Category Archives: Content Effectiveness

Untangling Content ROI

How to measure content ROI is a recurring question in forums and at conferences.  It’s a complex topic — I wish it were simple.  Some people present the topic in a simple way, or claim only one kind of measurement matters.  I don’t want to judge what other people care about: only they know what’s most important to their needs.  But broad, categorical statements about content ROI tend to mislead, because content is complicated and organizational goals are diverse.  I can’t provide a simple formula to calculate the value of content, but I hope to offer ideas on how to evaluate its impact.

The Bad News: The ROI of Content is Zero

First, I need to share with you some bad news about content that nearly everyone is hiding from you.  There is no return on investment from content.  If you don’t believe me, ask your CPA how you can depreciate your content.

A widespread misconception about content ROI is that content is an investment.  Yet accountants don’t consider most content as an investment.  They consider content as an expense.  The corporations that hire the accountants consider content as an expense as well.  In the eyes of accountants, content isn’t an asset that will provide value over many years.  It is a cost to be charged in the current year.  From a financial accounting perspective, you can’t have a return on investment when the item is considered as an expense, instead of as an investment.

Many years ago I took an accounting class at Columbia Business School. I remember having a strong dislike of accounting. Accounting operates according to its own definitions.  It may use words that we use in everyday conversation, but have specific ideas about what those words mean.  Take the word “asset.”  Many of us in the content strategy field love to talk about content assets.  Our content management systems manage content assets.  We want to reuse content assets.  The smart use of content assets can deliver greater value to organizations.  But what we refer to as a content asset is not an asset in an accounting sense.  When we speak of value, we are not necessarily using the word in the way an accountant would.

I warned that broad statements about ROI are dangerous, and that content is complicated.  There are cases where accountants will consider content as an investment — if you happen to work at Disney.  Disney creates content that delivers monetary value over many years.  They defy the laws of content gravity, creating content that often makes money over generations.  Most of us don’t work for Disney.  Most of us make content that has a limited shelf life.  Until we can demonstrate content value over multiple years, our content will be treated as an expense.

So the first task toward gaining credibility in the CFO office is to talk about the return on content in a broader way.  Just because content is an expense, that doesn’t mean it doesn’t offer value.  Advertising is an expense that corporations willingly spend billions on.  Few people talk about advertising as an investment: it’s a cost of business, accepted as necessary and important.

The Good News: Content Influences Profitability

Content is financially valuable to businesses.  It can be an asset — in the commonsense meaning of the word.  It’s entirely appropriate to ask what the payoff of content is, because creating content costs money.  We need ways to talk about the relationship between the costs of content, and revenues they might influence.

Profitability is determined by the relationship between revenues and costs.  Content can influence revenues in multiple ways.  Content is a cost, but that cost can vary widely according to how the content is created and managed.  The overall goal is to use content to increase revenues while reducing the costs of producing content, where possible.  The major challenge is that the costs associated with producing content are often not directly linked to the revenue value associated with the content.  As a result, it can be hard to see the effects on revenues of content creation costs.  Content’s influence on profitability is often indirect.

Various stakeholders tend to focus on different financial elements when evaluating the value of content. Some will seize on the costs of the content. How can it be done more cheaply?  Others will focus exclusively on the revenue that’s related to a set of content items. How many sales did this content produce?  These are legitimate concerns for any business.  But narrowly framed questions can have unintended consequences.  They can lead to optimizing of one aspect of content to the detriment of other aspects.  Costs and revenues can involve tradeoffs, where cost-savings hurt potential revenue.  Costs also involve choices about kinds of content to produce, so that choices to spend on content supporting one revenue opportunity can involve a decision not to produce content supporting another revenue opportunity.   For example, a firm might prioritize content for current customers over the needs of content for future customers, especially if revenue associated with current customers is easier to measure.

The key to knowing the value of content is to understand its relationship to profitability.

Customers Generate Profits, Not Content

Spreadsheets tend to represent things and not people.  There are costs associated with different activities, or different outputs, such as content.  There are revenues, actual and forecast, associated with products and services.  The customers that actually spend money for these products and services are often represented only indirectly.  But they are the link between one set of numbers (expenses involved with stuff they see and use) and another set (revenues associated with stuff they buy, which is generally not the content they see).

Unfortunately, the financial scrutiny of content items tends to obscure the more important issue of customer value.  Content is not valuable or costly in its own right.  Its financial implications are meaningful only with respect to the value of the customers using the content, and their needs.  The financial value of content is intrinsically related to the expected profitability of the customer.

The financial value of content is clear only when seen from the perspective of the customer.  Let’s look at a very simplified customer lifecycle.  The customer first enters a stage of awareness of a brand and its products.  Then the customer may move to a stage where she considers the product.  Finally, if all goes well, she may become an advocate for the brand and its products.  At each stage, content is important to how and what the customer feels, and how likely he or she may be to take various actions.  So what kind of content is most important?  Content to support awareness, content to support consideration, or content to support advocacy? Asked as an abstract hypothetical, the question poses false choices.   The business context is vital as well.  Is it more important to get a specific sale, or to acquire a new customer?  Such questions involve many other issues, such as buying frequency, brand loyalty, purchase lead times, product margins, etc.

There can be no consideration of a product without awareness, and no advocacy without favorable consideration (and use).  And awareness is diminished without advocacy by other customers.   The lifecycle shows that the customer’s value is not tied to one type of content — it is cultivated by many types.  At the same time, it is clear that content is only playing a supporting role.  The customer is not evaluating the content: she is evaluating the brand and its products.  Content is an amplifier of customer perception.  The content doesn’t create the sale — the product needs to fulfill a customer need.  While bad content can hurt revenues for otherwise excellent companies, content doesn’t have the power to make a bad company overcome poor quality products and services. Content’s role is to bring focus to what customers are interested in learning about.

Conversion is a Process, Not an Event

Marketing has become more focused on metrics, and so it is not surprising that content is being measured in support of sales. A/B testing is widely used to measure what content performs better in supporting sales.  Marketers are looking at how content can increase revenue conversion. This has often resulted in a tunneling of vision, to focus on the content on the product pages. Conversion is seen as an event, rather than as a process.

Below is a landing page for a product I heard about, and was interested in possibly purchasing.  It represents a fairly common pattern for page layouts for cloud based subscription services.  The page is simple, and unambiguous about what the brand wants you to do.  The page is little more than a button asking you to sign up (and, in the unlikely event you missed the button on the page, a second button is provided at the top).  I presume that this page has been tested, and the designers decided that less content resulted in more conversions per session.  If people have few places to go, they are more likely to sign up than if they get distracted by other pages. What’s harder to judge is how many people didn’t sign up because of the dearth of information.

A product page that is entirely about a Call-To-Action. The product remains a mystery until the prospect agrees to sign up.
A product page that is entirely about a Call-To-Action. The product remains a mystery until the prospect agrees to sign up.

Some online purchases are impulsive.  Impulse online purchases tend to be for inexpensive items, or from brands the customer has used before and is confident in knowing what to expect.  Most other kinds of purchases involve some level of evaluation of the product, or of the seller, sometimes over different sessions.  In the case if this product, the brand decided that it could encourage impulsive sign-ups by offering a two-week free trial.  This model is known as “buy before you try”, since you are presumed to have bought the product at sign-up, as your subscription is automatically renewed until you say otherwise.

A focus on conversion will often result in offering trials in lieu of content.  Free trials can be wonderful ways to experience a product. I enjoy sampling a new food item in a grocery, knowing I can walk away. But trials often involve extra work for prospective customers.  Online, my trial comes with strings attached.  I need to supply my email address.  I need to create an account, and make up a new password for a product I don’t know I want.  If it is a buy-before-you-try type trial, I’ll be asked for my credit card, and hope there is no drama if I do decide to cancel.  And I’m being forced to try the product on their schedule, and not my own.

Paradoxically, content designed to convert may end up not converting.  The brand provides little information about their service, such as what one could expect after signing up.  The only information available is hidden in a FAQ (how we love those), where you learn that the service will cost $100 a year — not an impulse buy for most people.  When prospective customers feel information is hidden, they are less likely to buy.

Breaking the Taboo of Non-Actionable Content

There is a widespread myth that all content must be designed to produce a specific action by the audience. If the content didn’t produce an action, then nothing happened, and the content is worthless.  It’s a seductive argument that appeals to our desire to be pragmatic.  We want to see clear outcomes from our content.  We don’t want to waste money creating content that doesn’t deliver results for our organization. So the temptation is to purge all content that doesn’t have an action button on it. And if we decide we have to keep the content, we should add action buttons so we have something we can measure.

I don’t want to minimize the problem of useless content that offers no value to either the organization or to audiences.  But it is unrealistic to expect all pages of content to contribute directly to a revenue funnel.  By all means weed out pages that aren’t being viewed.  But audiences do look at content with no intention to take action right away.  And that’s fine.

Creating content biased for action only makes sense when the content is discussing the object of the action.  Otherwise, the call to action is incongruous with the content.  A UX consultant may tell a nonprofit that people have trouble seeing the “donate now” button. But the nonprofit shouldn’t compensate by putting a “donate now” button on every page of their website — it looks pushy, and is unlikely to increase donations.

Conversion metrics measure an event, and can miss the broader process.  Most analytics are poor at tracking behavior across different sessions.  It is hard to know what happened between sessions — we only see events, and not the whole process.  Even sophisticated CRM technology can only tell part of the story.  It can’t tell us why people drop out, and if inadequate content played a role. It can’t tell us if people who bought supplemented their knowledge of the product with other sources of information — talking to colleagues or friends, or seeing a third party evaluation. To compensate for these gaps in our knowledge of customer behavior, businesses often try to force customers to make a decision, before they seem to disappear.

By far the biggest limitation of analytics is that they can’t measure mental activity easily.  We don’t know what customers are thinking as they view content, and therefore we tend to care only about what they do.  The opacity of mental activity leads some people to believe that the opinions of customers aren’t important, and that only their behavior counts.

The Financial Value of Customer Opinion

Customers have an opinion of a brand before they buy, and after they buy.  Those opinions have serious revenue implications. They shape whether a person will buy a product, whether they will recommend it, and whether they will buy it again.  Content plays an important role in helping customers form an opinion of a brand and product.  But it’s hard to know precisely what content is responsible for what opinions that in turn result in revenue-impacting decisions.  Humans just aren’t that linear in their behavior.  Often many pieces of content will influence an opinion, sometimes over a period of time.

Just because one can’t measure the direct revenue impact of content items does not mean these items have no revenue impact.  A simple example will illustrate this.  Most organizations have an “about us” page.  This page doesn’t support any revenue generating activity.  It doesn’t even support any specific customer task.  Despite not having a tightly defined purpose, these pages are viewed.  They may not get the highest traffic, but they can be important for smaller or less well known organizations.  People view these pages to learn who the organization is, and to assess how credible they seem.  People may decide whether or not to contact an organization based on the information on the “about us” page.

Non-transactional content is often more brand-oriented than product-oriented.  Such content doesn’t necessarily talk about the brand directly, but will often provide an impression of the brand in the context of talking about something of interest to current and potential customers.  These impressions influence how much trust a customer feels, and their openness to any persuasive messaging.  Overall content also shapes how loyal customers feel.  Do they identify with being a customer of a brand, or do they merely identify has being someone who is shopping, or as someone who was a past-purchaser of a product?

Another type of non-transactional content is post-purchase product information.  A focus on content for conversion can overlook the financial implications of the post-purchase experience. People often make purchase decisions based on a general feeling about a brand, plus one or two key criteria used to select a specific product.  If they are looking to book a hotel, they have an expectation about  the hotel chain, and may look for the price and location of rooms available.  They may not want to deal with too many details while booking.  But after booking, they may focus on the details, such as the availability of WiFi and hairdryers.  If information about these needs isn’t available, the customer may be disappointed with his decision.  Other forms of post-purchase product information include educational materials relating to using a product or service, on-boarding materials for new customers, and product help information.

The financial value of non-transactional content will vary considerably for two reasons.  First, no one item of content will be decisive in shaping a customer’s opinion. Many items, involving different content types, can be involved. Second, the level of content offered can be justified only in terms of the customer’s value to the organization.  Content that’s indirectly related to revenues is easiest to justify when it’s important to developing customer loyalty. Perhaps the product is high value, has high rates of repurchase, or involves a novel approach to the product category that requires some coaching to encourage adoption. Developing non-transactional content makes most financial sense when aimed at customers who will have a high lifetime value.

Measuring the impact of content that influences customer opinions is hard — much harder than measuring content designed around defined outcomes, such as the conversions on product pages.  But with clear goals, sound measurement is possible.  Content that’s not created to support a concrete customer action needs to be linked to specific brand and customer goals.  Customer goals will consider broader customer journeys where the brand and product are relevant, and where is there is a realistic opportunity to present content around these moments.  Appropriate timing is often critical for content to have an impact.  The goals of a brand will reflect a detailed examination of the customer lifecycle, and a full understanding of the future revenue implications of different stages and the brand’s delivery of services prior to and following revenue events.

The Ultimate Goal: Content that Supports Higher Margins

The two most common approaches to “Content ROI” involve improving conversion rates, and reducing content costs.  These tactics are incremental approaches —useful when done properly, although potentially counterproductive if done poorly.

To realize the full revenue potential of content, one can’t be a prisoner of one’s metrics. The things that are easiest to quantify financially are not necessarily the most important financial factors.  Many organizations fine-tune their landing pages with A/B testing.  Many of the changes they make are superficial: small visual and wording changes.  They are important, and have real consequences, lifting conversions.  But they only scratch the surface of the content customers consider.  The placement and color of buttons gets much attention partly because they are relatively simple things to measure.  That does not imply they are the most important things — only that their measurement is simple to do, and the results are tangible.

Conversion metrics measure the bottom of the marketing funnel: making sure people don’t drop out after they’ve reached the point of purchase page.  What’s harder to do, but potentially more financially valuable, is to expand the funnel by focussing on who enters it.  Content can attract more people to consider a brand and its products, and attract more profitable customers as well.

The biggest opportunity to increase revenues is by attracting people who would be unlikely to ever reach your product landing page.  How to do this is no mystery — it’s just hard to measure, and so gets de-emphasized by many metrics-driven organizations.  The first approach is to offer educational content, so that prospective buyers can learn about the benefits of a product or service without all those pesky calls-to-action.  People interested in educational content are often skeptics, who need to be convinced a solution or a brand is the right fit.  The second approach is through personalization.  The approach of intelligent content points to many ways in which content can be made less generic, and more relevant to specific customers. Many potential customers can’t see the relevance of the product or brand, and accordingly don’t even consider them in any detail, because existing content is too generic.

But profitability is not just about units of sale.  Profitability is about margins.

The first avenue to improving margins is reducing the cost of service.  Many content professionals focus on reducing the cost of producing content, which can potentially harm content quality if done poorly.  The bigger leverage can come from using content to reduce the cost of servicing customers.  Well-designed and targeted content can reduce support costs — a big win, provided the quality is high, and customers prefer to use self-service channels, instead of feeling forced to use them.

The second avenue to improving margins involves pricing.  Earlier I noted that the financial value of content depends on the financial value of the customers for which the content is intended.  A corollary holds true as well: the financial value of prospective customers is influenced by the content they see.  Valuable content can attract valuable customers.  It’s not only the volume of sales, it’s about the margin each sale results in.

Customers who see the brand as being credible and as being leaders are prepared to pay a premium over brands they see as generic.  This effect is most pronounced in the service industry, where experience is important to customer satisfaction, and content is important to experience.  Imagine you are looking to hire a professional services firm: a lawyer, an accountant (who appreciates the value of content), or perhaps a content strategist (maybe me!).  What you read about them online affects how you view their competency.  And those impressions will impact how much you are prepared to pay for their services.

These effects are real, but require a longer period to realize. Long-term projects may not be appealing to organizations that only care about quarterly numbers, or to product managers who are plotting their next job hop.  But for those committed to improving the utility of content offered to prospective customers, the financial opportunity is big.

Discovering Value

When seen from the perspective of how brand credibility affects margins, content marketing that often doesn’t seem linked to any specific outcome, now matters significantly.  It is not simply who knows about your firm that matters: it is about how they evaluate your capabilities, and what they are prepared to pay for your product or service.  Potential customers not only need to be aware of a firm, and have a correct understanding of what it offers, they need to have a favorable impression of it as well.

Content that provides a distributed rather than direct financial contribution needs its own identity. Perhaps we should call it margin-enhancing content.  Such content enables brands to be more profitable, but does so indirectly.  The task of modeling and monitoring the impact of such content requires a deep awareness of how pieces may interact with and influence each other.  By its nature, estimating the strength of these relationships will be inexact.  But the upside of endeavoring to measure them is great.  And through experience and experimentation, the possibilities for more reliable measurements can only improve.

Measurement is important, but it’s not always obvious how to do it. For much of human history, people were unaware of radiation, because it could not be directly seen.  Eventually, the means to detect and measure it were developed.  The process of measuring the financial value of content involves a similar process of investigation: looking for evidence of its effects, and experimenting with ways to measure it more accurately.

— Michael Andrews

What is the Value of Keywords Today?

The power of search engine keywords is waning. Since the introduction of semantic search with Google’s hummingbird search rewrite, they no longer have a decisive influence in search ranking. At best, they are simply one of dozens of factors involved with semantic search results. Perceptions about keywords have been slow to change for authors and marketers who don’t specialize in SEO, and even for some SEO consultants. Google  throttled the flow of keyword information to content producers, but many people still consider search keywords important or even essential.  Search keywords have become a crutch on which brands and authors rely to try to communicate with audiences.

It’s a challenge to reverse a decade or more of group-think relating to keywords.  For a keyword loyalist, giving up old habits can be hard, even habits that no longer make sense — especially when there are no obvious replacement tactics.  Keywords are more often used unthinkingly than used constructively.  The good news is that although keywords offer limited value to improve SEO, they can improve content quality in selective cases. It’s important to know the difference between the fetish use of keywords in content, and the creative application of keyword insights to improve the quality of content offered to audiences.  The difference between keyword hacks and keyword understanding is methodology.

Search Keywords Shouldn’t Describe Page Titles

The SEO industry has responded to Google’s introduction of semantic search with confusing advice. Although Google doesn’t match exact keywords on a page with keywords used in search queries, numerous SEO consultants still maintain search engine keywords are vital to how Google understands content.  Sure, Google can reinterpret search queries; but they argue if you write natively using the most popular keywords used in search queries, it’s simpler and more effective.  These people suggest that things have changed less than they seem. They note that Google still indexes keywords in search, and still has a keyword planner writers can use.

As Google has altered its behavior over time, SEO has deformed into an incoherent set of tactics.  Many ordinary content producers have lost the ability to understand what these tactics really deliver. They consult Google’s AdWords keyword planner to guide the creation of content, often at the urging of SEO consultants who encourage the practice. The AdWords keyword tool may present forecasts of impressions associated with a search keyword.  But ad impressions are not the same as search impressions (an impression being the existence of an item on a page accessed by a user, not necessarily an indication that the person noticed the item).  The algorithm Google uses to prioritize the display of paid advertising based entirely around keywords is different from the algorithm it uses to prioritize organic search results based on search terms and contextual information. It’s a mistake to use Google’s keyword planner for advertising and assume it will deliver a better search ranking or more qualified audience. But content producers make this assumption all the time, because it is convenient and they lack a conceptually sound process for developing and writing about content.

Significantly, Google’s AdWords encourage the decoupling of search keyword terms from the specific terms used in the content displayed in an ad.  Ad content can be related to the keyword bought without using the actual phrase.  The mandate  that you are supposed to use the exact term in your writing doesn’t even apply to advertising, the one area where Google encourages keyword research. Search engine keywords aren’t magic: they are simply a pricing mechanism for ads.

Search Engine Keywords Mask User Intent

Another common use of search engine keywords is to research popular topics.  SEO consultants and writers believe that search keywords provide them with data-rich market research that will tell them what content they should produce.  But search keywords have never been very solid as data to understand audiences. No matter what tool one uses, the tool won’t illuminate who is seeking information or necessarily why.  Making bold assumptions about people, their motivations, and their likely behavior based on a few search engine keywords is a risky thing to do.

Consider the case of people searching for the phrase “dead Wi-Fi.” This example is fairly typical of search terms: short, inelegant — and ambiguous. Who are the people typing this phrase and what is their intent?  Is the phrase “dead Wi-Fi” more likely to be entered by a 20 year old or a 60 year old? What might the phrase suggest about their level of understanding of wireless routers?  And most importantly, what can we infer about the intentions of the numerous people entering this phrase?  Are they all the same, or do different people have different goals when using the exact same phrase?  Why, when presenting search results matching the exact same search phrase, will different people make different choices about which article titles to click on? Rather than providing answers, the search keyword raises questions.

How search engine keyword can result in different audience behavior

Google prioritizes results to show the most popular pages that seem to match what Google interprets the search to be about. To illustrate, let’s suppose the first search result presents an article about Wi-Fi dead zones in your house.  Google presents a specific popular article on reception problems by interpreting dead to mean “dead zones.”  The eighth search result might provide an article on resolving general Wi-Fi problems, perhaps discussing when the Wi-Fi antenna on a phone or computer isn’t functioning. Here Google presents a popular page on fixing malfunctioning Wi-Fi equipment by interpreting the term dead to mean “not working.” The 15th search result might be entitled “Freedom from Dead Wi-Fi.”  This article title exactly matches the search term, but its purpose is not clear.  It is actually a page promoting the sale of new Wi-Fi equipment rather than a help article to fix existing equipment.   It features images and copy describing a futuristic looking box with many antennas that might appeal to the gamer crowd.

The search ranking for the article “Freedom from Dead Wi-Fi” was determined by two factors: people who entered a different phrase but decided to click on the title, and those who entered the exact phrase. Those who entered a different search query may have been attracted to the aspirational, if vague, promise of having a hassle-free experience.  The term “dead” might resonate with gamers in particular, who don’t want to be on the dead side of anything.  Those who entered “dead Wi-Fi” as a search phrase probably clicked on the title because of confirmation bias: it exactly matched what they thought they were looking for.  Confirmation bias is the tendency to identify with things that confirm our preexisting impressions or concepts.  So if you have content that has intrinsic popularity— it ranks highly anyway because it gets many page views — including a popular search keyword in the title may spur some additional page views due to the confirmation bias factor.  On the other hand, a title that merely sounds like it is helpful can run the risk of disappointing the viewer.  Some people viewing the “Freedom From Dead Wi-Fi” page wanted help on their current Wi-Fi problems. Pages viewed are not the same as audience interest in the content.

Without actually looking through numerous results, it’s not possible to infer much from the search keywords.   Viewing the content within the pages, one can find that the search keywords don’t represent a coherent set of user intentions.

Rethinking Keywords from an Audience Perspective

The purpose of any keyword research should be to understand the language of your audience, not to guess what will rank high on search engines.  And it is important to know what specific audience segments matter most to your organization.

Many people have a naive belief that aggregated, unsegmented Google keyword data provides a perfect mirror of their audience. SEO consultants and writers may believe they are promoting audience interests by using search engine keywords, but they are being data-focused rather than audience-centric.  They aggregate activity to create figures to justify content decisions, rather than start with the more granular needs of individuals and then identify common patterns. They put blind faith in often dubious numbers.

The Myth of the Undifferentiated Audience

People in different roles, from marketing to technical writing, want to believe their audience is undifferentiated. They want to believe that “everyone wants the same thing.” It’s simpler to do so. This mentality is common in marketing in particular: some marketing managers believe they need to talk to everyone and that everyone will want to listen to the brand.

There are a few brands that only care about page views, and care less about who the audience is. Advertising-supported publishers don’t care who visits their page: the ad shown will programmatically change according to who the person is.  Businesses that are purely transactional, such as hotel booking sites, similarly don’t care so much about audience segmentation: they want as wide an audience as possible to generate transaction fees.  But most businesses seek to capture value based on targeting specific kinds of customers, and providing products tailored to their needs.  If some of your customers a more profitable than others — because they buy more, pay more, or are cheaper to serve — simply pursuing page views will skew your brand value.

When brands act as if everyone is equally important, it generally signals a problem in business strategy, or poor operational oversight.  They don’t know, or at least don’t communicate internally, who are their most valuable customers and the need to focus on them.   As a consequence, we have situations where SEO consultants dictate editorial choices, or copywriters rely on keywords to write generic copy because they don’t understand precisely who the audience is, and how they think about the topic.

Shifting the Role of Keywords from Discovery to Understanding

Popular keywords that aren’t specific to the audience segment a brand wants to attract, only provide the illusion of data.  To provide value, keywords need indicate information to authors that is better than what they can get relying on available subject expertise.

Brands too often expect keywords to tell them what to say.  They focus on target keywords instead of target audiences.  They get fixated on the circular logic of “discovery”: they hope to discover the right keyword so audiences can discover the right content (theirs).  If keywords exist to promote discovery, they can’t at the same time be the object of discovery.  When this happens, the keyword becomes the end, instead of a means to an end.  The keyword defines the audience, instead of the audience being the party defining appropriate keywords.

If instead we shift the role of keyword away from “discovery” toward understanding, we get a more realistic goal. Brands need to understand which audience keywords will promote understanding of their content.  Here we assume the brand already knows what they want to say, they just need to know exactly how to phrase it.  The target is a message; the keywords are simply guidelines for presenting the message. The keywords relate to terms used by a specific audience, rather than a magic box of gold at the end of a rainbow.

Understanding Audience Segments Through Language

Audience keywords — the specific terminology used by an audience segment — is not something available from Google search data.  But audience keywords can be derived from various sources, and brands can find it worthwhile to understand linguistic differences.

One outcome of the vast quantities of text data that are now available is a growing understanding of language differences among groups of people.  Social media scholars, for example, notice words and even neologisms being used frequently by people associated with one another, while these same terms aren’t used widely in the general population.  Our language usage seems to be drifting back into distinct linguistic dialects, a consequence of both our online social connectivity and our selectively accessing content (the filter bubble).  Now that the age of mass media is over, we no longer expect everyone to talk about things the same way.

Some writers may object to being concerned with linguistic differences.  For example, advocates of plain language argue that all content should be written in a way that anyone can understand it.  While such a goal is surely admirable for some sectors — government in particular — it is not true that all parties are equally satisfied with plain language descriptions.  I’ve seen scientists frustrated by the quality of writing using plain language to describe a topic that required more specialized words, which were not allowed.  They complain that a discussion is oversimplified or key details are missing.  Similarly, writers may insist they are writing about a topic of narrow interest, so that anyone interested in the topic is likely to talk about it in the same way.  But even for niche topics, there can be novices and experts.  I am not suggesting that the vocabulary of all topics need to be segmented by audience; I am simply noting that it can be presumptuous to act as if no differences in audience needs exist.

Audience keywords involve a different set of tools and data than search engine keywords.  Audience keyword analysis basically involves comparing the frequency of words in a target texts (corpus) of an audience, with the frequency of words used in another set of texts, often representing the general population.   This comparison allows a writer to understand what vocabulary is most unique to the audience, and how they use this vocabulary.  There are commercial SaaS products that provide these capabilities, such as Sketch Engine.  There are also desktop software programs that one can use.  I’ve used the popular Antconc program, for example.  For those wanting to process large sets of data, text analysis libraries in Python and in the R statistical software can be used.

The next task is identifying what content exists that can reveal the vocabulary your audience uses to discuss a topic.  A range of sources offer a rich corpus of content to identify the vocabulary used by your customers:

  1. For audiences who belong to topic focused communities of interest, the texts of publications they read regularly, such as hobby magazines (for understanding keywords of enthusiasts), or specialized trade publications (for understanding the  keywords of a B2B vertical segment)
  2. Transcripts of focus groups of a target audience segment
  3. User comments from audiences in social media, or community forum discussions
  4. Terms used in internal search.

By analyzing such source content, writers identify words with special significance that are used more frequently by an audience segment than by the population as a whole.  They can understand their audience’s preferred terminology, and nuances in how they describe things, especially adjectives.  These can uncover value propositions.

Tribal publications — publications dedicated to distinct tribes such as specific professions or groups of avid fans of an activity — are different from general publications that don’t have such a tight audience focus.  They are more likely to use lingo or jargon, and reflect the internalized language of the audience who read these publications.  They are also likely to be read more loyally, and therefore promote the usage of words in a particular way.

A special comment about using internal search terms (also known as vertical search).  Why are internal search terms are okay, but external search engine terms not?  People using site search are more likely to be your target audience.  They have seen your site, got of sense of who you are, and feel motivated to explore further.  Vertical search was once considered an indication of UX or information architecture failures. Now vertical search is it a key differentiator for brands to guide their customers to find their products.  Search logs from internal searches can provide information about the terminology that people coming to your brand use.

Keywords are Clues, not Facts

Keywords can reveal interesting clues about audiences. Clues suggest something, but they should not dictate it.  A hint in a crossword puzzle is different from the answer.  Internal search keywords, for example, can provide hints about dimensions of topics, and ways to discuss topics, but are not themselves the answer to what you should be writing. Not being clear about this distinction results in the clueless, fatalistic question: “What does the data say we should do?”  Being data driven may be virtuous, but running on autopilot isn’t. Clues aren’t facts.

Keywords Aren’t Market Data

Keywords may provide clues to audience interests, but don’t provide direct data.  One can’t infer directly from keywords who is using them.  You need other forms of data to tie the reader to the keyword.  So if you find an odd kind of search query showing up on your internal search logs, it does not automatically indicate that you should be producing content using that keyword.  Search keywords are reliable indications of interest only when the search keywords match the keywords of the audience that you want to attract. Perhaps a number of people who aren’t your target audience mistakenly came to your content and are trying to find something you don’t offer, or care to offer. Your own internal analytics data will probably provide a better indication of what content you should produce than relying on internal search logs. There can be a role for  search terms to gauge potential interest on topics about which you have not written previously, but your internal content usage analytics will in most cases be a better indication of what resonates with the audiences you attract.

Relying On Keywords Can Distort Meaning

Algorithmic assessments should never be a substitute for judgment in writing.  Two terms that seem similar, but have different frequencies, are not necessarily identical in meaning.  Related and similar-sounding words can have subtly different meanings, or different connotations.  One shouldn’t use the most popular term simply because it’s the most popular.  Make sure the term chosen is exactly equivalent to the term not chosen.

Sometimes more formal (and less popular) terms carry more precise meanings.  The best way to connect a term that’s popular with your audience with a more precise term that you need to use in your content, is through cross referencing.

Keywords Can Help Brands Develop a Preferred Terminology for Topics and Audiences

If you routinely write about a certain topic, it may be worth your effort to analyze audience discussion relating to the topic.  Text analysis programs can help brands determine the audience-preferred terminology relating to a particular domain.  While this is obviously entails cost and effort, it may pay dividends.

Ideally all writers will have sufficient subject domain expertise internalized to know the preferred vocabulary for an audience segment.  But writers often need to write about varied topics, and writing is often outsourced to others. Having a list of audience-preferred terminology with associated definitions can enable any author to write appropriately on a given topic.  Text analysis can even support development of a style guide.  For fields such as health and wellness, where words have precise meaning, a preferred domain terminology is helpful if some writers are not deep subject experts.

In the not too distant future, I can imagine commercial firms will offer tailored keyword products.  Brands will be able to get a list of “keywords of 18 – 24 year old skateboarders” or “vacation-related keywords of upper income 50 – 60 year olds.”  For now, content strategists will need to do the legwork themselves.

— Michael Andrews