The Power of Purchase List Targeting

It’s important to have a trusted purchase list source. You should be informed of where the company gets its data, how often the data is updated and its policies on bad data. Once you have a good source, you need to take on the challenge of choosing your list options.

targetaudSince your response rate is directly related to who you are sending mail to, purchasing a mailing list can be a real challenge. There are so many options to choose from that it can be overwhelming. But first, it’s important to have a trusted purchase list source. You should be informed of where it gets the data, how often the data is updated and its policies on bad data. A couple of big purchase list players are Experian and Acxiom — you can check them out, as well as many other reputable list brokers. Once you have a good source, you need to take on the challenge of choosing your list options.

Top industry list option examples include:

  • Nonprofit: Income, net worth, age, children, causes donated to in the past, organization membership, fundraising engagement, location
  • Retail: Number of children, income, age, gender, apparel purchase habits, brands, online shopping habits, location
  • Political: Children, homeownership, voting propensity, location, age, political party affiliation
  • Entertainment: Age, income, children, hobbies, purchase history, location, marital status
  • Healthcare: Age, income, number of children, location, gender, homeownership
  • Education: Age, income, gender, highest level of education, location, interests

You may pick from demographics as well as psychographics. There are so many options, make sure to give yourself time to look over what will target your best potential customers. You want to get the right offer to the right people — the more targeted your list, the better response you are going to get. Marketing personas are fictional representations of your ideal customers, so if you have mapped personas beforehand, it will be easier to make your selections.

You can pre-map customer personas by taking a look at your best customers: Who are they? The more details you have, the more accurate the persona will be. Look for trends in how your customers find you and what they buy. Make sure you are capturing important information about customers in your data so that you can use it to build your personas. You should also interview customers to obtain key answers directly from the source. Too many assumptions can cause you to create an inaccurate persona.

Once you know the personas you are looking for, choosing the right selections for your list becomes easier. Select the options that best represent your customers. The more characteristics you pick, the better targeted your list will be. But keep in mind that more selections often result in a higher-priced purchase list. So make sure you only use the options that really reach your target.

Your list is now ready! Your final ingredients for successful direct mail are your creativity and your offer. Don’t spend all your time on the list and forget these other two components — without all three working together, your direct mail will not generate the response you are looking for. Make your offer clear and concise. Make your creative design catching, but not overwhelming. Give people a reason to read your direct mail.

5 Effective Audience Segments for Digital Marketing

Too often, we talk to marketers whose idea of audience segmentation is not just limited, but terribly egocentric. You are, I’m sure, at least a few steps ahead of the worst offenders, but you may still be leaving opportunities unaddressed. Here are some new ways to think about your audience.

Hitting the Target Audience SegmentToo often, we talk to marketers whose idea of audience segmentation is not just limited, but terribly egocentric. By egocentric, I mean that they view their audience segments in terms of their own product or service lines: Segment 1 is the folks we sell this service to. Segment 2 is the folks we sell that service to.

You are, I’m sure, at least a few steps ahead of the worst offenders, but you may still be leaving opportunities unaddressed. Here are some new ways to think about your audience.

1. Industry

Industry considerations are probably the grand-daddy of all segmentation. Even folks who think egocentrically about their audience are smart enough to realize that their products are likely to be appealing in different ways to different audiences. The features are the same, but the benefits change depending on the industry’s needs.

You can capitalize on this by creating content that is industry-specific and highlights the benefits that are most pertinent to that industry’s most common needs. As with all of the segmentation examples we’re discussing, this can be implemented in some combination of your website landing pages, email marketing subscriptions and even speaking engagements, among other things.

2. Company Size

Just as different industries will have different needs, so will organizations of varying sizes. Again, you’ll want to focus on differentiation of benefits of your product or service. For example, your product’s ability to eliminate the need for more staff as business grows is likely to be more valuable to a large organization than a small one — saving a few hours a week isn’t going to change the head count in an organization where those savings are multiplied by only one employee. But if the multiplier is dozens of employees, that’s a different story.

3. Role

The CFO may be the decider-in-chief when it comes to adding products or services for accounting and compliance teams, but her interests will be quite different from those of an in-the-trenches accountant in the same organization. If she’s smart, she’ll let those accountants have their say in what tools they get to use for their tasks. If you’re smart, you’ll position your solutions differently to each role. For one group you might want to highlight how your solution makes their lives easier day-to-day. For the other, cost savings or consistency across the organization might be the pain point to address.

4. Past Purchase Behavior

You don’t interact with your close friends the same way you do with acquaintances or complete strangers, do you? So why wouldn’t you differentiate your marketing for new prospects, lapsed customers and key accounts?

Technology is getting all the press these days, but good solid relationships matter, too. Talking to your customers can help you understand typical paths as companies grow (or contract) and mature or morph into new businesses. With that understanding, you can pro-actively engage with customers who are starting down similar paths. There’s real magic in knowing what a client will need before he does!

5. Content Consumption Behavior

Technology again gets a starring role in the realm of content consumption behavior. Tracking what content is most popular in aggregate is fantastic; it guides you to create more content like it. But tracking individual preferences is powerful, too, since it can help you make content recommendations that are most relevant to that prospect’s needs — and most useful to you in helping them through the buyer’s journey.

Not all of these segmentation approaches will make sense for your business, but technology continues to make tracking behavior and segmentation easier than ever, so you should be revisiting these concepts on at least an annual basis. As your business changes so might the ways you drill down into your funnel to best meet your prospects’ needs.

Your Website Is a Conversation, Not a Presentation

Is your website a conversation with your clients and prospects? Or is it a presentation?
This can be a tough distinction to make because, of course, your website is a proxy for you. You’re not actually sitting face-to-face with your prospects. But even without the back-and-forth of an actual conversation, you can get better Web results by striving to create a dialogue by encouraging engagement with your audience.

Social conversationIs your website a conversation with your clients and prospects? Or is it a presentation?

This can be a tough distinction to make because, of course, your website is a proxy for you. You’re not actually sitting face-to-face with your prospects. But even without the back-and-forth of an actual conversation, you can get better Web results by striving to create a dialogue by encouraging engagement with your audience.

In Other Words, You Want to Control the Narrative, Not Dominate It

Of course, you can’t control where your site visitors are going to click next. That’s the beauty and the curse of the Web’s non-linear nature. You can’t even control whether they start at “the beginning”. (If your social media, SEO and email marketing are relevant players, your website home page isn’t always going to be their entry point.)

But You Can Encourage Them to Take the Action You Desire

Strong copy, intelligent presentation, and a little bit of coding savvy can work wonders for your site — but for starters, you’ll want to define a solid set of goals. You have to know the action you ultimately want your site visitors to take. And you have to know, as the conversation moves along, what you want your audience to be thinking about. The thoughts your website provokes in consumers will be the best determinant of their course of action.

Recognizing that your audience has more options than “previous” and “next” has the added benefit of forcing you to stay tightly focused on your topic and think in terms of your audience’s interests, not your own agenda.

This is where many marketers go wrong. Staying focused does not necessarily mean diving into the minutiae of a topic. Nor does it mean forcing prospects to move forward with no destination possible other than your conversion point.

Because, of Course, There’s Always Other Options

But not options you want pursued: the browser’s close button, or your competitor’s website. Instead, you must guide them toward the action you ultimately want them to take by offering a range of possible paths. They may feel it’s time to reach out and contact you by phone. Or if their need is less pressing, they might want to subscribe to your newsletter and learn more over time. Or a trip to your “related materials” section might be in order, so they can dive into a topic in more detail.

You have to offer these options because there’s no way of knowing where a prospect is in the buying process when they arrive at your site.

There’s a fine line to be walked here: Just as droning on and on about a topic is likely to turn off prospective clients, so too can offering them every option under the sun.

With the exception of certain pages of your website — the home page, most notably — most of your digital marketing should be focused enough to appeal to just a select segment of your audience. They should be reading your email newsletter because it is likely to be of interest to them. That newsletter should contain links to the pages of your site that will be most relevant to their needs. And the calls to action embedded in that page should lead them to the next piece of content that addresses their needs and creates your case as the best solution for them.

The more audience segments you are trying to appeal to, the more difficult this can be, so it is important to craft your online marketing with specific segments in mind. Next time, we’ll talk a bit more about effective audience segmentation.

Segments vs. Personas

Personalization may mean different things to marketers, but we may break it down to, one, reacting to what you specifically know about the target and, two, proactively personalizing messages and offers based on both explicit and implicit data.

Tina ThrillseekerPersonalization may mean different things to marketers, but we may break it down to, one, reacting to what you specifically know about the target and, two, proactively personalizing messages and offers based on both explicit and implicit data.

The first one is more like “OK, the target prospect is clicking a whole a lot in the hiking gear section, so show him more related products right now.” This type of activity requires technical know-how regarding Web and mobile display techniques, and there are lots of big and small companies that specialize in that arena. Simply put, what good is all this talk about data and analytics, if one doesn’t know how to display personalized messages to the target customer? If you “know” that the customer is looking for hiking gear, by any means, usher him to the proper section. There are plenty of commercial versions of “product-to-product” matching algorithms available, too. We can dissect the data trail that the consumer left behind later.

All those transaction data trails become integral parts of the “Customer-360” (yet another buzzword of the day). Once that type of customer-centric view (a must for proper personalization) becomes a reality, however, marketers often realize “Oh jeez, we really do not know everything about everyone.” That is when the analytics must get into a higher gear, as we need to project what is known to us to the unknown territory, effectively filling in the gaps in the data. I’d say that is the single most important function of statistical modeling in the age of abundant, but never complete data — a state of omnipotence that we will never reach.

Then the next natural question is how we are going to fill in such gaps? In such situations, many marketers jump into an autopilot mode to use what we have been calling “segmentation” since the ’70s and ’80s (depending on how advanced one was back then). But is it still a desirable behavior in this day and age?

As “data-driven” personalization goes, no, using a segmentation technique is not a bad thing at all. It is heck of a lot more effective than using raw data for customized messaging. As a consumer, we all laugh at some ridiculous product suggestions, even by so-called reputable merchants, and that happens because they often enter raw SKU-level data into some commercial personalization engines.

If we get to have access to segments called “rich and comfortable retirees” or “young and upcoming professionals,” why not make the most of them? We can certainly use such information to personalize our offers and messages. It is just that we can do a lot better than that now.

The traditional segmentation technique has its limitations, as it tends to pin the target into one segment at a time. Surely, we all somewhat look like our neighbors, but are we so predictably uniform? Why should anyone be pigeonholed into one segment, and be labeled along with millions of others in that group? Even for rich and prestigious-sounding segments, it may be insulting to treat every member equally, as if they all enjoy the same type of luxury travel and put their money into the same investment vehicles. Simply put, in the real world, they do not.

Every individual possesses multiple dominant characteristics. For that reason alone, it is much more prudent to develop multiple personas and line them around the target consumer. The idea is the opposite of “group them first, and label them later”-type segmentation. It is more like “Build separate personas for all relevant behaviors, then find dominant characteristics for one person at a time.” With modeling techniques and modern computing power, we can certainly do that. There already are retailers who routinely use more than 100 personas for personalized campaigns and treatments.

The following chart compares traditional clustering/segmentation techniques to model-based personas:

Screen Shot 2016-06-08 at 11.16.08 AM

This segment vs. persona question comes up every time I talk about analytics-based personalization. It is understandable, as segmentation is an age-old technique with long mileage. Marketers feel comfortable around the concept, as segments have been the common language among creative types, IT folks and geeky analytical kinds. But I must point out that the segments are primarily designed for “general” message groups, not for individual-level personalization with wider varieties.

Plus, as I described in the chart, personas are more updatable, as they are much more agile than a clunky segmentation tool. I’ve seen segmentation tools that boast of more than 70 to 90 segments. But the more specific they become, the harder it is to update all of those with any consistency.

Conversely, personas are built for one behavior/propensity at a time, so it is much easier to update and maintain them. If the model scores seem to be drifting away from the original validation, just update the problematic ones, not the whole menu.

In the end, the personalization game is about which message and product offer resonates with the customers better. Without even talking about technical details, we know that more agile and flexible tools would have advantages in that game. And as I mentioned many times in this series, matching the right product and offer to the right person is a job anyone can do without a degree in mathematics. Just bring your common sense and let your imagination fly. After all, that is how copywriters imagine their target; by looking at the segment descriptions. That part isn’t any different from looking at the descriptions of personas instead; you will just have more flexibility in that matchmaking business.

Persona Marketing Tricks

How does a marketer go about creating the most effective set of personas? The first step is to create the 360-degree customer view out of available data. Personalization must be about the person, not about channel, product or even brand.

Personal.jpgHow does a marketer go about creating the most effective set of personas? The first step is to create the 360-degree customer view out of available data. Personalization must be about the person, not about channel, product or even brand.

For that, all event- and transaction-level data must be rearranged around the target individuals. Often, this data step turns out to be the first major hurdle for the marketers.

Then marketers, along with data scientists, should draw the list of required personas. After all, all analytical work must start with a clear definition of targets, and the targets must be set with clear business goals.

If you could ask for any personas for your marketing efforts, what would they be? Surely, the list would vary greatly depending on the lines of business that you are in. Obvious ones — such as “High-Value Customer,” “Frequent Shopper” or “Online Buyer” could be helpful for all types of retailers.

Going beyond that, marketers must expand their imaginations and think about the list from the customer’s point of view, while keeping a sight on the products and services that are to be offered to them. We must look at this as an ultimate “match-making” exercise between the buyers and the products, way more sophisticated than a rudimentary product-to-product level match (as in “If you purchased product A, you must also be interested in product B”).

The idea is to create personas imagining what you are going to do with them in marketing campaigns. “Frequent Flyer” maybe an obvious choice, but would you need a related but different one called “Frequent Business Traveler”? Would you extend the “Young Family” to “Avid Theme Park Visitors”? Why not both?

For B-to-B applications, we can think of many more along the lines of a “Consumable/Repeat Purchase” persona and “Big Ticket Items,” but the idea is to have both of them on the menu, as one may reveal both types of traits at the same time.

Similarly, if you are in a telecommunication business, what would be a good set of personas for broadband service? What type of personas can explain the “why” part of the equations? Simply for the sales of broadband, we can think of the following set as a starter:

  • Big Family
  • Home Office
  • High-Tech Professional
  • Avid Gamer
  • Avid Movie Downloader
  • Voice-over IP User
  • Frequent International Caller
  • Early Adopter
  • Etc., etc.

The key is matching the propensity of a customer and the product, and showing compelling reasons why they need to purchase a particular product. We all routinely consume all kinds of products and services, but each of us does it for different reasons. Personalizing the message based on known or inferred personal traits is the key to stand out in the age of over-communication.

Once we imagine the list, there are ways to build the personas. I can say that with conviction, as I’ve seen a persona called “NASCAR Fan” being used in an election season. So, don’t be shy and start being creative on your whiteboard today.

5 Data-Driven Marketing Catalysts for 2016 Growth

The new year tends to bring renewal, the promise of doing something new, better and smarter. I get a lot of calls looking for ideas and strategies to help improve the focus and performance of marketers’ plans and businesses. What most organizations are looking for is one or more actionable catalysts in their business.

The new year tends to bring renewal and the promise of doing something new, better and smarter. I get a lot of calls looking for ideas and strategies to help improve the focus and performance of marketers’ plans and businesses. What most organizations are looking for is one or more actionable marketing catalysts in their business.

To help you accelerate your thinking, here is a list of those catalysts that have something for everyone, some of which can be great food for thought as you tighten up plans. This year, you will do well if you resolve to do the following five things:

  • Build a Scalable Prospect Database Program. Achieving scale in your business is perhaps the greatest challenge we face as marketers. Those who achieve scale on their watch are the most sought-after marketing pros in their industries — because customer acquisition is far from cheap and competition grows more fiercely as the customer grows more demanding and promiscuous. A scientifically designed “Prospect Database Program” is one of the most effective ways great direct marketers can achieve scale — though not all prospecting databases and solutions are created equally.

A great prospecting database program requires creating a statistical advantage in targeting individuals who don’t already know your brand, or don’t already buy your brand. That advantage is critical if the program is to become cost-effective. Marketers who have engaged in structured prospecting know how challenging it is.

A prospect database program uses data about your very best existing customers: What they bought, when, how much and at what frequency. And it connects that transaction data to oceans of other data about those individuals. That data is then used to test which variables are, in fact, more predictive. They will come back in three categories: Those you might have “guessed” or “known,” those you guessed but proved less predictive than you might have thought, and those that are simply not predictive for your customer.

Repeated culling of that target is done through various statistical methods. What we’re left with is a target where we can begin to predict what the range of response looks like before we start. As the marketer, you can be more aggressive or conservative in the final target definition and have a good sense as to how well it will convert prospects in the target to new customers. This has a powerful effect on your ability to intelligently invest in customer acquisition, and is very effective — when done well — at achieving scale.

  • Methodically ID Your VIPs — and VVIPs to Distinguish Your ‘Gold’ Customers. It doesn’t matter what business you are in. Every business has “Gold” Customers — a surprisingly small percentage of customers that generate up to 80 percent of your revenue and profit.

With a smarter marketing database, you can easily identify these customers who are so crucial to your business. Once you have them, you can develop programs to retain and delight them. Here’s the “trick” though — don’t just personalize the website and emails to them. Don’t give them a nominally better offer. Instead, invest resources that you simply cannot afford to spend on all of your customers. When the level of investment in this special group begins to raise an eyebrow, you know for certain you are distinguishing that group, and wedding them to your brand.

Higher profits come from leveraging this target to retain the best customers, and motivating higher potential customers who aren’t “Gold” Customers yet to move up to higher “status” levels. A smart marketing database can make this actionable. One strategy we use is not only IDing the VIPs, but the VVIP’s (very, very important customers). Think about it, how would you feel being told you’re a “VVIP” by a brand that matters to you? You are now special to the brand — and customers who feel special tend not to shop with many other brands — a phenomenon also known as loyalty. So if you’d like more revenues from more loyal customers, resolve to use your data to ID which customers are worth investing in a more loyal relationship.

  • Target Customers Based on Their Next Most Likely Purchase. What if you knew when your customer was most likely to buy again? To determine the next most likely purchase, an analytics-optimized database is used to determine when customers in each segment usually buy and how often.

Once we have that purchase pattern calculated, we can ID customers who are not buying when the others who have acted (bought) similarly are buying. It is worth noting, there is a more strategic opportunity here to focus on these customers; as when they “miss” a purchase, this is usually because they are spending with a competitor. “Next Most Likely Purchase” models help you to target that spending before it’s “too late.”

The approach requires building a model that is statistically validated and then tested. Once that’s done, we have a capability that is consistently very powerful.

  • Target Customers Based on Their Next Most Likely Product or Category. We can determine the product a customer is most likely to buy “next.” An analytics-ready marketing database (not the same as a CRM or IT warehouse/database) is used to zero-in on the customers who bought a specific product or, more often, in a specific category or subcategory, by segment.

Similar to the “Next Most Likely Purchase” models, these models are used to find “gaps” in what was bought, as like-consumers tend to behave similarly when viewed in large enough numbers. When there is one of these gaps, it’s often because they bought the product from a competitor, or found an acceptable substitute — trading either up or down. When you target based upon what they are likely to buy at the right time, you can materially increase conversion across all consumers in your database.

  • Develop or Improve Your Customer Segmentation. Smart direct marketing database software is required to store all of the information and be able to support queries and actions that it will take to improve segmentation.

This is an important point, as databases tend to be purpose-specific. That is, a CRM database might be well-suited for individual communications and maintaining notes and histories about individual customers, but it’s probably not designed to perform the kind of queries required, or structure your data to do statistical target definition that is needed in effectively acquiring large numbers of new customers.

Successful segmentation must be done in a manner that helps you both understand your existing customers and their behaviors, lifestyles and most basic make up — and be able to help you acquire net-new customers, at scale. Success, of course, comes from creating useful segments, and developing customer marketing strategies for each segment.

Better Together: Pair Google Analytics With Google AdWords for Stronger Campaigns

If you have not yet linked your AdWords campaign with Google Analytics, you are missing out on some much deeper tracking possibilities that can ultimately help you build a stronger campaign. Here are a few things you can do with Google Analytics.

If you have had a Google AdWords campaign up and running for a while, you are probably already familiar with the various AdWords tracking tools. With a simple bit of code, you can track every conversion that takes place on a particular “thank you” or receipt page. You can also import offline conversions, which are a bit more complicated to set up, but very much worth the effort. If you have not yet linked your AdWords campaign with Google Analytics, however, you are missing out on some much deeper tracking possibilities that can ultimately help you build a stronger campaign. Here are a few things you can do with Google Analytics.

User Behavior Tracking
Google AdWords lets you track conversions. However, it doesn’t give you much insight about the visitors who did not convert. Learning more about their behavior on your site can help you identify areas that you can improve, ultimately increasing your conversion rate.

For example, Google Analytics will tell you how many pages the prospect visited, the amount of time they spent on your website, and whether or not they immediately bounced away. In other words, you can track the user behavior of your AdWords traffic to see what those prospects are doing.

Think of AdWords conversion tracking like a light switch. It’s either on or off. You either have conversions or don’t. And when you don’t, then excuse the pun, but you’re in the dark about why the AdWords visitors are not converting. This is why Google Analytics is such a great tool to add as you analyze your advertising performance.

E-commerce and Funnel Tracking
Google Analytics allows you to go deeper than Google AdWords conversion tracking does. If you sell products online, you can use Google Analytics’ e-commerce tracking to monitor specific information about product revenues, transaction details, and length of time from initial interest through completed sale.

Multichannel funnels in Google Analytics allow you to see each incremental step that buyers go through on their way to a completed sale. For example, your AdWords campaign may be driving 100 sales per month, but your AdWords reports do not tell you if those customers interacted with any other marketing campaign. By using the Multichannel funnels reports, you’ll see if organic search, referrals, email marketing, or another channel is playing an important role in your AdWords conversions.

Prospect Segmentation and Retargeting
Retargeting, or displaying your ads to prospects who have recently visited your site, is an important part of a solid Google AdWords strategy. Google Analytics can streamline this process for you by automatically segmenting your visitors and creating lists of people who are likely to buy. If you prefer to create your own segmented lists manually, Google Analytics helps you drill down to find your prospects’ demographics, location and online interests.

Split Testing Landing Pages
Success with AdWords advertising is not just about correctly setting up and optimizing your campaigns within Google AdWords. You must also properly setup and optimize your landing pages to maximize your sales. That means split testing your landing pages to find the best copy and layout for your target market.

Luckily, Google Analytics provides a simple and free tool called “Experiments” to split test your landing pages. By using Experiments within Google Analytics you can test two different landing pages to see which one converts more visitors into sales.

Layer New Dimensions onto Reports
The power of the Google Analytics and Google AdWords pairing is even more evident when you run reports within Google Analytics. For example, you can review ad performance for per ad placement on the page, mobile user behavior per keyword, and many other reports to learn more about your ads performance.

Of course, these techniques are just the tip of the iceberg. Both Google AdWords and Google Analytics provide strong, dynamic tools for monitoring your website and ad campaigns. When paired together, they allow you to sift through the data in whole new ways. Think outside the box, play around with the tools, and find your own preferred tracking combinations.

5 Elements to Move From Segmentation to Personalization

There is a big difference between segmentation and personalization. Most marketers do segmentation pretty well — they use some sort of marketing database or CRM system to identify audience members who will receive an outbound campaign. Sometimes a particular segment is identified as a “persona,” where a description of a fictional member of the segment is used to gain clarity and consensus among the teams — and to help align content that will best resonate.

However, segmentations alone are static, because they are based on a marketing calendar. They solve yesterday’s marketing challenge. People don’t interact with brands along a calendar. They interact across channels and in non-linear methods based on a multitude of stimuli — many of which are not controlled by the brand. Personalization is an additional layer on top of segmentation to ensure that campaigns are responsive to audience behaviors and relevant to their needs.

To move from effective segmentation to engaging personalization, there are five elements to consider:

1. Dynamic Targeting. Our multi-device browsing habits and constantly shifting interests will break traditional segmentation models. Broad segments like “gadget enthusiasts” or “Millennial” will no longer work. We must use the automation technology to create dynamic and agile models that can adapt to behaviors as they occur, and personalize the content at the individual level, not the segment or campaign level. Our goal is to target individuals based on a collection of identifiable characteristics and behaviors, rather than targeting a collection of individuals who share characteristics. As I’ve often said in planning meetings, “The way customers act, you’d think each one was a different person!”

2. Effective Content. Content must sell. Always. Too much of the marketing content out there is merely interesting. That has value, except it isn’t realistic to think that anyone has time to read everything that is interesting. We’ve got to set the bar higher. Content must be viewed as part of (or at least aligned to) the product – it must help solve the same problems that the product solves. This includes re-thinking how offline media assets get turned into digital experiences. For example, break up a TV spot into dozens of snackable visual elements with hyperlocal additions for price, store locations and availability. That turns content into commerce, and brings our content marketing closer to the analytics-driven marketing that drives revenue.

3. Revisit Cross-Channel Data Collection. While still complicated, cross-channel data is starting to become more actionable. A big part of the early success has nothing to do with technology, but with people. CMOs are realizing that there are efficiencies and opportunities if all channels are working toward the same goal, with the same view of the customer. To improve the maturity of these solutions, we will likely need more experimentation around both data collection and insights-driven campaign management. This unified, actionable view of the customer is still ahead of most companies, but most of us can get started by combining channels at key moments of the lifecycle.

4. Customer-level Media. Several campaign management vendors are tackling the challenge of analysis and customer engagement across owned, earned and paid media. Ask your vendors about their plans for improving customer journey mapping. Traditional linear customer journey maps are obsolete — you need technology to help you dynamically associate content and campaigns across the myriad individual experiences. At the same time, media buying is increasingly at the customer level, via hashtag identification and CRM-based targeting. Bring your own data to Facebook and Twitter, and find your key audiences across the Web — in the context that makes sense for your product and brand. 2015 will continue to see integrations through the various data services platforms (DSPs) and ad retargeting programs.

5. Brand Promise Ubiquity. Every interaction with a brand must live up to the brand promise – not just the how and what we do, but the why we do it. Marketing data can’t stay in the marketing department; it’s got to be utilized throughout the organization. Marketers are more curators of experience than controllers (broadcasters) of message, and our brand promise must be the banner under which every employee, agency and partner interacts with people. A recent study by research and consulting firm Software Advice found that using big data to match sales and service reps to the individual needs and personalities of customers will significantly increase satisfaction, call efficiency and sales revenue. That is just one example of how marketing must collaborate with other departments to optimize customer experience across every touchpoint.

How are you using integrated data to turn your segmentation strategy into a personalization strategy? Share your thoughts in the comments below.

Email Segementation: Make Your List More Than the Sum of Its Parts

Segmentation is also one of the most powerful and often under-utilized features of email automation applications. Though automation makes the process simpler, many marketers are put off by overhead in the form of upfront work required to develop and deploy rules and testing scenarios that result in more effective targeting and conversion. Should they bother?

Segmentation is the process of grouping names within your list into like interests, position in the buying cycle, demographics or other criteria relevant to your business.

Segmentation is also one of the most powerful and often under-utilized features of email automation applications. Though automation makes the process simpler, many marketers are put off by overhead in the form of upfront work required to develop and deploy rules and testing scenarios that result in more effective targeting and conversion. Should they bother?

Simply put: The answer is a resounding yes.

Using forms and engagement tracking, marketers can collect more information than ever before, and advanced data collection—progressive profiling—lowers form abandonment while acquiring new data through the querying of only data that has not yet been collected. When forms alone are not enough, email messages can be designed to A/B or multivariate test whole groups in order to garner specificity that leads to segmentation.

Segmenting lists using all of this type of data means you can selectively choose your most active (or profitable) groups, deselect the inactive, and develop campaigns designed to specifically reengage those who still hold promise. Data combined with automation means we benefit from better conversions and our prospects and leads benefit from messages in which they are truly interested. Targeted emails translate to better ROI in virtually every study.

Not only does segmentation make money through higher conversions, it saves money, too. When audiences are not separated into segments and are sent generic messages, open rates are lower. According to a study from MarketingSherpa, segmented emails get 50 percent more clicks than their untargeted counterparts.

Despite all the benefits of segmentation, not all marketers are onboard. For instance, Experian found that even though targeted email campaigns have a 40 percent higher open rate, 80 percent of marketers email the same content to an entire group.

Are businesses and marketers overcomplicating the process? Segmentation can be as simple or as complex as fits your needs, but customizing the process and making it unique to your business can give you the edge over competitors.

6 Steps to Segmentation

  1. Set a quantifiable and measurable goal for your campaign.
  2. Ensure your list contains enough names that it will still result in meaningful data, even after segmentation.
  3. Create segments using any data important to your business, such as: behavior, demographics, position in the sales funnel, and so on.
  4. Identify the most valuable segments—those that present the greatest opportunities.
  5. Create targeted messaging specifically designed to engage each segment.
  6. Track and measure results.
  7. When you treat new and current subscribers in the same manner and send them the same messages, you are missing one of the most important ways to nurture your lead to purchase. Segmentation can be as simple as dividing your list into new and current leads, but other ideas include:
  • Age
  • Gender
  • Marital status
  • Income
  • Occupation
  • Education
  • Presence of children
  • Owner vs. renter
  • Length of residence
  • Lifestyle segmentation
  • Past purchase
  • Last visit to website
  • Pages visited at website
  • Resources downloaded

Explicit data are demographics such as company size, industry segment, job title and geographic location.

Implicit data are the recipient’s actions or interactions, such as those who open, click, download a resource, watch a video, visit your website, share your content, and so on.

For some businesses, even though they have a large list, the list does not contain enough data to enable meaningful segments—but all is not lost. Many companies provide list-append services that allow you to add data to your current list by matching on a unique bit of data you do have, such as the email address.

Another segmentation idea is to identify those within your list who are returning customers and those with the highest value order. These two groups are generally the most valuable to your company and therefore warrant especially targeted messaging and hand-holding.

Segments can even be divided further into sub-segments, and those sub-segments divided again, and so on. However, creating relevant content for each segment is not without effort, so it’s best to not subdivide your list to the point where there are not enough names in the sub-segment to justify the work required.

With segmentation; you can greatly improve message relevance; set up better A/B and multivariate testing; target your audience with subject lines, designs, and images that resonate with the individual; and acquire higher click-thru and sales rates.

Bad Thing! Or Why Segmentation by Consumer Attitudes May Be Dangerous

For years, B-to-B and B-to-C marketers have relied on attitudinal segmentation research to help them group their current customer base, and potential customers as well, for communication, promotion, marketing and experience initiatives. The thesis has been that, by asking a small, but meaningful, set of attitudinal questions, they would be able to develop an index, algorithm or framework equation that ranked these consumers by propensity to buy, both near-term and long-term.

For years, B-to-B and B-to-C marketers have relied on attitudinal segmentation research to help them group their current customer base, and potential customers as well, for communication, promotion, marketing and experience initiatives. The thesis has been that, by asking a small, but meaningful, set of attitudinal questions, they would be able to develop an index, algorithm or framework equation that ranked these consumers by propensity to buy, both near-term and long-term.

These frameworks—they’re arithmetic, so we can’t call them “models”—typically include questions regarding the importance of elements like value for money, acting with the consumer’s interests in mind, credit and payment terms, having knowledgeable employees, offering products which will meet the consumer’s needs, and the like. From these questions, basic segment categorization can be determined; and, once these three, four or five segments are established, we’ve often seen marketers go on to build assumptive plans and conduct further, more detailed, research around them.

The goal of these approaches is to produce attitudinal segments, which the questions can predict with high accuracy, often in the 80 percent or 90 percent range. This creates what economists would call a “post hoc ergo propter hoc” situation, Latin for “after this; therefore, because of this.” It is a logical fallacy, essentially saying that A occurred (the responses to the attitudinal questions); and then B occurred (the cuts, or segments, of consumers). Thus, A caused B. Once the B, or segment creation, stage has been established, further fallacies, such as creating reliable marketing, operational and experiential strategies around these supposed propensities, can be built. It’s a classic situation, where correlation is thought to be the same as causation. As your economics or stat professors may have told you, correlation and causation are far from being identical concepts.

As a consultant and analyst, I’ve seen this result of this application of research and analytics play out on a firsthand basis on multiple occasions. Here’s a recent one. A client in the retail office products market had been using an attitudinally derived element importance question framework for small business market segmentation purposes. The segment assumptions went unquestioned until followup qualitative research was conducted to better shape and target their planned marketing and operational initiatives. Importance of certain products and reliable service were identified in the research as key areas of focus and opportunity for the office products retailer; but, in the qualitative research, power of both focus areas appeared, anecdotally, to be consistent across all segments. And, even though implied supplier roles were suggested to build purchases, this was much more “leap of faith”-based on the established quantitative research segment personas than actual qualitative research findings.

There are related issues with what we can describe as quasi-behavioral measures, such as single question metrics (likelihood to recommend to a friend or colleague or the amount of service effort required on the part of a consumer); or traditional customer loyalty indices (where future purchase intent is included, but also attitudinal questions such as overall satisfaction). It’s not that they don’t offer some segmentation guidance. They do—on a macro or global level; but they tend to be less effective on a granular level, especially where elements of customer touchpoint experience are involved.

And, they tend to have limitations as predictors of segment behavior, a key business outcome for marketers and operations management. When compared to research and analysis techniques, such as customer advocacy and customer brand-bonding, which are contemporary, real-world frameworks built on actual customer experience—high satisfaction scores, high index scores and high net recommendation scores produced likely future purchase results (in studies across multiple industries) which were often 50 percent to 75 percent lower than advocacy or brand bonding frameworks. I’d be happy to provide proof for anyone interested in reviewing the findings.

So, that’s the scenario. The challenge, and potential danger, for marketers and those responsible for optimizing customer experience is that these attitudinal and quasi-behavioral questions are just that—attitudes and quasi-behaviors. Attitudes are fairly superficial feelings, and tend to be both tactical and reactive. And, because they are so transitory, their predictive value is often unstable and unreliable. Quasi-behaviors are also open to many similar challenges. More importantly, attitudes and quasi-behaviors are not behaviors, such as high probability downstream purchase intent based on actual previous purchase, evidence of positive and negative word-of-mouth about a brand based on prior personal experience, and brand favorability level based on experience. These are especially valuable in understanding competitive set, and they have real, and very stable, predictive and analytical value for marketers.

As Jaggers, the lawyer, said to Pip in Charles Dickens’, “Great Expectations,” take nothing on its looks; take everything on evidence. There’s no better rule.” For marketers, that’s excellent shorthand for taking everything on behavior, and perceptions based on documented personal experience, rather than attitudes and quasi-behaviors.