Marketing automation has become far – just a tool for marketers to automate recurring tasks to recognize demanding customers.
The advancement of technology in this area has increased marketers to use customer data to reduce key understandings and to program programming programming that is delivered at the right time and on the right channels. It’s no wonder that the $ 5.5 billion industry will be in 2019.
Here are three examples of how to understand the marketing automation process to make life easier.
Identify patterns in data for hyper adjustment.
“Personalization” is a term used extensively, but has since become a very important meaning.
Do not blame me; I do not recommend that you need to stop identifying online shopping and marketing orders. What I recommend is to focus on hyper adjustment.
Marketing Automation with Learning Machine (ML) allows you to create a customer experience with historical interactions, such as buying habits, behavioral behavior and digital choice. But it does not take into account customer intentions.
In-depth technology technology, on the other hand, not only depends on the history of customer interaction but will consider its purpose.
For example, customers come to your site and get rich. During another visit, customers began checking their shoes.
In this scenario, similarities will not depend on transactional data and interactions to create personal experiences, but will consider its purpose.
Learning is far better than other ML and AI techniques to find out what customers are looking for because they have the potential to look for patterns in patterns.
According to Michio Kaku, AI is just as smart as a “lobotomized cockroach, mental addiction.” Processing techniques recognize and analyze patterns to predict actual activity. not seen yet.
Use in-depth learning to prevent customer retention.
Every business knows that customers can still be less profitable. And, customer retention can increase the company’s profits by manifold.
According to Bain and Co., a 5 percent increase in customer retention may increase the company’s profit by 75 percent. When it comes to improving customer retention, deep inclination can help.
How? By giving the customer what you need, when you need it. According to the Trendspotter report, 82 per cent of people will walk in stores offering personal offers.
Marketing automation accompanied by AI does the same by getting the right message to the right person at the right time.
But in-depth study may take much higher. It takes advantage of customers, personal preferences, spending patterns as well as micro options combined with external factors, such as weather, provide great advice and relevance to customers.
Customer behavior as science: Data analysis is large and in-depth.
Prescriptive anatomy is another technique that uses in-depth study of customer data to predict future patterns and patterns of behavior.
The marketing automation platform has been strong enough to expect predictions – as when customers will make their next purchase, what LTV customers, who are the most valuable customers, the time customers are buying, and what the right discounts are offered to customers.
In-depth learning is used in the advertising industry to produce 50 percent more efficient activity.
So many super marketers are excited about it.
However, in-depth study is not as easy as possible. Living as a marketer, it’s important to know how it works and how it can be used to benefit you. Marketers who try to fit the user should pay attention to technology.