Measuring multiple contributions of marketing to overall revenue growth is becoming more real-time and accurate thanks to machine learning. According to Capgemini, three in four organizations are implementing ML to increase sales of their products and services, and over 75 percent of the companies use these technologies to enhance customer satisfaction. These technologies are used by best marketers to anticipate, understand, and act on the problems their sales prospects are trying to solve with increased clarity than any other competitor.
Using machine learning and artificial intelligence to improve your marketing
- The primary reason to add machine learning and AI to the marketing stack of enterprises is that it can make sense of a large amount of data much effectively and faster than humans.
- This procedure can use data to make predictions and identify patterns almost instantly. Effective workflow optimization and improvement of website’s UX is possible when these insights are used by marketers efficiently.
- Applying machine learning algorithms in marketing is helping enterprises to automate lead scoring and cross-channel marketing campaigns, sales forecasting, and personalization to a new level of speed and accuracy.
The following are five ways machine learning and AI can be used to revolutionize marketing currently and in the future:
1. Evaluate data sets
The first step of machine learning and AI process begins with evaluating data sets, for example, machine learning can be used to find and evaluate user activity patterns on your website. Rather than filtering through large data in your Google Analytics profile yourself, machine learning algorithms will do the job within seconds – they will identify patterns and predict future user behavior, which can be used to optimize your site.
2. Optimize and create content
Marketers require relevant and engaging content to stay connected with their audience. Artificial intelligence, which is demonstrated by a machine instead of natural intelligence, can be used by marketing teams to curate content for their existing and potential customers. For instance: -‘Phrasee’, is an AI-powered tool used for copywriting that uses machine learning algorithms to create subject lines for emails and push notifications that the technology believes will drive high ROI.
3. Increase personalization
Personalization is the latest requirement that matters for customers. Research conducted by Accenture found that over 90 percent of consumers prefer brands that prioritize their choices and provide relevant offers as a result. More than half of the customers are happy to switch if they don’t let any personalized experience. Machine learning technology lets marketers deliver personalized experiences by employing algorithms that track users’ behavior on a granular level, learn the products each customer likes, and create recommendation lists and personalized homepages.
4. Improve marketing automation
Machine learning technology can also better automate marketing efforts and improve customer engagement as a result. For instance, most of the brands send generic emails to their customers, while ML can tailor content based on customers’ search history. For SaaS companies, marketing automation tools powered by AI can evaluate much disparate and larger data sets to better segment leads. Sales representatives can further prioritize these leads that are likely to convert.
5. Utilize chatbots
Chatbots are one of the most powerful customer service technologies especially for marketers who run businesses online. Positive experiences have been reported by customers who have engaged with this tool. ML-powered chatbots automatically answer customer queries with a high rate of accuracy. This is because chatbots are designed to learn from the website’s content and existing customers’ conversations to constantly improve the answers provided. Customers probably won’t be able to differentiate if they are talking to a robot.
Machine learning can transform your marketing efforts. It is required not to rush into the process instead, understand the working of technology and so that its role in your organization will typically do more good than harm.