Artificial Intelligence is making the world go topsy-turvy with its range of benefits. It is now used in self-driving cars, computers that can help detect cancers, and homes in smart locks, thermostats, speakers, and digital assistants. Unfortunately, the ever-increasing applications of AI have also created a shortage of qualified professionals in this field. Though the schools are developing new course curricula by adding such classes and trying to develop new programs to accommodate the demand, only a few potential personnel are still trained in them.
Even brands use this technology to improve their customer base and add authenticity to their product. But before that, let’s learn what machine learning is and how it can be used. Machine Learning is a part of artificial intelligence that empowers computers to analyze data and make accurate predictions. This technology entails several tools that help brands analyze content, keywords, and phrase, which can be used to attract the target audience. Then, based on the information, the brands can create personalized content, which will further help the marketers become more efficient and effective in nearly every aspect.
Five ways brands can boost their marketing campaign
Data segmentation can take a chunk of your time if you try manually. But with the help of predictive analytics, you can trim down the guesswork, identify the user segment, and have real-time user base information that every user will get tested at each stage of their journey with you.
Help to detect the omer churn-
Machine Learning has various tools (predictive analysis, cohort analysis, customer lifetime value, churn modeling, response modeling, attrition, and modeling) that can help brands detect customer loyalty toward untowardness.
The automation has enabled brands to calculate the churn rates and subscribers who leave the business after a specified time interval. The tools also help the brands to measure customer satisfaction rate, which is a,n important benchmark for business growth and helps to keep a vigilant check on customer delight with the product on mobile. For example, with help from the machine tools, you can get reliable information about when the last time the customers signed into their profile, when did they make the last chase, did they perform research and then purchased a purchase, or whether they made an impulsive buying decision and other trends. In addition, machine Learning Tools can help to analyze the data at a large scale.
With the help of this information, the brands can predict churn and take preventive steps to
Help the brands to crack down the fake products-
Recently, a startup company used this technology to crack the whip on fake products. They made it possible through the neuro tags. These tags are algorithm algorithm-protected. One among them is open, and the other is protected. The open tag is easily visible to anyone with a smartphone and close, ed the tag can be accessed by the person who has purchased the product.
The tags are monitored and protected by the algorithm and artificial intelligence; if anyone tries to duplicate the tag, it automatically gets invalidated. Though various technologies like RFID and holograms were constructed to eliminate counterfeit products and discourage these manufacturers, none could nip the evil in the bud. Still, we have seen many cases in the pharma industry where the packaging of fake medicines rules the roost. RFID technology is not a pocket-friendly option too. But with the advent of artificial intelligence, brands easily track their products and keep a check on the counter products too.
To create the right fit for the product-
Machine learning and its tools can be used to find the perfect fit for the product. For example, one of the important goals of the business is to detect the customer and identify their needs and define their value proposition, and test the products on different customers; AI has s; AIal tools like audience segmentation and natural language processing that can be used to produce significant results.
Helps the brand to overcome overall challenges-
The brands face several challenges in the form of fraud, fraud several AI techniques that can be empathy brands can employ strong systems to avoid the mishap. The big financial corporations widely employ techniques to understand the credit default patterns of the customers, and based on that; they take remedial action. AI has an excellent feature of pattern recognition that can be helped to detect the data on how to reduce the NPA in the financial scenario.
In the end, we would like to conclude that both small and big businesses can have a sigh of relief because wit help of this technology and its tools can help in better lead management. InThseveral companies have developed bots using this technology to create personalized interactions with the customers a. These smartly look up to the data and accurately converse with the customer. This technology is completely revolutionizing the marketing area of small businesses. Other machine learning tools be used to improve customer awareness and manage customer expectations by analyzing different problems. These techniques further help the busses to make the decision-making process fast.
There is no denying that brands can use this tool to improve the sales of their business, especially where the businesses have limited resources and stricter deadlines. Apart from that, these tools help in employee engagement too. There are several tools employees communicate with HR about policies and decisions; decisions are a blessing.
About the Author
Ankit Patel is a Marketing/Project Manager at XongoLab Technologies LLP & PeppyOcean, which offers global mobile app development solutions; he loves to write about new and upcoming technology, mobile & web development, business & marketing, and programming tools.