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6 Ways ChatGPT Can Improve Your SEO

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6 Ways ChatGPT Can Improve Your SEO

Most of the discourse surrounding the impact of artificial intelligence (AI) on SEO has been about content creation. This makes perfect sense. Large language models (LLMs) have fundamentally changed the speed at which businesses and individuals can produce blog posts, marketing copy, social media posts and much more.

I am not the first to provide the caveat that while AI tools can help you speed up your writing process, they can also open up your site to a variety of SEO risks including duplicate content, violations of Google’s E-E-A-T Guidelines, generally robotic copywriting that is devoid of brand voice and personality, and a host of other issues.

AI content generation is certainly something that can help SEOs and businesses in moderation. Google itself has essentially okayed the use of AI, as long as it is with intent to produce “helpful content”. This can be easier said than done.

In this article, I want to highlight some ways that free AI tools like ChatGPT can help SEO’s with all sorts of other tasks, other than creating content. There are a wide range of things that SEOs do everyday that can significantly be sped up or even completely done by free AI tools like ChatGPT. These can range from On-Page SEO optimizations to Technical SEO projects.

Let’s get into it.

1. Create Schema markup

Perhaps the most straightforward way in which tools like ChatGPT can simplify our work as SEOs is by writing schema markup for us. I will keep this section short, as the process in itself is fairly straightforward.

How to Use AI to Create Schema Markup

  1. Write a ChatGPT prompt that describes the schema you want to create, and for which page.

  2. QA the results and run them through a Schema validating tool.

  3. Implement the schema. Submit your URL to Google.

  4. That’s it!

Remember, ChatGPT typically will not visit a URL for you, so you will need to paste the entire text of your page in the prompt.

The response is a block of schema code that you can paste into a validator. Note that the response was not 100% perfect, hence the need to QA. ChatGPT missed the name of the publisher organization. Before dropping this code onto the published page in our CMS, I would change the name of the organization from “Example” to “Moz.”

1690232164 566 6 Ways ChatGPT Can Improve Your SEO

2. Keyword clustering (sample python code)

Another time-saving SEO task that you can jumpstart with ChatGPT is the semantic grouping and categorization of keywords. This can be done within the user interface (UI) of GPT, or through a python script that utilizes OpenAI’s API.

Using the UI, I have had success grouping around 100 keywords at a time. The output will typically be an indented, bulleted list of all your terms categorized into buckets.

A python script gives you more flexibility to increase your number of max tokens and allow you to work with longer lists of keywords.

Below is an extremely simple python script that prompts OpenAI to come up with categories for a list of keywords.

import openai


# Set up OpenAI API key and model ID
openai.api_key = "YOUR_API_KEY"
model_id = "text-davinci-003"


# Define the prompt to use with the OpenAI API
prompt = """
classify the following keywords into semantically related groups:
apple
london
banana
train
car
pizza
sicily
pasta
"""


# Use OpenAI's API to generate text based on the prompt
response = openai.Completion.create(
   engine=model_id,
   prompt=prompt,
   max_tokens=1024,
   n=1,
   stop=None,
   temperature=0.7,
)


# Extract the generated text from the response
generated_text = response.choices[0].text


# Print the generated text to the console
print(generated_text)

The output will look like something like this. You can use this output to modify groupings in your keyword tracking tool of choice, such as Moz Pro. If you are familiar with using Pandas, you can turn the generated_text output into a dataframe for an easy CSV export.

Fruits: Apple, Banana
Cities: London, Sicily
Transportation: Train, Car
Food: Pizza, Pasta

3. Generate meta descriptions

ChatGPT is exceedingly good at taking large amounts of text input and summarizing it. What better way for SEOs to utilize AI’s summarization capabilities than generating meta descriptions? Since meta descriptions are inherently summaries of pages, natural language processing (NLP) models do a good job of extracting the main ideas from multiple paragraphs of text and condensing them into one.

When feeding ChatGPT with text to summarize, you can also include a few keywords that you want it to include in its output. This is another instance where you will need outside data from a tool such as Moz Keyword Explorer to help you find focus keywords. Once you have an idea of the main keyword(s) of the page you want to optimize, you can include those in your meta description prompt. That prompt may look something like this:

Summarize the following text in 60 words, and include the following keywords: seo, content strategy
[full page text]

In my experience, however, ChatGPT is not very good at limiting its responses to a certain word or character length. You may get something like this, and need to change or remove a few sentences.

1690232164 378 6 Ways ChatGPT Can Improve Your SEO

Still, this simple task could potentially have saved you 10–15 minutes of working with a blank page (or CMS field) and given you a starting point for your meta description.

4. Create FAQs (and tag them with schema)

Another task that leverages ChatGPT’s summarization capabilities is the creation of frequently asked questions (FAQs).

Prompt GPT to create FAQs for a section of page copy that you paste into the tool, and AI will generate some sample FAQs for you. The responses it gives tends to be brief, which is ideal for tagging them with FAQ schema.

After you’ve reviewed and edited the FAQ suggestions that ChatGPT provides, circle back to tip #1 and paste them back into ChatGPT to generate FAQ schema that you can add to your page.

1690232164 871 6 Ways ChatGPT Can Improve Your SEO

5. Topical research

While OpenAI’s free ChatGPT tool does not provide Keyword Volume or other important SEO keyword metrics, it can still be an effective engine for generating content ideas related to a given keyword.

When paired with a tool like Moz Keyword Explorer, the results can be powerful.

Begin the process as you would normally approach keyword research. Identify a list of keywords that you want to include in your page. Then, ask ChatGPT to create topic ideas related to these terms.

I find that prompting the tool for around 50 topics gives you a good sample of page ideas without repetition.

The results are not all going to be perfect titles for you to copy and paste into your CMS without reviewing them, but they can rapidly (and I mean RAPIDLY) give you a sense of direction for your editorial calendar, content marketing strategy or even social media posts. Each of the concepts identified here about SEO, focusing on the specified keywords, has the makings of a well-intentioned blog post topic.

1690232164 658 6 Ways ChatGPT Can Improve Your SEO

6. SEO content briefs

Once you have done your keyword research and compiled terms that you would like to include into a new page on your website, try asking ChatGPT to use them to create a page outline for you, along with a possible page title.

This can serve as a great jumping-off-point for your editorial team (or you) to work with to write your full article. An outline or content brief for a page about keyword research may look something like this:

1690232164 472 6 Ways ChatGPT Can Improve Your SEO

As is a recurring theme with the use of AI for SEO, the results are not perfect, but they can generate ideas for you to take and run with. For example, you may realize that this outline does not get into the concepts of Search Volume or Keyword Difficulty, which you wanted to address on your page. You can tweak your prompt to specify a few additional keywords that you’d like to include, or manually edit ChatGPT’s output to suit your needs.

My guess is as good as any regarding the direction AI will steer the digital marketing industry, and more specifically SEO. What I do know is that right now, there are so many ways in which AI can make tedious aspects of my job less time consuming, so I can focus my attention on more strategic and big-picture problems. Hopefully this list helps you do the same.

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Comparing Credibility of Custom Chatbots & Live Chat

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Building Customer Trust: Comparing Credibility of Custom Chatbots & Live Chat

Addressing customer issues quickly is not merely a strategy to distinguish your brand; it’s an imperative for survival in today’s fiercely competitive marketplace.

Customer frustration can lead to customer churn. That’s precisely why organizations employ various support methods to ensure clients receive timely and adequate assistance whenever they require it.

Nevertheless, selecting the most suitable support channel isn’t always straightforward. Support teams often grapple with the choice between live chat and chatbots.

The automation landscape has transformed how businesses engage with customers, elevating chatbots as a widely embraced support solution. As more companies embrace technology to enhance their customer service, the debate over the credibility of chatbots versus live chat support has gained prominence.

However, customizable chatbot continue to offer a broader scope for personalization and creating their own chatbots.

In this article, we will delve into the world of customer support, exploring the advantages and disadvantages of both chatbots and live chat and how they can influence customer trust. By the end, you’ll have a comprehensive understanding of which option may be the best fit for your business.

The Rise of Chatbots

Chatbots have become increasingly prevalent in customer support due to their ability to provide instant responses and cost-effective solutions. These automated systems use artificial intelligence (AI) and natural language processing (NLP) to engage with customers in real-time, making them a valuable resource for businesses looking to streamline their customer service operations.

Advantages of Chatbots

24/7 Availability

One of the most significant advantages of custom chatbots is their round-the-clock availability. They can respond to customer inquiries at any time, ensuring that customers receive support even outside regular business hours.

Consistency

Custom Chatbots provide consistent responses to frequently asked questions, eliminating the risk of human error or inconsistency in service quality.

Cost-Efficiency

Implementing chatbots can reduce operational costs by automating routine inquiries and allowing human agents to focus on more complex issues.

Scalability

Chatbots can handle multiple customer interactions simultaneously, making them highly scalable as your business grows.

Disadvantages of Chatbots

Limited Understanding

Chatbots may struggle to understand complex or nuanced inquiries, leading to frustration for customers seeking detailed information or support.

Lack of Empathy

Chatbots lack the emotional intelligence and empathy that human agents can provide, making them less suitable for handling sensitive or emotionally charged issues.

Initial Setup Costs

Developing and implementing chatbot technology can be costly, especially for small businesses.

The Role of Live Chat Support

Live chat support, on the other hand, involves real human agents who engage with customers in real-time through text-based conversations. While it may not offer the same level of automation as custom chatbots, live chat support excels in areas where human interaction and empathy are crucial.

Advantages of Live Chat

Human Touch

Live chat support provides a personal touch that chatbots cannot replicate. Human agents can empathize with customers, building a stronger emotional connection.

Complex Issues

For inquiries that require a nuanced understanding or involve complex problem-solving, human agents are better equipped to provide in-depth assistance.

Trust Building

Customers often trust human agents more readily, especially when dealing with sensitive matters or making important decisions.

Adaptability

Human agents can adapt to various customer personalities and communication styles, ensuring a positive experience for diverse customers.

Disadvantages of Live Chat

Limited Availability

Live chat support operates within specified business hours, which may not align with all customer needs, potentially leading to frustration.

Response Time

The speed of response in live chat support can vary depending on agent availability and workload, leading to potential delays in customer assistance.

Costly

Maintaining a live chat support team with trained agents can be expensive, especially for smaller businesses strategically.

Building Customer Trust: The Credibility Factor

When it comes to building customer trust, credibility is paramount. Customers want to feel that they are dealing with a reliable and knowledgeable source. Both customziable chatbots and live chat support can contribute to credibility, but their effectiveness varies in different contexts.

Building Trust with Chatbots

Chatbots can build trust in various ways:

Consistency

Chatbots provide consistent responses, ensuring that customers receive accurate information every time they interact with them.

Quick Responses

Chatbots offer instant responses, which can convey a sense of efficiency and attentiveness.

Data Security

Chatbots can assure customers of their data security through automated privacy policies and compliance statements.

However, custom chatbots may face credibility challenges when dealing with complex issues or highly emotional situations. In such cases, the lack of human empathy and understanding can hinder trust-building efforts.

Building Trust with Live Chat Support

Live chat support, with its human touch, excels at building trust in several ways:

Empathy

Human agents can show empathy by actively listening to customers’ concerns and providing emotional support.

Tailored Solutions

Live chat agents can tailor solutions to individual customer needs, demonstrating a commitment to solving their problems.

Flexibility

Human agents can adapt to changing customer requirements, ensuring a personalized and satisfying experience.

However, live chat support’s limitations, such as availability and potential response times, can sometimes hinder trust-building efforts, especially when customers require immediate assistance.

Finding the Right Balance

The choice between custom chatbots and live chat support is not always binary. Many businesses find success by integrating both options strategically:

Initial Interaction

Use chatbots for initial inquiries, providing quick responses, and gathering essential information. This frees up human agents to handle more complex cases.

Escalation to Live Chat

Implement a seamless escalation process from custom chatbots to live chat support when customer inquiries require a higher level of expertise or personal interaction.

Continuous Improvement

Regularly analyze customer interactions and feedback to refine your custom chatbot’s responses and improve the overall support experience.

Conclusion

In the quest to build customer trust, both chatbots and live chat support have their roles to play. Customizable Chatbots offer efficiency, consistency, and round-the-clock availability, while live chat support provides the human touch, empathy, and adaptability. The key is to strike the right balance, leveraging the strengths of each to create a credible and trustworthy customer support experience. By understanding the unique advantages and disadvantages of both options, businesses can make informed decisions to enhance customer trust and satisfaction in the digital era.

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The Rise in Retail Media Networks

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A shopping cart holding the Amazon logo to represent the rise in retail media network advertising.

As LL Cool J might say, “Don’t call it a comeback. It’s been here for years.”

Paid advertising is alive and growing faster in different forms than any other marketing method.

Magna, a media research firm, and GroupM, a media agency, wrapped the year with their ad industry predictions – expect big growth for digital advertising in 2024, especially with the pending US presidential political season.

But the bigger, more unexpected news comes from the rise in retail media networks – a relative newcomer in the industry.

Watch CMI’s chief strategy advisor Robert Rose explain how these trends could affect marketers or keep reading for his thoughts:

GroupM expects digital advertising revenue in 2023 to conclude with a 5.8% or $889 billion increase – excluding political advertising. Magna believes ad revenue will tick up 5.5% this year and jump 7.2% in 2024. GroupM and Zenith say 2024 will see a more modest 4.8% growth.

Robert says that the feeling of an ad slump and other predictions of advertising’s demise in the modern economy don’t seem to be coming to pass, as paid advertising not only survived 2023 but will thrive in 2024.

What’s a retail media network?

On to the bigger news – the rise of retail media networks. Retail media networks, the smallest segment in these agencies’ and research firms’ evaluation, will be one of the fastest-growing and truly important digital advertising formats in 2024.

GroupM suggests the $119 billion expected to be spent in the networks this year and should grow by a whopping 8.3% in the coming year.  Magna estimates $124 billion in ad revenue from retail media networks this year.

“Think about this for a moment. Retail media is now almost a quarter of the total spent on search advertising outside of China,” Robert points out.

You’re not alone if you aren’t familiar with retail media networks. A familiar vernacular in the B2C world, especially the consumer-packaged goods industry, retail media networks are an advertising segment you should now pay attention to.

Retail media networks are advertising platforms within the retailer’s network. It’s search advertising on retailers’ online stores. So, for example, if you spend money to advertise against product keywords on Amazon, Walmart, or Instacart, you use a retail media network.

But these ad-buying networks also exist on other digital media properties, from mini-sites to videos to content marketing hubs. They also exist on location through interactive kiosks and in-store screens. New formats are rising every day.

Retail media networks make sense. Retailers take advantage of their knowledge of customers, where and why they shop, and present offers and content relevant to their interests. The retailer uses their content as a media company would, knowing their customers trust them to provide valuable information.

Think about these 2 things in 2024

That brings Robert to two things he wants you to consider for 2024 and beyond. The first is a question: Why should you consider retail media networks for your products or services?   

Advertising works because it connects to the idea of a brand. Retail media networks work deep into the buyer’s journey. They use the consumer’s presence in a store (online or brick-and-mortar) to cross-sell merchandise or become the chosen provider.

For example, Robert might advertise his Content Marketing Strategy book on Amazon’s retail network because he knows his customers seek business books. When they search for “content marketing,” his book would appear first.

However, retail media networks also work well because they create a brand halo effect. Robert might buy an ad for his book in The New York Times and The Wall Street Journal because he knows their readers view those media outlets as reputable sources of information. He gains some trust by connecting his book to their media properties.

Smart marketing teams will recognize the power of the halo effect and create brand-level experiences on retail media networks. They will do so not because they seek an immediate customer but because they can connect their brand content experience to a trusted media network like Amazon, Nordstrom, eBay, etc.

The second thing Robert wants you to think about relates to the B2B opportunity. More retail media network opportunities for B2B brands are coming.

You can already buy into content syndication networks such as Netline, Business2Community, and others. But given the astronomical growth, for example, of Amazon’s B2B marketplace ($35 billion in 2023), Robert expects a similar trend of retail media networks to emerge on these types of platforms.   

“If I were Adobe, Microsoft, Salesforce, HubSpot, or any brand with big content platforms, I’d look to monetize them by selling paid sponsorship of content (as advertising or sponsored content) on them,” Robert says.

As you think about creative ways to use your paid advertising spend, consider the retail media networks in 2024.

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Cover image by Joseph Kalinowski/Content Marketing Institute

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AI driving an exponential increase in marketing technology solutions

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AI driving an exponential increase in marketing technology solutions

The martech landscape is expanding and AI is the prime driving force. That’s the topline news from the “Martech 2024” report released today. And, while that will get the headline, the report contains much more.

Since the release of the most recent Martech Landscape in May 2023, 2,042 new marketing technology tools have surfaced, bringing the total to 13,080 — an 18.5% increase. Of those, 1,498 (73%) were AI-based. 

Screenshot 2023 12 05 110428 800x553

“But where did it land?” said Frans Riemersma of Martech Tribe during a joint video conference call with Scott Brinker of ChiefMartec and HubSpot. “And the usual suspect, of course, is content. But the truth is you can build an empire with all the genAI that has been surfacing — and by an empire, I mean, of course, a business.”

Content tools accounted for 34% of all the new AI tools, far ahead of video, the second-place category, which had only 4.85%. U.S. companies were responsible for 61% of these tools — not surprising given that most of the generative AI dynamos, like OpenAI, are based here. Next up was the U.K. at 5.7%, but third place was a big surprise: Iceland — with a population of 373,000 — launched 4.6% of all AI martech tools. That’s significantly ahead of fourth place India (3.5%), whose population is 1.4 billion and which has a significant tech industry. 

Dig deeper: 3 ways email marketers should actually use AI

The global development of these tools shows the desire for solutions that natively understand the place they are being used. 

“These regional products in their particular country…they’re fantastic,” said Brinker. “They’re loved, and part of it is because they understand the culture, they’ve got the right thing in the language, the support is in that language.”

Now that we’ve looked at the headline stuff, let’s take a deep dive into the fascinating body of the report.

The report: A deeper dive

Marketing technology “is a study in contradictions,” according to Brinker and Riemersma. 

In the new report they embrace these contradictions, telling readers that, while they support “discipline and fiscal responsibility” in martech management, failure to innovate might mean “missing out on opportunities for competitive advantage.” By all means, edit your stack meticulously to ensure it meets business value use cases — but sure, spend 5-10% of your time playing with “cool” new tools that don’t yet have a use case. That seems like a lot of time.

Similarly, while you mustn’t be “carried away” by new technology hype cycles, you mustn’t ignore them either. You need to make “deliberate choices” in the realm of technological change, but be agile about implementing them. Be excited by martech innovation, in other words, but be sensible about it.

The growing landscape

Consolidation for the martech space is not in sight, Brinker and Riemersma say. Despite many mergers and acquisitions, and a steadily increasing number of bankruptcies and dissolutions, the exponentially increasing launch of new start-ups powers continuing growth.

It should be observed, of course, that this is almost entirely a cloud-based, subscription-based commercial space. To launch a martech start-up doesn’t require manufacturing, storage and distribution capabilities, or necessarily a workforce; it just requires uploading an app to the cloud. That is surely one reason new start-ups appear at such a startling rate. 

Dig deeper: AI ad spending has skyrocketed this year

As the authors admit, “(i)f we measure by revenue and/or install base, the graph of all martech companies is a ‘long tail’ distribution.” What’s more, focus on the 200 or so leading companies in the space and consolidation can certainly be seen.

Long-tail tools are certainly not under-utilized, however. Based on a survey of over 1,000 real-world stacks, the report finds long-tail tools constitute about half of the solutions portfolios — a proportion that has remained fairly consistent since 2017. The authors see long-tail adoption where users perceive feature gaps — or subpar feature performance — in their core solutions.

Composability and aggregation

The other two trends covered in detail in the report are composability and aggregation. In brief, a composable view of a martech stack means seeing it as a collection of features and functions rather than a collection of software products. A composable “architecture” is one where apps, workflows, customer experiences, etc., are developed using features of multiple products to serve a specific use case.

Indeed, some martech vendors are now describing their own offerings as composable, meaning that their proprietary features are designed to be used in tandem with third-party solutions that integrate with them. This is an evolution of the core-suite-plus-app-marketplace framework.

That framework is what Brinker and Riemersma refer to as “vertical aggregation.” “Horizontal aggregation,” they write, is “a newer model” where aggregation of software is seen not around certain business functions (marketing, sales, etc.) but around a layer of the tech stack. An obvious example is the data layer, fed from numerous sources and consumed by a range of applications. They correctly observe that this has been an important trend over the past year.

Build it yourself

Finally, and consistent with Brinker’s long-time advocacy for the citizen developer, the report detects a nascent trend towards teams creating their own software — a trend that will doubtless be accelerated by support from AI.

So far, the apps that are being created internally may be no more than “simple workflows and automations.” But come the day that app development is so democratized that it will be available to a wide range of users, the software will be a “reflection of the way they want their company to operate and the experiences they want to deliver to customers. This will be a powerful dimension for competitive advantage.”

Constantine von Hoffman contributed to this report.

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