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SmartData Collective > Business Intelligence > Artificial Intelligence > AI Can’t Replace Creativity When Crafting Digital Content
Artificial IntelligenceExclusive

AI Can’t Replace Creativity When Crafting Digital Content

AI technology can be very valuable for marketing, but it cannot replace human creativity.

Ryan Ayers
Ryan Ayers
6 Min Read
AI in marketing
Shutterstock Licensed Photo - 2263440441 Poca Wander Stock
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Big data and AI technology have created a number of major changes in recent years. The proliferation of tools like MidJourney and ChatGPT have has disrupted the marketing profession in ways that were unimaginable just a year ago. In January, Reuters reported that ChatGPT had 100 million users, but that figure rose to 185 million by this month.

Contents
Marketers Must Still Rely on Creativity to Generate Great ContentWhat is Design Thinking?Design Thinking ToolsMind MappingConcept DevelopmentValue Chain Analysis

However, as beneficial as AI has been for the marketing profession, it has not been without its limitations. The biggest problem is that AI cannot replicate human creativity. This has led to some major challenges for marketers that have leaned too heavily on it to create content.

As sophisticated as AI has become, it is clearly no replacement for human creativity. Nevertheless, there are other ways AI can improve marketing strategies.

Marketers Must Still Rely on Creativity to Generate Great Content

The job of marketing professionals, however consistent in goal, allows for a nearly infinite amount of variety. With that comes freedom to be creative, inventive, and forward thinking. While such systems as AI and big data analysis have enabled impressive and effective ways to measure effective marketing strategies, there are still other ways to go about enhancing marketing campaigns for successful returns.

With the number of analytical tools, proven marketing strategies, predictive consumer behavioral patterns, and design techniques, there are still a number of other ways to engage consumers.

Here are some design thinking tools and techniques which can help to create compelling digital marketing content. However, let’s begin by unpacking what is meant by design thinking.

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What is Design Thinking?

Design thinking may be defined as a consistently applied approach that reaches to understand user and customer bases, their behaviors and wants in order to redefine business problems by challenging assumptive reasoning and past performance biases in business.

By taking the time to reconsider how and why business is operating effectively or ineffectively teams take time to explore alternative solutions. This is done by focusing on the development interest and patterns of the customer and demographic which are trying to be reached and served.

Brainstorming sessions allow for space and time to reconsider the eccentricities of human behavior and to then adopt and apply new approaches to business and marketing. This process can roughly be seen in actions like prototyping, testing, implementing, and measuring new concepts and ideas.

There is a well-known, five-stage model by which design thinking can be applied:

  1. Empathizing with users/ customers
  2. Defining those user needs
  3. Ideation: Challenging presumptive ideas
  4. Prototyping: creating those solutions
  5. Testing

These five phases do not necessarily need to be done in that order, and in fact may more often double back on themselves throughout the testing processes before a final, effective solution is found and established. A great example of this is how documentary filmmakers identify stories to tell from empathizing with human needs to then develop a product of interest.

Design Thinking Tools

Mind Mapping

Mind mapping has become a very effective tool for designers over the years, and for good reason: It helps to create space and time wherein people are given the opportunity to let their minds wonder and wander into new ways of thinking. The additional ability to visually manifest and track the connections between what may have once seemed like disparate ideas demonstrates how interconnected life and human behaviors are.

This can be done solo or with teams or people, and typically, the more diverse a group is, the more original and creative new ideas may be. This attempt to identify patterns and connections eventually leads to new understanding about what and why certain behaviors exist, why some strategies are more effective than others, and which are most suitable to the demographic trying to be reached.

Concept Development

This technique assists in the generation of new and different questions that enables a greater likelihood of original hypotheses. Those hypotheses become jumping points by which teams can ask further refining questions about how the product or technique identifies with user needs.

By imagining and attempting to predict customer needs new insights can be developed that guide research and refinement of prototyping. This assembly of ideas into actionable creates new products that can then be tested and measured for feedback as to effectiveness.

By generating ideas as quickly as possible and then giving customers the opportunity to engage creates more chances for data collection and learning to better predict and implement effective products and services.

Value Chain Analysis

The value chain is representative of all the partnerships and processes which are involved in the creation and presentation of a product or service. Value chain analysis seeks to examine the nuances of how an organization interacts with its production partners.

By spending time considering how business partners affect product value and customer interaction determines the effectiveness and thus profitability generated or slowed by the current partnerships. This technique focuses more on the business side, analyzing production methods and infrastructure weighing business models against the serviceability of those products and their assembly, deliverability, or production costs.

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ByRyan Ayers
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Ryan Ayers has consulted a number of Fortune 500 companies within multiple industries including information technology and big data. After earning his MBA in 2010, Ayers also began working with start-up companies and aspiring entrepreneurs, with a keen focus on data collection and analysis.

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