by Ebani Advertising | Sep 5, 2023 | Blog
Introduction
In the digital age, understanding user behavior on your website is crucial for effective online presence management. Google Analytics, a powerful web analytics tool, provides invaluable insights into your website’s performance, user engagement, and much more. To make the most of this tool, you need to stay up-to-date with its latest features and best practices. In this blog, we’ll explore tips on how to use Google Analytics to monitor your online presence effectively and highlight five recent updates that have enhanced its capabilities for understanding user behavior.
Tips for Using Google Analytics Effectively
- Set Clear Goals and Objectives: Before diving into Google Analytics, define your goals and objectives. What do you want to achieve with your website? Whether it’s increasing sales, improving user engagement, or boosting newsletter sign-ups, having clear goals will help you track the right metrics.
- Utilize Custom Dashboards: Google Analytics allows you to create custom dashboards tailored to your specific needs. Take advantage of this feature to display the metrics that matter most to you in one convenient view.
- Segment Your Audience: Segmenting your audience based on various criteria such as demographics, behavior, or traffic source can provide deeper insights. It allows you to understand different user groups and tailor your marketing strategies accordingly.
- Track Conversions: Tracking conversions is essential for measuring the success of your online presence. Whether it’s tracking e-commerce transactions, form submissions, or specific user actions, set up conversion tracking to monitor the outcomes you care about most.
- Monitor Bounce Rate: A high bounce rate can indicate that users are leaving your site quickly without engaging with your content. Investigate which pages have high bounce rates and work on improving their quality and relevance.
- Stay Informed with Real-Time Analytics: Google Analytics offers real-time data, allowing you to see what’s happening on your site at any given moment. Use this feature to monitor the immediate impact of marketing campaigns or track events in real-time.
- Regularly Review Reports: Make it a habit to review Google Analytics reports regularly. Analyze the data to identify trends, spot opportunities for improvement, and make data-driven decisions to enhance your online presence.
Five Recent Google Analytics Updates for Understanding User Behavior
- Enhanced E-commerce Tracking: Google Analytics has improved its e-commerce tracking capabilities. You can now gain deeper insights into online shopping behavior, including product impressions, clicks, and refunds. This data helps e-commerce businesses optimize their product offerings and user experience.
- Google Signals: Google Analytics now offers Google Signals, which provides enhanced cross-device tracking and reporting. This feature helps you understand user behavior as they move across different devices, offering a more comprehensive view of the customer journey.
- Event Tracking Enhancements: Event tracking has become more powerful and user-friendly. With updated event tracking in Google Analytics, you can easily track user interactions, such as video views, downloads, and button clicks, to gain insights into how users engage with your content.
- Advanced Analysis: Google Analytics now offers Advanced Analysis, a feature that uses machine learning to automatically uncover valuable insights from your data. It can help you identify trends, anomalies, and opportunities for optimization more efficiently.
- Google Analytics 4 (GA4): While not an update to the previous version but a significant evolution, GA4 is the future of Google Analytics. It provides a more comprehensive understanding of user behavior across platforms and devices. GA4 tracks events by default and offers a more flexible and event-driven approach to tracking, making it easier to gather insights on user interactions.
Conclusion
Google Analytics is an indispensable tool for monitoring and improving your online presence. By following best practices and staying informed about the latest updates, you can gain valuable insights into user behavior, track your website’s performance, and make data-driven decisions to enhance your online presence. Incorporate these tips and leverage recent updates like enhanced e-commerce tracking, Google Signals, improved event tracking, Advanced Analysis, and the transition to GA4 to ensure that you’re making the most of this powerful analytics platform. With a thorough understanding of your audience and their behavior, you can continually refine your online strategies and stay ahead in the digital landscape.
by Ebani Advertising | Aug 21, 2023 | Blog
In a world where technology is constantly evolving, voice-activated devices have emerged as a transformative force, altering the way we interact with the digital realm. The rise of voice search, driven by the increasing popularity of smart speakers and virtual assistants, has profound implications for content creators and marketers. In this article, we delve into the phenomenon of voice search, its impact on user behavior, and provide actionable strategies to optimize your content for this emerging trend.
The Growing Influence of Voice Search
The convenience and speed of voice search have propelled it into the mainstream. With devices like Amazon Echo, Google Home, and Apple’s Siri becoming ubiquitous in households, voice search is no longer a novelty but a part of daily life. Users can now simply speak their queries, and the device responds with relevant information.
Changing Search Patterns
Voice search has given rise to a significant shift in search patterns. While traditional text-based searches often consist of succinct keywords, voice queries tend to be more conversational and natural. Users ask complete questions and expect direct answers. For instance, a text search for “best Italian restaurants” may become a voice query like “What are the top Italian restaurants near me?”
The Implications for Content Creators and Marketers
The shift towards voice search has implications that extend to the realm of content creation and marketing strategies. Understanding these implications is crucial for staying relevant in this evolving landscape.
User Intent and Context
Voice search is inherently intent-driven. Users are looking for quick and concise answers to their queries. Therefore, content must be tailored to address specific questions directly. Marketers should focus on creating content that aligns with users’ needs, providing clear and relevant information.
Natural Language and Featured Snippets
To optimize content for voice search, it’s imperative to use natural language. Voice queries mirror human conversation, so content should read conversationally. Additionally, targeting featured snippets is advantageous, as voice assistants often source their answers from these concise summaries.
Local Search Optimization
A significant portion of voice searches is location-based. Users frequently inquire about local businesses, services, and directions. Implementing local SEO strategies, such as claiming your Google My Business listing and ensuring consistent business information across directories, enhances your chances of being featured in voice search results.
Strategies for Voice Search Optimization
Now that we’ve explored the impact of voice search, let’s delve into practical strategies to optimize your content for this evolving trend:
1. Long-Tail Keywords: Incorporate long-tail keywords that reflect natural language queries. Anticipate the questions users might ask and weave those phrases into your content.
2. Question-Based Content: Create content that directly answers common user questions related to your industry. Use headings that match the questions users might ask.
3. Conversational Tone: Write in a conversational and approachable tone. Imagine you’re addressing a friend’s inquiry.
4. Structured Data Markup: Implement structured data markup to help search engines understand the context of your content and potentially feature it as a rich result.
5. Mobile Optimization: Voice search is often conducted on mobile devices. Ensure your website is mobile-friendly for a seamless user experience.
Embracing the Voice-First Future
The rise of voice search is indicative of a broader shift towards a voice-first digital landscape. Content creators and marketers who adapt to this trend are poised to connect with their audiences more effectively. By crafting content that caters to conversational queries and user intent, businesses can position themselves for success in this evolving era of search.
FAQs About Voice Search Optimization
Q1: Is voice search only relevant for local businesses?
No, while local businesses can benefit significantly, voice search is becoming relevant across various industries and sectors.
Q2: How does voice search impact traditional SEO?
Voice search emphasizes natural language and user intent, which means that traditional keyword-centric SEO is evolving towards a more contextual approach.
Q3: Are there any tools to help with voice search optimization?
Yes, tools like SEMrush and Moz offer features to analyse and optimize for voice search.
Q4: Will voice search replace text-based search entirely?
It’s unlikely. While voice search is growing, there will likely always be situations where text-based searches are more convenient or appropriate.
Q5: How do I track the impact of voice search on my website’s traffic?
Utilize tools like Google Analytics to track traffic sources and identify trends in voice search-related traffic.
In conclusion, the rise of voice search signifies a fundamental change in how users interact with digital content. By embracing the nuances of voice-driven queries and adapting content creation strategies, businesses can position themselves to thrive in this dynamic landscape. As technology continues to evolve, optimizing for voice-activated devices is not just a strategy – it’s a necessity for staying relevant and engaging with modern audiences.
by Ebani Advertising | Aug 2, 2023 | Blog
Imagine a world where every advertisement you come across feels tailor-made just for you, resonating with your preferences, needs, and desires. This is the reality that AI-powered personalization is creating in the realm of advertising. In this blog post, we delve into the transformative impact of artificial intelligence on advertising campaigns and how it is reshaping the landscape through advanced personalization techniques.
Understanding the Power of AI-Powered Personalization
In the age of data, information is abundant. However, sifting through this vast sea of data to extract meaningful insights can be a daunting task. This is where AI steps in, with its unparalleled ability to analyse massive amounts of data swiftly and effectively. AI algorithms scrutinize consumer behaviour, preferences, and intent by examining various touchpoints – from browsing history and social media activity to purchase patterns and demographic information.
Unveiling Consumer Insights
The key to successful advertising lies in understanding your audience. AI empowers marketers with invaluable insights into consumer behaviours and trends. By recognizing patterns and correlations within data, AI can predict what products or services a consumer might be interested in. This knowledge is the foundation of creating highly targeted campaigns that resonate with individual needs.
Case Studies: AI in Action
Let’s explore a couple of case studies that highlight the game-changing potential of AI-driven insights in advertising:
1. Dynamic Content Generation
Incorporating AI-powered personalization into dynamic content generation allows advertisers to create multiple versions of an ad, each catering to a specific segment of their audience. For instance, a fashion retailer can showcase different clothing styles based on a user’s previous purchases or browsing history. This level of personalization significantly enhances the user experience, leading to higher engagement rates.
2. Recommendation Engines
Online platforms like Netflix and Amazon have mastered the art of recommendation engines. By analysing user behaviour, AI algorithms suggest content or products that align with the user’s preferences. This approach not only keeps users engaged but also drives sales by presenting them with options they are more likely to explore.
3. Predictive Analytics
Predictive analytics, fuelled by AI, enables advertisers to anticipate future consumer behaviours. By considering historical data and ongoing trends, advertisers can fine-tune their campaigns to align with what consumers are likely to desire next. This proactive approach ensures that ads remain relevant and compelling.
Integrating AI-Powered Personalization into Advertising Strategies
The seamless integration of AI-powered personalization into advertising strategies can yield remarkable results. Here are some tips for leveraging this technology effectively:
1. Crafting Compelling Ad Copy
AI can analyse user data to understand linguistic nuances that resonate with different segments of the audience. This insight helps in tailoring ad copy that speaks directly to users, capturing their attention and driving engagement.
2. Optimizing Ad Placements
AI can determine the most effective placement for an ad based on a user’s browsing habits. This ensures that ads appear where they are most likely to be noticed, increasing the chances of interaction.
3. A/B Testing with AI
A/B testing becomes even more potent when coupled with AI. Machine learning algorithms can quickly analyse test results and recommend adjustments to optimize campaign performance.
The Future of Advertising: Where AI Leads the Way
As we navigate the age of data, AI-powered personalization is undeniably a game-changer for the advertising industry. By delivering relevant and compelling content to consumers, AI enhances the user experience and boosts conversion rates. From understanding consumer behavior to predicting future trends, AI holds the key to unlocking new dimensions of advertising success.
FAQs About AI-Powered Advertising
Q1: Is AI-powered personalization suitable for all types of businesses?
Absolutely. Whether you’re a small e-commerce start-up or a multinational corporation, AI-powered personalization can be tailored to suit your business needs.
Q2: Does AI eliminate the need for human creativity in advertising?
Not at all. While AI assists in data analysis and insights, human creativity remains pivotal in designing engaging ad content.
Q3: How can I start implementing AI-powered personalization in my campaigns?
Begin by assessing your available data and exploring AI solutions that align with your goals. Collaborate with experts to ensure a seamless integration process.
Q4: Are there any ethical concerns regarding AI in advertising?
Ethical considerations, such as data privacy and algorithm transparency, are important. Striking a balance between personalization and privacy is crucial.
Q5: What skills do marketers need to leverage AI effectively?
Marketers need to understand the basics of AI and data analysis. Collaborating with data scientists and AI experts can further enhance AI utilization.
In conclusion, AI-powered personalization is ushering in a new era of advertising, where campaigns are no longer generic messages but personalized experiences. With the ability to dissect data and predict consumer behaviours, AI is at the forefront of revolutionizing advertising strategies. By integrating AI-driven insights into various aspects of marketing, businesses can create more meaningful connections with their audiences, ultimately driving engagement, conversions, and success.
by Ebani Advertising | Jul 15, 2023 | Blog
The Past
Traditionally, advertising agencies concentrated on crafting compelling advertisements, negotiating media contracts, and prioritizing client service. However, the advent of digital transformation disrupted this pattern, forcing agencies to rapidly adapt. In the wake of the digital era, businesses demanded more integrated and interactive strategies that transcended the one-way communication offered by traditional media. Ad agencies were compelled to transition into communication technology companies to stay relevant in this fast-paced digital evolution.
The Transformation
A communication technology company represents a natural evolution from a traditional advertising agency. The need for agencies to solely provide services in traditional advertising has dissipated with the surge in online platforms. The incorporation of technology and communication has become a necessity. Agencies now are expected to offer a full suite of digital services, such as website development, online advertising, social media management, and SEO.
Case Study: Real World Examples
R/GA
R/GA, based in New York, originated as a film production company in 1977. Recognizing the rising significance of technology in marketing, R/GA evolved into a prominent digital advertising agency known for its technology-driven marketing solutions. They offered services like interactive online ads, website development, and mobile apps.
One outstanding campaign by R/GA was with Nike for the creation of ‘Nike+ FuelBand,’ a wearable technology that allowed users to track their fitness activity. This innovative approach transformed the FuelBand into a medium for continuous consumer-brand interaction, significantly enhancing Nike’s brand visibility and engagement.
TBWA\Media Arts Lab
TBWA\Media Arts Lab, closely associated with Apple, is another agency that transitioned into a communication technology company. They expanded their offerings to include services like digital advertising, content marketing, social media strategy, and data analytics. Their ‘Shot on iPhone’ series, showcasing high-quality photos and videos taken by iPhone users worldwide, is a testament to their effective blend of technology and communication.
Wieden+Kennedy
Wieden+Kennedy, a traditional agency, adapted to the shifting media landscape by integrating technology into their campaigns. Their ‘Old Spice Man’ campaign started as a television commercial and later expanded to digital platforms, including YouTube and social media. This online campaign allowed the ‘Old Spice Man’ to interact with fans in real-time, attracting millions of views and boosting Old Spice’s brand image.
The Road Ahead: Challenges and Opportunities
The evolution from traditional advertising agencies to communication technology companies presents immense opportunities despite the challenges. The increasing demand for integrated, data-driven, and interactive communication strategies offers agencies the chance to deliver more effective, personalized, and holistic advertising solutions.
However, this transformation involves significant challenges such as constant upskilling, rapidly changing technologies, and managing data security and privacy issues.
Conclusion
In conclusion, the digital revolution has triggered a significant shift in the operations of advertising agencies. As they transition into communication technology companies, they leverage technology and data to create more meaningful, engaging, and personalized ad campaigns. The transformation has not only enabled them to stay competitive but has also positioned them as leaders in the rapidly evolving digital advertising landscape.
The transition requires more than just integrating technology; it also requires fostering a culture of learning, innovation, and agility. With the power of data and technology comes the responsibility of ethical considerations, including data handling, privacy, and security.
The future looks promising as advertising agencies continue to evolve, harnessing technology to deliver more impactful and personalized communication strategies, driving meaningful conversations and building stronger relationships between brands and their audiences in the digital era.
Part II: Transitioning From Traditional Media Practices to the Evolution of AI and the Way Forward
Transition from Traditional Media Practices
Traditional media practices had their core focus on television, radio, and print media – these were the primary mediums for advertising agencies to reach audiences. The advertising industry, during this era, was characterized by linear, one-way communication. Advertisers broadcasted their messages to consumers with little to no opportunity for engagement or interaction. However, the onset of the digital age and the proliferation of the internet and social media began to significantly alter the advertising landscape.
The Digital Transformation
The rise of digital platforms catalyzed a shift away from traditional media practices. Consumers began spending more time online, and advertisers saw an opportunity to reach these audiences through more targeted, personalized campaigns. Advertising agencies had to re-evaluate their strategies and business models to adapt to these changes.
Digital transformation pushed advertising agencies towards multichannel marketing, where they began creating advertisements for various platforms including websites, social media, and mobile apps. The transition wasn’t just about switching from one platform to another; it fundamentally altered how agencies approached advertising. Advertisers started focusing on interactive communication, enabling customers to participate and engage with the brands.
This period marked the beginning of agencies morphing into communication technology companies. Their roles were no longer limited to just creating ads, but also involved technology deployment, data analytics, and customer relationship management.
The Advent of AI
The emergence of Artificial Intelligence (AI) was another turning point in the evolution of advertising agencies. AI has revolutionized the advertising industry, providing tools for automation, personalization, and predictive analysis. It has enabled advertisers to gain insights into customer behavior, preferences, and purchasing habits like never before.
Agencies started using AI algorithms to predict future consumer behavior based on historical data. They could anticipate consumer responses to different marketing strategies and tailor their campaigns accordingly. AI also automated repetitive tasks such as ad buying and placement, saving agencies time and resources.
The integration of AI within their operations marked another milestone in the transition of advertising agencies into communication technology companies. Now, they could not only create and distribute ads across multiple platforms but also use AI to optimize their campaigns and achieve better results.
The Way Forward: Embracing AI and Future Technologies
Looking ahead, the future of advertising agencies as communication technology companies seems to be intertwined with the future of AI and emerging technologies. With advancements in AI capabilities, agencies are expected to take personalization to a whole new level. For instance, using AI algorithms, they can create personalized ads tailored to each individual based on their preferences, online behavior, and purchasing history.
Furthermore, technologies like Augmented Reality (AR) and Virtual Reality (VR) are opening new avenues for interactive advertising. Agencies can leverage these technologies to create immersive ad experiences, bringing products to life and allowing consumers to interact with them virtually.
Another significant development is the growing importance of data privacy and ethics. As agencies collect and process large amounts of personal data, they must ensure they are respecting users’ privacy and adhering to data protection regulations. This will be a crucial aspect of their operations in the future.
Conclusion
In conclusion, the journey of advertising agencies from traditional media practices to communication technology companies is a story of continuous adaptation and evolution. It’s a tale of embracing new technologies and trends while maintaining a steadfast commitment to delivering value to clients. As agencies look forward to a future powered by AI and emerging technologies, they need to stay agile and innovative, continuously learning and adapting to stay ahead in this fast-paced industry.
The evolution of advertising agencies into communication technology companies is not just about integrating technology into their operations. It’s about fostering a culture that embraces change, values learning, and prioritizes innovation. As they continue this journey, they have the opportunity.
by Ebani Advertising | Jul 1, 2023 | Blog
All images in this article were created using generative AI. These images were created using the prompts light bulb, flower, pastel, geometric shapes, simplicity, clean lines, and minimal still life. Midjourney
Summary: There is tremendous apprehension about the potential of generative AI—technologies that can create new content such as text, images, and video—to replace people in many jobs. But one of the biggest opportunities generative AI offers is to augment human creativity and overcome the challenges of democratizing innovation.
In the past two decades, companies have used crowdsourcing and idea competitions to involve outsiders in the innovation process. But many businesses have struggled to capitalize on these contributions. They’ve lacked an efficient way to evaluate the ideas, for instance, or to synthesize different ideas.
Generative AI can help overcome those challenges, the authors say. It can supplement the creativity of employees and customers and help them produce and identify novel ideas—and improve the quality of raw ideas. Specifically, companies can use generative AI to promote divergent thinking, challenge expertise bias, assist in idea evaluation, support idea refinement, and facilitate collaboration among users.
The term “democratizing innovation” was coined by MIT’s Eric von Hippel, who, since the mid-1970s, has been researching and writing about the potential for users of products and services to develop what they need themselves rather than simply relying on companies to do so. In the past two decades or so, the notion of deeply involving users in the innovation process has taken off, and today companies use crowdsourcing and innovation contests to generate a multitude of new ideas. However, many enterprises struggle to capitalize on these contributions because of four challenges.
First, efforts to democratize innovation may result in evaluation overload. Crowdsourcing, for instance, may produce a flood of ideas, many of which end up being dumped or disregarded because companies have no efficient way to evaluate them or merge incomplete or minor ideas that could prove potent in combination.
Second, companies may fall prey to the curse of expertise. Domain experts who are best at generating and identifying feasible ideas often struggle with generating or even accepting novel ideas.
Third, people who lack domain expertise may identify novel ideas but may be unable to provide the details that would make the ideas feasible. They can’t translate messy ideas into coherent designs.
And finally, companies have trouble seeing the forest for the trees. Organizations focus on synthesizing a host of customer requirements but struggle to produce a comprehensive solution that will appeal to the community at large.
Generative AI tools can solve an important challenge faced in idea contests: combining or merging a large number of ideas to produce much stronger ones.
Our research and our experience working with companies, academic institutions, governments, and militaries on hundreds of innovation efforts—some with and some without the use of generative AI—have demonstrated that this technology can help organizations overcome these challenges. It can augment the creativity of employees and customers and help them generate and identify novel ideas—and improve the quality of raw ideas. We have observed the following five ways.
1. Promote Divergent Thinking
Generative AI can support divergent thinking by making associations among remote concepts and producing ideas drawn from them. Here’s an example of how we used Midjourney, a text-to-image algorithm that can detect analogical resemblances between images, to generate novel product designs based on textual prompts from a human. (We utilized Midjourney, ChatGPT, and Stable Diffusion for the examples in this article, but they are just a few of a host of generative AI tools that are now available.) We asked Midjourney to create an image that combined an elephant and a butterfly, and it produced the chimera we dubbed “phantafly.”
We then used the detailed rendering from Midjourney to inspire prompts in Stable Diffusion, another popular text-to-image model. Stable Diffusion generated a range of ideas for different product categories, including chairs and artisanal chocolate candies (see images below).
The authors prompted Midjourney to produce an image combining an elephant and a butterfly; they dubbed this creation “phantafly” (left). Then the authors prompted Stable Diffusion to generate designs for chairs and for artisanal chocolates inspired by “phantafly” (right). Midjourney; Stable Diffusion
Rapidly and inexpensively producing a plethora of designs in this way allows a company to evaluate a wide range of product concepts quickly. For example, a clothing company that uses generative AI to create new designs for T-shirts could stay on top of trends and offer a constantly changing selection of products to customers.
Consider another example of how this technology can connect ideas to create concepts that an individual or a team might never have come up with themselves. We used ChatGPT, a type of generative AI known as a large language model, to guide the production of ideas. We asked it to generate ideas through a process of trisociation by connecting three distinct entities (an extension of the bisociation creativity technique). Our team gave ChatGPT the following prompt: “You will play the role of an ideator. You will randomly generate 10 common nouns. You will then randomly select any two of the 10 nouns. You will then ask me for a third noun. You will generate a business idea by combining or associating the two nouns you identified and the noun I identified.”
ChatGPT generated the nouns “food” and “technology.” When prompted, we provided the additional noun “car.” ChatGPT produced the following business idea in short order: “A smart food-delivery service that uses self-driving cars to transport meals to customers. The technology aspect could involve using AI to optimize delivery routes, track food temperature in real time, and provide customers with real-time updates on the status of their orders. The service could target busy professionals and families who want convenient and healthy meal options without sacrificing taste and quality.”
In a separate round, ChatGPT produced the nouns “airline” and “chair.” When prompted, we provided “university,” and ChatGPT came up with a business concept that provides a convenient, cost-effective way for students and academics to travel to conferences and workshops around the world along with access to a library of educational books during the flight. It proposed that the company be called Fly and Study or Edu-Fly.
2. Challenge Expertise Bias
During the early stages of new-product development, atypical designs created by generative AI can inspire designers to think beyond their preconceptions of what is possible or desirable in a product in terms of both form and function. This approach can lead to solutions that humans might never have imagined using a traditional approach, where the functions are determined first and the form is then designed to accommodate them. These inputs can help overcome biases such as design fixation (an overreliance on standard design forms), functional fixedness (a lack of ability to imagine a use beyond the traditional one), and the Einstellung effect, where individuals’ previous experiences impede them from considering new ways to solve problems.
Here’s an example of this process. We asked Stable Diffusion to generate generic designs of crab-inspired toys but provided it with no functional specifications. Then we imagined functional capabilities after seeing the designs. For instance, in the collection of crab-inspired toys shown below, the image in the top left could be developed into a wall-climbing toy; the image next to it could be a toy that launches a small ball across a room. The crab on a plate near the center could become a slow-feeder dish for pets.
The authors asked Stable Diffusion to come up with crab-inspired toy concepts. Stable Diffusion
This is not a completely novel way to come up with unusual products: Much of the architecture and ride functionality in theme parks such as Disney World has been driven by a desire to re-create scenes and characters from a story. But generative AI tools can help jump-start a company’s imaginative designs.
3. Assist in Idea Evaluation
Generative AI tools can assist in other aspects of the front end of innovation, including by increasing the specificity of ideas and by evaluating ideas and sometimes combining them. Consider an innovation challenge where the goal is to identify ways to minimize food waste. ChatGPT assessed the pros and cons of three raw ideas: (1) packaging with dynamic expiration dates (labels that automatically change either the dates or colors based on the environmental conditions in the places where they are stored); (2) an app to help users donate food; and (3) a campaign to educate people on types of expiration dates and what they represent in terms of freshness and fitness for use. ChatGPT produced a balanced analysis of the pros and cons that mirrored what we might expect from an exchange between two interested persons discussing the merits of such ideas.
When ChatGPT evaluated the concept of dynamic expiration-date packaging, for instance, it determined that it would help consumers better understand the shelf life of products and encourage food manufacturers to produce smaller batches that would be replenished more frequently on grocery shelves. In addition, ChatGPT pointed out that dynamic expiration dates may require significant changes to the manufacturing and packaging process and as a result, could increase the costs to both manufacturers and consumers.
ChatGPT determined that the food-donation app could encourage people to use up their food before it goes bad and reduce food waste by giving unopened, edible food to those in need. It cautioned that the app may require a large user base to be effective and that the transportation and distribution of food from a wide variety of unregulated sources could pose safety concerns.
Generative AI’s greatest potential is not replacing humans; it is to assist humans in their efforts to create hitherto unimaginable solutions.
It stated that the pros of an education program for consumers were increasing consumer awareness of the meaning of different expiration labels and helping them make more-informed decisions about food purchases and waste. But ChatGPT warned that this education program could be overly complex because expiration dates are not standardized across all food products. And it cautioned that educating users on different types of expiration dates can be costly if the program is broad in scope, particularly if it involves widespread campaigns or educational materials.
Generative AI can go beyond simple pros and cons and help humans evaluate dimensions of creativity such as novelty, feasibility, specificity, impact, and workability. We asked ChatGPT to assess the same examples using these criteria.
Here is its assessment of the dynamic expiration-date packaging concept:
Novelty: Somewhat novel. There have been efforts to develop smart packaging that can extend the shelf life of food products, but the idea of dynamic expiration dates is an emerging concept.
Feasibility: May be challenging to implement as it requires the development of new packaging materials and technologies. It would also require collaboration with food manufacturers, regulators, and distributors.
Specificity: It’s specific in that it addresses the problem of food waste by providing consumers with more-accurate expiration dates for their food.
Impact: Could have a significant impact on reducing food waste and improving food safety. When provided with more-accurate expiration dates, consumers would be more likely to use their food before it goes bad.
Workability: It would most likely require significant resources and expertise to develop and implement and may take several years to fully realize its potential.
Here is ChatGPT’s assessment of the app for donating food close to expiration:
Novelty: Not particularly novel. There are already many programs and organizations dedicated to reducing food waste and donating surplus food to those in need.
Feasibility: Highly feasible. There are many established models and an infrastructure in place to support food donation efforts.
Specificity: Specific in its aim to reduce food waste and address issues of food insecurity.
Impact: Has the potential to make a significant impact as it addresses both food waste and hunger. By redirecting surplus food to those in need, it can help reduce food waste while also improving food security for vulnerable populations.
Workability: Highly workable in that it can be implemented quickly and at a relatively low cost. It would require partnerships with food manufacturers, distributors, and food banks, as well as volunteers to collect and distribute the donated food.
Finally, here is how ChatGPT evaluated the idea to educate users on different types of expiration dates:
Novelty: Not particularly novel. There have been efforts to educate consumers on the meaning of expiration dates and how to properly store food to extend its shelf life.
Feasibility: Highly feasible. It can be implemented through various means, such as public awareness campaigns, educational materials, and media outreach.
Specificity: Specific in its aim to educate consumers on the different expiration dates and how to properly store food to reduce food waste.
Impact: Potentially significant. Educating consumers on the different expiration dates and how to properly store food will make them more mindful of food waste and take steps to reduce it.
Workability: Highly workable and can be implemented at a relatively low cost. It would require collaboration with food industry groups, government agencies, and other organizations to develop and distribute educational materials.
Using ChatGPT’s assessments, it would be relatively easy to evaluate these three concepts, or quickly score or organize them based on the criteria that matter most.
4. Support Idea Refinement
Generative AI tools can solve an important challenge faced in idea contests: combining or merging a large number of ideas to produce much stronger ones. For example, an organization that is trying to win a contract or a grant to develop a food-waste-reduction program can use the tools to combine the three concepts discussed earlier. We did this in two steps. First, we asked ChatGPT to flesh out each of the concepts:
- “Dynamic expiration dates are a solution aimed at reducing food waste. This involves incorporating technology into packaging that can track and adjust the shelf life of products in real time. By using sensors, the expiration date can be updated based on changes in environmental factors, providing consumers with a more accurate estimate of when a product will go bad.”
- “An app that enables consumers to donate food close to its expiration date aims to reduce food waste by giving unopened, edible food to those in need. The app connects individuals who have surplus food to local organizations that can use it. By using technology to facilitate food donations, the app can help reduce food waste and provide for those in need.”
- “Educating users on the different types of expiration dates can help users make informed decisions about purchasing and consuming food, reducing waste, and saving money. By clarifying the meaning of ‘best before,’ ‘use by,’ and other expiration labels, an education campaign can help users better understand how to determine if food is safe to eat and when it is time to dispose of it.”
Next we asked ChatGPT to merge all three ideas into one food-waste program. In short order it produced the following description: “The comprehensive food-waste-reduction solution involves creating smart packaging with dynamic expiration dates, establishing a program for donating surplus food, and educating the public on the importance of understanding food expiration dates. The smart packaging helps consumers make informed decisions about food freshness, the donation program ensures surplus food is put to good use, and education raises awareness about the impact of food waste. This solution has the potential to significantly reduce food waste and create a more sustainable future by empowering consumers, working with industry and government, and making better use of surplus food.”
5. Facilitate Collaboration with and Among Users
When developing new product ideas or designs, generative AI can facilitate collaborations between a company’s designers and users of a prospective product and among users themselves. In other words, the technology makes co-creation of new offerings much easier and less expensive. For example, a business can give users access to tools to generate designs and then create a personalized version of the product based on the customer’s preferences. Alternatively, users’ designs could be posted on a crowdsourcing platform where they are evaluated by the community. The top designs could then be further developed by additional collaborators.
To illustrate the potential, we show how a flying car—something people have been trying to develop for more than 100 years without much success—might be designed. We gave Stable Diffusion this prompt: “Design a product that can fly but also drive on the road, a flying automobile.” Stable Diffusion generated several designs, and we selected what we considered to be the most promising one: the vehicle in the lower right corner of the image below.
The authors asked Stable Diffusion to design a flying automobile. Stable Diffusion
Then we asked Stable Diffusion to take that design and reimagine the concept so that the car “resembles a robot eagle.” The image below shows the variations that the generative AI program quickly produced—from the top left design that looks most like a robot eagle to the more feasible concept of a flying automobile in the lower right corner.
The authors chose one of the flying-automobile designs and asked Stable Diffusion to reimagine it to resemble a robot eagle. Stable Diffusion
A second example illustrates how designers can use such tools to collaborate on thematic variations of a structural design. They began with a flying-automobile design generated by AI and asked the tool to produce versions that resembled a dragonfly, a tiger, a tortoise, and an eagle (see image below).
This image is another AI-generated concept of a flying car (left) with versions that resemble a dragonfly, a tiger, a tortoise, and an eagle (right). Stable Diffusion
An alternate approach is for human collaborators to use a tool like ChatGPT to develop details of the product and then use one like Stable Diffusion to obtain visual designs based on a series of prompts that build upon one another. We gave ChatGPT a similar prompt to what we had given to Stable Diffusion: “Describe a product that can fly but also drive on the road, a flying automobile.”
ChatGPT provided this description: “The flying automobile is a sleek and futuristic vehicle that is built for the ultimate adventure. It has the appearance of a stylish sports car with smooth curves and polished exterior but with hidden rotors that allow it to take flight.”
When we gave that description to Stable Diffusion, it provided the image below on the left. Next we asked ChatGPT to reimagine the description to include the information that the product must resemble a dragonfly and have illumination markers for flying at night. It came back with the following: “With its slender body, extended wings, and hidden rotors, the vehicle is reminiscent of a dragonfly come to life. The illuminated markers located along the wings and body create a stunning visual effect, helping to make the vehicle visible in the darkness.”
Stable Diffusion translated that description into various versions that maintained the feasible design and added elements of illumination based on the pattern of a dragonfly’s wings. The images below on the right are examples.
The authors used ChatGPT to describe a flying automobile and asked Stable Diffusion to generate a design from that description (left) and then variations on the design that incorporate dragonfly details and illumination (right). Stable Diffusion
Humans have boundless creativity. However, the challenge of communicating their concepts in written or visual form restricts vast numbers of people from contributing new ideas. Generative AI can remove this obstacle. As with any truly innovative capability, there will undoubtedly be resistance to it. Long-standing innovation processes will have to change. People with vested interests in the old way of doing things—especially those worried about being rendered obsolete—will resist. But the advantages—the opportunities to dramatically increase the number and novelty of ideas from both inside and outside the organization—will make the journey worthwhile. Generative AI’s greatest potential is not replacing humans; it is to assist humans in their individual and collective efforts to create hitherto unimaginable solutions. It can truly democratize innovation.
Use it to promote divergent thinking. by Tojin T. Eapen, Daniel J. Finkenstadt, Josh Folk, and Lokesh Venkataswamy
