2023, wow, what a year! From Hollywood strikes to a new king of England, 2023 brought a treasure trove of pop culture moments and social movements that captured the world’s attention. But even amidst billion-dollar Taylor Swift tours and the cult of Pedro Pascal, one topic of discussion has dominated nearly every narrative. AI.
Unless you’ve lived under a rock for the past year, you’ve probably used or at least heard of generative AI tools. Actually, even the boulder dwellers among us have probably had ChatGPT write an email reply by now.
AI is everywhere, and that goes doubly so for the marketing world, with digital content marketing being the area with the most pronounced impact. So, get your reply prompts ready as we discuss how AI transformed the content marketing landscape in 2023.
Can AI Tools Keep Pace With the Trade?
2023 saw an explosive expansion of tools for writing blogs, drafting social media posts, designing graphics, and more, all through the power of AI. What usually takes content marketers hours to accomplish can seemingly be condensed into a matter of minutes. But, this raises the question of whether AI-generated content can provide the same value to marketers as work created by human writers and designers. The answer, as it turns out, isn’t so clear.
Finding the Art in Artificial Intelligence
Proponents of marketing AI tools are quick to cite their ability to increase productivity, support more consistent content schedules, and reduce creative resource use. It’s hard to argue that having content ready at the push of a button won’t improve your productivity and bring more potential strategies within reach.
On the other hand, AI skeptics focus heavily on the middling quality of work AI tools can produce. Many writers complain about a lack of creativity and personality in AI writing, which lessens reader engagement and leads to higher bounce rates from blogs and social pages.
Search Algorithms Side with Quality Over Quantity
While it remains to be seen whether AI generators can close the gap between man-made content and their own, it’s important to note that quality is already a major consideration for SEO purposes.
Google and large social media sites like TikTok emphasized their algorithms will prioritize high-quality content, AI-generated or not, over all else. So before you try gaming the system with a flood of keyword-littered AI essays, consider if your best bet actually to be seen is taking time to perfect one post.
Leading Brands Leverage AI Across the Enterprise, Will Yours?
Whether your business works with AI or not, it’s undoubtedly the hot new capability every marketing company wants to tout for themselves. 2023 saw marketing industry behemoths like HubSpot and Salesforce go all in on AI with new features and products featuring the technology added to their user platforms. Even advertising platforms like Meta’s Facebook and Instagram have integrated generative AI tools to assist marketers in leveraging the technology for targeted content creation.
As AI continues to evolve and expand in 2024, so will the possibilities for more curated content creation and deeper customer engagement. Whether its role will be augmenting content marketing or transforming media creation as a whole remains to be seen.
One trend we are confident will remain steady, and even grow in significance, is the focus on content development within B2B marketing roadmaps. Especially in a new era where previous boundaries around writing resources and bandwidth have been leveled by technology, companies are enabled to efficiently produce content at scale. Whether or not that content is right theme or voice for their audience, that’s a different story. That’s where an agency partner can come in handy to ensure any AI tools and new technology are working for you, not against you.
Curious where a stronger content strategy could take your business in the new year? Contact Bluetext to learn more about messaging, positioning, content marketing and more.
Ever wish you had a magic tool to help communicate trends, patterns, and insights based on complex data sets? Luckily, that tool exists, and it’s something you’ve already seen and used in its most simplistic form – data visualization. It’s believed that around 65% of people are visual learners, so it’s not surprising that data visualization tools are so effective and widely used in many industries.
Data visualization can be simple or complex, ranging from simple charts, graphics, and maps, to more complicated visual representations. These tools analyze complex data sets, identify patterns, extract valuable insights, and present it in a visual format that’s easy to digest and make informed decisions from. Take a look at this very simple example from Tableau using a word cloud chart to emphasize the frequency (and thus importance) of a set of words. The more important or frequently used a word is, the larger and brighter it appears.
This data visualization example is rudimentary but effective. Advanced data visualization is more than just converting data into charts and graphical formats. It’s part of a company’s BI (business intelligence) strategy that generates new insights and helps communicate them more effectively, making for easier understanding, collaboration, and decision-making. And with the overconsumption of content in today’s world, who doesn’t want help making well-informed, smart decisions?
The value of data visualization is clear, but how do you know which type of data visualization is right for your need? Especially with AI entering the chat, there are several types of data visualizations to consider. Here are 5 data visualization types that you should know about.
1. Interactive Visualizations
People have been using static data visualizations like charts and maps for centuries, but what makes data visualization more useful is the ability to manipulate it. Interactive data visualization allows users to interact with the data directly within the visualization itself to explore and better understand it. The ability to interact with the data has a number of benefits compared to traditional static data visualizations. It provides a more immersive experience that lets users feel empowered to explore the data in more depth. It also helps uncover insights like patterns and trends that might not have been obvious in a static format. All of this leads to better data-driven decisions.
2. Collaborative Analytics & Visualizations
We can’t talk about collaborative data visualization, sometimes known as social business intelligence, without discussing analytics. Analytics plays a huge role in business operations, but understanding all the different data points can be a complicated and overwhelming venture. Using business intelligence (BI) software, organizations can collaborate on shared goals faster and be better aligned cross-functionally. The key to this is embedded analytics. Traditional BI systems rely on data stored on an internal database, but embedded analytics integrates BI tools and functionality into business applications which gives users access to data and insights directly within your applications (such as websites, apps, CRM, etc.). The convenience and accessibility of these insights allow for even more collaboration and faster decision-making between teams. Some of the most popular BI tools on the market today include Microsoft’s Power BI, Tableau, Qlikview, and Domo.
3. VR and AR Visualizations
You haven’t splurged $16k on family movie night using Apple’s Vision Pro VR/AR headset? Neither have we. But we have learned how AR and VR can create more immersive data visualization experiences by enabling users to engage with data in three-dimensional spaces. Users can see the various layers of datasets with additional context that spreadsheets or traditional visualizations can’t convey. A larger density of data can be shown at once, which allows for much faster cognitive processing compared to 2D visualizations. This new “immersive analytics” field will help data scientists tell better stories by breaking down the complexity of the data, offering more involvement and understanding in data analytics to everyone, not just data professionals.
4. Real-Time Data Visualizations
We’re constantly seeking the most up-to-date information and sources, so it makes sense that the most relevant data visualizations would be in real-time. Real-time data visualization allows you to monitor and analyze data as it’s generated, enabling users to make fast, informed, data-driven decisions. In addition to better, more confident decision-making, another huge benefit is improved accuracy and productivity. Real-time insights can help identify anomalies or errors as they occur, enhancing the reliability of the data. Typically, real-time data may involve working with sensitive or personal information, so it’s important to ensure that data security and privacy are accounted for. As more and more data continues to generate in real-time, the demand for real-time insights will grow.
5. AI-Powered Visualizations
At its core, artificial intelligence is the simulation of human intelligence processes though machines, and it has changed the way we problem solve. We could speak to the various definitions of AI, the different types, the implications, applications, and considerations, the ethical delimas, and more all day, (and probably lose some sleep over-thinking it). But right now we’re focused on AI’s impact on data visualization.
Traditional data visualization uses algorithms to create charts and graphs from data, whereas AI-driven visualization uses algorithms that can learn, understand, and respond to the data, potentially even better than a human can. AI-driven data visualization has several key benefits that the previous types of data visualizations don’t (at least not to the same extent). Automating repetitive tasks producing meaningful information is one of those. AI-powered data analytics can streamline your workflow and automatically generate personalized charts and graphs that easily communicate complicated information and insights. This saves time and resources, and combining the AI insights with human SMEs makes for better, well-informed decisions and smarter AI model builds that continue to improve as it learns more.
All of these data visualization types have the same common goal – to empower users to make faster and more confident data-based decisions. (See Bluetext’s blog on using data to create powerful PR narratives). With the rapid growth in AI, big data, data science, and machine learning, the importance of data and data visualizations for understanding and interpreting complex information will continue to surge.
What’s the latest in AI tools? After months of new software making significant waves in the creative industry, Adobe has finally launched its own AI image generator. While still in the beta stages of development, the debut of Adobe’s Firefly & Generative AI marks a significant enhancement to the creative suite already in use by millions. So rather than paying for and downloading additional products, such as DALL-E or MidJourney, designers now have the tools of AI at their fingertips within Photoshop, Illustrator & Premiere applications.
Much like other AI tools on the market, Adobe’s product allows users to type in a prompt and have an image created in return. But one critical difference is Adobe is one of the few companies willing to discuss what data its models are trained on, and eliminates the controversial copyright concerns. According to Adobe, every asset being fed into its models is either out of copyright, licensed for training, or in the Adobe Stock library, which the company has the right to use. This gives Adobe’s product an additional leg up in the AI race as there is no risk of copyright or trademark infringement which has been creating much controversy amongst the design community. VP of Generative AI & Sensei, Alexandru Costin, claims, “We can generate high-quality content and not random brands’ and others’ IP because our model has never seen that brand content or trademark.”
So is it worth the hype? Bluetext’s designers took a tour of the beta program to test its capabilities and pressure test some potential applications. Our main takeaways? Well, like any AI tool on the market, there are obvious advantages, but still notable weaknesses proving AI technology is indeed a work in progress and never a full replacement for human abilities.
Let’s explore some of Bluetext’s experiments with Generative AI.
One of the most impressive feats of Adobe’s generative fill is the ability to enhance imagery with additional subjects. So what had previously taken creative hours to clone, align, fill, and blend imagery. But now, AI tools can accelerate that process by enabling a designer to select an area, type in a prompt, and receive three results to select from. For example, we took this photo of simple but scenic mountains.
We asked Adobe AI for a series of additions, including more mountains, a cliffside mansion, and even a goat.
Overall we were extremely impressed with the tool’s ability to blend new creative into the previous scene, as the new mountains and mansions were almost a seamless match to the focus, lighting, and textures of the original scene. While not all of the generated options were a great fit for our requested prompt, the majority of outputs fit the requested prompt pretty spot-on.
So with that experiment’s success, we decided to pressure test some more difficult subject matter. One of the core obstacles to AI-generated imagery tools is the inability to produce realistic and believable human subjects. AI tools often have what is called the “uncanny valley” effect. This phenomenon refers to the natural emotional response of eerie or unsettling feelings that people experience in response to not-quite-human. The majority of people have an aversion to the imagery that is meant to appear human but with some caveat of disproportion or unrealism. This phenomenon occurs often with computer-generated imagery that technically appears human, or humanoid, but has a “can’t put my finger on it” inconsistency that appears robotic or unnatural. After the prompt in Adobe AI to generative fill in “a man/family eating ice cream” into the amusement park scene below it confirmed our hesitancies.
The generated responses yielded a mix of graphic styles, resulting in distorted human photography and clip-art-esque illustrations. Facial features and phalanges were expectedly distorted, as these are the features that are most difficult to create hyper-realistic depictions.
While adding people to the scene created challenges, we found removing people was very realistic. The removal of foreground elements is a significant strength in Adobe’s tool, as it cuts out significant time to remove elements from a scene and recreate backgrounds. Our result generated a perfect match to the park’s backgrounds in a matter of seconds, with impressive accuracy and attention to detail that would have taken any designer hours to complete.
Another powerful potential application of generative fill is the resizing of imagery for specific proportions. For example, say you found a great image you want to use as a website hero zone background. The only problem is this selected image is portrait orientation, making it incredibly difficult to adapt to wider landscape or even square formats. Adobe’s generative fill allows the user to select specific areas, and generate that exact texture, background, or graphic elements across a new canvas size. Especially for abstract and texture-based imagery, this seamlessly recreates the design to fill negative space. The previously limited portrait image is now croppable and has more flexibility to be scaled to various formats for websites, display ads, social platforms, and more.
Overall, our stance on AI-generated design tools remains the same. There are undeniable advantages to accelerating tedious tasks and supporting ideation phases, however, still require a significant amount of human attention and editing. AI tools are not, and likely will not, ever be a full replacement for human talent and still face severe limitations in creating certain subjects like human faces or fingers. AI tools are much more adept at scenery, abstract subjects & textures and when used correctly can be a powerful addition to your creative team.
With all the buzz on AI-generated copy and design tools, we’re all wondering the same unspoken question: Can Google detect AI tools? Is this…allowed? Or looked down upon? With more and more companies beginning to leverage AI-powered tools for their marketing needs we are all wondering whether speed and efficiency may come at the cost of SERP rankings.
The answers to these questions are muddled, but here’s what we do know: Google itself relies on advanced algorithms and machine learning to detect and evaluate the quality of website content. The entire purpose of search engines is to provide users with the most relevant and useful content possible, hence our society has become so search engine dependent on everything from research to daily needs. Google algorithms are designed to identify and flag low-quality or spammy content.
Google’s spam policy stance defines “Spammy automatically generated (or “auto-generated”) content as content that’s been generated programmatically without producing anything original or adding sufficient value; instead, it’s been generated for the primary purpose of manipulating search rankings and not helping users.”
Historically, auto-generated content generated by machine learning scrips has had a reputation of being lower quality and overstuffed with keywords aimed at manipulating Google’s search results. This has led Google initiatives to detect this type of content and remove it from the SERPs in an attempt to preserve the integrity of its search results for the end user.
Google Search Central has stated that “scraping content, even with some modification, is against our spam policy.” As well as confirming that Google has put implemented, “…many algorithms to go after such behaviors and demote site scraping content from other sites.”
Prioritizing high-quality, human-generated content on Google results provides a better search experience for users and maintains their credibility. But with the rise of the new AI tools that promise more natural and higher quality outputs, marketers and writers have the opportunity to utilize these tools to generate higher quality, more helpful content for the users rather than an endless amount of spam content. Quality over quantity has become the universal goal for AI generators and users.
Therefore, the content generated by GPT-3 and other AI language models like ChatGPT, is at risk of being detected as machine-generated and flagged by Google’s algorithms. Like recognizes like, so there’s a good chance that machine learning algorithms will recognize similar machine learning. As far as technology has come, it will never be a complete substitute for human intellect. The writing style, grammar, and sentence structure of AI-generated content are often not as natural or accurate as human-generated content.
Whether or not search engine consequences currently exist for websites leveraging AI-generated content has not been confirmed, nor denied by Google. For any company seeking to rank high in search engine results, it’s better to be safe than sorry and maintain a close human eye on your SEO strategy, from content to keyword selection. Contact Bluetext for more information on our expert search engine optimization services.
In a time of economic uncertainty, it’s more important than ever to stay ahead of the curve as well as the competition. Stale digital marketing strategies simply won’t make the cut. Here at Bluetext, we’re committed to providing our clients with the latest and greatest when it comes to up-and-coming marketing strategies and trends. In this blog, we’ll look at five key predictions to bolster your marketing strategy in 2023.
Content Marketing in 2023
Gone are the days of strict, professional content and messaging for companies. In 2023, consumers are looking for you to empathize with them, breaking down the traditional walls that separated corporate from compassion. Lean into emotive content filled with transparency, empathy, and relatability. Your customers want to know they can trust you, especially in times of economic uncertainty when every penny counts. Ditch the sales-based pitch in your content and speak to your customers as if they were your friends.
In today’s culture, TikTok is all the rage. The average user now watches 19 hours of video content every week, and a lot of that is happening on their mobile devices, accounting for 80% of all mobile data traffic. In other words, short-form video is huge and should be taken seriously by companies heading into 2023.
Producing content specifically for TikTok, Instagram Reels, and YouTube Shorts also lends itself well to companies, as shorter content takes less time and effort to produce. Additionally, viewers are more likely to engage with a shorter video that gets straight to the point versus a video they have to sit through for 30 minutes.
Using AR in marketing campaigns was certainly on the rise in 2022 and will continue to grow in both capabilities and use as we get into 2023 and beyond, with the global AR market expected to reach $28 billion by 2028. While AR may seem to be only available to large companies with large marketing budgets like Ikea, there are opportunities for smaller companies to lean into the augmented reality trend. Even something as simple as adding augmented reality functionality to your business card could be a great way to set yourself apart from the competition. You could add buttons to text or call, include a pop-up video showing off your product, and more.
Although the technology behind artificial intelligence is still maturing and a sound business case is still being developed, that doesn’t mean you’re not able to jump ahead of the curve. It is predicted in 2023 that the science behind marketing data analysis will benefit greatly through AI with tools such as TensorFlow and Gretel, allowing your company to glean more information from your data than ever before and drive higher profitability.
The power of conversational AI will also continue to grow (looking at you, Chat GPT) on the back of terabytes of data, enhancing your ability to actively engage with your customers on a personalized level. Tools like Campfire and Kore are making it easier for businesses to take advantage of the power of artificial intelligence with their platform-based solutions.
The metaverse was certainly a trending topic throughout 2022 and will continue to make headlines into 2023 and the future. According to a recent study, 59% of consumers are excited about transitioning everyday activities to the metaverse, with a similar number of metaverse-aware companies (57%) already adopting the concept. In 2022, we saw a variety of events being hosted in the metaverse, a trend that will continue into next year via virtual tradeshows, customer experiences, and facility tours. We’ll also see an increase in metaverse use for internal business processes such as employee onboarding, training, and even company happy hours.
Advertising in the metaverse will also continue to rise in popularity as the metaverse itself continues to grow. In order to align with the metaverse ethos, ads will need to be immersive and complement the user experience, allowing advertisements to become part of the gameplay and establish meaningful engagement with users.
You may already be aware of these upcoming trends and the implications they could have for your business but unsure of how to start addressing them. Bluetext has the expertise and industry experience to help you grow your brand and implement effective changes to your marketing strategy. To learn more about our offerings, contact us today.
No matter what industry your company is in, or who your target market is, the goal of any customer interaction is to foster a relationship that converts to revenue. In today’s digital landscape, customers’ expectations have elevated to instant yet personalized feedback to their questions at the click of a button. While this seems like an impossibly daunting task, it has become an expected digital experience with the help of technology. Artificial intelligence-powered live chat, chatbots, and messaging apps have all helped companies achieve this blend of efficiency and customization. Below, we dive deep into the power of conversational marketing and how to implement the right strategy for your business.
What is Conversational Marketing?
In its essence, conversational marketing is a series of one-to-one interactions in real-time across multiple channels. Conversational marketing enables you and your team to foster relationships with both potential customers and existing customers, improving overall online customer experience and brand perception. A successful conversational marketing strategy ensures your customers feel satisfied and supported in all their questions, and trust your brand throughout every stage of the sales funnel. Additionally, as we know, data is a powerful tool, and utilizing conversational marketing technology can increase that amount of data allowing you to tweak your strategy and increase conversions. Every conversation could be considered a mini focus study and learning experience for how to continually improve your business.
As your business scales up, so will the number of questions from prospective and existing customers. That being said, there will come a time when it is simply not feasible to increase the number of sales representatives you have to answer every question that comes in via your website. That’s where chatbots come in. Chatbots have become the go-to conversational marketing tool for a lot of businesses. Platforms like Drift, which integrate seamlessly with your existing website make chatbots a very easy and effective way to up your conversational marketing efforts. Chatbots are very effective when it comes to easing customer pain points quickly and provides a visual cue of reassurance upon landing on a web page that support resources are readily available. Pre-programmed answers to frequently answered questions allow you to talk to your customers, regardless of the time of day. This is especially beneficial for businesses with an international reach, as customers outside your local time zone will always feel supported. If the query is too unique to respond with a canned response, chatbots can connect the customer with a live representative who can better answer their questions. Plenty of conversational marketing platforms enable businesses to identify which leads are most likely to buy and then move them to the front of the line.
Pulling data from your chosen conversational marketing tool on customer engagement will only get you so far. At the end of the day, you’ll need to gather feedback from your customers, asking them their thoughts on how to improve the customer and prospect experience on your site. This will not just enable the customer to feel that they have a say but also will help in the optimization of the tools after some time. Adding a quick feedback survey to the end of a chatbot or live chat conversation will go a long way in improving customer satisfaction.
How to Get Started
Implementing a successful conversational marketing strategy starts by choosing the web pages where you want your conversational bot to engage with your visitors. Sometimes it makes sense to have a constant chatbot available on every page, at all times. Other times, and especially when utilizing live chat versus a chatbot, it pays off to choose the pages that get the most traffic, have the most conversion opportunities, or have visitors with a high intention of buying. This will help maximize the number of interactions you enter into, and the likelihood of success of those interactions. Now that you’ve decided where you want to speak to your customers on your website, it’s time to define what kind of information customers will ask for, and how in the simplest terms you can provide them with that information. As a general rule of thumb, try to keep the conversations simple. Your customers will expect the interaction with your company to be smooth and want to get answers and guidance quickly.
Regardless of the size of your company, having a conversational marketing strategy is key to increasing customer satisfaction and therefore revenue. Are you looking to begin your conversational marketing strategy but not quite sure where to start? Contact Bluetext and see how we can help.
New year, same buzzwords. We’re all familiar with the phrase “machine learning”, but finding a practical application for it that supports your business model is another story. The key to effective digital marketing campaigns is taking full advantage of emerging technologies, and if you’re looking to increase your marketing team’s productivity and efficacy, look no further than machine learning. From paid media campaigns to search marketing strategies, recent machine learning enhancements have skyrocketed its digital potential. As brand marketing becomes more closely integrated with performance marketing, introducing ML to your digital marketing strategy is an effective way to assist your team on both fronts.
According to Google’s Chief Search Evangelist, “The future of brand marketing is digital, and it’s automated. As a brand marketer, if you can start thinking like performance marketers when it comes to KPIs, measurement, and budgets, you’ll be poised to win.”
Looking for ways to get started with machine learning in your marketing processes? Here are a few ideas:
Introduce personalization at scale.
Personalized advertising is a tried-and-true success tactic, and machine learning makes personalization at scale easier than ever. Whether you’re personalizing for 100 users or 100,000, AI makes the process quick and effective. Better-targeted ads, personalized messaging, and individualized user journeys are just a few ways that ML can boost your brand.
Leave the bidding to the machines.
Free up your team’s time by handing off PPC management to a tool like Google Smart Bidding. With automated bidding, your team can focus more on strategic planning and goal-setting instead of cent-by-cent differences.
Implement a chatbot on your website.
Chatbots are simple integrations that can have a major impact on the conversion rate of your site. The best chatbots use AI to make the customer’s journey as simple as possible, guiding them to the right information or product with minimal back-and-forth. Trusona uses a pre-populated chatbot, so users don’t have to lift a finger to type a response; they can simply choose from the options presented.
Iterate, optimize, and iterate again.
Iteration is one of the greatest strengths of processes that use machine learning; rapid analysis of digital performance means that your team can respond in real-time to shifting trends and interests. Ultimately, the introduction of machine learning to your brand’s marketing tactics will result in better products and better performance.
Implementation of machine learning could be the next major step in your brand’s growth. To learn more and see how Bluetext can partner with you in that growth, contact us.
Have you ever navigated to a new website with a question, and spent too much time hunting for an answer? While companies spend large amounts of time developing and building out an information architecture for their user journeys, they may not always have the use case of each unique user in mind. To be fair, they aren’t mind readers! There are times when consumers may simply need to be guided to exactly what they’re looking for – and there is no better way to ensure that than with a chat experience integrated on your site.
As consumer behavior changes over time, it is important to be able to meet your user and provide a user experience that matches what they have become accustomed to. In the same way that it has become the norm to order a pizza online instead of calling into your neighborhood spot, the prevalence of 24/7 support and availability should be captured in the online experience.
With younger generations, in particular, an instant messaging option is a preferred way to communicate, and if companies can make it easier for their customers to get what they are looking for through a chatbot, this will pay off. A recent study found that up to 68% of respondents indicated that they are more likely to use a business that offers convenient communications if they have the option to choose where to make a purchase.
A seamless integration for a chat experience where a bot or a real person responds in real-time is critical. It can be extremely frustrating when users are waiting around for something that should warrant a quick response. Ever been stuck on the phone waiting for hours to get past automated messaging machines to ask a question? It’s incredibly frustrating and more often than not people get impatient and hang up. Online inquiries are no different, if you leave a user aimlessly browsing on their own and unsuccessful in finding their answer they will get impatient and bounce from your site. Installing an automated chatbot gives users a clear destination for their questions, and avoids the dead-end drop-off. While chatbots may not be real people, it gives users the illusion of a more personal experience and grows brand trust that your company is willing to solve their problems. Convenience is key in today’s society, and online browsing is no exception.
Online chatbots sound great in theory but can seem intimidating to execute. However, with the assistance of a website design and development agency, such as Bluetext, you can integrate a chat service into your current or new website design. The advantage of working with a full-service digital marketing agency is that they can analyze your search traffic patterns, help identify some common user journeys and pain points, but also style and develop a chatbot fit to your brand identity. This creates an even more seamless user experience on your site because the chatbot integrates and matches the current website, almost like a well-dressed store employee ready and able to answer any questions.
Is it time for your website to step up its support game? Consult Bluetext to find out what kind of chatbot or user experience modifications can improve your website.
The creative industry is abuzz with excitement, fears and anticipation of what recent AI developments may bring. Many generative AI tools have emerged in the marketplace, each promising their own unique advantages. As explored in our previous post, generative AI tools can be a powerful aide to the ideation process. So how do you go about using generative AI to enhance the ideation efforts? For a creative, visual output, text-to-image AI tools will utilize an input-output format. Meaning, the generative AI models are trained to follow instructions in a prompt provided and generate an image based on entered keywords, styles, and more. Bluetext recently leveraged Midjourney to explore its capabilities.
Bluetext was sought out by a financial software company looking to create an attention-grabbing go-to-market campaign that would improve overall awareness of the unified brand and increase in qualified leads. The campaign needed to be creative and impactful. Visuals needed to be striking enough to capture the attention of their potential customers and differentiate them from their competitors, and compelling enough to effectively address the pain points of their target audience.
One of the ideas that arose during the campaign conception process was to show a hyperbolic demonstration of one of the target audience’s biggest challenges – that dated technology can hold them back, literally. To help with the ideation process and find inspiration for the campaign visuals, Bluetext turned to MidJourney.
The process involved a delicate game of trial and error — entering prompts and making tweaks to the keywords, information and instructions we provided in order to try and generate a range of visuals that may fit with the campaign strategy and vision. Here’s a sample of what we tried:
Base Prompt: “Business man, technology holding back”
Refined Prompt: “Realistic, sideview of a businessman sitting in a chair in the office, shirt is connected to printer cables behind him, he is being pulled back from his desk by cables, 8k”
Refined Prompt: “Ultra realistic photo, side view of business man sitting at desk working on a computer, behind him are more computers, wires from the computers behind him are attached to his shirt pulling him away from his desk”
Variations on Selected Image: “Ultra realistic photo, side view of business man sitting at desk working on a computer, behind him are more computers, wires from the computers behind him are attached to his shirt pulling him away from his desk”
Prompt:”Side view photo, young business man looking at computer, wires from other computers behind him are wrapped around his torso, tied to chair, hands on desk, wires tight and look like they are pulling guy away from desk”
Prompt: “Ultra photoreal, ultra-detailed, side view, businessman sitting at desk working on computer, computers behind man have wires reaching out and wrapping around the man, tangling and tying him to chair”
Prompt: “Photorealistic, ultra detailed, side view, young businessman sitting at desk looking at computer, more computers are behind man and have wires reaching out and wrapping around the man, man is tied to chair with the wires, man looks frustrated”
Outcomes & lessons learned:
As you can see from the examples above, this technology is by no means perfect. After hours of iterating, we struggled to get the visual output to match exactly what we were trying to convey.
This brings us to a few key takeaways. Generative AI tools have very real limitations, like in the realism of art (see the human appendages below) and in output control. Also, while generative AI is a great starting place for brainstorming, it will likely not produce your final product. It is best used as an ideation-stage tool to help get your creative juices flowing.
As demonstrated above, generative AI tools will produce results, but they may not always be exactly what you are looking for. That is why it is important to set realistic expectations for the AI model’s capabilities and refine your prompt writing to produce successful outcomes. The best prompt writing process to follow depends on the specific generative AI tool being used and the desired outcome, but general tips can help improve the quality of the output generated by the AI model:
- Be clear and specific about the desired outcome or task. This helps ensure that the AI model understands what it is being asked to do and produces relevant output. For example, if you are using an AI model to generate a creative writing piece, clearly specify the genre, tone, and other relevant details.
- Provide the AI model with as much, high-quality input data as possible. The quality of the input data can significantly affect the output generated by the AI model, so it is essential to provide diverse and representative input information that aligns with the desired outcome.
- Experiment with different prompts and input data to identify which ones produce the best results. The quality of the output generated by the model can vary depending on the information and instructions provided, so testing out a variety of inputs can help increase your chances of receiving a relevant and accurate response.
- Review the output carefully. While AI models can generate impressive output, they are not perfect, and may require some editing to meet the desired standards.
Interested in head-turning campaign creative for your business? Get in touch with Bluetext to learn how technology-powered creatives can bring your vision to life.
It’s no secret that Conversational AI has become a familiar part of our everyday lives. With the rise of virtual assistants like Siri, Alexa, and Google Assistant, the way that we interact with technology has become more personalized than ever before. But the benefits of AI go far beyond simple voice commands and smart speakers; Conversational AI is a tool that can optimize efficiency in a wide variety of industries and contexts, from customer service to healthcare to education.
Outcomes & Benefits From Business Process Perspective
Conversational AI systems, also known as chatbots or virtual assistants, are designed to provide personalized communication with users. For some, their first thought of AI might include Siri announcing the weather, or Alexa updating their shopping list. However, what many people don’t realize is that the capabilities of Conversation AI go much deeper and can be the key to optimizing business operations. AI can improve the efficiency, effectiveness, and personalization of communication with customers, employees, and stakeholders.
As AI technology continues to advance, businesses across a broad range of industries are discovering innovative ways to integrate it into their operations to enhance processes and productivity. As market offerings of AI continue to expand, almost every industry is finding new and unexpected ways to leverage new technologies. The capabilities of AI are limitless; here are just a few of the most unique and surprising real-world use cases of AI.
- Real Estate: Online real estate platform Compass is using AI to create custom listing videos for clients in just a few clicks. Their AI-powered phrase recognition technology is able to pull out key listing attributes and pair them with the best suited images, generating a professional and personalized video for potential buyers.
- Construction: AI produces a multitude of benefits for construction and manufacturing companies. From increasing safety to optimizing work schedules, AI in the construction industry has proven its value. Buildots, a construction tech company, has created a wearable 360-degree camera that uses AI to monitor construction sites by detecting schedule deviations, incorrect installations, and unsafe conditions.
- Financial: According to Insider Intelligence’s AI in Banking report, 80% of banks are aware of the benefits of Conversational AI in their industry. It enables frictionless, 24/7 customer interactions, lowers the possibility of human error, and increases customer satisfaction for a multitude of use cases, including but not limited to bank transfers, closing and opening accounts, card replacements, and password resets. Aside from these advantages, AI in financial settings can also identify variations in transaction patterns and other warning signs that could indicate fraud.
- Media & Telecommunications: Businesses can leverage AI to monitor and analyze audio and video data to report findings in real time. Call centers, for example, can utilize AI-enabled solutions to transcribe and document phone conversations, which can then be analyzed to detect customer sentiment, identify key topics and issues, and mine discrepancies. Additionally, AI in customer care centers can help bolster real human interaction by managing mundane tasks and helping find a solution in a fraction of the time that it would take a real person.
- Healthcare: AI-powered chatbots can help patients schedule appointments, send reminders, and provide information about appointment logistics. Conversational AI tech can also provide patients with information on health conditions, treatment options, and self-care instructions.
- Higher Education: By leveraging conversational AI, educational institutions can provide more personalized and efficient learning experiences, improve student outcomes, and reduce the workload on teachers and administrative staff. One way that AI can help to automate tasks for educators is by providing automated assessment and feedback on student assignments, while also identifying areas for improvement and recommending learning resources.
Power of Amelia AI
Amelia AI, Bluetext’s partner, and client of brand services, has established itself as an enterprise leader in Trusted AI by consistently providing reliable and secure AI solutions. Amelia uses a combination of natural language processing (NLP), machine learning, and cognitive reasoning to understand the intent of user requests and provide relevant responses. Unlike traditional chatbots, Amelia learns from every interaction, evolving and improving its understanding and responses over time in order to better all future interactions.
One of the key advantages of Amelia is its ability to integrate with existing enterprise systems, enabling seamless communication across departments and workflows. Amelia can also be deployed across multiple channels, such as web, mobile, and voice, providing a consistent and personalized experience to end users. Amelia is able to optimize business efficiency across all types of industries by streamlining processes and elevating customer service and experience. For example, Amelia AI was hired to fill the role of Virtual Engineer for CGI clients, specifically handling incident resolution and ticket management. Through the engagement, Amelia helped CGI reduce client outages by 30 percent.
Amelia also paired up with Visionworks to transform their customer experience operations by operationalizing the process to schedule eye exam appointments, provide order status updates, answer store-related questions, and more. Amelia represents a significant step forward in the development of conversational AI, providing organizations with a powerful tool to improve customer engagement, reduce costs, and drive innovation.
The Future of AI Optimization
As natural language processing and machine learning algorithms improve, AI technology will become increasingly adept at understanding and responding to human speech in more complex and nuanced ways. Companies that have successfully incorporated AI into their business operations have proven that they can automate routine tasks, reduce operational costs, and enhance customer satisfaction and retention. Beyond improving processes, AI technology can lend valuable insights into customer behavior and preferences, ultimately improving and personalizing their experience. With the potential to transform nearly every aspect of business, it’s no wonder that AI is becoming an increasingly popular technology for companies to adopt.