Machine learning has already improved effectiveness of marketing efforts in communication with customer, organization's productivity, business performance efficiency etc. but it has potential to improve marketing efforts key to business success.
In the digital age, marketers cannot succeed without automation, data analytics, AI and machine learning. This digital economy calls for implementation of various strategies and adaptability with trending technologies. But adopting these technologies without understanding its implications can have negative impact as well.
Let's understand how Machine Learning can be applied in Marketing
Machine learning help marketers in customer segmentation based on their likes, interests, preferences. Consumer has diverse need and by identifying choices and preferences on social media, machine learning generate a visual report and grouped people with similar nature and discover untapped area.
- Forecasting with Regression model
Regression technique in machine learning assist marketer in sales forecasting, optimising marketing expenditure and setting pricing strategy. ML allows marketer to predict numerical values thus in optimising different aspects in customer overall journey.
With the help of natural language processing, a machine learning system can understand probe-text or voice-based content and segregate them based on the tone and sentiments of consumer. These text classification and summarisation help marketer in extracting valuable consumer insights, feedback and reviews on company's offerings which is significant for strategic decision making. ML also assist marketer in extracting data from online news articles and other sources about marketing trends and competitors position, brand positions etc.
Marketer can build their own machine learning algorithm for news aggregation, content extraction and summarization, social media monitoring and sentiments analysis etc.
- Automated data visualization
Data analysts make use of excel and Tableau to manually create visualization but the advancement in AI and ML make this process even faster than a human do. Automated enterprise analytics solution like Qlik centralised different data sources to generated generate dashboard and valuable reports. Advance machine learning enables in clarifying marketing trends over the period and identifying customer behavioural pattern and thus taking actionable decision.
- Computer vision for brand recognition
AI-embedded computer vision is the advanced application of AI. Marketer uses machine learning powered computer vision for product recognition in user generated content and extract user feedback from unlabelled images. Also, it helps marketer to calculate immediately earned media with the help of video analysis.
So, Ai, machine leaning and its sub-field can be implemented in many use cases to enhance marketing efforts, improve business performance and thus ensure business success. Marketers cannot compete without mastering big data, analytics and other technologies but implementing these without understanding its impact can be more dangerous. Thus, to leverage the benefits of AI, ML required a thorough understanding of its impact on business outcome.