Three Ways in Which AI is Transforming Marketing

Three Ways in Which AI is Transforming Marketing

Marketing is arguably the most crucial part of selling products and services by creating awareness and intent among the right customers. Although traditional marketing strategies continue to show success, competition and growing demand for personalized and relevant experiences limit the overall potential of conventional marketing. 

Optimizing resources, strategies, and experiences to convert visitors into customers using conversational artificial intelligence (AI) techniques for marketing is vital for business success. AI helps extract the insights from the dataset and allows organizations to give a more personalized experience. They use customer behavioral data and statistics to optimize the conversion. The insights and leads from the dataset are based on potential customer behavior and statistical parameters, such as duration of engagement, timestamps of visits, and actions of interest.

AI has transformed traditional marketing techniques in three ways, which can be used in marketing strategies.

Audience segmentation

The data points in customer behavioral parameters such as engagement with conversational AI and the peak times of action allow the proper segmentation of the audience, which fits the potential customer database for a particular product or service. The precise segmentation of the audience saves many resources for a company by targeting the correct users. The AI classification algorithms such as Support Vector Machine, K Neighbours Classifier, and Neural Networks can accurately segment the audience data points. 

Example:

Classification of the audience as active or passive based on the actions taken by them can help companies invest fewer resources in the active audience. It results in a high return on investment, as companies don't overspend their resources on active audiences.

Advanced analytics

Information extraction out of raw data through analyses and visualizations helps understand the structure and statistical insights of the dataset used for developing marketing strategies. Additionally, such analyses also act as a feedback system to evaluate if the previously implemented marketing strategies perform well. Other techniques such as competitor analysis and product campaign analysis also provide insights for an optimized marketing technique. 

Analyzing customer behavior through AI feature extraction from a dataset is a proven way for customer analytics. These features can further be trained on various AI models to solve regression- and classification-based problems, depending on the marketing objectives.

Regression models evaluate the predicted value concerning the given input features. 

Example:

If you need to predict the peak time of audience engagement in a day depending on input features, a regression model can help point out different peak times for different audiences. Targeting an audience group at a predicted peak time increases the chances of conversion. 

Optimized targeting

Optimized targeting is a successive technique since precise audience segmentation and advanced analytics target potential customers. Hence, AI automation methods such as automated email marketing and target advertising based on customer interests enhance the conversion rate of potential customers.

Recommendation engines on the online business portals are also optimized targeting methods. The recommendation algorithms work on the historical data of the visitors to analyze their interests and behavior for recommending the correct product or service to them. Lead generated in customer contact details opens an opportunity to convert a potential customer into an actual customer. 

Example:

If a visitor actively engages with formal shirts, the website should not recommend casual or funky T-shirts to the same visitor. Instead, the visitor should be recommended formal accessories such as shoes, ties, and watches. AI uses item-based collaborative filtering or user-based collaborative filtering to handle these recommendations.

Conclusion

These AI techniques or algorithms are customized for specific business cases. Customization helps obtain higher accuracy and generalization of models. 

Cogent Infotech can help you set up these methods around your business for optimized marketing strategies. You can book a consultation meeting with the AI research experts of Cogent Infotech for more information related to AI in marketing.