Do you remember the last time you felt the warm grip of a good book that makes you want to read on, page after page? How great writers craft their masterpieces with seemingly simple words—or even using a few uncommon ones to describe an object, like using “vast” for “big” or “numerous” for “many”—is a skill that isn’t innate; it’s studied, practiced, polished, and continuously improved upon. It’s how masters of the craft make literature memorable.
What about the shorter pieces found online? No, not fanfiction (but if you find such pieces interesting, then good for you). Think about blogs that focus on travel, business, gaming, food, what have you. What makes you read those posts time and time again? Is it the topic or how it is written? Is it the wit, the humor, the seriousness, or the passion? Whatever the reason, you keep coming back to them.
The same is true for visual content marketing. When people like how you write your pieces or how you present your data, they will be anticipating your next post. Why? Because you pique and satisfy their interest and/or because you’ve mastered how to use your posts to their fullest potential. The bottom line is that visual content is not just about the pretty pictures; it’s also about the witty words, the terrific texts, and the crafty copy.
Words hold a power different from that of images, and vice versa. The best use of both is a balance of those abilities that can provide a multitude of effects on readers. But before you strike that middle ground, focus on your text first because it will give you many ideas on what to do after writing it. When crafted from the heart, great copy can accomplish many things, including those listed below.
The same goes for pieces that don’t fall within the categories of literature or journalism: With every bit of information you put out that readers take in, you give off the feeling that you’re talking to and with them. You’re presenting what you have in what could arguably be the clearest way possible. In essence, you’re directly communicating with them.
Think of it this way: Without text, it’s like you’re playing a combination of charades and Pictionary; without images, it’s like Wheel of Fortune. Mix those three together, and you’ve got something more complete and effective.
Mix visual and written content together, and you’ve got something more complete and effective. Click To Tweet
Give Context
Clever image use has been the crux of photojournalism. It’s storytelling using a picture: In one shot, you highlight different elements of prose, like a protagonist, an antagonist, the setting, a struggle, the climax, or any combination thereof. But those kinds of pictures are far and few between, and getting that perfect shot is a one-time opportunity. If you’re creating an image, sure, you can manipulate the details, but the best you can do is something akin to what a good photojournalist captures.
This is where words come in: to fill the logical gaps and missing details. They can help provide what you think the image lacks—the bigger picture, so to speak—or at least give enough information for you to come up with your own conclusion, especially when the topic is open-ended.
It can even change how you look at an image, depending on how you use your copy to frame the portrayal. Words can affect how visualized data is seen. And it also works the other way around.
Provide Deeper Meaning
Aside from context, texts can also enhance the emotions a picture solicits. They can give the moral in a picture of triumph and success; they can depict the suffering in an image of despair. They can provide hope or take it away. They can spark ideas and waken a passion deep within the reader.
Words have the power to make your piece more than it appears to be. A picture doesn’t speak for itself more than when you pair it with words, but words can express themselves in ways deeper than anyone can ever imagine. It’s beautiful how the right words can push the right buttons and make a piece describe itself in flawless dignity.
When done well, your post can reach farther through shares, especially with how much attention people put on social media platforms. That’s when you reach a new audience, eager to take in the information you provide. By then, your posts are also having the same effect on your new audience, and the cycle begins again: affect, share, repeat.
There’s more to writing than just stringing words together to tell a story, to persuade, to converse, or to express. The art goes deeper than that. For anyone who studied writing and is always working to improve their craft, relying solely on imagery can make your content sound—and look—nice, but there’s no substance to it if there’s no synchronization and harmony between the topic and the elements.
The same goes for visual content marketing. If your visual elements don’t work together, or don’t match well, then the least you risk is not being taken seriously; the worst is you turn away people who could have been potential leads.
Your copy isn’t just a bunch of words meant to fill a page with nonsensical gibberish. You crafted it because it’s meant to be read. You want it to be read. When you plan your visualization methods and processes around your text, you will see that those words are not just there; they are part of your content. They are an element of your design and your post. It’s not an either-or scenario where image and text are concerned; rather, strike the balance. Getting the best of both worlds is beneficial for you and your post. You just need to be smart on how to use both.
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I recently mentioned in an AMA discussion on Inbound.org that I expect – and plan – for most of my content to fail. On average, I expect just one in five of my articles to succeed.
Ultimate failure can happen at the start of the content creation process – the ideation stage.
We might be rushed, unsure of our objectives, or just confused about what it is our audience wants. All of these factors can play into the quality of the content we wind up producing and, in turn, what results that content does (or doesn’t) achieve.
Here are the secrets to coming up with ideas for content your audience wants to see, and consequently, the number of articles you write that can be ticked off as successes, not failures.
Write down all your ideas, all the time
The last time you had a content idea you weren’t sure about, what did you do?
If you didn’t note it down right away, you may have missed a trick.
The fact is that not all article ideas – very few article ideas, in fact – are ready to be written right away. Most of the time, more thought needs to go into developing them. That’s fine.
But you’re losing out when you’re not noting down everything that could become a fully developed idea.
Of course, not everything you write down will turn into an article, but that doesn’t mean recording those ideas isn’t important. One thought could well trigger something worth running with later down the line.
Not every idea you write down will turn into an article, but recording those ideas is important. @SujanPatel. Click To Tweet
If you don’t already, get yourself (and use) an app like Evernote to easily record and organize your ideas wherever you are.
A common mistake marketers make is rushing the ideation stage. Generally, they’re working on tight deadlines, but sometimes they just don’t realize how important the idea itself is.
Coming up with ideas and deciding which ones to run with is not something you should rush. Don’t push ahead with an idea because you think (or are being told) you need to get it together and just produce something.
Let’s say you usually spend 15 minutes coming up with an idea for an article, and three hours writing it. If that article fails because the idea wasn’t up to scratch, that’s three hours and 15 minutes of your time wasted.
Now, if you could extend the time you spend on ideation to an hour and still spend three hours writing the article, and in turn that article is a success, those extra 45 minutes are well worth it, right?
Extend your ideation time so you don’t waste hours in creation, says @SujanPatel. Click To Tweet
Don’t be tempted to rush this part of the content creation process. Ensuring that your ideas don’t suck is never a waste of time. Rush past this bit and there’s a good chance you’ll wind up wasting all of your time.
Confirm interest in an idea
This is a mistake I’ve seen marketers make time and again (and I’ll happily admit I’m guilty of it myself).
I’m going to call it ideation blindness. It’s a condition in which we come up with an idea, and because it’s our idea, we automatically think it’s pretty good (if not great) and worth running with.
This is a problem, largely because our brains don’t always act in our best interests.
What our brains want is not necessarily what they need. Things that make our brains “happy” can in fact lead to huge errors in judgment. Basically, our brains want to get their own way, regardless of how bad for us it might be.
Your brain is wired to get its own way. Validate your ideas with others, says @Neuronarrative. Click To Tweet
When it comes to our article ideas, we can’t rely on our brain’s judgment. It’s clouded by our brain’s “happy” response. Consequently, we need to get a second opinion or seek further evidence that our idea will resonate with other people, too.
Let’s take a look at a few ways to do that.
Keyword research
People searching online for information on a topic you’re considering writing about is a solid indicator it’s worth covering.
Google’s Keyword Planner is a great starting point, although you may need to think a little outside the box when it comes to what you search for.
Chances are no one’s searching for the exact title you have in mind. Think up as many related phrases as possible that someone might search for if they were interested in that topic.
For example, here are a few things I might search for if I was using Keyword Planner to validate the idea for this article:
You can also try looking for evidence that people are talking about the topic in question on sites like Quora and Reddit (chances are, if they’re talking about it there, they’re searching for it on Google, too).
Most people think of outreach as something you do after you’ve created content to promote it.
They’re not wrong. But it can also be an incredibly valuable tool at the ideation stage. The process is similar to outreach used for promotion. You:
Create a list of people you think might be interested in your idea.
Contact them and tell them about your idea (usually with an email).
Ask them if they would be interested in reading an article about it.
If you get even a couple of yes responses, chances are you’re onto a winner. What’s more, you’ve already kick-started your promotion by finding people who are interested in it – and likely to share it for you when it’s finished.
Asking people around you
This one is so simple it almost doesn’t feel worth mentioning, but since so many marketers overlook it I’m going to talk about it anyway.
Before pushing ahead with an idea, ask people around you what they think. This could be colleagues or customers. It could even be friends or family if they have enough knowledge of your niche to be able to offer an informed opinion.
Don’t overthink this one. You don’t need to discuss your idea in detail. A quick “does this sound like something you’d be interested in reading” and a yes or no should suffice.
Fine-tune the idea to make it the best it can be
Have you heard about 10x content?
It’s something I talk about quite a bit, though Rand Fishkin coined the idea. You can view the Whiteboard Friday in which 10x content was first mentioned here.
If you’d rather have a summary, 10x content means content that’s 10 times better than anything else currently ranking for that topic.
Basically, if you want to give your content the greatest chance of succeeding you need to ensure that it’s better than anything out there. Making this happen should play an important part in your ideation and research process.
Here’s how you do it:
Search the topic you want to write about.
You may find you need to broaden or narrow your search to get the results you need. For instance, when following this process for this article, I might broaden the topic by searching for “why content marketing fails.”
Open each of the articles ranking on the first page of the search results.
This assumes all the results are relevant. If they aren’t, skip the irrelevant ones and move on to the second results page. Alternatively, change your search phrase.
Read each article carefully.
Write down their best points.
Write an article that incorporates all these elements.
And more.
Even if you choose not to follow this method exactly, you can learn a valuable lesson: Researching your idea properly is an important part of the ideation stage.
Not only can it help confirm whether an idea has legs (if no one’s written anything similar to your idea, it might be unique or it might be no one cares), but it also has a huge impact on the quality and usefulness of the final article.
What processes do you follow to ensure that your article ideas don’t suck, and are going to give you the best chance of success? It’d be great to hear your thoughts in the comments.
Please note: All tools included in our blog posts are suggested by authors, not the CMI editorial team. No one post can provide all relevant tools in the space. Feel free to include additional tools in the comments (from your company or ones that you have used).
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Cover image by Joseph Kalinowski/Content Marketing Institute
Sure, you can pretty much create an infographic for any blog post, but that doesn’t mean it will perform spectacularly. Creating a great infographic requires a great idea first and foremost.
In this guide, I break down the ideation process so that coming up with more memorable infographic ideas doesn’t have to be so hard. In fact, these principles are relevant not only to infographics but any content you create.
When it comes to producing high value content – shareable and link-worthy – create an infographic that solves a burning problem.
Create a problem-solving infographic to produce shareable & link-worthy content. @NadyaKhoja Click To Tweet
This approach requires you to first think about the problem that you’re trying to solve or the questions you’re trying to answer with your infographic story. This usually requires you to put yourself in your readers’ shoes.
First, ask yourself: What are the problems my audience is facing?
Your next step is to identify or discover topics and stories from those answers.
For instance, why do you think AMAs on Reddit and Inbound.org are so popular? It gives normal people the opportunity to ask questions of those who may be more successful than them – questions they believe will lead to their own eventual success.
With infographics, content typically formatted as a how-to guide follows this principle. One example is this one by Silver Door on how to successfully manage a team while working remotely – a burning and growing problem as remote teams become more common.
The data is presented in a simple and easily digestible format, offering a solution to a pain point.
As you attempt to provide solutions to burning problems, identify the data or the information you possess that your audience wants or needs, and present it in a way which provides value but also positions you as a leader in the industry.
2. Challenge the status quo
Next, creating content that challenges the status quo is a great way to position you and your company as experts and influencers in a certain area.
Create #content that challenges the status quo to position you or your company as an expert, says @NadyaKhoja. Click To Tweet
Consider this example from our study (and infographic) where we looked at nearly 200,000 tweets using hashtags. We made the statement that hashtags are useless. This challenges the typical assumption that they actually provide value in marketing.
Much like the myth-busting principle, creating content that challenges the status quo is sure to cause some controversy and debate. But these types of pieces tend to get the conversation going, thus making more people aware of your brand.
3. Change the perspective
The next principle is to reframe the question or alter the perspective. The best way to describe this principle is by looking at an example from the Bill and Melinda Gates Foundation.
The organization wanted people to understand the importance of malaria vaccinations. Instead of simply presenting the facts and listing the impact – the death toll caused by malaria – the foundation created an infographic about the world’s deadliest animals.
When you see that nearly 1 million people die every year from mosquito bites, and only 10 deaths are caused by shark attacks, the data becomes much more surprising and memorable.
By offering a comparison, and presenting the question in a different way, the foundation made the idea that a malaria vaccination is a simple way to avoid death so much stickier.
When you are using this principle, first identify the question you are trying to answer, and then approach it from a completely different angle.
For every story you hear, chances are there is an origin story. In the book Made to Stick by Chip and Dan Heath, one chapter discusses the origin stories of certain proverbial phrases.
I believe the one they were talking about specifically was the phrase, “A bird in the hand is worth two in the bush.” According to the Heath brothers, and many other sources, this proverb dates back to the 1600s. And it’s still used often today.
Now, aren’t you curious about the story behind this proverb, and perhaps the stories behind other common phrases that we know and use? Our curiosity and determination to find meaning are what make origin stories so popular.
Think about some common beliefs and behaviors people have today. For example, why did kale and quinoa suddenly become such health phenomena? They aren’t new foods, they have existed for a long time, and their health properties have been known as well.
A common way of portraying this principle with an infographic is by creating a timeline infographic of an event, specific industry, or person.
Create a timeline infographic of an event, specific industry, or person, says @NadyaKhoja. Click To Tweet
Anna Vital does this frequently by visualizing timelines of successful entrepreneurs, such as this example of the life of Steve Jobs.
These are just a couple examples of places to start. Your goal is to discover the origin story that resonates with your audience and then visualize it.
5. Find extreme cases
Similar to identifying the origin story is discovering the extreme case. These outliers are often eliminated from surveys because they can heavily influence data and skew results.
One example might be to identify the average time people spend on Facebook. According to Business Insider, the global average is about 20 minutes a day. But for users in the United States, the average time was double. Now that makes the statistic that much more interesting, doesn’t it?
You can see the headline now: U.S. Residents Spend Twice as Much Time on Facebook as the Rest of the World.
Finding the outliers like this can help inspire highly shareable content and infographic ideas. For instance, let’s say you sell a product like dog treats. You survey customers and identify that dogs consume an average of 2.5 treats a day. But you also discover one dog that consumes 15 treats a day. Now you have a special story.
From this case study, you can create an infographic visualizing how many pounds of dog treats are consumed a year by your customers’ pets, and highlight the outliers.
One example that stands out is a recent infographic map showcasing the median annual income for millennials across the United States.
Looking at this map, it’s shocking to see how little so many millennials are making. But this data is not the average income for millennials, which is likely much higher. If you read the article, you can also see that included in the survey were millennials who were still students, and only working part time. Considering all the factors, it’s not as shocking that the numbers are so low. But by only focusing on the median, the data is presented as an extreme case and viewers are more likely to read the article to learn why.
6. Go outside your immediate field
The next principle is to go outside your immediate field. Shopify offers an example of this. Technically, it’s in the e-commerce business, but it produces content on a range of topics, particularly entrepreneurship. Shopify knows that many entrepreneurs have a store and sell product online (the e-commerce tie-in). Shopify sells the dream of entrepreneurship first, and e-commerce is a by-product.
Here’s an example of an infographic about building long-term client relationships. Is it directly relevant to e-commerce? Not exactly. It’s more along the lines of general business management, but the content is still important if you have an online store.
The point is, don’t focus solely on your immediate field when thinking of content and infographic ideas. Venture outside of that tiny bubble and find out how you can tie in topics outside of your specific business.
Don’t focus solely on your immediate field when thinking of #content & infographic ideas, says @NadyaKhoja. Click To Tweet
7. Mash up two or more topics
The last principle is the act of mashing up multiple ideas or topics for your infographic. Take two seemingly unrelated concepts and find an element that connects them. This is a particularly good way of combining trending topics with evergreen ideas.
DOZ, a marketing software company, mashed its tool’s capabilities with a trending topic (election) in an infographic analyzing the type of language used on Twitter by some of the presidential candidates.
The infographic also became a PR win, as Adweek published it.
Think of some possible trending topics that can be mashed up with an aspect of your business. Maybe it’s comparing the Lord of The Rings to your SEO strategy or Harry Potter to your company culture that lets you use the mash-up principle to appeal to a wider audience.
Conclusion
It can be discouraging to spend hours working on an infographic that you think is incredible, only to publish it and find that not even a cricket will tweet it. But just like any type of content marketing, there is a lot of competition and only the best get shared and seen. Don’t just create an infographic for the sake of making it. Create one that follows the principles of great content, and it will be seen.
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Cover image by Joseph Kalinowski/Content Marketing Institute
PNR: This Old Marketing with Joe Pulizzi and Robert Rose can be found on bothiTunesandStitcher.
In this episode, we compare the newly buzzed-about Heineken ad to Pepsi’s debacle from a few weeks back – and conclude that they aren’t all that different. We also discuss ESPN’s decision to cut 100 on-air content creators, and explore The New York Times’ debut as a Snapchat Discover publisher. Our rants and raves feature AT&T’s home page and net neutrality, then we close the show with an example of the week from Pirelli tires.
PowerPost – Welcome to the Age of Power Publishing: As content marketers, we understand the importance of creating content that not only educates, but inspires consumers to take action. As a result, we have entered a new era of “brands as publishers” – where brands are increasingly becoming publishers in their own right. With brand publishing and content distribution come several key steps to the publishing process. But the elongated process of content creation, review, scheduling, and tracking analytics can often take more time than we have. Built by marketers for marketers, PowerPost is a time-saving tool for companies who manage content for multiple brands with multiple users – whether it’s a regulated industry or creative agency. With PowerPost, your team can publish from one location across all of your online platforms, quickly and efficiently turning your brand into a power publisher. To help more brands excel at publishing, join us for a webinar on May 9th with CMI founder Joe Pulizzi. We have also created a comprehensive e-book, with insights from 50 experts in the content marketing field, and their strategies on conquering the five pillars of brand publishing: content planning, workflow, distribution, analytics, conversion. Claim your download at powerpost.digital.
2. Notable news and upcoming trends:
Heineken shows Pepsi how to connect people who are worlds apart (11:30): Both BusinessInsider and AdWeek heaped praise on a new video spot from Heineken, in which pairs of people with opposing social and political viewpoints choose to engage in a conversation over a beer rather than letting their differences continue to divide them. AdWeek calls the powerful spot “the antidote to Pepsi’s pop-candy take on our messy political reality.” Though Heineken minimized the product placement and upped the emotional appeal, Robert and I wonder if the two ads are really all that different – especially as both were designed to be one-time “stunts,” rather than ongoing, content-driven conversations.
ESPN evolves its content strategy, losing 100 on-air personalities in the process (21:35): One of the last week’s biggest media stories was ESPN’s decision to cut more than 100 on-air employees, as well as a limited number of non-talent personnel, as reported on Yahoo Stories. In his company-wide memo, which was later posted publicly, ESPN President John Skipper frames the cuts around a shifting content strategy and the need for greater versatility in the face of changing consumer viewing habits. I think the story may have been blown a bit out of proportion – considering the relatively low number of layoffs. However, if you are at all involved in content marketing strategy, you should be paying attention to ESPN’s “over-the-top” strategy and how the company is re-organizing to move away from its role as a third-party content distributor.
Click to enlarge
The New York Times becomes Snapchat’s latest Discover publisher (31:10): Speaking of new media models, Mashable brings us an exclusive report on the Times’ debut as a daily edition on Snapchat, calling it a “dramatic moment for one of the world’s oldest and most respected news brands to dedicate resources to a young app. Robert views this as a smart brand marketing play, and was really encouraged by the quality of the stories selected for the platform. Not only do the articles seem well targeted to the interests of Snapchat’s youthful audience, Robert hopes the experience will serve as a gateway that drives app users to engage with the Times’ content in more monetizable ways.
3. Rants and raves (38:00):
Robert’s rant #1: In a news story that broke just prior to recording, a federal appeals court has declined to review an earlier decision upholding the FCC’s net neutrality regulations. As explained in this Recode post, a lobbying group representing web giants like Facebook and Google is among the vocal opponents of the Trump administration’s promise to roll back Obama-era policies preserving an open internet. As this is surely not the final word on the subject, Robert implores everyone – marketer or otherwise – to stay informed on this issue as it continues to unfold.
Robert’s rant #2: The idea that “you are never too old to chase your dreams” has been mined for many popular internet memes, including a recent viral Facebook status post, which reveals the age some celebrities were when they got their big breaks. While Robert has no argument with the concept of remaining young at heart when it comes to following your passions, he feels the examples given in this case are not only inaccurate, but they are teaching the wrong lesson: As he sees it, they really speak more to the power of persistence when it comes to achieving success than the age factor.
Joe’s rant: We seem to have a lot of phone mishaps in my household, requiring us to have to replace lost or broken equipment more often than the average family. As an AT&T customer, I visited the AT&T website for new phone info recently, and found a fun ad featuring Mark Wahlberg explaining some of the telco’s new policies when it comes to giving consumers access to entertainment on their terms. For a company that is trying to redefine the terms of engagement when it comes to media consumption, they sure missed the mark by inviting site visitors to “watch the TV ad” – something few people would really be interested in doing voluntarily.
Joe’s rave: I recently started reading Dune, and noticed that my copy features an introduction from renowned author Neil Gaiman that lists six of his favorite books published by Penguin Books (including Dune), along with a detailed synopsis of each one. In a nutshell, Penguin found an entertaining way to use its content to get me interested in reading more of the books they publish – a simple, yet smart content marketing technique, if you ask me.
4. This Old Marketing example of the week (52:35):
While we’ve talked about content marketing efforts produced by the Michelin brand on more than a few occasions – including their well-respected restaurant guides – there’s another tire manufacturer whose stellar content had escaped our attention, until now. Pirelli began publishing an annual calendar in 1963, gifting copies of the limited edition publication to its top corporate clients. What always made Pirelli’s calendars stand out was the quality of the photography featured, as well as the caliber of the photographers who participated in the project each year – including notable artists like Richard Avedon, Annie Leibovitz, and Carl Lagerfeld. But the 2017 calendar edition feels like a whole new animal, as the company decided to reboot its original concept by moving away from the classic pin-up style in favor of featuring well-known actresses (like Jessica Chastain, Nicole Kidman, and Julianne Moore) in a more natural, realistic setting – i.e., devoid of the heavy makeup, heavy retouching, and skimpy costumes that some have criticized over the years as being exploitative towards women. It’s a fresh, modern, and more artistic take on the company’s signature content effort – and an interesting This Old Marketing example of how a company can adapt its legacy content to stay in sync with the shifting tastes and interests of its audience.
More and more, I am hearing marketers talk about how they have a strategy … and then proceed to say they are set because they have an editorial calendar.
At the risk of sounding ranty, I’d love to yell from the rooftops: An editorial calendar is not a content marketing strategy!
An editorial calendar is NOT a #contentmarketing strategy, rants @MicheleLinn. Click To Tweet
While this conflict may seem like an issue of semantics, the confusion and meshing of these terms point to a bigger issue.
I am a big believer that you need to have both a strategy and an editorial plan or calendar. And you need to understand how each is different because the absence of one may explain why you are feeling uncertain in your efforts.
A simple analogy
Let’s say you are building a home. An architect leads the design of the structure by creating an architectural plan. But then a civil engineer makes the design possible – implementing and adjusting the plan to realize the architect’s vision.
Do you need an architectural design for your new home? Absolutely. It’s the vision of what you want to achieve. You would help your architect understand your needs (your why) – your strategy. Where do you want to move? How big of a house do you need? Are you beginning your family and want room to grow, or are you looking for something more compact and easy to maintain (one of those trendy tiny houses, perhaps)? How does your home fit into your overall family budget – and how much do you want to spend? These are just some of the questions you need to answer before creating a plan.
With that architectural strategy, you are ready to have the civil engineer create a building plan to implement the vision. That’s akin to your editorial plan or calendar.
In short, just like when you are building a home, you can’t have an effective building plan without an architectural strategy, and you can’t execute your strategy without your plan. (And, if you are designing a house with your spouse, you both need to get on the same page as well – just like your team needs to get on the same page with your strategy.)
First comes strategy
If your editorial plan isn’t feeling quite right, chances are high that you don’t have a solid strategy – or your team doesn’t have a shared understanding of what that strategy is.
If your editorial plan isn’t feeling right, chances are you don’t have a solid strategy, says @MicheleLinn. Click To Tweet
In very simple terms (I recognize this doesn’t account for all of the nuances out there), your strategy needs to answer these three questions:
Who are we educating/helping? (Note: I did not say “targeting,” as your goal should be helping. Creating a persona is one way to do this.)
How can we help them in a way that no one else can? (This is your content tilt.)
How will we know we are successful? (These are the business goals you have for your strategy.)
You need to clearly understand the answers to these three questions – and having this clarity isn’t as common as you may think.
In our most recent content marketing research, 37% of B2B marketers say they have a documented content marketing strategy, with an additional 41% indicating they have an undocumented strategy. (I won’t rant about the importance of documenting your strategy … but you should.)
But, when you look at what their strategy includes, just over half have a content mission, a deep understanding of their personas, and goals tied to their content.
Again, if you don’t have these things in place, something is going to feel off. And, while your strategy typically comes from the leadership team, don’t make excuses if you don’t have one.
Here are a few other things to consider:
Does everyone else on the team have the same understanding of the strategy? Ask them the answers to the three questions above and see how consistently everybody is communicating the strategy.
Keep the answers to those three questions simple and ask your team to post them on a wall or keep them close by until they internalize them. I can’t stress this enough: If you don’t stick to your audience and mission – with a focus on your goals– you will flounder.
Unlike your plan, your strategy is relatively set in stone and won’t change too often.
Then comes plan
Every single thing you publish and communicate needs to support the three key items in your strategy. Every. Single. Thing. And that’s where your editorial plan comes in.
Your editorial plan is tactical and detailed. It explains what you are going to do and who will do it. If you have your big ideas nailed down and are struggling with execution, chances are you need to spend some time with your editorial plan.
Your editorial plan is tactical. It explains what you are going to do and who will do it, says @MicheleLinn. Click To Tweet
While there are many other details to consider, here are the types of activities you include in editorial planning, many of which should show up in your editorial calendar:
Five to seven key areas or categories to cover in your editorial
Key web pages that require ongoing attention (Not sure which pages require your attention? Learn about the four key reports to help you as well as the five opportunities to consider.)
Content to update and republish (Learn about the system we use to decide which posts we want to republish as well as details on our process.)
Measurement plan (You can see a sample of a template we use to share insights with the team on a monthly basis.)
As you can see, all of these details are tactical and important. A high-level strategy is necessary, but without an editorial plan to support it, your content marketing program will have a tough time gaining traction.
Remember, you need an architect to draw your vision of a new home (the strategy), but you also need the civil engineer to create the construction plan to practically implement the vision.
Do you have both strategy and a plan? Does that create a comfortable home for your content marketing? Or do you have a plan, but without a strategy – your content marketing program lives day to day but it doesn’t live up to your vision?
Where are you feeling discomfort in your content marketing program? Would it make sense to fine-tune your content marketing strategy or your editorial plan – or both?
Want to learn more – and gain practical help – from CMI’s Michele Linn? Make plans today to attend herpresentationsat Content Marketing World Sept. 5-8 in Cleveland, Ohio.Registertoday for early-bird rates and use code BLOG100 to save an additional $100.
Cover image by Joseph Kalinowski/Content Marketing Institute
We live in an age where science fiction ever more quickly becomes science fact. Big data and Artificial Intelligence (AI) are revolutionizing industries across the developed world, from retail to finance to domestic and international spying. These technologies are automating functions previously considered tasks only a human could do, and offering detailed, personalized predictions a human could never make. Now these tools are underpinning a new era of content marketing technology: content intelligence.
What is Big Data?
First, some definitions. Big data involves computationally analyzing extremely large data sets to reveal patterns, trends, and associations; especially those relating to human behavior and interactions. It is used in everything from predicting stock performance to seasonal buying behavior to helping the NSA know whether your post about “blowing up the joint” refers to your bomb-making or DJing skills.
Every human who uses any form of digital communication generates data constantly, both about themselves and about humans in aggregate. Big data refers to the ability to find, sort, and make sense of this ocean of ones and zeroes. It encompasses structured, semi-structured, and unstructured information, both human-generated and from sensors, machines, and public records.
Structured data generally means information residing in a fixed field within a record or file, such as that found in spreadsheets and relational databases. Information that’s tagged to show some elements within the data, such as metadata in email or photos, is semi-structured data. Unstructured data meanwhile, includes content such as untagged text, images, audio, video, and so on.
Big data can also includes demographic or psychographic information about consumers. Think product reviews and commentary, blogs, content on social media sites, and the digital exhaust streamed 24/7 from mobile devices, sensors, and technical devices.
Defining Artificial Intelligence
The definition of AI is more nebulous because what is considered AI is constantly changing. One way of thinking of AI is as intelligence exhibited by any device that perceives its environment and takes actions to maximize its chances of achieving a goal. Another instance is when a machine mimics “cognitive” functions such as “learning” and “problem solving”—also known as machine learning.
Alan Turing, father of AI. (Image courtesy Infobunny.)
Capabilities currently classified as AI include understanding human speech, self-driving cars, and interpreting complex data. As the technology improves however, capabilities once defined as AI are removed from the definition. For instance, optical character recognition is no longer perceived as artificial intelligence, but as a routine technology. The same with GPS navigation systems.
Another way of thinking of AI is that it merely refers to algorithms we don’t fully understand yet.
The implications of this technology could feel as if we’re living in an anime cyber thriller, hurtling towards some utopian (or dystopian) future—the finale isn’t clear yet.
Applying Artificial Intelligence to Content Marketing
We’re barely at the beginning of applying the technologies of AI—such as natural language processing and machine learning, to content marketing. Artificial intelligence today has very narrow applicability. It is typically built to do one complex thing—usually a complex data-driven thing—more efficiently than a human can do it. Over the last two to three years, several technology startups launched that are purpose-built for individual content tasks. These companies are trying to apply AI capabilities to a task that’s very time-intensive for humans, to make it more efficient and effective.
Paul Roetzer
AI technology is still raw, and arguably pretty stupid. “It’s basically no smarter than a preschooler in a lot of cases,” says Paul Roetzer, the Cleveland based founder of the Marketing AI Institute, a resource for those interested in applying AI to content marketing. “But it can be trained to do one thing exceptionally well, almost super-human, and that’s where a lot of the companies are focused.”
AI as it applies to content could involve any content-related task we do as marketers, predicts Roetzer. Whether finding keywords, picking blog post topics, determining what to share on social media, writing hard copy, creating landing pages, or writing headlines. Everything we do that requires us to manually create a strategy or plan, develop content, and promote it can be automated or enhanced with artificial intelligence.
It pays to be skeptical about anything touted as ‘AI’ however. Thirty years after the 80’s, AI is once again a buzzword. Many software tools that call themselves AI aren’t really. They’re more like 80’s expert systems that merely rely on hard coded rules.
Who’s Making it Happen?
The main software leaders in the AI field are the obvious players, such as IBM’s Watson, Google, Apple, Amazon, Microsoft—all the big tech companies.
IBM Watson
However, this field is young. Think Internet in the early 90’s young. There are few content AI or marketing AI platforms as yet. There are mainly tools that perform specific tasks in equally specific contexts. You currently need multiple different tools to build AI into a content strategy. One related challenge marketers will face, argues Roetzer, is that the majority of those tools won’t be independent companies within 18 months. The big companies are buying up promising AI upstarts because there is a lack of talent that can actually build AI solutions.
What About Purely Marketing Companies Developing AI?
San Francisco’s Salesforce has made massive investments, buying multiple AI companies for a cool couple of billion dollars. That technology was then built into Salesforce Einstein, which launched in September 2016. San Mateo-headquartered Marketo now has predictive content recommendations, although this technology seems to have been mainly from acquisitions.
The Marketo and Salesforce marketing automation platforms use lead scoring technology. It examines which content someone’s consumed, how much they’ve consumed, and their demographic and firmographic to give them a score. Based on this data it automatically sends them to sales, and starts sending them relevant content. It will then send them different content based on what they continue to consume.
Curata founder and CEO Pawan Deshpande
“I don’t know if it’s quite intelligent though,” muses Curata CEO Pawan Deshpande (Curata is my employer). “Because it’s basically a hardcoded set of rules determined by the marketer. It’s not learning from past performance and evolving and adapting. Marketing automation doesn’t really have much in the way of machine learning in it at present—but it certainly could.”
Boston-based Curata has been around since 2007. It uses natural language processing and machine learning to power two software platforms. Curata CMP offers full funnel predictive content analytics and editorial calendaring. Curata CCS is a curation platform that discovers content, filters out noise, sanitizes text, extracts metadata, automatically summarizes, and makes it easy to review, curate, publish and promote content. It uses machine learning to self-optimize and learn user preferences to find better content.
Other marketing companies using AI in content tools include Manhattan-based opentopic, which has a personalization project called Sia built on Watson. Austin-based OneSpot uses image recognition and natural language processing to automatically tag and categorize content and images. It then uses machine learning to automatically surface relevant information to the right visitor on the right channel at the right time. Conversica is headquartered in California with offices in Missouri and Washington. It uses AI to automate the lead contact and qualification process, and identify which leads intend to purchase and are ready to buy.
Storytelling Machines
Natural language generation refers to a computer using data to produce natural language as a human would write it. Machines write 100 percent of Associated Press earnings reports, along with some of their basic sports news stories. Two major players in this area are Narrative Science, headquartered in Chicago, and North Carolina-based Automated Insights.
Persado has $66 million in funding and offices in New York, San Francisco, Chicago, Rome, Athens, London, and Germany. Persado uses natural language processing and natural language generation to automatically create Facebook ads, landing page content, and email subject lines. They are unique in that they are in the creative realm of using machines to create content that isn’t data-driven.
There are dozens of other players in this field.
So What is Content Intelligence?
Content intelligence may draw on artificial intelligence and big data, but it is neither of those two things. It’s the systems and software that transforms data into actionable insights for content strategy and tactics. Content intelligence means having the full context of an individual piece of content. Not only that—but the whole corpus of content, to make better decisions about anything pertaining to the content in question.
Forrester analyst Ryan Skinner defines content intelligence as “technology that helps content understand itself—what it’s about, how it speaks, how effective it is at accomplishing certain goals, what emotions it calls to mind, etc.”
So what does having the full context of a piece of content mean? It’s understanding what the content is, what it’s related to, how it’s performed in the past, and how related content has performed in the past. This includes understanding how competitor content may have performed as part of the broader context it sits in. As well as other content it’s competing with in search engine optimization and search engine results pages.
Content intelligence means understanding everything there is to know about a piece of content. And to the extent that the past can help predict the future, using that comprehensive understanding to guide decision making for that piece of content. It doesn’t necessarily have to include the automation and execution of those decisions.
The Evolution of Car Navigations Systems
Once an organization has the full context of a content item, automation and execution of certain tasks and cases is the next step. Think of the evolution of car navigation systems. For decades when people wanted to get somewhere, they would look at a paper map, then approximate a route.
But the information a map gives you is woefully incomplete. It just doesn’t give you much context for your trip. For example, you don’t know any of the speed limits, or where there’s stop lights, or any rest areas or gas stations on the way. Forget about real-time changing conditions such as roadworks or traffic. So people would plan out trips just based on a map and guesstimate most things.
Then GPS comes along and lets you pinpoint exactly where you are on your journey. (Although it didn’t necessarily tell you which path you needed to take.) Next came the navigation system. It could suggest an optimal route, absent traffic information. It could say where you are, where you want to go, and some good ways of getting there.
The next evolution was Google Maps and Waze. These platforms have real-time traffic data—not to mention satellite navigation such as Sirius, offering a real-time dynamic understanding of traffic flows and patterns.
The next step beyond is automation. It doesn’t just give you intelligence on what to do and guide your decisions. It actually does it for you: i.e. the self-driving car. We haven’t quite conquered this as yet—but we’re close.
Content Marketers Are Still Using Maps
Many content marketers are now at the very first stage of using maps when it comes to content strategy. They don’t really understand where they are because they mainly look at ‘vanity metrics’ such as pageviews, social shares, and so on. These are top of the funnel metrics that offer a rough approximation of how content is doing. But they don’t measure content lower in the funnel, or show content’s impact on your business.
Some marketers today however, go beyond vanity metrics. They connect all the dots by pulling in significant quantities of data that’s hard for a human to compile, let alone compute. These companies pull together data from many disparate sources and apply that to content to get a fuller understanding, manifested as analytics and reporting. They can look at a report and get comprehensive data at a glance. They can then make an intelligent and informed decision about a course of action, which was formerly not possible.
These marketers understand the business results they’re driving exactly. This includes the leads, revenue, and sales pipeline a particular piece of content is generating. This is where the technology is at today.
Content intelligence technology is nascent. It’s exciting relative to where we’ve come from, but at this stage it’s mainly collating full context data to provide intelligence. “I think we’re really at the data aggregation stage,” says Deshpande. “Simply collecting all the data about content from disparate systems is a challenge. After that, machine learning systems have the full context to make intelligent recommendations.”
The next step for this technology will see it do the majority of computation and inference to determine the best course of action, based on a given set of data. Currently this is where marketers apply their intuition. This could include choosing whether or not to refresh an evergreen article say, or whether to spend money on paid promotion for an article that’s popular and could go viral. The best course is often not obvious however, requiring a lot of data exploration digging, which machines are much better at.
Which Problems Does Content Intelligence Address?
Every marketer alive today proclaims how “data driven” they are. But if you look at how content is utilized, it’s still mostly based on intuition and guesswork. At marketing conferences, if you want to know what content to create you’ll always be advised to go ask your sales team. Or to go search online and see what questions people are asking. Or to look at search volume. These are all good inputs, but they’re mainly based on what’s worked in the past.
What to Share
Sales teams typically share content based on anecdotal feedback. You’ll often hear one sales person yell out on the floor, “Do we have a piece of content about analytics that I can share with this prospect?” And someone else will say, “Yeah, here’s a tasty piece.” These anecdotes reinforce behaviors. So if something worked well and someone hears the story about how a piece of content helped them close a deal, the next sales rep is likely to repeat the same pattern. When demand generation teams look at what data to share, they will do AB-testing on emails, but beyond that a lot of it is just very anecdotal, or looking at very rudimentary metrics as well.
Jeff Brewer, Lead Software Engineer at Lux Research and a former quant in futurist Ray Kurzweil’s hedge fund, believes content intelligence can really pay dividends when paired with consumer behavior models. “This means moving beyond content suggestion by anecdote to using consumer models and characterizing content from previous interactions to suggest what to share next,” he says. “Besides improving sales outcomes, a data-driven suggestion platform can evaluate new, untested content to determine efficacy with minimal risk to the sales pipeline. This helps both sales and marketing departments hone their craft. These models can be as unique as every company’s set of products, content, and markets. AI based content intelligence customizes these models for each company.”
There are many other channels where most decisions about how to utilize content come down to intuition: social channels, websites, advertisements, and so on. This is where content intelligence can add the most value. It can make those decisions informed, and even automate some of those decisions in a scalable manner.
What to Read Next
On a web page you’re usually presented with the most popular or most recent stories. With content intelligence, expect instead to see stories based on your previous browsing history and position in an organization’s hierarchy. Along with what your title is, what you’ve consumed in the past, what other people in your organization have consumed in the past. Even which content—or certain pieces of content, shared in succession—has the highest conversion rate at the stage you’re currently at in the consumption cycle.
Those are just a few factors. But there are literally hundreds of possible factors that can be fed into an algorithm to find the right weight for all those inputs, to know exactly what context something has, and what the right piece of content is. Content intelligence helps utilize your existing content inventory most effectively.
Which Content to Update
Another way content marketers can use their inventory more effectively is by knowing when to refresh evergreen articles. Say a particular article or blog post performed really well, but it hasn’t been refreshed in a year. You are automatically sent a prompt for this article to be refreshed and shared.
There’s a constant stream of things a content marketer can do to be a lot more effective, that don’t take up much time. But it’s hard to figure out what they are. Content intelligence can surface that information in an easy-to-understand, and easy-to-act-on way. So you can login every day, or every week, get some really useful feedback or advice, make those changes, and see specific growth in certain areas.
You can do this at every different touch point with content intelligence. Your website, a sales person on the phone or emailing with a prospect. Any time you have a touch point with a customer, you can show targeted information that’s highly valuable to them.
Which Content to Create
The content creation process is another area to be optimized. Content intelligence can make recommendations about what you should be creating based on what performs well, or what your competitors are doing. And the recommendations can vary based on what your goals are. So you could say, “we have a goal of a certain number of leads or pageviews generated for this quarter.” And you could receive recommendations to help you achieve that. The recommendations will differ based on the goal.
While machines can mainly only create data-driven content for now, that’s evolving quickly. IBM partnered with a movie studio and created a video trailer using AI, which took over the creative process. Coca-Cola has used AI to generate TV adverts, selecting the music and creating scenes. If Pepsi had content intelligence, they could probably have avoided uniting the entire Internet in universal opposition to their latest ad.
How to Promote
Think about how hard it is to know what to promote, when to promote, and where to promote it. Content intelligence will enable highly personalized, cross-channel promotion that humans are just not wired to do.
“I am a big believer that the first major AI platform to be built, will probably be the first billion dollar AI company, because it will completely redefine marketing strategy,” says Roetzer. “Think about a company trying to spend a hundred thousand dollars, or a million, or hundred million dollars on marketing. Humans are incapable of figuring out the best way to spend that money. Given all the channels, all the need for personalization, all the different possibilities of what you can do with that money, there is just no way… the greatest strategists in the world together can’t figure out the optimum way to spend a million dollars. But AI can. It’s the hardest problem to solve, but that’s the one that is going to change everything.”
The Solution to Content Shock?
Mark Schaefer
Tennessee-based marketing strategist, speaker, and author Mark Schaefer coined the term content shock in 2014. It describes the phenomenon of an ever increasing arms race to produce more, and more compelling content. This content is seldom personalized, and consumers’ attention span is resolutely finite. But marketers keep producing more and higher quality content for a slice of a pie that’s not growing.
Content intelligence is a significant competitive advantage for organizations fighting to overcome audience content shock. They have the insights to produce better, more engaging content. And more intelligent means of distribution to get content to the right sections of audience where it’s most compelling. Content intelligence enables you to present the right content to the right person, every time.
For a B2B marketer, downloading an eBook on most sites means you’ll likely be presented with that same eBook as a call-to-action if you revisit two days later.
If you’ve created enough great content however, with content intelligence you can truly tailor the experience someone has with your brand and site to an individual level. It’s the Netflix or Amazon approach. You don’t feel there are too many products on Amazon, because you only see the stuff that matters to you, based on your behavior. If content is the same way—if you only see what’s relevant to you all the time—it doesn’t matter to you how many millions of eBooks are out there.
Source: Ceralytics
Who Are Some of the Players in Content Intelligence?
The term content intelligence has been around for over a decade. But the companies building the technology are generally less than ten years old.
Curata CMP pulls in data from many different sources. This including the content itself, social metrics, traffic metrics, lead metrics, marketing pipeline metrics, sales pipeline metrics, and revenue metrics. It shows the precise business impact of every piece of content you produce.
Headquartered in Brighton, England, BuzzSumo pulls together social sharing data for all content across the web. Idio has offices in London and New York, and uses machine learning to analyze content, marry it to a consumer profile, and serve personalized content. Washington D.C. based TrackMaven focuses more on competitive analysis. It helps you track how your marketing performs against competitors, peers, and industry influencers. Conductor Searchlight has offices in New York City and San Francisco. It shows you how your content is doing in SEO and how your competitor’s content is doing. Florida-based Ceralytics is a platform for creating, analyzing, and promoting your most effective content.
Where is the Technology Moving Next?
Content intelligence is increasingly looking at what’s driven business results in the past, and advising you what to do going forward based on your goals. Or telling you where you will end up in terms of those metrics. It will automate parts of this process. This year expect a focus on helping to optimize your current content inventory for immediate benefit. Longer term, expect more of a focus on external data sources.
The past doesn’t always predict the future. Content marketing is inherently a very creative process, and thinking outside the box should not be underestimated. So expect the more mundane, repetitive, unskilled parts of content marketing to be automated by content intelligence. But not the need for experimentation.
How to Prepare for Content Intelligence
The insights content intelligence provides are only as good as the amount and quality of the data you have. To leverage this technology for competitive advantage requires a sufficiently long history of well-structured, well-maintained, trustworthy data. Deshpande offers an example of the importance of this from when he worked at Google in 2005.
“Back then Google Translate worked best for Chinese and Arabic,” he says. “And it wasn’t because Google had the best algorithms for those particular languages—it was because they had the most data. The Department of Defense had translated so many documents in those two languages that Google had the most training data to input into the system. It really demonstrates how data is more important than the algorithms behind it.”
Know What You’ve Got
One of the most important steps an organization can take is to conduct a content audit of inventory. Best practice is to do this at least once a year, and it’s also vital to effectively utilize content intelligence. This audit should capture the content text, images, metadata, and other associated attributes invisible to the content consumer. For example: the persona, the buying stage it’s designed for, the vertical it’s for, and who wrote the article, especially for organizations using ghostwriters.
Given sufficient examples/inputs and their resulting outputs, a machine learning algorithm learns which inputs correlate with which outputs. Then it can predict which inputs correlate to positive outputs, and optimize for a desired output. Content marketing inputs are those in your content inventory. Performance related data makes up the outputs. This means things such as leads generated, revenue generated, social shares, traffic data, variants such as time on page or bounce rate; whatever you’re trying to optimize for.
You can then examine marketing pipeline metrics to see how these inputs turn into opportunities for sales. For example, which leads consume which content, how often they consume it, when they consume it, and so on. Did someone consume something when they were an opportunity, at purchase decision, or much earlier? Which of these pieces of content then led to revenue, and how much revenue? Then there’s outside, broader context data such as competitive data, and related topics and trends at the time.
Promotion and Distribution
The last phase is understanding how content is distributed and promoted. It can be hard to tell why a piece of content did well. Is it because it’s fundamentally strong, compelling content, and therefore got traction because people are sharing it? Or was it just heavily promoted mediocre content?
For example, on the homepage of Google News they used to have a ”recommended stories” section. These stories got the highest click-throughs, so the team felt they were making good recommendations. But it turned out they were getting the highest click-throughs because it was the first thing on the page. It was the problem of display bias.
Collecting, Storing, and Cleansing Data
Again, clean data—and lots of it, is imperative. You can’t just go out and buy a machine learning algorithm, flip it on, and start seeing immense value. Any time you use an AI application, with machine learning in particular, you have to teach the machine by giving it data.
Cleansing your data means de-duplicating it. I.e. making sure there aren’t two contacts with same email address, or the same contact with two different email addresses. Simple things like that ensure your data is correct. There’s a tool called IBM Watson Analytics which allows you to upload a dataset to find out how good your data is.
Marketing automation systems warehouse content consumption data that pertains to leads further down the funnel. But vendors don’t currently retain that data well for storage reasons. For example, Marketo only stores web activity data for 90 days, after which they start purging the data. Oracle stores your web activity data for 25 months.
The longer your data goes back, the better. So it will pay to pull data outside of your marketing automation system and build a data warehouse. Other systems pull social data. It’s easy to go and see how a piece of content is doing today in terms of social shares. You can look at a snapshot and say, “Ok, I got this many shares on LinkedIn.” It’s harder to go back and see how the numbers changed over time. So the sooner you start cataloging and storing that information the better, so you get more historical context.
Google Analytics is pretty good for storing historical data, but even that has issues. If a company has over 500,000 pageviews in a given time period, Analytics starts sampling data. It’s too much for their channel, so you’re don’t actually get truthful data.
Every system has its downsides, and it’s important to know what the downsides are. To avoid being hindered by those limitations, it will pay to store data outside many systems.
Clippy’s Revenge
There are some applications around now that are about as useful as Microsoft Clippy. Clippy was the famously intrusive Microsoft Word paperclip that used to give unhelpful, obvious suggestions. (Microsoft euthanized Clippy in 2007.) Many content intelligence tools are arguably still at the Clippy stage.
While everyone likes to make fun of Microsoft, they’ve morphed Clippy into other technologies. Now if you use the same language or phrasing over and over in a Word document, it offers subtle, non-obvious stylistic suggestions beyond just spelling and grammar. Rather than being an annoying paperclip in the corner, it’s built into the workflow. That’s where content intelligence is working towards to provide value.
The adoption of content intelligence will likely come down to a question of trust in the technology. Firstly trusting that the data is right. Then that the insights are right. Then trusting that the system’s suggestions will actually help rather than hurt. And finally trusting the system to automatically perform the suggested action on its own.
Think about this analogy. In the 1920’s when elevator technology first started displacing elevator operators—that was a big deal for elevator passengers. Many people would take the stairs because they just didn’t trust an elevator sans operator. This dynamic exists with people’s attitudes towards self driving cars. Content intelligence needs to overcome the same level of trust. The technology needs to develop and provide insights and automation. But even with that, it may take even longer for folks to really trust it to make the right decisions.
Where did you say the stairs were?
The Content Intelligence Disruption
We’ve reached the point with certain systems where we trust machines more than we do ourselves. It doesn’t make sense for us to tell an elevator what the best routing is to get to a floor. Many people now trust a GPS navigation system over their own intuition in most cases when driving cars. This is the point content intelligence needs to reach before we see wider adoption.
Content intelligence right now is reducing or removing the need for freelance writers who produce low level copy. It may do the same for certain marketing operations and demand gen positions. (There will be plenty of software engineers kept in gainful employment however.)
It will likely take another two years for the intelligence to offer more consistently helpful insights. And perhaps another three years to gain wider adoption and trust. That said, content intelligence, like all new technology, will offer first movers a significant competitive advantage—whether vendors or users. It will also eventually devolve into a more utility-like function as economies of scale allow full industry penetration. From now until then however, marketers ignore this technology at their peril.
