How Artificial Intelligence is Changing Marketing and Support
Posted: Tue Jan 21, 2025 4:52 am
According to the ComNews portal, every fourth Russian company uses artificial intelligence this year . Neural networks are used in real estate agencies, online schools and medicine. They automate routine work and save budgets because they can perform the functions of several employees from different departments.
In this article, we will tell you what tasks companies use AI for in their marketing and user support departments. And what results can be expected from implementation.
The main advantage of AI-based tools is that they store and process large amounts of data. This means that they speed up some of the tasks of a marketer or support manager and help make more informed decisions.
At the end of 2023, Avito Jobs surveyed 300 Russian companies from various industries . According to the survey results:
32% of companies plan to implement AI solutions in marketing and support processes in the near future,
35% do not plan to implement AI technologies,
20% are just beginning to identify the scope of AI technologies in their business.
Below we will tell you what tasks AI tools can be used for in different departments. Well, maybe your company is in that 20%.
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Process automation
Only 6% of companies believe that the implementation of technology and artificial intelligence does not affect their production and sales speed. The remaining 94% are confident that the implementation of AI tools helps them increase conversions and revenue.
Artificial intelligence algorithms in marketing and support are used to:
Conduct primary scoring. Companies are actively testing AI tools to evaluate marketing leads. Instead of manually parsing applications after a webinar, marketers use a primary evaluation algorithm. It sorts applications by the required criteria. At the start, a company receives hundreds of applications, and in the end - a list of the most targeted or "hot" ones. For the support department, such scoring helps determine the level of customer satisfaction and prioritize requests. AI tools
themselves help to create such an algorithm : it is enough to create a prompt, according to which the tool will compare the application with the list of criteria. This will help to minimize errors.
Transcribe interviews and recordings. Hourly recordings of custdev interviews or demonstrations of the service to a key client are converted into text in a few minutes. And additional questions to the AI help not to waste time searching for key ideas.
Forecast demand. Tools with AI and machine learning algorithms help analyze the behavior of user groups and predict their behavior, and therefore conversions and revenue. For marketing, this is a source of data for setting up marketing campaigns, and for support, it is a tool for dealing with user churn .
We left even more research and opinions in the article about the future of AI tools .
Segmentation and personalization
AI can also handle user segmentation. It will help you quickly find clients by key parameters and create a new segment.
Companies are testing different approaches to dividing the base into groups. For example, by purchase frequency in RFM analysis , product categories, response to marketing campaigns, or low activity in the personal account. AI can extract all this data from the customer base and offer a new segment for testing the hypothesis and increasing conversion.
Hence, the key trend in marketing and support over the past couple of years is targeted personalization, or hyper-personalization . Users expect individual approaches from brands and ignore generic advertising messages. But personalized content, offered at the right time and on the right channel, helps stimulate purchases and reduce churn.
Machine learning algorithms analyze customer data to offer them the right product at the right time. This is personalization at the level of a specific customer, not a segment. You can personalize newsletters, advertisements, and website content. For example, an algorithm tracks customer actions on a website to predict the likelihood of a purchase in a given session or their return to the website over time. For users who are similar to the segment of those who do not make purchases, the algorithm shows a pop-up with a limited-time discount. If the algorithm predicts that the customer will make a purchase, then the pop-up is not shown to them.
In this article, we will tell you what tasks companies use AI for in their marketing and user support departments. And what results can be expected from implementation.
The main advantage of AI-based tools is that they store and process large amounts of data. This means that they speed up some of the tasks of a marketer or support manager and help make more informed decisions.
At the end of 2023, Avito Jobs surveyed 300 Russian companies from various industries . According to the survey results:
32% of companies plan to implement AI solutions in marketing and support processes in the near future,
35% do not plan to implement AI technologies,
20% are just beginning to identify the scope of AI technologies in their business.
Below we will tell you what tasks AI tools can be used for in different departments. Well, maybe your company is in that 20%.
Automate your marketing with Carrot quest
Use the platform tools and ready-made mechanic templates to list of switzerland cell phone number conduct your first tests in 7 days and get your first applications during the free period.
Test Carrot quest
Process automation
Only 6% of companies believe that the implementation of technology and artificial intelligence does not affect their production and sales speed. The remaining 94% are confident that the implementation of AI tools helps them increase conversions and revenue.
Artificial intelligence algorithms in marketing and support are used to:
Conduct primary scoring. Companies are actively testing AI tools to evaluate marketing leads. Instead of manually parsing applications after a webinar, marketers use a primary evaluation algorithm. It sorts applications by the required criteria. At the start, a company receives hundreds of applications, and in the end - a list of the most targeted or "hot" ones. For the support department, such scoring helps determine the level of customer satisfaction and prioritize requests. AI tools
themselves help to create such an algorithm : it is enough to create a prompt, according to which the tool will compare the application with the list of criteria. This will help to minimize errors.
Transcribe interviews and recordings. Hourly recordings of custdev interviews or demonstrations of the service to a key client are converted into text in a few minutes. And additional questions to the AI help not to waste time searching for key ideas.
Forecast demand. Tools with AI and machine learning algorithms help analyze the behavior of user groups and predict their behavior, and therefore conversions and revenue. For marketing, this is a source of data for setting up marketing campaigns, and for support, it is a tool for dealing with user churn .
We left even more research and opinions in the article about the future of AI tools .
Segmentation and personalization
AI can also handle user segmentation. It will help you quickly find clients by key parameters and create a new segment.
Companies are testing different approaches to dividing the base into groups. For example, by purchase frequency in RFM analysis , product categories, response to marketing campaigns, or low activity in the personal account. AI can extract all this data from the customer base and offer a new segment for testing the hypothesis and increasing conversion.
Hence, the key trend in marketing and support over the past couple of years is targeted personalization, or hyper-personalization . Users expect individual approaches from brands and ignore generic advertising messages. But personalized content, offered at the right time and on the right channel, helps stimulate purchases and reduce churn.
Machine learning algorithms analyze customer data to offer them the right product at the right time. This is personalization at the level of a specific customer, not a segment. You can personalize newsletters, advertisements, and website content. For example, an algorithm tracks customer actions on a website to predict the likelihood of a purchase in a given session or their return to the website over time. For users who are similar to the segment of those who do not make purchases, the algorithm shows a pop-up with a limited-time discount. If the algorithm predicts that the customer will make a purchase, then the pop-up is not shown to them.