In today's digital world, Artificial Intelligence is re-shaping every industry one of them being Marketing.
But what does AI do in marketing?
AI in marketing serves as a means of collecting data, and consumer insights, anticipating customers' next movements and making automated marketing decisions. AI is frequently employed in situations where speed is critical. Artificial intelligence (AI) can improve the return on the investment done in marketing.
Why AI in marketing?
With so much competition in almost every industry, you must stand out to stay relevant for generating profits and serving a larger audience. AI can help you in achieving your marketing goal of standing out, as marketing in AI serves a means to provide your clients with a digital and personalized experience by using efficient customer segmentation strategies.
Once the segmentation is done you must be visible to current and potential clients, create trust in your IT/high-tech brand and engage them once they have been converted to keep them and generate advocacy. As a result, developing connections with customers on their terms can be done quickly using AI.
In this blog, we’ll be briefing you about 5 practical ways to boost your marketing strategies by incorporating artificial intelligence in it.
1. Planning and Creating Content-
Content strategy is heavily influenced by artificial intelligence. It assists marketing teams in selecting important subjects for SEO and competitive research.
Content generation is another application of AI in marketing. Natural language processing (NLP) is an AI technique that organizes data into a written tale that sounds like it was authored by a person. (Natural language generation is another term for this process.) NLP may be used to write articles, white papers, and social media postings, depending on the program. NLP is in common use by the most well-known and popular news organizations for generating content for both print and electronic media.
Every AI-generated story is intended to read like it was written by a human. To best serve your audience, the data insights and writing style of each tale are determined by the rules and conventions specified by your brand.
2. Creating personalized email-
Normally staff frequently devotes hours to drafting and arranging weekly emails to a variety of client groups. You can't send a tailored email to every single consumer, even if you use sophisticated subscriber segmentation. Email marketing may benefit from artificial intelligence as marketers may utilize AI to create more focused and relevant communications by using historical subscriber behavioral data.
In an email, marketers may utilize NLP technology to customize calls to action (CTAs), subject lines, and body copy. It can be used in recommendations for products and drip marketing as well. Artificial intelligence allows you to deliver personalized, selected emails to every consumer. AI-assisted emails might become even more engaging for every subscriber by evaluating a customer's reading patterns and themes of interest to offer particular information most appropriate to that person.
AI may also assist in deciding what actions clients in specific segments can do after getting a message tailored to them.
Let's begin by saying yes or no to a few straightforward questions. For instance, after sending an email:
Will the intended audience read it? Will the client read it? Will the customer choose to buy a product from the brand? Will the customer terminate the service?
3. Using AI for smart segmentation-
All marketing initiatives should include target group segmentation. It's tough to persuade a customer if you don't know who you're trying to persuade. Marketers used to create a broad aim for themselves, asking questions such as, "Do we want a greater degree of awareness, commitment, retention, revenues, or something else?" They then calculated the best target group for the campaign by hand. Marketers may now properly determine the optimal target group with AI and Predictive Analytics. The procedure is not only faster and more precise, but it can also aid in the identification of new segments of this group with similar characteristics.
Here are some examples of how AI may be used to improve consumer segmentation accuracy:
- List the qualities of your primary target audience, including who they are and what they look like.
- Use AI to go deeper into your data and discover new personality types.
- Give these personality types tailored messaging and treat them as sub-segments.
4. Use artificial intelligence to build relationships-
Detailed segmentation of the target group is a good start, but as a marketer, you must also send the correct messages at the right time through the right channels.
Email, mobile devices, desktops, laptops, and social media are all options. To maintain the proper degree of client engagement, AI may assist you in crafting optimal messages, determining their amount, and selecting channels. You may gain an impression of the target audience's preferences for interacting with your communications by analyzing the number of messages delivered to clients and comparing it to the number of active clients. Some consumer groups, for example, will not use specific channels.
All of this can be predicted with AI. A notice sent to the phone or a social media account will not convince someone unlikely to view the email. The same is true for optimizing content delivery times to reach customers when they are most likely to pay attention to your message.
In reaching your consumers wherever they are:
- Check who you're sending messages to, when you're sending them, and how you're sending them.
- Utilize your preference centers and artificial intelligence to acquire data on client preferences for communication frequency, channels, and timing.
- To compare the success of AI-optimized campaigns to past results, conduct A/B and multiple-choice testing.
5. Customer engagement and churn forecast-
Machine-learning algorithms may also assist detect disengaged client groups on the verge of churning or defecting to a rival. In this area, AI-powered solutions may assist in gathering data, developing a predictive model, and testing and validating that model on actual clients. This information might reveal the person's current churning state. While quick-churn customers (those who quit a product immediately after purchasing it) are tough to re-engage, late-churn consumers (those who have a long-term engagement with your brand) can be enticed to continue using it.
AI-powered churn prediction, when paired with targeted content production, helps keep more of your customers engaged, resulting in increased lifetime value and revenues.
Because every product and organization is different, machine-learning algorithms must be customized or constructed from the bottom up to forecast turnover. You may utilize this knowledge to produce more effective content for disengaged users.
Marketers should embrace AI as a tool to assist them in better customer segmentation, increasing consumer interaction, and leveraging dynamic content tactics to remain ahead of the competition. All of these features, as well as many more, will eventually become essential components of any marketer's arsenal.
The need for personalized consumer experiences and the type of marketing materials will develop in tandem with the expansion of the offer for consumers and the expanding options of making contact with them. That is why we believe AI will be with us for many years to come.