In 2023, artificial intelligence has become ubiquitous. What was once considered science fiction is now an integral part of everyday business operations. AI is present in your smartphone, shopping experiences, and perhaps even in your morning coffee routine.
Small shops, e-commerce stores, and giant tech companies – everyone is using AI. They use it to streamline processes, predict market trends, and create more engaging customer experiences.
How Teams are Using AI Today
Marketers understand the actual value of their work in separating high-impact tasks, such as creative thinking and strategy, from tedious and exhausting work.
And here’s the great part: our report on AI Trends for Marketers indicates that 90% of marketers say these tools free them from those tedious tasks.
So, how exactly are teams using AI today? Let’s find out.
Content Creation
AI tools support creative content creation by generating text, crafting images, and even creating music or code, depending on your input and requirements.
It’s not just a buzz – 48% of marketers in our survey are already using these tools to create content. AI connects the dots, fills in the gaps, and turns ideas into something tangible.
Let’s say you’re working on an advertising campaign. You have the idea, but you need images and catchy text.
Here, AI comes to the rescue. It generates options and tweaks them based on your feedback; voila, you have personalized content in a fraction of the time. It’s about working smart, not harder.
Data Analysis and Reporting
AI tools consolidate complex data analyses and turn insights into easy-to-understand reports and compelling visualizations.
Here’s something to think about: around 45% of marketers in our survey use generative AI for this exact purpose. But why is this shift so important?
Quarterly reporting used to be a daunting task. Data analysts and marketers would sift through massive amounts of data from various platforms to gain some insights.
Now, AI does the hard work by scanning data and uncovering trends and compiling them into sleek presentations. For example, ChatSpot integrates with our CRM to create instant progress reports.
This streamlined and automated process saves time and leads to smarter, more informed decision-making.
Research and Inspiration
Imagine you’re brainstorming for a new advertising campaign and then hit a roadblock in the ideation process. AI kickstarts your creative thinking by providing endless inspiration and countless research possibilities.
This is how many marketers in our survey use generative AI for research.
With access to vast databases of creative content, AI generates ideas based on trending topics, audience preferences, and past successful campaigns. It also supports keyword research, content optimization, and competitor analysis.
And the best part? AI can do this in seconds, giving you more time to focus on bringing those ideas to life.
Of course, take everything with a grain of caution and use your critical thinking skills. AI may be advanced, but there’s always a risk of generating inaccurate or biased content. Use AI to overcome creative blocks and spark new ideas, not to replace your creativity and expertise.
Predicting Customer Behavior
Using comprehensive databases, AI identifies interaction patterns and consumer preferences to predict customer behavior. It combines this data with insights derived from neuroscience studies to gain a deeper understanding of how customers think and respond to stimuli.
Why is this important? It’s about understanding your customer’s mind. Take Predict AI from Neurons as an example. It’s based on a massive database containing eye-tracking data from over 120,000 people and more than 100 billion points of brain response data.
What
What does this mean for you? In seconds, Predict gives you insights into how and why customers respond to your ads and brand.
Vizit follows a similar path. This AI-powered tool provides you with data about the images and designs that prompt your customers to click the “Buy” button.
This knowledge allows you to tailor your products and marketing strategies to perfectly align with your audience’s wants and needs. Instead of aiming in the dark, you make informed decisions.
When you better understand your customers, you create experiences that resonate with them. This leads to customer satisfaction and a more distinguished brand.
6 Examples of Artificial Intelligence
While generative tools represent one side of the smart marketing coin, predictive analytics represents the other. Predictive analytics uses artificial intelligence to categorize data and forecast future trends, customer behavior, and market dynamics.
Domain Authority Assessment
Domain authority is a search engine ranking score that predicts how likely a website is to rank on search engine results pages (SERPs). Moz’s Domain Authority (DA) checker tool is one of the best tools (if not the best).
DA estimates the website’s ability to rank. This way, SEO professionals can prioritize their efforts better.
Sites with higher DA are more likely to rank well, giving SEO professionals an idea of how difficult it may be to rank well in a specific field. SEO professionals, marketers, and public relations experts can also identify valuable link-building opportunities using the DA link quality rating.
According to Chima Mmeje, Senior Content Marketing Manager at Moz, DA uses a complex neural network instead of the simpler linear model used by industry peers. The update enhances the ability to understand link quality and detect spam.
“While DA doesn’t directly predict rankings, it relies on our exclusive internal metrics at Moz, such as the number of links, spam score, and link distribution, to estimate a page’s ability to rank well. This update helps users understand and improve their website’s standing on search results,” says Mmeje.
What we like: AI predictive analytics better processes and analyzes large amounts of complex data than traditional methods. Identifying and understanding patterns in search engine behavior, backlink profiles, and other core ranking factors provides deeper insights and more accurate predictions about a site’s ability to rank well. Implementing predictive customer scoring.
Predictive Customer Scoring
How do you determine which customers are the most likely to convert? This is where predictive customer scoring comes in.
Predictive customer scoring uses artificial intelligence to evaluate potential customers based on their likelihood of conversion. In our webinar “10x Your Marketing & Sales Productivity with ChatSpot AI by HubSpot,” ScaleOps Consulting and HubSpot partner showcased how they utilize ChatSpot for this exact purpose.
They create an ideal customer profile based on previous purchasing behaviors and then identify potential customers that best match this profile.
Why is this so important? Predictive customer scoring removes the guesswork.
It uses data, not intuition, for forecasting. This means fewer human errors and biases along with more efficient targeting of customers who are likely to convert.
The result? The sales team focuses its efforts on where it achieves the most benefit from the customers who are most likely to convert.
What we like: Artificial intelligence removes reliance on intuition and replaces it with data-driven predictions, resulting in greater accuracy and efficiency in customer targeting. Customer Support Ticket Classification.
Customer Support Ticket Classification
Wondering how major players like Zapier keep their products top-notch and their customers happy?
Here
A trick by Reid Robinson, the senior product manager at Zapier. Zapier is used to bring in product support issues and then delivers them to GPT-4 for sorting and analysis.
Every week, he receives a report that highlights the key issues that need to be addressed. Fixing problems before they escalate helps maintain Zapier’s product quality and shows customers that he cares about their experience.
What we like: Anything that supports the customer support process and makes it more efficient is a win. The proactive approach to addressing issues shows attention and a desire to put customers first.
It reduces the time and effort spent on manual sorting, freeing up valuable resources that can be used for other tasks.
Regular Data Analysis
Data analysis doesn’t have to be a monthly source of strain. Reid Robinson at Zapier makes data analysis easy with the new Assistants API feature.
“Export the data every week, ask ChatGPT Assistant to analyze the data using Code Interpreter, and then output the analysis with a visual chart in Slack,” Robinson says.
What makes this special? It’s the continuity and ease. You will receive useful visual reports without fail every single week. This means no delays in data or last-minute rushes.
You’re always informed and making informed decisions based on the latest data.
Creating a Central Data Hub
ASUS, the multinational computer, phone, and electronics company, has offices worldwide.
The business intelligence team oversees the global marketing strategy and investments, with each regional branch reporting on marketing activities at different times, in various formats, and on diverse platforms.
This lack of standardization has become a significant hurdle. To solve this issue, ASUS uses the AI-powered Improvado platform to create a central data hub.
This hub has become a unified source for the organization’s diverse data needs including management, data analysis, business intelligence, and digital marketing.
The hub connects with Google Data Studio templates, which are automated and centralized, with custom models to filter data by region, product, and marketing campaigns.
This unification improves data availability, eases the experience, and provides deeper insights. ASUS adopts a unified approach to handling data to save time and resources – up to 80 to 100 hours a week in IT and 30% annually in marketing.
Conducting Deeper SEO Research
Standard SEO research focuses on analyzing core keywords and assessing content at a surface level.
The problem with this approach? It often misses inspecting the details of search engine algorithms. It also overlooks the importance of understanding user intent, content context, and the complex relationship among ranking factors.
The B2B SaaS agency Stratabeat prefers to do things differently.
Tom Shapiro, the CEO of Stratabeat, highlights how they use marketing tools based on natural language processing models from Google Cloud Platform, IBM Watson, and OpenAI as part of their SEO toolkit.
He adds, “The architecture allows us to conduct deeper SEO research and more thorough analysis of Google search results and content SEO assessment.”
The AI-driven approach provides better insights into how search engines rank and perceive content in search engine results pages (SERPs). It’s no longer just about keyword density in SEO evaluation; it’s about overall relevance, quality, and content context relative to user queries.
What we like: This approach provides insights that go beyond traditional metrics, leading to improved search engine rankings and content optimization.
5 Examples of Generative AI
There is a lot of optimism around artificial intelligence. Our recent survey data indicates that 68% of marketing leaders at the director level and above believe that implementing AI and automation will drive business growth unprecedentedly.
In terms of…
Here are five ways generative artificial intelligence makes a big difference.
Improving Content Drafts
If used correctly, AI becomes your editing friend. Think of it as an advanced assistant that helps refine your content drafts.
AI tools can suggest improvements in grammar, style, and tone, ensuring that your message is clear and resonates with your target audience.
Wordtune is an AI assistant that fixes errors, understands context and meaning, rewrites text based on writing patterns, and generates text based on context.
Ben, the content manager at Wordtune, uses the tool to refine his content writing process in three ways:
“The first is exploring and expanding on the topic I want to write about,” Ben begins. “Let’s say I want to write about adapting content for different social media platforms, and I want to provide an example of a piece of content adapted for the platforms.”
In this case, Ben says he would use AI to quickly summarize the tone of each platform.
Ben adds that the second use case is expanding sentences and rewriting content.
“When I write, it is a very intuitive process involving reaching a flow. I can jump from point to point, and AI does a great job of smoothing out those jumps for my readers,” he explains. “The first sentence I write isn’t always perfect, so I rewrite some sentences using AI to make them clearer.”
The third use case Ben mentions is editing. He notes that there are always gaps and mistakes when you write. Adding an extra set of AI eyes has been very helpful.
“I use these three methods regardless of the writing task: email, social media posts, and long-form articles. Although the writing process for each piece can be entirely different, I stick to these three use cases to ensure I maintain my content while preserving my style,” Ben says.
At the same time, Ben also focuses on the “assistive” aspect of using AI, emphasizing that it complements his thinking rather than replacing it.
What we like: Ben pointed out how important it is to maintain your style and voice when using AI for writing.
He also highlighted the flexibility of AI in various writing tasks, showing that it can be a useful tool regardless of the type of content you’re creating. From helping to expand ideas to rephrasing sentences and editing, AI can be a valuable tool no matter the type of content you’re creating. It’s up to you to figure out where these tools fit into your workflow.
Enhancing Ongoing Link-Building Strategy
The Hunter.io team uses generative AI tools to maintain an ongoing link-building strategy and monitor if any links have broken.
Why is this important? Any marketer knows that a link-building strategy is essential for improving search engine rankings and increasing traffic to your website. They also know that tracking all those links can be an extremely challenging task.
Antonio Gabryk, the media director at Hunter, realizes how short-lived backlinks can be.
“We discovered that within less than two years of actively building links, we lost approximately 9% of the total links that were built,” Gabryk says. “Generative AI helped us recover over 50 links in less than a month.”
Gabryk shared the following steps to help you develop your link-building strategy:
1.
Collect all backlinks in a spreadsheet.
2. Build a Google Apps Script using AI assistance that will automatically check if the specified URLs still point to our target page.
3. Run the script.
4. Get the results.
Source: https://blog.hubspot.com/marketing/11-artificial-intelligence-examples-from-real-brands-in-2024
Leave a Reply