Everybody is talking about AI these days. And no doubt that AI has already had a significant impact on various industries and continues to revolutionize the way we work and live. Within the realm of marketing, it is set to play a significant role in shaping the future of in-house marketing. From automating repetitive tasks to providing insightful data analysis, AI has the potential to transform the way businesses approach marketing and advertising. In this article, we will delve into the ways in which AI is influencing in-house marketing and what this means for businesses in terms of strategy and implementation. We will also examine the challenges and opportunities that come with incorporating AI into marketing efforts and what companies can do to stay ahead of the curve.

Businesses are now faced with the challenge of managing and making sense of vast amounts of data. However, the introduction of AI and Machine Learning technologies, along with other advancements like intelligent algorithms, Virtual Reality (VR), Augmented Reality (AR), screenless search, and voice search, has the potential to transform the way we create and consume content.

 

Marketers and content creators must adapt to these changes and be willing to embrace new technologies and strategies. By utilizing the latest tools and techniques, businesses can gain a competitive advantage and create more effective and engaging content. The key is to strike a balance between the power of machines and the creativity of humans. By working together, we can produce content that is both efficient and effective and that resonates with our audience.

 

In conclusion, the future of data-driven content is both exciting and challenging. But with the right mindset and approach, businesses can reap the benefits and stay ahead of the curve. It's important to keep an open mind and be willing to adapt as the landscape evolves. By embracing new technologies and working together with machines, we can create content that is more effective and engaging than ever before.

 

 

The Role of the Machine

The advancements in technology have greatly impacted the capabilities of computers and machines in creating marketing content. The incorporation of Artificial Intelligence (AI), Machine Learning (ML), and intelligent algorithms have enabled machines to perform tasks that were once thought to be solely the domain of humans.

 

One of the key technologies driving this change is AI, which refers to the increasing capabilities of machines to demonstrate intelligence that is traditionally attributed to human learning. ML, a subset of AI, relates to the ability of computers to learn and extract new meanings and insights from data sets.

 

Intelligent algorithms, which are sets of rules and processes followed by computers, also play a crucial role in removing repetitive human tasks. Natural Language Processing (NLP) and Natural Language Generation (NLG) are subfields of Computer Science and Artificial Intelligence that focus on the interactions and communications between humans and machines.

 

Chatbots, computer programs that simulate natural conversation, and Virtual Assistants (VAs) like Amazon Alexa, which provide assistance in both domestic and commercial settings, are also examples of technology that is being used to create marketing content. These tools are able to go beyond information provision and take action based on voice triggers, making them more efficient and useful for businesses.

 

As technology continues to advance, the use of machines in various industries is becoming more prevalent. In the realm of marketing and content creation, there are a number of ways that machines can be utilized to improve efficiency and effectiveness. Some of the key technologies include Artificial Intelligence (AI), Machine Learning (ML), Intelligent Algorithms, Natural Language Processing (NLP), Natural Language Generation (NLG), Chatbots, and Virtual Assistants (VAs). These tools can be used for a wide range of tasks, from fraud detection to customer service, online security, and even driverless cars.

 

However, it is important to remember that the role of machines in marketing content is not about replacing human jobs but rather about leveraging the strengths of both machines and humans to achieve the best results. By incorporating AI and related technologies into your marketing strategy, businesses can increase efficiency, improve content analysis and reporting, and ultimately achieve greater success.

 

Descriptive and predictive analysis.

Using descriptive and predictive analysis, businesses can gain a better understanding of past and current trends, as well as anticipate future changes, opportunities, and threats. This is achieved through the use of statistical analysis and machine learning/AI modelling. By utilizing this type of analysis, companies can benefit from more efficient insights and increased awareness of data changes, which can aid content and marketing teams in making informed decisions. For content writing, this can involve using seasonal trend data to predict popular topics to write about, or using data to provide a narrative for reports. Real-world examples of this include applications like Narrative Science's Quill.

 

Data visualisation and interactive reporting.

Data visualization and interactive reporting offer a more dynamic approach to analyzing and understanding data. By utilizing specialized software and applications, companies can gain real-time insights and a more in-depth understanding of their data. This can lead to increased efficiency and reduced manual labour, as well as a better understanding of the impact of content marketing on business goals and objectives. One example of this in practice is Heliograf, developed by The Washington Post, which allows for the creation of interactive and informative short reports.

 

Prescriptive data opportunities and advice.

Prescriptive analysis, which includes SWOT analysis, prescribed actions, and potential action prioritization, involves utilizing predetermined decision tree processes and approach towards data changes and new data sets. This allows for proactive advice on suggested next actions and focus areas, resulting in consistent application and action awareness on data changes, as well as the proactivity in identifying and sharing content and marketing opportunities as they arise. An example of this could be alerting your marketing team to new trending articles and socially trending topics that competitors are capitalizing on, but your company has yet to explore.

  

Gap fulfilment.

AI-driven content discovery allows for the identification of specific areas of opportunity within your business's content strategy, such as identifying gaps in coverage and uncovering new subtopics to explore. This information, coupled with relevant metrics, can be used to make data-driven decisions about the creation and promotion of content, ultimately leading to a more comprehensive and effective content strategy. With the ability to process and analyze large amounts of data quickly, machines are able to provide this information in real-time, enabling teams to take immediate action on new opportunities as they arise.

 

Content writing.

The use of AI for automated content creation, such as reports, blogs, articles, and even journalism, is on the rise. For any type of content that follows a specific format and is based on data, trends, and statistics, using machines for the creation process can be beneficial for businesses. This includes faster and more consistent content production, as well as error-free writing. Additionally, machine-generated content can be delivered in a timely manner without the influence of factors such as time of day, workload, or stress levels that can affect human writers. One well-known example of NLP-powered content creation is The Associated Press' use of Wordsmith by Automated Insights.

 

‘Story-making’.

I normally focus most on the importance of storytelling in content creation, but with the help of machines, we can take it to a whole new level. Machine learning models can be trained to uncover new insights and stories from data sets. Clustering techniques can be used to identify trends, opportunities, audience sentiment, and more. The potential for data-led story-making is endless when utilizing the power of machines in content creation.

 

Increased volume.

When it comes to automating content creation, the primary benefit is an increase in efficiency and output. By incorporating machines into the process of creating business marketing content, companies can expect to see a significant increase in the volume of content produced while reducing the need for human resources. This is achieved by utilizing machines to handle the more mundane and time-consuming tasks, allowing human team members to focus on more specialized and strategic elements of content creation. This shift towards machine-driven automation can be seen in various examples, such as the use of natural language processing (NLP) for creating news articles or automated journalism.

 

Handling complexity.

The proliferation of digital touchpoints has led to an increase in the number of interactions a consumer has with a brand before making a purchase. This has doubled in the last five years, thanks to the rise of mobile devices, voice search, wearables, and the ability for consumers to quickly access information for comparison shopping. By leveraging advanced analytics and data platforms, companies can gain valuable insights without the need for extensive data mining and analysis, making the marketing process more manageable.

 

Content promotion.

Machine-driven data frameworks can help improve the efficiency and effectiveness of identifying the right prospects, building lists of influencers, and promoting content on external websites. By analyzing large sets of data and identifying keywords and trending themes, machines can suggest optimal content promotion strategies. These strategies can then be executed through pre-determined workflows, allowing for the creation of complete content promotion campaigns. With the use of historical data, machines can quickly analyze the top-performing and highest-ranking content, determine the best target sites, and organize actions based on quality measurements and other human-like intelligence evaluations.

 

Company growth.

As machines continue to evolve and advance in their capabilities, their role in marketing content is becoming increasingly important. Companies are beginning to realize the benefits of incorporating machines into their strategies, such as increased efficiency and the ability to compete with larger brands. This shift towards machine integration in various areas of the business is also reflected in the growing expectations of their capabilities and presence in companies. With machines taking on more mundane and high-volume tasks, human resources can focus on specialized roles and higher-level strategies.

 

Integrated insights.

With the ability to combine and analyze various data sets, machines can uncover new insights that would not be possible through manual means. This can save businesses time and resources while also providing a competitive advantage by allowing them to act on opportunities before others do. This can be seen in the ability to apply unique expertise and identifying new content opportunities.

 

Deeper insights.

AI, machine learning, and intelligent algorithms can help uncover untapped content opportunities and make more effective use of untapped data for creating audience-specific marketing content. Whether it is a needle in the haystack, untapped content opportunities or making more out of the untapped data for creating audience-reflective marketing content. These technologies can help increase the quantity and quality of insights, leading to better business results.

 

Seamless content workflows.

Artificial Intelligence (AI) has the potential to revolutionize the content creation process by streamlining workflow and making it more data-driven. With AI, content ideation can be informed by data and insights, leading to more relevant and effective content. The writing process can also be improved with AI-enabled tools, such as natural language generation, that can help create high-quality, compelling content. Additionally, AI can help with content promotion, targeting the right audience, and even providing personalized content through chatbots and drip-feed marketing. By incorporating AI in the content creation process, businesses and marketers can achieve greater consistency in performance and place more emphasis on their expertise in refining and improving content.

 

Interactive content.

There is nothing new about interactive content, but it still fails to appear anywhere near as often as it could be for SMBs. Using computer programs, you are able to repurpose existing content and leverage its social sharing, PR, and engagement metrics with more exciting content type creation. It is unlikely that in the short term, interactive content will replace the more traditional text and image-based content seen in blogs, news and other website mediums; they are already revitalising marketing results and breathing fresh life (and results-based value) into business marketing content.

 

Performance gains.

Added machine involvement throughout the content process increases the likelihood of content performing closer to its optimum. Whether the content purpose is lead generation, brand exposure or audience education and information purposes, machines can facilitate better results based on historical performance, external data sources and top-performing content characterisation.

 

Resurfacing content.

A dominant content production failure is overlooking the repeat potential for content to resurface for new phases of business gains long after its initial inception. With machines providing social listening, trend monitoring and media awareness into your marketing alerts and updates processes, you can resurface and repurpose historical content with limited effort and optimum gains.

 

Increased engagement.

Leading us back to increased metric gains from ML and intelligent algorithm insights, increasing content engagement with data-led CTAs, heatmap data source use and on page/in-content refinements, you can maximise the engagement effectiveness of content. This supports perceived content value, impacting content results in areas such as SEO.

 

 

The Role of the Human

Unlike many expert assessments and mainstream media focus when it comes down to the future role of people in business and marketing content, I have a much more optimistic outlook and will explain why.

Most technological advancements are built for the purpose of making things easier, faster and more consistent. And while the progression of computers and AI specifically now incorporate levels of creativity plus other supplemental qualities, at a fundamental level, the main focus of these developments still pertains to the ‘easier, faster and more consistent’ methodology.

 

The role that people bring to the fore outside of data-driven intelligence includes emotional motivations, personal bias, and qualitative, subjective experience, which, when effectively supported by data, can produce something unique and special.

Regardless of how successful data collection and processing can be, and despite all of the isolated data-led successes that machines repeatedly produce, replicating outputs more reliably than any human being ever could compete with, there are the eureka moments that people provide that cannot be captured, distilled, replicated or processed. In the main, this inability to replicate ‘wow’ moments is based on the fact that we do not understand them completely ourselves. 

The following points reinforce the role of the human in marketing content. Because though I believe that AI and machines will play a huge part in content creation in the future, I don’t think we are there yet. But the near future belongs to those who understand the human/computer collaboration part.

 

Emotional awareness.

Content can make people laugh, cry, shout, scream and instigate all manners of reactions based primarily on emotional triggers. The global success of the John Lewis Christmas advertisements is a perfect example of this. Prior to a single airing on television, people are excited about what the next advertising campaign will be. There is little doubt that data and machines will have had some degree of inclusion in the marketing content ideation process; however, ultimately, the purpose of these TV Christmas adverts is emotional association. Even though qualitative data sourcing, perfecting emotion to the degree required for genuine human association and reaction is something, humans are the best place to deliver.

 

The art of storytelling.

Data can tell a story, but there is an art of storytelling which is undisputedly human. The ability for people to paint a picture through words, call upon memories to contextualise and humanise content and install nostalgic sentiment from audience familiarity and self-association is a truly human quality. The application of memories and anecdotes within marketing content has the power to lift the impact of outputs to create something memorable, shareable and able to support brand evangelism.

 

Tone of voice.

Tone of voice comes from people, not companies, and not computers. One of the reasons that blogs can have such an impact on traffic and brand visibility is that the content tone comes from the people writing the blogs. Frequently the most followed blogs are those that have numerous content writers, all with the freedom to express tone and personality through their blog posts.

 

Language evolution.

Language itself is a malleable tool which humans misuse, modify and change at will, sometimes leading to brand new language phraseology and nuances, at other times short-term, limited span (forgettable) content crazes (think about the 1990s and the inclusion of ‘cowabunga’ in the English Oxford Dictionary). It is difficult to place any logical certainty towards why terms like cowabunga ever existed, but they transform people through content into sentimental times gone by – a key tool in the human marketers' content toolkit.

 

Relatability.

Humans cannot relate to computers; it is not feasible. A vast majority of marketing and business content includes tonality and pitch supporting the relatability of the subject matter and the expertise of the writers to the identified audience personas being targeted. Relatability extends past key term use and user-generated content inclusion within marketing material, it involves empathy, understanding and real-world awareness difficult to teach in a computer environment.

 

Personality.

The individual qualities and characteristics that form a person's unique character. Personality is a unique biological quality. Via content, people are able to express and convey their personalities which leads to emotionally triggered business gains stemming from the audience and readership understanding and link to the content provided.

 

Business context.

Very few businesses have the same goals, objectives or requirements when they outsource expertise. The role of the marketing expert and content creator often incorporates some degree of business analysis, goal setting and situational understanding. This business understanding surpasses the data and informational levels of relationships and progresses into empathy. For content marketing and building to reflect distinct businesses, marketing messaging, and company cultures, there is the necessity to empathise and identify with the company. This business contextualisation through empathy and added understanding are human qualities required to create differentiated content outputs.

 

Trust.

People trust other people more than any other reference point. This can be seen through the proliferation of review websites, independent product/service testing and reporting websites, aggregator websites, forums, and trusted (believed impartial) video content growth. To establish trust, you need to demonstrate and substantiate credibility and expertise, and while machines can assist people in doing this, they cannot replace them.

 

Leadership.

There is a herd mentality that is ingrained in the behaviour traits of many audience personas. They (people) find it easier to make decisions based on following the path set by others. This practical leadership provision within content generally requires real-life people, displaying real-world purpose, positioning and benefits.

 

Authorship.

Also referred to as style, authorship explains the preference of writing style, approach and personalisation that not only differentiates content from one writer to the next but also has the ability to continually evolve (evolve over time and change based on environmental impact).

 

Authority.

Authoritative content has unique stand-alone value, setting it aside from competing examples, primarily based on the expertise provided by the person writing it. Expertise is almost impossible to replicate with any degree of credibility by anyone outside of the expert in question. Depth and completeness of problem-solving, practical experience-based reflection, as well as life skill reference, points all underpin this human factor for effective marketing content.

 

Accountability.

Taking on the accountability and ownership of content outputs and outcomes is an essential part of the content remit. Accountability cannot be attributed to computers/machines and plays an important part in content quality controls and measures, as well as the analysis, reporting and, ultimately, the success of content produced.

 

Opinion.

Opinionated content drives social shares, comments and debate. Opinions can be controversial, valid and misplaced, but ultimately, they have the ability to add another human aspect to the content created, which supports responsiveness and identification with people.

 

Video and visuals.

Great strides have been made notably within audio and text-based fields of content creation; however, the main growing content digestion trends surround video, broader vision, and interactive content types. The ideation, collaboration, and creative structures required for these content types are much more human-involved, with far fewer data-driven opportunities at this point in time (notably within the ideation phases and visual/video content understanding by machines).

 

When looking at distinctive human roles over the next few years, there is an added value of an emphasis on the positions related to content building and curation throughout the process that becomes increasingly human-dependent. Added to this are new roles, which will become apparent as we discuss human/computer collaboration.

Human/Computer Collaboration

 

Taking a look into the new roles and responsibilities created by human and computer collaboration, I think we can see the evolution of both approaches to create many unique and exciting opportunities as well as new functions which otherwise wouldn’t exist.

These newly formed and growing responsibility areas are some of the most exciting and perceived valuable by businesses, and you may be surprised to hear that quite a few of them have been around for some time now.

There is even a name for collaborative robot and human working, as this region has evolved to a stage, superseding previous benchmarks and expectations set (called ‘co-bots’).

The next few points focus on the changing approaches for content creation, looking forward to anticipated and increased human/computer working, plus a few of the new roles and responsibilities created by this collaborative environment.

 

Data Analysts.

Stemming from the traditional fields of mathematics, computer science, and data analytics, marketing and content experts will all find themselves increasing their expertise levels closer towards that of a data scientist. With data trends, comparison, time series, and substantially greater data involvement in all business decision-making, the perfect content writer and marketing professional will be a hybrid of many distinct parts. This will likely include (as it is already visible today) content, marketing, data (scientist and analyst), plus a few other areas such as PR and social media expertise.

 

The heavy lifting of machines will enable this multi-awareness increase as well as the more likely combined teams of multiple expertise. This is facilitated by employing more specialist content, data and marketing experts (with some overlapping expertise) and fewer content producers.

 

This migration of reducing production-level staff and increasing efficiency gains from added machine emphasis, combined with increased senior (expertise/experience/capability) staff and added specialism areas to the business, is the main trend appearing throughout.

 

Data Scientists.

Building on the data analytics roles that have been growing in SMB and larger companies as required business and marketing roles, a Data Scientist adds to that expertise area with a focus on solving complex problems, identifying the hidden problems that require attention and spotting the trends (untapped threats and opportunities) that business and marketing competitive advantages are created from. Data Scientists come from the same big data backgrounds seen with many Data Analytic/Analyst CVs; however, they often have more traditional data qualifications and experience-based seniority within the field.

 

Integrated services.

The days of isolated experts working on single-channel, medium, or solo part of wider projects are long behind us. We discussed subtopics such as multipliers justifying increased integrated working, as well as the growing volume of user touchpoints and new technologies, reinforcing the functional needs to work integrated also. These increases will see role and responsibility changes that cater for the added importance of effective cross team, department and specialist areas, as well as likely, cross company integration (when factoring in external agencies and potential freelance staff fulfilment) success measurement, refinement and progression.

 

Brand usurpers.

It is not new that some of the most established businesses, industry leaders and brands can change over time, but what machines can bring to the table is speed and impact of SMB uprising. Consider the speed at which Uber took the taxi industry by storm and continues to grow globally. This has been fuelled by AI. Next Uber will become self-driving (driverless cars) and follow the ‘production to senior’ staff employment flow detailed in point (1). Uber is not an isolated case of a business progressing from relative obscurity into industry leader over a handful of years, and the costs of technological investment will only get more accessible as we see increasing advancements.

 

Technology experts.

Image, video, audio, and other types of content and marketing supportive technology (VR, AR, personal assistants, etc.) are becoming increasingly embedded into peoples lives. This provides new expertise areas tied to technology that you will begin to see filtering into the mainstream jobs. Creating VR and AR content is completely different to producing video content. The same can be said for building single page web applications and infographics over content targeting personal assistant inclusion. The mixture of expertise required for such diverse technology type content creation, optimisation and marketing make it a clear choice for collaborative change.

 

Community content and audience building.

Too much of historical business and marketing content has been inwardly focused. With deep data for audience understanding, content interaction and data-led success refinement, there is an increasing bridging between brand and community through the types of content created, plus the audience being an active participant within the content feedback loop. This regularly appears in traditional resource sections of websites but is becoming more engrained into the business and marketing culture as well as the business content mindset now. This is something that will only gain in momentum once increasing volumes of companies begin to identify the gains as with shortening sales cycles, increasing upselling and wider brand reach and engagement metrics. Part of this changing approach includes the tailoring of content and increased niche persona and audience access by genuine, real-world understanding and pain point resolution by the business.

 

Text migration.

There will be added creative expert (content and marketing) roles required to account for the increasing move towards alternative content preferences away from the text. The change in mobile use and smartphone technology, plus the increased integrated SERPs use of image and video content, means that mixed content types may well outgrow traditional text as the preferred digestion approach by consumers.

 

Screenless.

Screenless user search, discovery and content delivery (personal assistants and home speakers a good example of this in action) increase the business case for targeting screenless marketing devices. As you would anticipate, this changes the technical expertise requirements as well as the wider awareness for creating content that is able to deliver results in newer and growing opportunity areas. I would expect the next five years to see screenless search accounting for 40% or more of total search engine marketing.

 

Experiential and interactive.

We are already experiencing the rise of and growth in experiential retail. This is primarily (but not exclusively) millennially driven, reflecting the younger consumers' need to have a more engaging experience. This can include increased offline/online integration, mobile apps usage and Virtual Reality bridging the online/offline buying environment. When building on the results and value elements of marketing content, ensure that expert attention and repurposing opportunity includes dynamic capabilities. The more this dynamism becomes the business content norm, the more increased gains will be delivered through content and marketing differentiation and perceived value.

 

Hyperlocal.

The use of wearable technology (smartwatches, mobile phones, personal trackers, fitness devices and more) empowers companies to target users with increase immediacy and hyper locality. An example of this in action is Google Beacons and the hyperlocal retail experiences. Companies can use hyperlocal audience tracking and engagement to deliver highly personalised and immediate marketing signals to trigger user actions. This can include sending SMS updates to people as they walk within a few metres of your store or providing marketing messaging (smart discounts and product information) as people look at products on shelves within your shop. This type of action-based marketing, product and content positioning could be the game changer that revitalises the decline in physical retail outlets and stores, combining technology with real-world, differentiation and application, to increase the value given to the user.

 

Testing and experimentation.

Fundamental components for any data-driven methodology, hypothesis testing, A/B, multivariant and other forms of testing and experiments will move from optional focus and intermittent application into key audience and result-orientated action plans and performance roadmaps. Repurposing content and refining content for business and marketing gains are paramount expertise items and expect this to substantially increase over the next few years.

 

Data curation.

Human/robot collaboration will facilitate greater content curation and volume-based content provision, at a level never seen before. It is a known fact that companies are creating more content than ever before, and people are respectively consuming more, so the challenge then moves onto the ability to facilitate meaningful content curation and delivery to the increased scale without detriment to quality. The increased advantages of data understanding and efficiency for prescribing content building are second to none when combining the data processing and AI from computers with the emotive and experiential humanistic qualities of people. A marketing channel likely to see large increases in tactical deployment from this include native advertising.

 

Digital story-making and storytelling.

Driven by data and delivered on varying digital marketing platforms, digital story-making and storytelling is growing in traction, and even offline and more traditional marketing mediums strive to include digital and data within their approaches to increase results. Evidence of this in practice can be seen with shorter form content creation and repurposing for digital mediums; increasing use of video, VR, AR and other screenless search and discovery interactions; plus the reduced digital barriers to entry combined with increased big data access.

 

Framework automation.

The first value brought by machines always impacts efficiencies. This can be seen as much in the new technology machine age as it was in the early movements from human labour and power moving to steam power. People understand efficiency and use it to allocate budget as well as to forecast ROI. By automating the data-driven elements of content writing (putting together the bulk of the body content for articles, blog posts, news stories, etc.), the standardised elements of content productions become faster and increasingly scalable. The monotony between ideation, research and article building become automated, so the expertise, creativity, passion, opinion and other human qualities can be applied.

 

Engagement frequency.

Interestingly, while the levels of engagement and interactions between companies and consumers will increase, the amount of time people spend digesting business and marketing content will likely remain consistent (or potentially reduce). The logic supporting this statement is that people are becoming increasingly concise in their new content tolerance, meaning that content is becoming easier to skim read, and in lots of situations shorter form content being published. Added to this is the repurposing of salient content messaging and takeaway opinions on micro blogging platforms and social media sites, enabling most content awareness to be facilitated with minimum content reading. Consumer movement from desktop to mobile and content type migration from text to image, audio and video all help shape the engagement towards shorter and more frequent touchpoints.

 

Value-based clustering.

The grouping of content to provide increased expertise, authority and trust all tied around a persona type and/or topic area, has grown in popularity over the past several years, with the changing technology opportunities, enabling extra interactivity and experiential value. These content hubs/clusters/sections of value will continue to grow in application and results derived over the years to follow, with added emphasis on the community and experience aspect of them.

 

Added collaboration roles.

Above I discussed the topic of increased human needs and how this will lead to new role creation necessary to maximise the outputs from collaborative working between humans/robots. The areas expected to be impacted the most initially would be:

•           Proof-readers and content coordinators

•           Usability and user experience specialists

•           Data Scientists and Analysts

•           Channel writers and content promotion experts

•           Content and marketing strategists

•           Ideation specialists and researchers

•           Technology leads

•           Senior integration account managers/campaign leads