In recent years, we have seen the rise of artificial intelligence in the digital marketing space. While many saw the need to use these tools to help automate processes, some worried that human marketers could one day become obsolete.
In this article, we’ll discuss how AI is used in digital marketing and give some examples of marketers using these tools to automate their work. We’ll also share more insights on how these case studies worked and whether they were a success or a challenge for the marketer. Most importantly, let’s examine whether these AI tools will be ready to replace humans.
Are you ready? Let’s dive in.
What is Artificial Intelligence in Digital Marketing?
There are plenty of reasons why digital marketers have turned to using artificial intelligence in their line of work. Over 80% of marketers around the world use an AI tool along with their online marketing strategies. Another interesting statistic is that 88% of marketers who use AI have been able to personalise their customer journey.
Admittedly, these are impressive numbers. They show that more and more professionals have adopted automation to make their jobs easier. Some tools can be used in data collection, machine learning, natural language processing, and data analysis.
The best part about using these tools is that they can give insights into vast amounts of data on customer behaviours at lightning speed. With these results, it’s not hard to understand why so many people are adapting AI tools into their strategy.
Marketers use AI in digital marketing in two ways: the backend and the customer-facing side. Backend AI tools help marketers develop customer profiles, forecast product demand, perform programmatic ad buying, and many more actions. On the other hand, marketers use AI to improve the experience of the customer. This leads to customer satisfaction and brand loyalty.
Examples of Businesses that Used Artificial Intelligence in Digital Marketing
Here are some examples of Singaporean businesses that used AI tools as part of their digital marketing campaign. We’ll also be discussing the specific tools they used to execute these campaigns.
1. Zalora
Image Credit: Zalora
First on our list is the leading fashion eCommerce platform in Southeast Asia, Zalora. In a drive to integrate AI tools for enhancing customer experience, the company rolled out TITAN, a proprietary platform-as-a-service (PaaS) OpenAI integration that makes use of generative AI technology.
Through this tool, Zalora was able to improve online fashion customer experiences, create new efficiencies in its operations, and drive growth opportunities. The tool also looks promising for creating more conversational and immersive shopping experiences for customers complete with data-driven recommendations that they will find useful.
TITAN comes with a conversational shopping assistant that offers real-time interactive features and smart prompts.
This algorithm manages to personalise the experience of each online customer using their purchase history, preferences, and browsing behaviour. As a result, they get a more tailored shopping experience with better conversion and customer engagement rates.
2. DBS Bank
Image Credit: DBS
As one of the largest financial institutions in Singapore, DBS Bank is in a position to leverage AI and use it to streamline its digital marketing efforts. The bank has been able to create over 100 AI/ML algorithms that analyse its internal data with 15,000 customer data points. As a result, they can celebrate the milestones of their customers along with them and offer personalised product recommendations.
The AI tool has also helped them create highly targeted marketing campaigns tailored for individual customers. This led the bank to see a significant boost in campaign efficiency, better ROI, and higher engagement rates compared to traditional marketing methods. Through its efforts, DBS Bank has positioned itself as an “AI-fueled” bank that’s future-proof.
3. Grab
Image Credit: Grab
Grab has long positioned itself as a leader in the ride-share market in Southeast Asia. As it transitioned to become a superapp, it has also adopted the use of AI tools to leverage its processes. Particularly, it made use of AI for customer segmentation and predictive analytics. Through this, Grab can analyse vast amounts of user data to identify customer behaviour and predict patterns.
This has allowed Grab to craft personalised marketing messages, offer exclusive promotions, and improve the user experience on its app. On the customer side, this has led more customers to become loyal to the app.
These are just some of the examples of Singaporean brands that have embraced the use of artificial intelligence in digital marketing. As these tools get more fine-tuned, we can expect more brands to follow their examples and leverage these tools for better results.
How to Start Using AI in Your Digital Marketing Strategy
There is room for everyone in a digital marketing team to adopt the use of AI in their everyday jobs. Whether the task calls for something simple, like task automation or data collection, or more complicated tasks, like idea generation and audience analysis; there’s bound to be an AI tool that can help automate things.
But let’s take a look at the different areas in digital marketing where an AI tool can be utilised:
1. Brainstorming
Image Credit: Optimonk
AI tools have become the answer to one problem that creatives struggle with: writer’s block. Through the use of AI-powered SaaS tools, you can come up with keyword suggestions and topic ideas. These tools can also identify emerging trends so you can create data-driven marketing campaigns.
Some of the most popular AI brainstorming tools that you can use to help when you are stuck for ideas include:
- ChatGPT
- HubSpot AI Content Writer
- Lucidspark
- Miro
- Milanote
- HubSpot Campaign Assistant
2. Personalisation
Image Credit: UseInsider
One of the biggest reasons why marketers use AI tools in digital marketing is that they allow them to create personalised experiences for their campaigns, especially in eCommerce.
Before the onset of AI tools, personalisation was only something that marketers envisioned and tried to achieve. But because it required a lot of information and A/B testing on their end, it didn’t seem to work. Thankfully, one-to-one personalisation tools allowed them to achieve these results.
How to use AI for personalisation:
- Website and mobile app content personalisation: Using advanced AI personalisation tools, businesses can make their site or app feel like it was specifically designed for their customers.
- Omnichannel personalisation: Marketers practice omnichannel marketing to craft consistent customer experiences throughout all touchpoints. But thanks to AI, personalised content and recommendations can be delivered right away.
- Predictive segmentation: In the past, brands used traditional segmentation by filtering their customers based on location, demographic, device, and purchase history. Thanks to AI, a customer’s future behaviour or response to a discount can already be predicted.
- Customer journey orchestration and optimisation: Marketers know that the customer journey doesn’t stop with a site visit. Instead, they have to be there every step of the way to ensure the customer completes their journey by making a sale. Through AI, marketers can automate and optimise the process with triggered messages.
- Relevant product recommendations: Especially in eCommerce, being able to automate the customer’s experience is a great way to keep them shopping on the platform. AI tools can offer personalised recommendations based on their customer’s preferences, interests, previous purchases, and other data.
When it comes to AI tools for personalisation, the available ones offer a variety of solutions. Here are three categories of personalisation, along with the popular tools that you can use:
| AI tools for personalising most customer touchpoints (SMS, email, mobile apps, websites, etc) | AI tools for website personalisation | AI tool for cold email outreach personalisation |
| Insider | Dynamic Yield | Lyne |
| Braze | Klevu | |
| CleverTap | Monetate | |
| Adobe Target | Intellimize | |
| Adobe Campaign |
3. Research and Customer Data Analysis
Image Credit: Luzmo
Every marketer knows how important it is to analyse how well a past campaign performed. By automating this process, you can easily identify areas of success that you can use to craft better marketing strategies.
Using an AI tool for this purpose can help you consolidate huge amounts of data in a quick period. AI marketing tools are capable of analysing consumer data from various sources, including market trends, social media, and many more. Some of the tools you can use for this purpose include:
These tools are also able to help you conduct competitor analysis so you have a look into the tactics, keywords, and market positioning strategies they are using.
4. Conversion Optimisation
Image Credit: Hotjar
Digital marketers make changes to their websites all the time as a way to get people to convert. They may try to change the colour of their call-to-action (CTA) button or change the positioning of an offer. Having the right conversion optimisation tools can come in handy:
- Unbounce: A tool for quickly building, publishing, and tweaking landing pages for testing. It comes with built-in features for A/B testing and variant analytics.
- Optimizely: Another tool that can be useful in conducting experiments on your landing pages is Optimizely, which has tools for audience targeting and visual creation. It is a no-code platform that allows you to run quick tests on various audience segments.
- Hotjar: A neat feature of Hotjar is that it gives you a real-time visual record of the actions and behaviours of your site visitors. Through this heatmap feature, you get to know which areas people are clicking on and what isn’t working.
5. Content Creation
Image Credit: TeamGPT
There are also AI tools available for creating content. Tools like ChatGPT, Jasper, Surfer SEO, and Copy.ai, can write an outline, headlines, or an entire article in minutes. These tools can also help analyse user engagement and behaviour so you can make better content optimisation decisions.
If you plan to use an AI tool for content creation, you need to follow these best practices:
Create a Great Prompt
Content creation starts with a prompt or a text input to generate content. You’re telling the AI what to do before you can get a result. Since this prompt can affect how good your content is, you need to know how to start with a prompt.
Some tips to follow include:
- Don’t treat it like a search engine
- The more details you provide, the better your results will be
- Have a goal
- Ask open-ended questions
- Provide a context
Use the Generated Content as a Starting Point
Once the AI generates content for you, you can use it as a baseline, a source of inspiration, or a brainstorming tool. The tool can create basic content for anyone. But if you want to make it specific to you, you need to make a lot of changes by adding your perspective.
Avoid Plagiarism
One problem with AI-generated content is that it is plagiarised content. AI models have been trained to go through large amounts of data, which often include copyrighted material. Even if you don’t intentionally plan on replicating existing work, it can happen when you use AI to generate content.
Instead of copy-pasting AI-generated content, you can edit the article and make it your own. After that, you can run the finished content through plagiarism detection tools to make sure it passes as an original article. Some of the available plagiarism detection tools are:
- Grammarly
- Copyleaks
- Plagiarism Checker
- Copyscape
- Scribbr
6. SEO
Image Credit: Ahrefs
AI tools can also be helpful in your search engine optimisation (SEO) strategy. Doing SEO manually on a new site can be daunting and time-consuming. But thankfully, there are online marketing tools that can streamline the process and deliver results.
Some of the best AI tools for SEO include:
- Ahrefs: Allows you to look for keyword ideas and ranking opportunities. You can also use the tool to check URLs for the top organic keywords and do competitor research.
- Semrush: Semrush is another useful SEO tool that helps you keep track of how well your keywords are ranking. You can also use the tool to break down keyword ideas and check difficulty, and variations so you can brainstorm for topics.
- Clearscope: A lot of people use Clearscope to write content after they already identified keyword opportunities. It’s useful for both optimising existing content and writing from scratch.
7. Reporting
Image Credit: MarketMuse
Finally, you can use artificial intelligence in digital marketing to look at your insights. These tools help ensure you are getting accurate data by looking at different insights, trends, and patterns. You can also generate comprehensive reports that come with beautiful visuals to make your reports easier to digest.
Some of the tools you can use for reporting include:
- MarketMuse
- Customfit.ai
- Peak.ai
- Mutiny
- Outranking.io
- On-Page AI
- Albert.ai
Overdependence on AI tools for content creation can also be a problem. Before using AI-generated content, make sure to fact-check and edit it. A lot of instances have already occurred when AI has been found to make mistakes and inaccuracies in its data. Use these tools as a guide instead of the finished product.
Are Human Marketers Becoming Obsolete Because of AI?
To be honest, it’s scary to think that some jobs will greatly be affected by AI, more so than others. Some of these jobs include:
- Data collection/analytics
- Online customer service/support
- Content ideation
But it’s also important to note that these kinds of jobs are the ones that digital marketers don’t enjoy doing. Most marketers see these as repetitive and time-consuming tasks. When it comes to the more in-depth marketing roles, AI is still far from posing a threat to the jobs of humans. After all, this field is all about empathy, creativity, and understanding human behaviour; things that AI are not capable of. AI can’t replace your job because:
- It can’t develop original ideas
- It can’t write with human empathy and emotion
- It lacks critical thinking
- It can’t build relationships with other humans
AI is merely a tool that can help make your job as a digital marketer a lot easier.
Artificial Intelligence in Digital Marketing: Should You Be Worried?
AI is taking the digital marketing world by storm as these tools help streamline processes, especially the mundane ones. These tools have been proven to improve efficiency, customer experience, and ROI. But will it take over the jobs of humans? It’s too early to tell right now since some tools still manage to make errors.
As these tools continue to evolve, we can be confident that the use of artificial intelligence in digital marketing will be widespread. The best way to stay on top of the game is to keep an eye on emerging trends and how these tools can be used.
Frequently Asked Questions
What is the role of artificial intelligence in digital marketing?
Artificial intelligence in digital marketing enhances customer targeting, personalization, and automation. AI analyzes vast amounts of data to predict consumer behaviour, personalize content, optimize ad campaigns, and improve customer interactions through tools like chatbots and recommendation engines.
How to integrate AI into digital marketing?
To integrate AI into digital marketing, start by identifying areas where AI can add value, such as data analysis, customer segmentation, or content personalization. Implement AI tools that align with these needs, such as machine learning algorithms for predictive analytics or AI-driven chatbots for customer service. Continuous testing and optimization are essential for successful AI integration.
How big is the AI market in digital marketing?
The AI market in digital marketing is rapidly growing, with projections estimating it could reach billions of dollars globally by 2025. The adoption of AI is driven by its ability to significantly improve the efficiency and effectiveness of marketing efforts.
How long has AI been used in marketing?
AI has been used in marketing for over a decade, with early applications focusing on programmatic advertising and data-driven customer segmentation. The evolution of AI technology has since expanded its use to more sophisticated areas such as predictive analytics, personalization, and content creation.
