The Influence Of AI On Content Marketing

The Influence Of AI On Content Marketing

In the digital age, for marketing to be effective it needs to include a content marketing strategy. Therefore, the way marketing approaches content strategy has evolved from the days of collecting demographic information to more sophisticated ways of engagement using technology. As marketing practices matured so did Artificial Intelligence (AI) to be more applicable to everyday business use cases. When AI was introduced to marketing, the result was a tremendous change in how businesses engage with customers.

The potential of AI can be seen across industries outside of marketing. Finance, healthcare, education, and telecommunications have been redefined by AI. Marketers across industries are leveraging in-depth analysis of customer data to gain actionable insights that drive business.

Automation In Marketing

The new marketing practices are capitalizing on automation to drive revenue. Businesses are learning how to create a content strategy, do SEO and social media management, and optimize email marketing with the power of AI. Such advancements provide better customer insights, more revenues, and better brand positioning.

AI Influencing Marketing Examples

1. Using Chatbots To Manage Customer Experience

 Part of the shift of consumer behavior online was the surge in people relying on chatbots for customer service. Gone are the days that customer service was done on the phone, the new way to connect with customers is online. Companies like Uber and Facebook utilize AI-powered chatbots to converse with users. AI capabilities make the interaction feel like the customer is talking with an actual human rather than a robot. The sophistication of chatbots has made customer service available 24/7 without human errors and inconsistencies. Industries such as banking use chatbots for basic customer service requests and pass customers along to live customer service agents for more complicated queries.

2. Improving Keywords

 Another advantage of AI-powered marketing is improved keyword intent for marketers. Google, as the leader in keyword marketing, is constantly working on improving its algorithm to enhance search results for people. By focusing on the information that people want to see, Google is focusing on user intent. Machine learning (ML), a subset of AI helps marketers identify the right keywords to find patterns in consumer behavior. Marketers rely on these data-driven decisions to segment customers better and personalize the marketing message.

3. Hyper Personalized Content

 One of the most significant benefits of using AI in marketing is the hyper-personalization of content. The customer journey has been redefined by personalization that is based on consumer behavior, interests, and interaction with different kinds of content. For marketers building a digital avatar of a customer is a powerful way to build brand loyalty, increase engagement, and drive conversions. Personalized content such as email marketing can cut through the noise on the internet that is competing for the customer’s attention and focus on what is important to the customer. AI is an iterative technology that figures out what works and what does not. As it learns customer preferences, it can customize messaging and automate content based on customer preferences.

Conclusion

Marketing is an industry dedicated to innovation given its sensitivity to customer demands. As AI became more ubiquitous in society, businesses across industries capitalized on its power. Specifically, marketing used AI-powered technology to develop a stickier content strategy. Applications such as chatbots, better keyword intent, and hyper-personalized content improve the customer experience and make marketing more powerful daily.

The Importance Of Textual Analysis

The Importance Of Textual Analysis

What Is Textual Analysis

Businesses use textual analysis to mine vast sets of data with minimum human effort. For businesses, investing in textual analysis tools saves time and resources allowing the focus to shift to more value-driven tasks. Most of the new data is created in an unstructured format. Traditionally, data has been stored in a pre-defined structured format for ease of access and analysis. Unstructured data presents a challenge for analysis. It is in free form requiring specialized tools to extract meaningful insights. 

Today, it is hard to estimate how much digital data is on the internet. The meteoric rise of data can be attributed to the last two years when 90% of all the data in the world was generated. From social media messages to emails and Google searches, the sources of online data keep multiplying from people spending more time online.

Advantages Of Textual Analysis

For a business, using a textual analysis tool such as the Content Analytics Platform (CAP) has several advantages:

1. Scalability

 A textual analysis tool provides instant analysis and results. You can save time and make teams more productive by automating the process of textual analysis and then repeating it.

2. Real-Time Analysis

 These days the world operates faster than ever. Accurate textual analysis can help a business acknowledge dissatisfied customers on time or handle a PR crisis. This is done by real-time monitoring of reviews, chat, social media channels, and customer feedback. Using real-time insights prepares a business to take the action needed before a crisis or problems unfold.

3. Consistent Results

 Manual work is prone to errors and inconsistencies. In a business, routine tasks such as replying to customer feedback can become repetitive and time-consuming. Textual analysis can alleviate tedious tasks with consistent analysis of data.

Why Does Textual Analysis Matter?

Textual analysis can be used in a variety of industries with impactful results, such as:

– Sentiment analysis for social media to understand a psychological and emotional state of a person active on social media

– Make distinctions in different contexts and forms of communication

– Recognizing a pattern of communication in a target audience

– Detecting bias or incendiary speech in communication

– Analyzing real-time communication and social interaction

Textual analysis can be applied to any piece of writing in a variety of fields. From social sciences, psychology, political science, marketing, literature, and sociology, textual analysis can be used to analyze the context, audience, and purpose behind communication. This enables industries to spot trends and anticipate the needs of the audience. It enables businesses to develop product lines, interact with customers, and scale the business while being responsive to customer feedback and attitudes.

Conclusion

Textual analysis is just part of the new wave of tools being developed to transform the way content is consumed and communicated. It gives insights that shape Artificial Intelligence (AI) practices for the development of more accurate machine algorithms. It also takes the tremendous amount of data available on the internet and tries to make sense of it for a business in real-time.

RACI Matrix For Project Management

RACI Matrix For Project Management

What Is Project Management

Project management (PM) is a discipline that focuses on the planning and organization of resources to move a project towards completion. Project management can be a one-time project or a series of goals that can include resources from different departments of the company including HR, finance, and technology.

The principles of project management make it different than daily operations. Fundamentally, a project has a beginning and an end. Therefore, everything that happens in the project has the goal of a successful outcome. The phases of a project include initiation, planning, execution, monitoring, controlling, and closing. Technological advances have made the field of project management more sophisticated. The introduction of automation made it possible to use technological tools that let the computer do the work instead of expending human labor hours. Automation frees up the team’s time for other important things that cannot be automated that require human intelligence and ingenuity for execution. These technological tools are advanced but simple to use. A user can set up a computer system to determine responsibility or create a management dashboard with which the user saves a lot of time that could be used elsewhere.

What Is A RACI Matrix

Project managers use Responsibility Assignment Matrix (RAM) models to increase efficiency in the completion of a project. One of the types of RAM models is a RACI matrix. The RACI matrix is specific on identifying who is R (responsible), A (accountable), C (consulted), and I (informed) regarding a specific subject matter that would be used in a system development project. The use of the RACI is broader than just IT systems development projects, it could be used for any project. So, if a user wants to be efficient, he can specify where people can get their answers from in a document. If a user is trying to build something, he could determine that and then publish it for the people involved in the project to go and refer to. A user can specify a location where someone who needs to have input can go to get an answer. This can be done throughout all the things mentioned in the RACI.

RACI Matrix In Project Management

In project management, RACI is only one model, there are other models that could include support needs. This enables a user to add support to that particular model. Scion Analytics offers the Content Analytics Platform (CAP) with unique capabilities such as content mapping as well as where anyone could build a customizable RACI matrix. CAP has capabilities that could look at an RFP or a text back and determine any kind of requirements. Then base the requirements on the words to determine which people need to be involved in parts of the RACI. The CAP offers a model called Responsibility Assignment Support Consulted Informed matrix (RASCI) which includes Support. That is just one of the varieties of available models, there are a lot of other types of models. The RASCI reads through a text back and breaks it down into components. The components can be by legal or paragraph then it looks for words set up in a library. It then takes keywords and points them at the areas of the company that the user wants to identify for the Responsibility matrix.

RACI Matrix In Project Management Example

An example of the RASCI is when a user is reading the text back and sees the phrase “help desk”, he is going to know that “help desk” gets pointed to an area of the company called support. Therefore, the RASCI helps identify for the user that whenever the word “help desk” appears that support is going to be responsible and held to service level agreements (SLA). The SLA represents an area or a vendor of the company that is held to an indicator for their quality of service.

Conclusion

The RACI matrix is a useful tool in project management that increases the efficiency and the productivity with which the project is completed. The CAP offers various models of the RAM that can automate the process with which companies tackle projects.

Disadvantages Of Unstructured Data

Disadvantages Of Unstructured Data

Difficult To Analyze

Since there is a lot more unstructured data than structured data, there are also challenges associated with this type of data. First, unstructured data is difficult to analyze. An average person with a working knowledge of Excel cannot mine unstructured data. This is more realistic for using structured data sets with business intelligence. Processing unstructured data is reserved for data scientists and data analysts with proper training and tools. Unstructured data in raw format is difficult to wrangle and interpret.

Requires Specialized Tools

Second, unstructured data requires specialized tool. Most businesses invest in a specific data management tool to analyze data. For example, the text analytics platform from Scion Analytics, the CAP liberates value from unstructured data with AI and NLP powered capabilities. With minimal training, a business can use the CAP to analyze and process data they did not even know they had. These new insights could amount to data drive an actionable decisions on business intelligence that was previously based on guesswork.

Storage

Other challenges of unstructured data include the storage aspect. Structured data has a predefined format, and it is easy to store and organize. Due to a lack of schema and structure, unstructured data is expensive and difficult to store. Having to manage the storage aspect of unstructured data is just one facet that differentiates it from structured data.

Indexing Difficulties

Since structured data has been traditionally used for a long time, approaches to unstructured data are still being developed. Indexing unstructured data is difficult and prone to error due to free form structure and a lack of pre-defined attributes. The difficulty of accessing and analyzing unstructured data makes search results not very accurate. Finally, the complexity of unstructured data makes security a challenge. Whereas security methods for structured data are available, they are still being developed around the security of unstructured data.

Conclusion

The buzz about unstructured data has gripped businesses across industries. Many businesses from healthcare to technology have been revolutionized by access to previously hidden insights that reside in unstructured data. Executives across the world embraced unstructured data with its boundless opportunity.

A new crop of technological advances grew up around unstructured data. Text analytics platforms, statistical models, and AI powered tools have been developed to harness unstructured data. This innovation has not gone unnoticed by the business sector. Benefits of unstructured data are far reaching in implications. For a business if 80-90% of data is unstructured, the insights gained from analyzing this data set are unlimited. These insights create new revenue streams, scale businesses, and push innovation forward into the future.

What Is Automated Content Mapping?

What Is Automated Content Mapping?

What Is Content Mapping?

Content mapping accelerates data transformation resulting in improved business processes and project planning.Scion Analytics has developed technologies that are a catalyst for organizational growth. Automated Content Mapping (ACM) is a unique capability to the Content Analytics Platform (CAP). 

Until recent years, unstructured data remained inaccessible as a transformational tool for businesses. Typically, 80-90% of an organization’s data is unstructured, the potential of tapping into that data source is a tremendous opportunity to gain knowledge on the organization’s content. Transforming unstructured to structured data provides the ability to make smart decisions and become more productive.

ACM, powered by Artificial Intelligence (AI) and Natural Language Processing (NLP) technologies, is an advanced level of textual analysis with automation that adds significant value to a business in any industry.

Why Does Automated Content Mapping Matter?

Productivity

For a business, the accessibility of advanced textual automation has a powerful influence on productivity. It reduces errors, saves time and money, and enables a business to scale. The development of these leading technologies has changed the paradigm of business operations. Businesses are discovering the art of the possible with smart automation which has previously been constrained by manual processes.

RACI Matrix

One of the most well-known Content Mapping (CM) artifacts is the RACI matrix, the most popular model of the Responsibility Assignment Matrix (RAM). RACI stands for Responsible, Accountable, Consulted, and Informed as it identifies key roles and responsibilities in a project. Social media giants like Instagram use RACI models to become more agile in operation and aggressive about innovation. The platform comes with 9 RAM models, but a customizable model can be built as well.

Project Planning

Why does Automated content mapping matter in project planning? It provides a huge timesaving. For example, typically for a business to create a RACI matrix manually takes approximately 10 hours or more. Using the ACM, creating a RACI takes 3 minutes or less.

Automated Content Mapping Examples

The Automated Content Mapping capability in CAP can be used for more than Responsibility Assignments. Here are a few examples:

Requirement Associations

For a business, the ACM can map Business Requirement Documents (BRD) and Functional Requirement Documents (FRD) to appropriate departments. The BRD outlines high-level business needs regarding what the business wants to do. The FRD is composed of the functions required to fulfill the business need. The FRD guides the business on how business requirements should be done. Content mapping makes data mapping of BRD and FRD fast, and accurate, responsive to business needs.

Bid/No Bid

 In the government contracting industry, ACM is used to identify content that needs to be reviewed by department heads in a Request for Proposal (RFP). This capability radicalizes decision-making in the proposal development processes by quickly flagging risks, requirements, and required resources.

Document Review 

Another application of ACM is document review. It maps response forms for the appropriate proposal color team to review. This speeds up the proposal review and ensures that the right personnel are assigned to response sections.

Pricing

A practical application of ACM is automating the pricing structure in business operations. Data mapping can identify items and services then automatically calculate costs therefore reducing errors in pricing.

Tasks

Identify tasks and assign them to their associated phases/steps and teams. For example, a user can look at a keyword or a phrase and say this belongs to accounting. This capability helps determine what area of the organization needs to be involved with the sale or the team.

Content Mapping Best Practices

At Scion Analytics, we harness the power of robust technologies such as Automated content mapping to be a catalyst for innovation. We developed this unique capability in the CAP, the only one of its kind in the marketplace, so businesses can take advantage of unstructured data in new ways.

The ACM capability takes the subjectivity out of creating reports and matrices. It uses customizable dictionaries to map consistent and uniform allocations. Once team leaders agree upon a dictionary, it can be used with various documents or be customized for each document. This process ensures automated allocations are not based on individual preferences like manual allocations.

Scion Analytics goal behind creating ACM was to make content mapping steps as easy as possible for users by simplifying and automating steps so even non-technical business users can use it. For customization, ACM configuration is a simple process of selecting Dictionary Categories and assigning them Excel cells and columns. Additionally, we provide out-of-the-box Excel templates. No macros or programming is needed.

Content Mapping Service

We believe leading the marketplace in content mapping technologies is only part of the solution. Scion Analytics takes a consultative approach to transform businesses. By building customized microservices that deliver instant results and developing capabilities like Automated content mapping. It saves you time and money and frees your business from manual processes.

We empower you to imagine what you can do with CAP

Scion offers our services to help your team get up and running quickly by providing our Technical Service Team to create Dictionaries and Templates. In addition, our Technical Service Team provides training as well. However, because it is rather easy to create Dictionaries and Templates, many users learn on their own in one or two hours. Scion Analytics gives you the strategy and tools to innovate past your competition.

ACM is a new breed of smart textual analysis automation that redefines the way content is optimized for business. As businesses adopt new ways of processing content and information into knowledge, resulting in insights that pave the way to progress.

The Benefits of AI In Content Marketing

The Benefits of AI In Content Marketing

How AI Has Impacted Marketing

AI technology has been adopted by a diverse array of industries. From financial services to healthcare, service delivery and the customer experience are being redefined by automation. One industry that has seen a radical change in practices due to AI has been marketing. Marketing is highly sensitive to the customer experience and the customer journey. It makes sense that the introduction of AI would change traditional ways of doing marketing. Some of the most significant benefits have been seen in content marketing. What kind of content customers consume and how it is being delivered is in a state of transition. Due to automation, content has become more intimate with a hyper-personalization that has been taken out of the context of 1:1 communication onto the internet.

Benefits of AI In Content Marketing

1. Hyper-Personalization Of The Customer Message

Generic marketing campaigns and mass messaging are history. With so much noise on the internet, marketers have recognized that a generic message blasted out to thousands of people is ineffective at best and at worst intrusive. These days customers expect hyper-personalized content that is curated based on their interests, behavior, and content consumption. Here are some statistics that support this trend.

– 52% of consumers would switch to another company if they were not getting personalized communication

– 80% of marketers believe personalized messages are more effective than generic

– 72% of businesses prioritize making the customer experience better as one of their top objectives

2. Better Marketing Campaigns

 The effectiveness of a marketing campaign is based on engagement and conversions. AI can make those objectives more effortless for marketing. Rather than tailoring thousands of messages manually, AI can automate the process of personalization. In marketing, AI is iterative, with each marketing campaign it figures out what works and what does not. Just like

humans learn with experience, AI systems learn overtime to deliver a more effective marketing message.

3. Tailored Content Strategy

 AI-powered marketing helps businesses to provide the right content to the right audience at the right time. AI uncovers data-driven insights that lead to new opportunities in marketing. Now, marketers can analyze a limitless amount of data on different customer segments such as income levels, personal interest, social media platforms, etc. By slicing and dicing data, marketers can uncover new opportunities and angles to make messages stickier and more personalized. Other technology tools such as text mining can do sentiment analysis on social media to uncover customer behavior trends and moods underlying social media communication. This enables marketers to be more responsive to audiences and anticipate their needs.

The Future of AI In Marketing

In the future, AI-powered marketing will eliminate the need for manual processes in marketing. Such tasks as doing keyword research and organizing a content calendar, creating email marketing, and lead generation will no longer require a human touch.

The efficiency and productivity of AI will transform marketing practices. Also, using AI to uncover data-driven insights will lead to new opportunities. Marketers will be able to automate redundant and mundane activities and focus on higher value-added activities that will encourage innovation

How To Improve Readability

How To Improve Readability

What Is Readability

A writer’s best-kept secret is readability. Readability is the practice of effective communication. To use transparent communication that is accessible to the most general audience. Why does it work? Readability works well for a variety of subjects because it produces digestible content. In 2010, the average reader had an attention span of 12 seconds. By 2021, that attention span has shortened to 7 seconds.

Readability Example

Most people are busy and do not have the time or the patience to read long complex sentences. They want content that is clear and to the point. For example, if a reader is searching on “how to learn Chinese”, they can come across two different search results. One search result is: “The study of Chinese language is a complicated undertaking that takes into consideration the nuances of Chinese characters and how to read them. Chinese tautology has a rich cultural meaning underpinning the semantic context”. That sounds confusing and the reader must overly exert themselves to process the context. Another search result can be: “The Chinese language is a hard language for new students to study. Because of the Chinese culture and characters, there’s a lot to understanding it.” The message has clarity and brevity and gives the reader exactly what they were looking for.

How To Improve Readability

1. Use Plain Language

Plain language improves readability because it is concise and to the point. It does not rely on jargon or complex sentence structure to communicate. Federal agencies are mandated to use plain language as well as some businesses prefer to use it. Research has found that the average American reads at an 8th-grade level. Using plain language ensures that the content is accessible to the widest audience.

2. One Idea Per Sentence, One Idea Per Paragraph

 Short sentences and focused paragraphs increase readability. A good rule to follow is to use one idea per sentence and one idea per paragraph. It is a good practice to start the paragraph with the main idea and follow

with the details. This ensures that the right message is communicated to the reader, and they do not get lost in long-winded sentences.

3. Leave Out The Adjectives And Adverbs

 Adjectives and adverbs have a place when it comes to expository and creative writing. However, for writing that relies on plain language and focuses on readability, a writer should omit them. Adjectives and adverbs provide nuance and descriptions to verbs and nouns in some writing formats. But readability is about precision in communication which leaves little room for interpretation. A writer can increase readability by sticking to an active voice and omitting adjectives and adverbs.

4. Use A Readability Tool

To improve readability, a writer must have good writing habits. But sometimes even professional writers need extra help. By using a readability tool, such as offered by the Content Analytics Platform (CAP) by Scion Analytics, a writer can automatically assess and improve the readability level of content.

Conclusion

Readability makes good writing great and accessible to the reader. A writer should always strive to improve readability for a better experience for the reader.

Benefits Of Plain Language

Benefits Of Plain Language

In 2010, when President Obama signed into federal law the Plain Writing Act of 2010 it was to mandate that federal executive agency use plain language as a standard of communication. The premise of this law is that the American public deserves plain language communication from its government. As plain language became more ubiquitous across the government and business sectors, the tangible and intangible benefits of plain language and readability become more emphasized.

6 Reasons To Use Plain Language

1. Plain Language Is Efficient

These days people have short attention spans. A decade ago, marketers measured that the average reader’s attention span was 12 seconds. Now, the average reader’s attention span is a mere 7 seconds. That is about as long as it takes to read these two sentences. A writer needs to capture the attention of the audience and that is best done with plain language. That is because it gets your message across in the most efficient way possible.

2. Plain Language Is Clear

For businesses, a message is only effective when it is understood. Plain language is based on an 8th-grade reading level ensuring clarity and simplicity in communication. Did you know that the average American reads at an 8th-grade level? For messaging to be inclusive and accessible, it needs to be clear to the general audience.

3. Plain Language Is Easy To Understand

This is especially important when it comes to writing an instructional manual. Plain language is easy to understand, and instructions written in plain language are easy to follow. For a business, this reduces complaints, inquiries, and confusion from customers that are unable to follow complicated instructions.

4. Plain Language Is Better For Marketing

When it comes to user experience on the website and digital marketing collateral such as blog posts, web pages, and articles, plain language offers businesses more of a competitive advantage. Websites written in plain language have less of a bounce rate. Marketing collateral written in plain language drives revenues and builds customer loyalty as it is more

appealing to a wider audience. Also, consider that marketing promotions for a complicated product in the tech space tend to perform better when written in plain language as opposed to technical jargon.

5. Plain language Creates A Positive Image

Using plain language creates a reputation for your business as one that puts people first. Because when you have clear communication, it comes across as having consideration for your audience. Making sure that your audience feels acknowledged by transparent and honest communication. This promotes a positive reputation for the brand as well as customer loyalty. The internet is full of noise and competing for marketing messages. By using plain language, a business stands out from the crowd and tailors its message to the customer.

6. Plain Language Is Universal

While plain language became law for government agencies, it was also used across different industries to improve communication. Businesses such as banks, insurance companies, law firms, legal services, and IT companies use plain language to communicate with customers. This saves time and money with every message that the business puts out.

Conclusion

The benefits of plain language are tremendous for businesses that are looking to have transparent and efficient communication with customers.

What Is Plain Language Writing?

What Is Plain Language Writing?

When the Plain Writing Act of 2010 was signed into law by President Obama the whole country took notice of plain language writing. The law mandated that federal agencies use plain language in all their communication. This was done to create transparency in communication between the government and Americans. Several corporations and business entities followed suit after the government under the premise that plain language communication is transparent and honest. As human beings, we feel more comfortable and connected with communication that is simple and easy to understand. It also improves readability. Any deviance from simple language becomes open for confusion and misinterpretation.

So, what is plain language writing? How can a writer become better at using plain language?

6 Fundamental Rules For Plain Language Writing

1. Write For Your Audience

One of the cardinal rules of plain language writing is to write for your audience. The needs of the audience and the reading level of the audience must be considered. Research has found that the average American reads at an 8th-grade level. Keeping those statistics in mind do away with convoluted language and jargon and focus on what matters most- the reader.

2. Make Your Major Point First Before Going Into Details

Plain language writing is digestible. The writer should emphasize the main point first in the paragraph before going into supporting details. This focuses the reader and gets the point across without the reader losing interest.

3. Limit One Paragraph To One Point

Another fundamental rule of plain language writing is brevity. Plain language writing is known for using short sentences. It eliminates the grammatical mistakes of using long-winded or run-on sentences and keeps paragraphs limited to one idea. By keeping paragraphs focused, it organizes and structures the writing for maximum clarity and gets the message across to the reader.

4. Use Easy-To-Understand Words

An important rule of plain language writing is words that are easy to understand. The writer must do away

with complex words and jargon. If the writer must use technical words, they should be defined on the first reference. This is to ensure that the reader comprehends every word and there is no room for misinterpretation.

5. Use Active Voice

 Did you know there is a similarity between plain language writing and Ernest Hemingway? They both use active voice much more than passive voice in writing. Research has found that most of the bestselling novels of all time are written in active voice. Why? Because active voice provides clarity to the reader as to who is doing the action. Passive voice is less grammatically correct and harder to digest for the reader.

6. Write The Facts, Omit Everything Else

Plain language writing is journalistic in the sense that is a matter of fact. It sticks to the point, and it eliminates unneeded words and hyperbole to deliver the most concise message to the reader.

From government entities to businesses across industries, plain language writing is the foundation of effective communication.

What Is Readability?

What Is Readability?

Readability is a practice that determines how easy or difficult it is for a reader to understand a piece of text. There are different methods and equations for measuring readability which is comprised of different elements of writing. For example, word choice or syntax can influence readability. In marketing copy, a business that chooses the word “nonchalant” instead of “easygoing” is a business that is selecting to use words with poorer readability. For customers, these words are unfamiliar or complex leading to confusing and open-ended interpretations of the text. A business focused on effective communication is committed to sending out the right message.

Great business practices are built on effective communication. It can be the deciding factor between a business that performs well and engages with customers versus a business that is lagging in sales. But what makes communication effective? How can marketing and sales collateral inform the customer as well as attract attention? How can a business improve communication tactics? As businesses become more sophisticated so does how the business communicates internally and externally. This is in part due to the concept of readability.

On a general level, other factors go into a text’s readability such as sentence length, structure, and average syllables per word. Why is readability important? For a business, a customer needs to easily process information without straining to understand the text. Marketing copy that is full of jargon and complex ideas might make a customer lose interest in the company, bounce from the website, and not make a purchase.

One of the formulas that are used in readability is the Flesch Reading Ease Formula. It is used to assess the grade level of the reader. The Flesch Reading Ease Formula has become the standard used by many US government agencies such as the US Department of Defense.

The Specific Mathematical Formula Is For Flesch Reading Ease Formula:

RE = 206.835 – (1.015 x ASL) – (84.6 x ASW)

RE = Readability Ease

ASL = Average Sentence Length (i.e., the number of words divided by the number of sentences)

ASW = Average number of syllables per word (i.e., the number of syllables divided by the number of words)

Readability Benefits

Reader Engagement

To fully understand the benefits of readability, the accessibility of text needs to be put into the context of the Digital Age. The pioneers of readability, Rudolf Flesch and Robert Gunning, could not foresee the tremendous volume of information that would flood the Internet. In its nascence, the Internet was a convenient way to share information that evolved into a content machine. These days, over four billion people are online, and businesses are aware that “content is king” contributing to an even greater demand for sticky content.

The sheer volume of information has probably shortened the attention span of readers. Research has found that in 2000 the average reader attention span was 12 seconds. In 2021, the average reader’s attention span is 7 seconds. That is a short time frame for the writer to grab attention and convince the reader to continue reading.

The pressure for content to be engaging keeps mounting as businesses undergo digital transformations. The benefit of a readability score is that it assesses how easy the text is to read. The easier the text is to read the more likely it will hold the reader’s attention. Readability provides quantifiable measurements for a text that can be used to set targets and metrics as part of a content strategy.

Plain Language

Another benefit of readability is its use of plain language guidelines. Plain language is a movement towards simplifying the content. It was started to make complex legal documents easier to read and is now mandated by the government and used by businesses around the world. In 2010, President Obama passed the Plain Writing Act of 2010 requiring federal executive agencies to adhere to plain language guidelines.

Why is plain language important? The basis of the law was the consideration that the average US adult reads at an eighth-grade level. This statistic shows the necessity of using inclusive language in government communication and beyond. Because plain and easy-to-understand language makes complicated topics more accessible to theaverage reader. It also improves the website user experience by addressing the website audience like a friend without formalities, in plain language.

What Is A Readability Score

For businesses, a variety of readability tools are available to help with messaging. By utilizing a readability tool, a business can generate a readability score. A readability score can signify to a business what level of education someone needs to read a piece of text easily. For example, using the Flesch-Kincaid readability score of 8 is approximately equivalent to a reading level of US grade 8. An 8th-grade reading level is appropriate to ages 13-14 and the writer must strike a balance between being informative yet accessible.

How To Improve A Readability Score

In business, the clarity and effectiveness of the message are important for successful communication. Once a business has come to rely on a readability tool, it can find ways to improve a readability score. The following are proven tactics for better readability:

1. Use Shorter Sentences

There are different readability formulas but one common denominator in all of them is: sentence length. By shortening a sentence, a writer can ensure a better readability score. For example, the sentence: “The friends had gathered for dinner under the candlelight with blue china patterns to be served orange duck with rice.” Can be shortened to: “The friends had gathered for dinner. It was served on blue china patterns. They enjoyed an orange duck with rice under the candlelight.” By breaking up sentence length, the reader can digest the point of each sentence easier. It also makes it easier to scan the text.

2. Minimize The Number Of Long Words

 Another component on which readability is score is word length. Some tests, such as the Flesch-Kincaid, use the number of syllables to calculate word length. Other tests, such as Coleman-Liau, calculate word length based on letter count. For example, using the word “prohibited” instead of “banned” will decrease readability. Using shorter, simpler words is a good tactic to use when writing for the public. However, writing for a legal or the financial industry, a writer may have to use more complicated terminology that is appropriate for that audience.

3. Write For Your Audience

One of the foremost rules of plain language and readability is to be inclusive and transparent with your audience. A piece of writing is so much more effective when it takes into consideration the language particular to the audience it is addressing. A good example is a legal industry which is known for having legal terminology and jargon associated with its communication. If a writer chooses to use terminology, he should offer definitions in the text. With the readability, the goal in mind should be not to ostracize your reader. Considering that the average American reads at an 8th-grade level, that is the baseline most writers need to be mindful about when writing.

4. Use Punctuation

The goal of punctuation is to help your reader understand what is being said. Run-on sentences, fragments, inappropriate or misplaced punctuation lower readability scores. If the use of punctuation is an issue, writers should consult grammar checks or brush up on punctuation rules to make sure it is used properly.

5. Stick To A Structure

For the best readability, it is important to have text that is grammatically correct, clear, and concise. Another factor to consider is how to structure the text. A writer should think about the story he wants to tell. What are the key points? Does the reader need to know more information before engaging with the key takeaways? Having an outline for the text can help the writer prioritize the focus of the article. It also helps the reader follow the story and internalize the message, things that are conducive to readability.

Industries That Use Readability

Education

Readability as a tool and as a practice has meaningful application in many industries. For example, in education teachers use readability to decide whether a particular text is suitable in a curriculum for students. If “To Kill a Mockingbird”, the English literature classic is appropriate for a 9th-grade reading level, it may therefore be too simplistic for an 11th grade English class.

Business

In the business sector, many types of businesses utilize readability to simplify documents, so they are easier to read. This is true both for internal and external communications. For example, a tech company may run readability on an instructional manual it composed for its users. Furthermore, if that tech company uses the Content Analytics Platform (CAP) from Scion Analytics it can take advantage of creating dictionaries.

By using dictionaries in readability, a business can specific words that it wants to avoid in writing, jargon, inappropriate phrases, cliches, and legal risk words. The flexibility and customization of a dictionary help businesses ensure that their message is easy to communicate to the intended audience.

Marketing

Finally, readability is widely used by marketing departments to assess how well readers engage with digital marketing materials. Running readability of online texts such as blog posts, web pages, and articles can help professionals establish metrics for text. Using metrics, these professionals can improve the text to get better business results.

Conclusion

Readability is a practice and a tool that can help businesses communicate more effectively. Its adherence to plain language and reliance on short sentences, simple words, and easy to digest language makes it indispensable in engaging the reader with the right message.