of personalization across all channels, not just email. That data was also used to inform reports about customer identity and personalization processes across channels. A second survey was fielded specific to email personalization, which has 256 respondents. Two-thirds of respondents are at B2B businesses, and nearly a third are in small businesses (10-99 employees).

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VENDOR SURVEY DETAILS The following 62 companies were sent a vendor survey to help inform this research. The 33 in bold completed it: 1. Act-On Software

22. eTrigue

43. NetResults

2. Actito

23. Evergage

44. Pleisty

3. Adestra

24. Experian Marketing Services

45. RedEye

4. Adobe Campaign 5. Apptus Technologies

26. Granify

6. Autopilot

27. GraphicMail

7. Barilliance

28. Greenrope

8. Bluecore

29. Hubspot

9. BlueShift

30. Infusionsoft

10. BoomTrain 11. Callidus Software 12. Campaign Monitor 13. Canopy Labs 14. Certona 15. ClickMail 16. Constant Contact 17. Drip 18. Dynamic Yield 19. Eloqua [Oracle] 20. Emarsys 21. Epsilon

25. GetSmartContent

46. Reflektion 47. Responsys [Oracle] 48. RichRelevance 49. Right On Interactive 50. Sailthru 51. Sales Engine / Manticore

31. Intercom

52. Salesforce Marketing Cloud

32. iPresso

53. Salesfusion

33. Iterable

54. SAP hybris

34. LiveIntent

55. Selligent

35. Leadsius

56. SharpSpring

36. LeadSquared

57. Silverpop / Unica

37. Lyris

58. SMTP, Inc.

38. Mailjet

59. Teradata

39. Marketo

60. Unica [IBM]

40. MindMatrix

61. Vero

41. Monetate

62. WhatCounts

42. Movable Ink EMAIL PERSONALIZATION: INCREASE OPENS, CLICKS, AND REVENUE WITH THE RIGHT STRATEGIES AND TECHNOLOGIES

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These technology companies are composed of email service providers, marketing automation vendors, and other types of personalization vendors. Below is a breakdown of vendor types included. These vendors approach personalization in different ways.

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About VB Insight Research at VB is future-focused and predictive. It’s actionable. It’s something that you can rely on when making business decisions. That’s no simple matter. It requires more than pontification, more than a few desultory vendor interviews, and more than a few phone calls. It requires rigor, deep analysis, patient datacollection, and tested insights. That’s how we do research at VB, and that’s our commitment to you!

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