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Must Marketers be Data Scientists?

Big data is having big effects on content marketing, nowhere more than in its ability to make sense of the complexity of human language. Understanding data science is necessary for agile marketing in 2019. Here’s how marketers can utilize data to hone their craft.

Mining for Meaning

Most web content consists of unstructured text. Mining this text for meaning and relevance is what search engines do. Search engines provide you with what they think are the most relevant and meaningful experiences, based on your search keywords. Understanding those results is the primary clue agile marketers use to better understand audience intent.

How does this work? Search engines are giant natural language processing engines that produce an urban dictionary full of definitions of keywords based on how they are used in digital media. In a sense, search engines “understand” how we use natural language over time. (This is why there’s so much hidden value in site search.)

Testing out Answers

The clues from this natural language processing rarely lead to cut-and-dried answers but are analyzed as statistics. Agile marketers use the data to make decisions about information their target audiences are the most likely to need. They provide the information in ways they think will be most useful to them. But, all things considered, multiple versions of the same information are equally likely to serve audience needs. This is where agile marketers are equally likely to serve audience needs. Marketers become data scientists–by serving multiple versions of the same digital experiences randomly to their audiences and testing the results. The experiences that get the best results win. 

This technique, known as A/B testing or multivariate testing, yields performance data that provides an ever-more-clear picture of how to better serve the target audience. A/B testing pits one variant against another (A vs. B) while the more powerful multivariate testing allows hundreds of even thousands of possibilities to compete with each other for supremacy. Patterns that tend to yield better results can be used as shortcuts by other digital marketing teams within the organization.

Agile Marketing is Machine Learning

In this way, agile marketing can sometimes be thought of as a form of machine learning, where the inputs of the machine are the practices and the outputs are improved performance. As the machine gets ever better at detecting working patterns for the target audience, it “learns” to optimize digital assets over time.

The machine is not just an optimization engine, however. The machine is a prioritization engine. Every marketer is faced daily with a challenge to do more with less. That means continually examining the mix of activities and weeding out poor performers and building new ones in their place, based on the data.

The market is constantly in flux, and a savvy marketer is continuously adjusting the ix to match shifting audience needs and business priorities. That’s why behavioral data is the next step in the game: incorporating your visitor’s behaviors to truly understand your intent and adapt to it. This kind of agility was not possible prior to digital marketing. Now it is table stakes.

The 1H B2B Marketing Restrospective

The second quarter is behind us which also signals the end of the half. So what’s next?

Here in the US we’re taking vacations to recharge. No matter how much disconnecting we do, in those quiet moments we’re reflecting. We’re wondering about where we left money on the table and how we’re going to adapt our plays so that we win more in the coming months.

The Marketing Restrospective

In agile software development the team spends time at the end of each sprint performing a self review. This review is called a retrospective. The retrospective is a relatively brief meeting that seeks to answer three questions:

  1. What worked well for us?
  2. What did not work well for us?
  3. What actions can we take to improve our process going forward?

The purpose is not reflection on outcomes.  The purpose is to reflect on the methods the team used to produce the outcomes. The goal is to become better at creating great work. By honing the abilities of the team, the outcomes will improve in a sustainable manner. 

There’s a popular point of view that every function can be “agile.” I don’t think that’s true. Agile lends itself to work that can deliver value in an episodic manner. Not all work can be done in this manner. But that doesn’t mean we can’t learn something from agile about continuous improvement of the process.

At the heart of the retrospective is an assessment, by the team, of how well the marketing business processes worked, the identification of places where the process can be improved, and a finite set of actions that are going to be taken to improve the process. Let’s see how that works.

The Three Retrospective Questions

What worked well for us?

This seems like the simplest question but it can be a challenge to answer. There is not always consensus across the team. The purpose of this question is not only to celebrate success but also to eliminate things for the next question. Often things that are going well can be honed but resist the urge to oversharpen.

What did not work well for us?

This is the question that is both critical to improvement and a potential trap. Misery loves company and it’s easy to fall into a death spiral of complaints and commiseration. The key is to focus and prioritize. Agile teams know how to do this because they plan their work this way.

For teams less experienced in agile planning, it’s important to timebox this activity. Get the list out. Don’t spend too much time assessing it at first. Once the first pass is on the board, have the team vote on which are the most important things that didn’t work well so that you have a prioritized list of the most important gaps in performance. 

If it’s helpful you can use a grouping methodology like: “People, Process, and Platform” to organize the opportunities.

What actions can we take to improve our process going forward?

This is where the rubber meets the road. Which of those things are you going to select to work on and actually deliver improvement in the near-term? This is another time box. While you may not work day-to-day in sprints, this is where you’re going to have to commit to delivering improvement in 30 days. 

Why 30 days? There’s nothing magical about that timeframe but it is set in stone. You have 30 days to make a difference.

Go back to your list. Are the problems/opportunities granular enough that you can do something in 30 days? If not, refactor the list until you have 30 day “doable” actions in a prioritized list.

Finally select what you’re going to work on and deliver in 30 days. Remember, you have to do this stuff in addition to your team’s day job. At the beginning set your sights low. Get a sense of your capacity by delivering improvements. When you’re more experienced you can take bigger more aggressive bites.

Developing good habits

One of the most interesting things about agile development is the focus on continuous improvement of the process. It’s built into how the work gets done. In other business functions improvement is often a project, not a process. Your team’s challenge is to make improvement — reflection, planning, execution — a coequal part of their work regiment. 

Conduct your 1H retrospective. Don’t spend more than four hours on the work. Choose your actions and get started. But don’t wait until the next half to repeat the process. Do it every 30 days. Rinse and repeat. Build improvement into your process. Achieve your objectives. Grow your business.

Originally posted on Biznology

SearchChat Podcast: Your Customers are Begging for (Better) Personalization

In today’s episode of SearchChat, Steve Zakur and I tackle the TopRank blog and what skills B2B content marketers need to have. How do you take those people coming in the front door, the first interaction on your site, and engage them so it’s not the last page they look at? At the end of the day — no matter what your marketing techniques are, if you can’t measure them, you don’t know for sure how much they even mattered.

We also discuss the Mary Meeker trends report and what it says about your data. Data is now fundamental to help people work, and the most successful companies have intelligently integrated it into everyone’s daily workflow. We talked about this last month on whether data is a moat — SearchChat Podcast: Data Is Not a Moat for Your Business. What Is? When used properly, data can improve customer satisfaction. And here’s some powerful data — a survey of retail customers shows that 91% prefer brands that provide personalized offers / recommendations.

Meanwhile, many businesses are struggling to implement data — as a new study showed 41% of shoppers say that most personalized messages still feel like mass marketing. Those messages, they feel, were not created with their specific needs in mind. Lastly, we discuss the three trends driving the second golden age of martech. Instead of marketing cloud suites vs. best-of-breed point solutions, we can have the best of both.

0:00 Intro

2:00 Must-have skills for B2B content marketers, and why measurement is so crucial to the role

9:00 Mary Meeker trends report: what does it say about your data?

16:30 Personalized messages still feel like mass marketing

25:10 3 trends driving the second golden age of martech

29:00 Outtro

SearchChat is available on

Search Chat is SoloSegment’s podcast dedicated to all things search AI and content marketing related. Who is SoloSegment? We’re a technology company focused on site search analytics and AI driven content discovery to improve search results, increase customer satisfaction and unlock revenue for your company. If you think we might have the answer to your conversion problems, feel free to connect with us.

What’s Inside Behavioral Data?

Personas have been used for a number of years by B2B digital marketers to craft content that aligns with a visitor’s context. But we all know that personas are also so… 2015. The rise in personalization has revealed both the limits and challenges of persona-based content creation — creating and maintaining content for every persona is a lot of work and getting that content in front of the visitor at the right time is tricky.

Move from personas to personalization

In order to get that content in front of the right person, you have to know a bit about the visitor. Usually that’s done with either first party or third party data that you’ve gathered or obtained about the visitor. But both regulatory changes (see GDPR) and industry practices (see ITP 2.1) are going to limit the effectiveness of such tracking in the near future. So you’re going to have to take a different approach to identifying and segmenting users.

Using behavior data and contextual data for segmentation is one way to be able to deliver relevant content in an environment where persona data may not be available. With this approach, visitors don’t need to hand over any personal data for you to best understand who is visiting your site and what their goals are, and what content they need to see to progress their journey.

There are two types of behavioral data 

  1. Historical behavior: What pages have they visited? What have they viewed on the site? What articles did they read? Where have they clicked? What content have they downloaded? Marketers (especially with the help of advanced technology like text analytics and machine learning) can make use of all of this aggregate behavioral and contextual data to model patterns that are associated with task achievement. 
  2. Real-time behavior: Models are great, but putting them to work is where the magic happens. The real-time data related to a  particular customer’s experience (the pages they look at and the context of those pages)is compared to the model. Task predictions take place and content effective at progression towards those tasks are presented to users. At a minimum, contextual data can be used to recommend related content.

Understanding past behavior is the critical input to being able to predict effective future journeys. This type of personalization reduces the workload on content creators because it maximizes the use of content that you already have on your website. It’s also content that your visitors have already told you is effective. 

How do you use behavioral personalization on your site?

Getting started with personalization can be difficult. Many integrated MarTech stacks include personalization capabilities but many companies don’t use those capabilities. Often that comes down to one of two choke points: IT teams enabling some of the capability, and/or content teams creating the content to be presented.

Behavioral personalization can mitigate some of those concerns by using the content that you already have, data that’s readily available, and easy to deploy technologies to offer content suggestions that progress journeys towards completion. 

Despite fitting your persona classification, your visitors and prospects are wildly diverse with no two achieving their objectives in the same way. No amount of information about demographics or firmographics will help solve that journey diversity problem. Behavioral data packs a wealth of knowledge about not just your visitor, but their relationship to your products. Use that and you’ll connect more visitors with the content that matters.

Keep Your Content from Disappearing into the Blogroll

Your content marketing is too valuable to waste

How findable is the content on your site? If the answer is that you aren’t sure — you may have a problem. And you aren’t alone. Many marketers spend great lengths of time on content marketing. But a lot of that content goes unread. The main problem is that the people you want to read it can’t find it.

B2B content is just as vital

When we talk to B2B content creators they often lament the fact that their content — especially blog posts on corporate websites — seems to be a lone voice in the wilderness. Their point of view is expressed and then lost for all of time. The metrics make depressingly clear the irrelevance of the effort.

In B2B where a purchase is a group decision, this is an even greater concern. There are multiple decision makers that need to weigh in. It’s all the more important to have a wide variety of relevant content available that is accessible to the right people, at the right time in their journey.

Buyers crave personalization

The more you can direct individuals to content that addresses their business or functional concerns the more likely they are to buy. Infosys research suggests 31% of customers say they wish their shopping experience was far more personalized than it currently is, and 74% of customers feel frustrated when website content is not personalized.

Personalization becomes key.

A recent report from Seismic shows that personalized content helps achieve B2B objectives. 80% of respondents claimed all of their top objectives were better met when content is personalized. But many marketers avoid engaging in it because it is such a manual process.

The step ahead: automation

Automation is one way to abandon the tedious and sometimes futile work of hand-crafting content experiences and customer journeys. Behavior-based content recommendation suggests the next content piece to a viewer based on where they are at in their journey. Content can not only be found and used to answer questions, but is also offered at the moment it’s most needed.

Content marketing isn’t enough. You need content findability. You need a well cultivated content experience. Is your content well segmented for each user’s needs? Does your blog have sections so the content can be navigated? And with many different products, decision-makers and questions, you may need to bring automation to content. Otherwise, you risk your valuable content vanishing into the blogroll.

SearchChat Podcast: How AI Drives Value for Your Business

In this episode Steve Zakur and I are curious about the ways AI can be used to drive greater value for your company. We have our opinions about our own software of course, but this is a bigger question: how can you use AI to make your entire team and business smarter?

What companies need to think about right now is AI augmentation — augmenting decision making. Sometimes we’re thinking way too big about AI, instead of in a targeted fashion about what it can do for us now. This is the importance of practical AI.

A ChiefMartec piece recently asked if martech stack utilization is a misguided metric. If your stack is disconnected from value, it might be. Make sure the value is measurable and make sure the data can integrate. Does that end result provide value?

When what you have is a hammer, everything looks like a nail. You can’t look to the stack to save you in every situation. Good stacks are important, but if you aren’t pointing your marketing stack in the right direction or thinking about what you need it to do for you, you’re going to struggle.

0:00 Intro

1:50 The rise of practical AI

12:35 Stack utilization is a misguided metric

21:05 The stack won’t save you

29:00 Outro

SearchChat is available on

Search Chat is SoloSegment’s podcast dedicated to all things search AI and content marketing related. Who is SoloSegment? We’re a technology company focused on site search analytics and AI driven content discovery to improve search results, increase customer satisfaction and unlock revenue for your company. If you think we might have the answer to your conversion problems, feel free to connect with us.

The Trouble with Buyer’s Journey Maps

Let me ask you a controversial question: Is it time for you to rethink the buyer’s journey for your business? I know that for many companies buyer’s journeys represent a relatively new approach, but some recent shifts in the marketplace suggest there might be a better way.

Don’t get me wrong. Developing personas and journey maps for your business is almost always a worthwhile exercise. Your marketing strategists and creative agencies craft personas, buyers’ journeys, and similar tools to anticipate customer needs. And that’s a Good Thing™. Anything that helps get you closer to your customer and better understand what drives their behaviors is a huge win.

Most companies who invest in personas, journey maps, and comparable tools do so to understand customer behavior, anticipate their needs, and develop appropriate responses to guide customers along their purchase path. You’re trying to understand which phase of their journey your customer is in – research, comparison, buying, using, and so on – so you can create the right content to answer their questions and help them progress towards their end goal. And, to be fair, yours too.

At the same time, you should think about whether you might have another, better option to accomplish the same objective for your business.

The real reason journey maps, personas, and similar tools exist is because we don’t know what customers want. Those journey maps serve as proxies for actual behaviors because we don’t have a clear picture of precisely what a given customer is doing at any given moment. These “steps,” “phases,” or “stages” at least give us somewhere to aim. But, let’s be honest, they’re not the same as connecting with actual customers at their precise moment of truth. In practice, doing that has been tough to pull off.

Or, at least that used to be true.

One consequence of the floods of data your customers leave behind during visits to your site or app is that they provide amazing training data for machine learning algorithms. And those machine learning algorithms are beginning to understand and predict the behaviors your customers exhibit, not just as part of a segment, but as individuals. After all, as someone once said, AI makes big data little. And that suddenly opens the door to personalization for many businesses in a very real way. There are a number of startups doing some truly amazing work in this area (Full disclosure: I’m a partner in one of them). And it’s time for you take note.

Now, yes, the history of personalization is rife with over-promised and under-delivered “solutions.” And, again to be completely honest, you’re unlikely to create individualized content for every single person on your site (more on this in a moment). But, these tools do offer the ability to point customers to your existing content that’s most appropriate to where they actually are… not just where you think they might be. This is a hugely important development. And one you should be prepared to take advantage of.

Does this mean that your investment of time and money into developing personas and journey maps was wasted? No. Definitely not. As I mentioned a moment ago, it’s still challenging for companies above a certain size to create individualized content for every distinct person who might be on their site. Not at scale, anyway. But what you can do is use your personas and buyer journey maps to create content that suits customers at various stages of their journey, then use smart technology to point those customers to that content at exactly the moment where it can do the most good towards moving customers towards their goal. And that’s a huge win for everyone.

So, to return to my controversial question, do I think it’s time to rethink buyers’ journeys? I do. Do I think that better tools exist to help customers progress along their purchase path? Absolutely. Do I think that means your existing personas and buyer journey maps have no value? Definitely… not. Instead, it’s time to use each tool where they’re most effective. And to create the right experience for your customer at every touchpoint. And there’s nothing controversial about that.

SearchChat Podcast: Data Is Not a Moat for Your Business. What Is?

If a moat is an uncrossable chasm, then data may not be a moat. No amount of data can make it impossible for the competition to catch up. But it could be an inconvenience to the competition who is trying to climb your walls.

The struggle is that there is very little data a company can capture that other companies can’t capture. Everyone has access to third party data, but maybe first party data can slow the enemy down a bit. There is also an interesting counter-argument: that massive databases, real-time response and hyper-personalized experiences do actually make that difference.

In this episode Steve and I explore how data is like oil: it makes the engine run. But data as a differentiator is not the game. The game is, what do you do with the data?

We also explore how Word is now incorporating AI-based features to improve writing within Word. As I like to say — all data is training data. Never to be totally one-upped on the AI game, Google also dropped an interesting release: CallJoy, which allows small businesses to answer calls using AI.

This is a big deal. The more that we can make this technology visible in practical ways, the more trust there will be in the technology in more sophisticated ways.

0:00 Intro

2:00 The empty promise of data moats

13:30 Counter-argument: data as differentiator

20:05 Word is using AI to Improve your writing

25:05 Google launches CallJoy

31:50 Outro

SearchChat is available on

Search Chat is SoloSegment’s podcast dedicated to all things search AI and content marketing related. Who is SoloSegment? We’re a technology company focused on site search analytics and AI driven content discovery to improve search results, increase customer satisfaction and unlock revenue for your company. If you think we might have the answer to your conversion problems, feel free to connect with us.

5 Keys to Data-Driven Content Marketing

Content marketing is informative, entertaining, and helpful. But great ideas for content aren’t enough. Who decides they are “great”? The customer decides. How do we know the decision of the customer? Data–the more the better.

Content Marketing Starts with Creating Great Content

Your content must consist of compelling, audience-centric, findable, shareable stories. If you build it, they might not come. Content must be built with audience interests in mind so that they will find it and come share it with their peers. Once built, it must be published and promoted. Content does not market itself.

You measure the effectiveness of content marketing according to how often it is used and shared.

Content is Useful Only in Context

You can’t just create content in a vacuum. In digital media, content is only as valuable as the number and quality of references to it (links, social shares, etc.). It is more useful if it builds on existing work than if it duplicates it. It is more useful still if it is built as a part of a system of other content that answers specific questions in a several-step information journey. This is especially difficult for traditional marketers, who want to tell self-contained stories.

You measure how well connected content is, within its context, by performing link analysis.

Content Needs Information Paths

Chances are that your audience will choose a different path through your content than the path that you designed. That’s to be expected. Digital media and books are not the same. In books, it is the author’s story. The reader implicitly concedes this point and passively consumes the story according to the author’s agenda. Digital media need not be consumed in such a linear fashion. The digital reader or viewer is in control. It’s their story, and they’re piecing it together from multiple sources on the fly. This fact vexes some traditional marketers because, like book authors, they are accustomed to crafting media to be consumed serially.

You measure and track users through your content to create experiences that align with their journeys.

Great Content Speaks Your Customer’s Language

Because the audience builds their stories using multiple sources, you must use language that the audience understands. Though you want to tell your story, your story will not make sense ijn the context of the audience’s story if you don’t use common language. Coining your own terms can lead to jargon that’s confusing to your audience. It’s natural for marketers to desire unique trademarked names for their products, but when you need to explain too many words, your message loses its punch.

You learn the common language by conducting keyword research and by listening to social channels.

Content Marketing Requries a Publisher’s Reputation

As in all other forms of publishing, credibility is the currency in the digital world. A sure way to gain credibility is through transparency. Not only must you publish the truth as openly as possible, you need to avoid hyperbole and other forms of exaggeration. This can be especially hard for some public relations professionals who are used to telling only the “good stories.”

You can measure the credibility of your content by performing sentiment analysis and other forms of social listening.

Content marketing is emerging as the primary way many brands engage with audiences, to the degree that resisting content marketing has become a  career-limiting decision. For example, only 12% of UK companies do not focus on content marketing.

Perhaps data-driven content marketing’s most striking aspect is its use of data to understand the audience. Data allows marketers to provide the content they need to solve the audience’s problems and to answer their questions. Are you making the most of it?

What’s Wrong with Advertising: The Case for Data-Driven Content Marketing

As content marketing has been practiced today, it resembles custom publishing. Companies tell stories that romanticize their brand, distributing those stories through various channels and amplifying them through social media. Content marketing has come to be more akin to advertising.

Let’s go back to the basics for just a minute. Here’s the definition we should all be starting with for content marketing, from the Content Marketing Institute.

Content marketing is a strategic marketing approach focused on creating and distributing valuable, relevant and consistent content to attract and retain a clearly-defined audience–and, ultimately, to drive profitable customer interaction.

So, as to our question — what’s wrong with advertising? Nothing, really. But I focus on the following part of the definition: “to attract and acquire a clearly defined audience–and, ultimately, to drive profitable customer action.”

The kind of content marketing that can punch up through the noise has two distinguishing features. It is data driven and inbound. At SoloSegment, our focus is on mining audience data–big data, if you must–and identifying what content will be useful in a buyer’s journey. We then utilize that data to provide the right content to the right customer at the right time.

You need to build content that will be clearly purposeful and useful in a buyer’s journey. If you do it well, you turn prospects into clients and clients into brand advocates. This method focuses on messages that are valuable to your clients, not about you.

Marketing from the outside-in attracts prospects to your digital experiences and helps them answer their questions about your products or services. If you do this in a way that respects people’s time and gives them value in exchange for their attention, you can guide them through the customer journey toward purchase, adoption and advocacy.

Advertising stops finding customers the moment you close your wallet, but great content can bring in new customers years after your paid for it. Is your content marketing still about get-attention advertising, or are you truly providing value?