Introduction

In my previous article, I shared how I developed a Chrome extension using ChatGPT within 15 minutes, despite having no prior knowledge of frontend development. Recently, I completed another Chrome extension project with the help of ChatGPT. In this article, I want to summarize and share the entire development process and insights, hoping to provide some inspiration and assistance to you.

In this article, I will walk you through the process of developing the TABSNAPSHOT extension using ChatGPT. We will start from the basic requirements and move on to some key points to consider when developing with ChatGPT.

Requirements

The idea for this extension came from a real-life scenario. I spend most of my time browsing web pages and PDFs. Chrome provides an excellent reading experience, but I often find myself opening specific pages related to a particular topic. For example, during my midterm exam preparation, I needed to open three pages (a lecture PDF and two article links) every time I opened Chrome. Using Chrome’s built-in features, I had two options:

• Create a folder and save these three pages as bookmarks inside the folder. I could open all the pages at once using the “Open all bookmarks” option in the folder.
• Add these three pages to Chrome’s “Reading List” and open them one by one from the Reading List.

However, I rejected both of these methods because:

• The process of creating a folder and adding pages to it is too tedious: creating the folder, adding a page to the folder, and saving it require too many steps. Besides, I usually use Chrome folders to collect web pages rather than storing these temporary pages I need to read.
• The Reading List doesn’t support adding PDFs, and dealing with PDF pages separately would be a very cumbersome process.

So, I clearly identified the need for a tool that could temporarily save one or multiple tab pages and open these pages with minimal actions, similar to the Open All Bookmarks option.

Development Approach

Unlike my previous GitHub Searcher project, I had no specific idea of how to implement this extension. I wasn’t even sure if Chrome provided APIs to achieve these functionalities. After giving it some thought, I came up with a rough plan:

• Implement a button in the extension popup to save all currently open tabs as a “snapshot.”
• Use the extension’s popup window as the main control panel for the extension.
• Display all saved snapshots in the popup window. Clicking on a snapshot should open all the tabs saved in that snapshot.

With this plan in mind, I named the extension TABSNAPSHOT and proceeded to write the code with ChatGPT.

Development Process

Basic Functionality

Since I relied entirely on GPT to write the code, I communicated my requirements and approach clearly to GPT. However, due to GPT’s nature, there were some challenges and issues that arose.

My initial prompt was as follows:

I want to develop a Chrome extension called tabsnapshot. This extension should:

1. Save the URLs of all open tabs in the browser when the user clicks the “Create Snapshot” button in the extension’s popup window (i.e., create a snapshot).
2. Display the saved snapshots as items in the popup window, with the snapshot’s creation time as the item’s name.
3. When the user clicks on a saved snapshot in the popup window, open the URLs saved when the snapshot was created.

Please develop this extension and provide all necessary files.

However, the code generated based on this prompt had several issues:

• The manifest_version was set to 2.
• Only the URL of the first open tab was saved in each snapshot, not all open tabs.
• Saved snapshots were not persisted. When I closed and reopened Chrome, the saved snapshots disappeared.

To address these issues, I provided additional instructions to GPT:

I want to develop a Chrome extension called tabsnapshot. This extension should:

1. Save the URLs of all open tabs in the browser when the user clicks the “Create Snapshot” button in the extension’s popup window (i.e., create a snapshot).
2. Display the saved snapshots as items in the popup window, with the snapshot’s creation time as the item’s name.
3. When the user clicks on a saved snapshot in the popup window, open the URLs saved when the snapshot was created.

Please develop this extension and provide all necessary files.

Additional instructions:

1. The manifest_version value should be set to 3.
2. Each snapshot item should save all open URLs, not just one URL. You can consider using an array or map for storage.
3. All snapshot items must be persisted. When I close and reopen the browser, I should see all previously saved snapshot items.

With these additional instructions, GPT generated code that met my requirements. I had the basic functionality of TABSNAPSHOT, allowing me to create snapshots, save them, and open them with a single click.

The initial UI for this basic version was quite simple:

Once the basic version was implemented, I had a foundation to build upon. I continued to enrich and optimize the features of TABSNAPSHOT.

Delete Functionality and UI Enhancement

In the initial version, I only had the functionality to create snapshots but lacked the ability to delete them. I asked GPT to add the delete functionality:

I need you to add snapshot deletion functionality to this extension. Without changing the existing functionality, add an “x” button next to each snapshot item in the popup window. Users can click this button to delete the corresponding saved snapshot. Please provide the updated code after adding the delete functionality.

With the code provided by GPT, the UI was updated as follows:

Although the “x” buttons were functional, the UI was not aesthetically pleasing. I asked GPT to improve the style while keeping the delete functionality intact:

Great, but the style of the delete button is not appealing. Can you make it similar to the “Create Snapshot” button and maintain the delete functionality?

The improved style of the delete button, along with other UI enhancements, looked like this:

We can see that the optimized delete button looks much better, even richer in style than the Create Snapshot button mentioned in the prompt, so we continue to let GPT optimize the UI, and the final UI looks like this:

At this point, TABSNAPSHOT is fully operational, and all the current features are sufficient to address the pain points I mentioned in the requirements scenario.

But because of my OCD, we continue to add features and optimizations to TABSNAPSHOT.

Rename and Open Snapshot

From the above UI, it can be seen that each snapshot entry is named after the time it was created. When there are many entries, it becomes difficult to distinguish which content each snapshot contains. Therefore, here we added the renaming functionality to TABSNAPSHOT:

The first feature we are going to add is the renaming functionality. Please add a rename button to the left of the delete button with a style consistent with the delete button. When the user clicks the rename button, the original text of the snapshot entry will become editable. Users can rename the snapshot by modifying the text and confirming with the Enter key.

However, GPT did not provide a perfect solution in this case. When clicking the Rename button and modifying the text, the Enter key did not save the changes. Users had to click somewhere else in the popup window to save the changes. We had to use a few more prompts to guide GPT and make the necessary modifications to finally complete the development of the renaming functionality:

Here, we also changed the way snapshots are opened to a specific button:

Great! Now I would like you to modify the logic for opening saved snapshots. Currently, the logic is to click on the snapshot entry to open it. I want you to change the way snapshots are opened to clicking an open button. This open button should be located to the right of each snapshot entry. The style of a snapshot entry should be: Snapshot Name, Open button, Rename button, Delete button.

The final result looks like this:

Open All and Delete All

To further enhance the functionality of TABSNAPSHOT, I asked GPT to add “Open All” and “Delete All” buttons:

Excellent. Now I want you to add two buttons to the right of the “Create Snapshot” button:

• “Open All”: Opens all saved snapshots.
• “Delete All”: Deletes all saved snapshots.

The updated UI with these features was as follows:

Now that we have completed all the major feature points, we will fine-tune some of the details of TABSNAPSHOT.

Detail Optimizations

Optimizable details are as follows:

• If the tab contains a local PDF for browsing, it should automatically refresh after opening; otherwise, manual refresh might be necessary.
• Add a tab count for each snapshot entry.
• Simplify the default snapshot naming format (retain only month, day, hour, and minute).
• If multiple snapshots are created within the same minute, automatically add numbering to avoid duplicates.
• Snapshot preview.

When communicating with GPT through prompts, it’s essential to describe your requirements clearly. You can make your prompts more vivid by providing examples:

Next, we are going to add a tab count feature to the snapshots. When creating a snapshot entry, the number of tabs included in that snapshot will be displayed after the snapshot name. For example, a name for a snapshot containing three tabs would be sample [3]. Please note that this [3] should not be editable by the user through the rename button. You can place the snapshot entry name and tab count in separate elements but display them on the same line.

Please add a logic check for snapshot creation. If multiple snapshots are created within the same minute, start numbering from the second snapshot created within that minute, following the order of creation. For example, the name of the first snapshot created at 15:53 on 11/1 would be 11/1 15:53, the second snapshot created at 15:53 on 11/1 would be 11/1 15:53 (2), and the third one would be 11/1 15:53 (3).

One thing worth mentioning is the snapshot preview feature. I have found it challenging to convey the exact effect I want to GPT, which might be why the implemented feature did not meet my expectations. Perhaps I haven’t clearly defined what the preview feature should look like.

From a hover-based implementation to a click-based popup window:

Now I want to add a preview feature to this plugin. Leave a space at the bottom of the popup window as the preview area. When the user hovers over a snapshot entry, the preview window will list all the links from the tabs included in that snapshot in the form of a list. Please implement this feature based on the above code.

Now I want to add a preview feature to this plugin. When the user clicks on a snapshot entry, the browser will pop up a preview window (please note that this preview window is not the plugin’s popup window). The preview window will list all the links from the tabs included in that snapshot in the form of a list. Please implement this feature based on the above code.

The final version, with all optimizations completed, is as follows. This is the v0.1.0 version released after open-sourcing:

• Plugin UI

• Preview window UI

Key Takeaways from Developing with ChatGPT

Here are some key points and lessons I learned during the development process with ChatGPT:

• Clearly define your development goals and expectations. Ensure you can articulate your requirements logically; otherwise, the responses from ChatGPT might not meet your needs.
• Break down your project into small functional points. Develop one feature at a time, starting with the basic functionality and then refining and optimizing it.
• Long prompts might cause ChatGPT to lose context. Consider using previous prompts to edit and submit or start a new chat to maintain context.
• Use consistent terminology and agreements with ChatGPT during the development process.

Logo

You can also design an attractive logo for TABSNAPSHOT:

Conclusion

This article has covered my entire journey of developing the TABSNAPSHOT extension with the help of ChatGPT. It includes the iterative thought process and the key points summarized at the end. I hope this experience can assist you in your projects.

As you can see, TABSNAPSHOT is still a very basic and simple extension with plenty of room for improvement. However, if you have a similar use case to mine, feel free to use TABSNAPSHOT to simplify your browsing experience.

If you find TABSNAPSHOT helpful or if you have suggestions for improvements, please feel free to Star, Fork, and submit Pull Requests !!!

References

• https://github.com/B1NARY-GR0UP/tabsnapshot
• https://chat.openai.com/

The post How to Build Your Own Chrome Extension Using ChatGPT appeared first on ProdSens.live.

Example 1: Triangle Pattern – I

1
1 2
1 2 3
1 2 3 4
1 2 3 4 5

let rows = 5;
// pattern variable carries the final pattern in string format
let pattern = "";
// outer loop runs for `rows` no. of times
for (let n = 1; n <= rows; n++) {
   // inner loop runs for n
   for (let num = 1; num <= n; num++) {
      pattern += num;
   }
   // Add a new line character after contents of each line
   pattern += "n";
}
console.log(pattern);

Example 2: Triangle Pattern – II

1
2 2
3 3 3
4 4 4 4
5 5 5 5 5



let rows = 5;
// pattern variable carries the final pattern in string format
let pattern = "";
// outer loop runs for `rows` no. of times
for (let n = 1; n <= rows; n++) {
   // inner loop runs for n
   for (let num = 1; num <= n; num++) {
      pattern = pattern+n;
   }
   // Add a new line character after contents of each line
   pattern += "n";
}
console.log(pattern);

Example 3 : Triangle Pattern – III

1
2 3
4 5 6
7 8 9 10


let rows = 4;
// variable contains the next element of the pattern
let variable = 1;
// pattern variable carries the final pattern in string format
let pattern = "";
// outer loop runs for `rows` no. of times
for (let n = 1; n <= rows; n++) {
   for (let num = 1; num <= n; num++) {
      pattern += variable+" ";
      variable++;
   }
   pattern += "n";
}
console.log(pattern);

Example 4: Number Pyramid Pattern – I

    1
   123
  12345
 1234567
123456789



let rows = 5;

// pattern variable carries the final pattern in string format
let pattern = "";

// outer loop runs for `rows` no. of times
for (let n = 1; n <= rows; n++) {
   // Inner Loop - I -> for the spaces
   for (let space = 1; space <= rows - n; space++) {
      pattern += " ";
   }

   // Inner Loop - II -> for the numbers
   for (let num = 1; num <= 2 * n - 1; num++) {
      pattern += num;
   }

   pattern += "n";
}
console.log(pattern);

Example 5: Square Star Pattern – I

*****
*****
*****
*****
*****


let rows = 5;

// pattern variable carries the final pattern in string format
let pattern = "";

// outer loop runs for `rows` no. of times
for (let n = 1; n <= rows; n++) {
   // Inner loop for printing stars
   for (let num = 1; num <= 5; num++) {
      pattern += "*";
   }
   pattern += "n";
}
console.log(pattern);

Example 6: Square Star Pattern – II

*****
*   *
*   *
*   *
*****


let rows = 5;

// pattern variable carries the final pattern in string format
let pattern = "";

// outer loop runs for `rows` no. of times
for (let n = 1; n <= rows; n++) {
   for (let num = 1; num <= 5; num++) {
      // print star only if it is the boundary location
      if (n == 1 || n == rows) pattern += "*";
      else {
         if (num == 1 || num == 5) {
            pattern += "*";
         } else {
            pattern += " ";
         }
      }
   }
   pattern += "n";
}
console.log(pattern);

Example 7 : Right Triangle Pattern

    *
   **
  ***
 ****
*****



let rows = 5;

// pattern variable carries the final pattern in string format
let pattern = "";

// outer loop runs for `rows` no. of times
for (let n = 1; n <= rows; n++) {
   // Inner loop - I -> prints spaces
   for (let space = 1; space <= rows - n; space++) {
      pattern += " ";
   }

   // Inner Loop - II -> prints stars
   for (let num = 1; num <= n; num++) {
      pattern += "*";
   }
   pattern += "n";
}
console.log(pattern);

Example 8 : Pyramid Triangle Pattern

    *
   ***
  *****
 *******
*********



let rows = 5;

// pattern variable carries the final pattern in string format
let pattern = "";

// outer loop runs for `rows` no. of times
for (let n = 1; n <= rows; n++) {
   // Inner Loop - I -> prints spaces
   for (let space = 1; space <= rows - n; space++) {
      pattern += " ";
   }

   // Inner Loop - II -> prints stars
   for (let num = 1; num <= 2 * n - 1; num++) {
      pattern += "*";
   }
   pattern += "n";
}
console.log(pattern);

The post Basic Pattern – Javascript Interview appeared first on ProdSens.live.

Brand equity — that intangible asset that sets your brand apart and directly impacts its success, can either flourish or wither at the hands of artificial intelligence (AI).

Using artificial intelligence in your external communications can be a threat to any brand equity you’ve built up, but does this mean you shouldn’t use it at all?

In this article, we’ll explore the delicate dance between technology and human connection, exploring the AI risks when it comes to your brand equity.

What is brand equity?

Brand equity is the value gained from a consumer’s perception of a company, service, or product — beyond its functional attributes. It is the cumulative effect of various factors that contribute to how a brand is perceived, recognized, and differentiated from others within its industry.

There are four main elements of brand equity:

• Brand awareness: The recognition and familiarity consumers have with a brand. If a customer has strong brand awareness, they are more likely to think of it when making purchase decisions — this is the first step to building brand equity.

• Brand associations: The characteristics, qualities, and attributes that consumers associate with a brand. This can be through previous experiences, recommendations, or even online perceptions.

• Perceived quality: The consumer’s perception of the overall quality of the brand. This will differ from person to person and does not always reflect the actual quality, instead being based on parameters that are important to the individual.

• Brand loyalty: When a consumer chooses to buy from a particular brand over others. This could be related to repeat purchases or recommendations for higher ticket items, such as mortgages.

Brand equity will have a significant impact on the company’s success. Stronger brand equity often means brands can justify higher prices, enjoy customer loyalty, and be protected against competitors.

How does brand equity relate to AI usage?

Like everything else in marketing, AI can affect brand equity. With AI tools widely available, the two elements of brand equity that could be impacted are brand awareness and brand associations, i.e. what they see of your brand before having their own experiences.

When AI is harnessed effectively, it can either boost or erode brand equity depending on whether it enhances authentic customer interactions or turns them into robotic, disconnected experiences. In essence, the smart use of AI can either reinforce your brand’s value or, if mishandled, risk damaging the trust and emotional connections you’ve worked so hard to build.

How the overuse of AI can affect your brand equity

Brand equity is the culmination of years of trust-building, consistent messaging, and positive customer interactions. It’s the intangible asset that sets your brand apart in the hearts and minds of your audience.

The right AI-driven experiences can drive awareness and solidify positive brand associations in the minds of your customers. But while the temptation is there to utilize AI-generated content to speed up output, it’s important to know when to use it and when to stop.

Dangers of overusing AI for your customer communications

AI can be a valuable asset, but it can also be a potential liability in your marketing toolkit. It’s crucial to tread carefully and be mindful of the potential dangers lurking when AI-generated content is used within your communications.

Losing that personal touch

Your brand was made by humans, for humans. If your customers start to feel as if their interactions with your brand are too automated and lacking that vital human empathy, the emotional connection you’ve spent so much time building will begin to weaken. For example, you ask an AI tool to produce an article around a specific topic, and you upload that content straight to your site without fact-checking or personalizing it. That piece will stand out from the articles already on your website, either because of the change in tone of voice or mistakes and inaccuracies within it, leading the reader to question your branding, authority, and trustworthiness.

That loss of personal touch to content can not only affect what your customers feel about your brand but can also impact your site’s ability to rank. A recent AI vs. humans experiment carried out by Reboot found that pages created by copywriters outperformed AI-generated content in search engine result pages (SERPs).

Privacy concerns

Using AI tools to collect and analyze personal data can raise privacy concerns within your customer base. Because artificial intelligence is about always learning and improving, AI tools will store any information put into them, which includes any data. Allowing another party to store customer data opens up more opportunities for it to be viewed, copied, and even stolen by outside sources.

If your consumers believe their personal information is being misused by AI tools or their privacy is compromised, you can erode the trust in your brand and damage your overall brand equity.

To negate these privacy risks, some AI tools give you the option to opt out of this data storage. On ChatGPT, for example, there is a setting you can use to prevent it from saving your chat history.

Not understanding intent

Understanding and fulfilling intent is what helps your content to rank, and keeps your customers happy. AI content tools and recommendation systems might be unable to pinpoint customer intent or preferences. Continually missing the mark of what your customers want could negatively impact their perception of your brand’s competence.

If you’re looking to combat this pitfall, you can try asking the AI tool to create a piece of content with a particular search intent in mind. As with all content produced by artificial intelligence, though, this will need to be thoroughly fact-checked and edited by a skilled copywriter.

Loss of brand identity

Your communications could lack consistency with your brand’s image if they are solely produced by AI tools or even a mix of AI and human-generated content. Recognizable features of your brand are watered down, which could lead to confusion among your customers and a dilution of the all-important brand image.

Not only this but how can you be sure your tone of voice stands out when your competitors have access to the same AI tools? You know your brand best, and it is in your best interest to ensure any information you put out there is accurate, relevant, and on-brand.

Lack of human interaction

For complex or emotionally sensitive issues, customers might prefer human interaction rather than AI. If you don’t offer this option or rely too much on AI for customer service by only offering chatbots or email assistance run by artificial intelligence tools, you may start to notice increased dissatisfaction and reduced loyalty.

Can AI tools recreate recognizable brand communications?

As mentioned before, AI will affect your customers’ awareness and perception of your brand, primarily if you use it in your communications. Can you trust AI-generated content to adopt your tone of voice accurately?

Brand tone of voice is a direct manifestation of its personality and values. It’s what drives brand perception and feeds into equity if you take away all of the visuals, logos, and videos.

Let’s see how a popular AI tool, ChatGPT, deals with mimicking the tone of voice of a famous and instantly recognizable brand.

AI tackles Cards Against Humanity

Cards Against Humanity has one of the most identifiable brand voices out there, which feeds into customer perception. There are specific qualities and characteristics that those familiar with the brand would expect from its communications.

To test out the AI tool, we input the prompt:

Please write a 120-word ‘About Us’ section to be used on the Cards Against Humanity website. Make sure this copy is instantly recognizable to customers by matching the brand’s tone of voice and style of writing.

The word limit was to make sure the copy fits in line with the existing page the brand already has. For reference, this is the brand’s current About Us page on the site:

It’s short, to the point, and has brand-specific humor; it doesn’t take itself too seriously. It’s a tone that anyone familiar with the brand would associate with their messaging. But how will an artificial intelligence tool compare?

Going off the prompt, this is what ChatGPT produced:

While the finished products are dissimilar, you can pick out inspiration from the brand’s existing content. With phrases such as ‘renegades of irreverence’ and ‘inner misfit’, Cards Against Humanity’s somewhat overtly offensive branding comes through.

However, Cards Against Humanity thrives within the sarcasm, self-deprecating space, which is where the ChatGPT content misses out. It doesn’t quite have that tongue-in-cheek humor that is apparent from its existing About Us page.

How this could affect brand equity

Consistent branding is pivotal in constructing and upholding a positive brand perception. If you’ve built up a consumer base familiar with a particular tone of voice and personality but then start to move away from this, you’ll go against their perceptions and chip away at their brand awareness.

Even though Cards Against Humanity has already formed relatively strong brand equity through years of consistent messaging and good-quality products, that doesn’t mean it’s invincible. If the brand decides to go ahead with AI-generated content for its future communications, it risks going against its consumer perceptions and damaging its brand equity in the long run.

Striking the balance between automation and the human touch

AI isn’t the enemy of brand equity. But you do need to be careful when using it. Balancing creativity caution with AI is like finding the perfect blend in your morning coffee — too much AI can leave a bitter taste.

You should aim to avoid your AI-generated content coming across as robotic or inconsistent with your brand identity. By selecting the appropriate AI tool and always referring back to your brand’s unique voice, you still have the ability to craft captivating content that truly connects with your audience. Here’s how you do it:

1. Have a solid TOV guide

Why is having a tone of voice (TOV) guide a big deal?

It’s a roadmap for your messaging, ensuring your brand always sounds like, well, your brand!

This consistency is crucial for brand recognition and recall. When your audience can easily identify your style and personality across different channels, it’s like having a familiar face in a crowd — feeding into brand awareness and perception.

A well-crafted TOV guide can even set you apart from competitors in a sea of voices, helping you stand tall in your niche.

How to create a TOV guide:

• Start by digging deep into your brand’s purpose. What’s your mission? Who’s your audience? What values drive your business?

• Once you’ve got those nailed down, pinpoint your brand’s personality traits. Are you fun and casual, or all about professionalism?

• Lay down some ground rules. Decide on vocabulary preferences, sentence structures, and even whether to use emojis (yes, they can be part of your TOV!).

But it doesn’t stop there. The key to a good TOV guide is keeping it fresh. Revisit and update it as your brand evolves. Get your team on board, train them up, and keep the dialogue open for feedback and tweaks.

2. Train AI tools to recognize and use your TOV

You can train many AI-content tools to use your brand’s TOV as you would with any new starter. Start by feeding it some of your brand’s past content so it begins to understand how you structure your sentences, how informal your messaging is, and how you talk to your audience.

Then, using Natural Language Processing (NLP) and machine learning, AI recognizes patterns in your communications and starts to produce similar content. With time and ongoing pointers, amendments, and tweaks, most tools can begin to recognize and use your TOV.

But remember, it’s an ongoing practice. You have to continuously fine-tune and review its outputs to keep it singing in perfect harmony with your brand’s voice.

3. Monitor AI content and edit

Even after you’ve trained your chosen AI tool to mimic your brand’s TOV, you still have to thoroughly check and edit the content it has created. Just as you would proofread and edit any work from a content writer.

Monitor the output and use your TOV guide to ensure it hits the brand’s values, tone, and messaging standards. AI tools occasionally throw out incorrect facts or statements without context. Publishing anything incorrect that can be disproven by your audience will alter brand associations and even perceived quality, so it’s important to have a rigorous fact-checking system in place.

4. Test and give feedback to the AI tool

Think of the AI tool as an eager employee. If you want it to improve, you need to provide thought-out feedback.

Start by conducting structured evaluations of its outputs against predefined criteria, measuring aspects like accuracy, relevance, and adherence to your brand’s tone of voice.

Then, maintain a clear and consistent feedback loop, offering specific and constructive comments to help the AI tool learn and improve over time, ultimately aligning it more closely with your brand’s unique requirements.

How to safely build brand equity with AI

The good news is that by adopting a thoughtful approach to AI and making some adjustments, you can generate content for your brand that is entirely distinctive and tailored to your identity.

There are some ways you can use AI tools that will work to spot patterns in your analytics to inform your ongoing strategies, as well as improve customer experiences.

Spotting data patterns and unearthing customer insights

Analyze customer data

Some AI tools can analyze large datasets, such as customer churn rates and sentiment analyses on social media, to identify patterns, trends, and correlations. This valuable insight into customer behavior can help to inform your brand to craft personalized marketing strategies and improved user experiences, ultimately leading to better decision-making and enhanced customer satisfaction.

It’s worth keeping in mind the privacy concerns point from above, though, making sure the AI tool you use has the option to not store chat history for this.

Stay in the loop with social media

There are AI tools that can track brand mentions, sentiment analysis, and emerging trends on social media. This will allow your social media marketing team to spend more time elsewhere, crafting perfect campaigns to work with the AI’s findings.

Do market research

Artificial intelligence has reshaped the field of market research, providing tools that can dissect data and generate invaluable insights. This is a great way to save your team time that would otherwise be used to analyze this data.

An example prompt to do so could be:

Generate a report summarizing the current market trends and customer preferences for [specific product, service, or industry]. Include information on key businesses and any notable shifts in consumer behavior. Please provide statistics and insights from the past year.

Improving customer experiences

Personalize content

After you’ve already used AI to sift through customer datasets, you can use the findings to produce personalized content tailored to their needs and preferences. This can span from customized product suggestions to tailor-made marketing messages.

24/7 chatbots

24/7 AI chatbots enhance the customer experience by delivering quick and reliable service around the clock — chatbot conversions are also pretty powerful for your bottom line. You can provide instant, consistent, and cost-effective customer support, handling routine queries efficiently and freeing human agents for more complex issues.

Automatic subtitles and image captions

With video becoming one of the preferred methods of consuming content, AI-powered subtitle generators such as Kapwing and VEED’s tools are getting increasingly popular. This helps with accessibility, which can improve user experience and save your team time.

How to avoid AI risks when it comes to your brand equity

Safely building brand equity with AI involves a strategic approach to harnessing the technology while mitigating potential risks. Here’s how to do it:

1. Define your brand’s AI strategy: Begin by setting clear objectives for AI integration in your branding efforts. How will you use it? Will you use the tools to generate content, automate processes, or gather insights? Ensure you have answers for these and the goals behind them. What are you hoping to achieve?

2. Apply strict quality control: Establishing a robust review and approval process for AI-generated content will help to protect your brand awareness, associations, and perceived quality. Human oversight will always be needed to catch errors and maintain consistency in messaging.

3. Remain transparent: Maintaining transparency with your audience about your AI use will help to build and keep their trust. If chatbots or automated systems are handling customer inquiries, make it clear that customers are interacting with AI. If a blog post has been produced using AI, add a disclaimer about it highlighting who the piece was checked by to make sure you’re still hitting ‘experience’ and ‘expertise’ in E-E-A-T.

4. Focus on data privacy and security: Safeguard customer data rigorously. Comply with data protection regulations like GDPR or CCPA, and communicate your commitment to data privacy to enhance brand trust. Similar to the above, share any instances where personal data is handled by AI systems and the steps taken to make sure it remains confidential.

5. Be prepared for a crisis: Even with the most watertight approval processes, some mistakes still slip through the net. This is no different when using AI. To safeguard the audience trust you’ve built, ensure you implement a plan to address potential AI-related crises, such as misinterpretations or mishandling of sensitive issues.

Key takeaways

There will always be AI risks if using it in customer-facing content, but this doesn’t mean your brand shouldn’t use it.

To successfully integrate AI into your brand’s strategies while building brand equity, you should ensure all uses align with the brand’s values, messaging, and customer expectations.

Have solid processes in place for everything from proofreading and fact-checking to keeping all customer data confidential. This way, you’ll be able to protect your brand awareness, associations, perceived quality, and, ultimately, your brand equity.

The post AI Risks: Can Artificial Intelligence Affect Your Brand Equity? appeared first on ProdSens.live.