This article is from our Q&N session, “Machine Learning in Marketing and sales” which is asked many times on different platforms. How can machine learning be useful in marketing?
Changes in technology every day are exaggerated day by day. There is an undisclosed thing. If you are in the domain or field of marketing then you must have knowledge and understanding of this technology. You heard many times Artificial Intelligence (AI) term but its interlink with Machine Learning (ML) but both are not the same things.
In simple words, Artificial Intelligence (AI) is a wide field they mean Machines and Computers perform human work with efficiency. Like Automated Data Entry work etc. On another side Machine Learning (ML) is a sub-branch of Artificial Intelligence (AI), which is used for model automation and data analysis.
The main idea is that the Computer can analyze the data and train the model. Make a future decision with humans and any effort.
The truth is that many marketers are already using these technologies and improve business growth. Like Digitial Marketing, Market Campain, Revenue Management, Risk Analysis, and many more. If you are not ready to implement today then you go behind than your competitors. But in the future, you need to know about “How can machine learning be useful in marketing”.
In this article, I’ll explain the Top 5 ways or Solutions they can help in marketing using machine learning.
Customer Behavior Analysis
As a marketer, you know that the Customer is everything. So if you entertain customers in will manner then your sales are bosted. Machine learning is involved in marketing and sales as well. You can monitor customer’s behavior and do analysis on them. There are many ways and focus on following these points. You can write a machine learning algorithm for Customer Behavior Analysis.
- How Many users visited your website. For analysis, you can filter out on Location, Platform, and medium, etc. Google Analytics is the best example of this task.
- You can also check How many Customers or users have opened our emails. It will help your target audience.
- How many Clicks & Downloads your product, it will boost your sale and you can focus on Top Trending products.
- Observation of Customer Social Behavior. Customer trends in social media, which competitor product has larger engagements, No of likes and shares, etc.
Dynamic Pricing through Machine Learning
In the marketing field, dynamic pricing is an approach to offer stretchy or flexible prices to customers. It’s very common in specific fields like (Travel, Tour, and performing industries). Using machine learning you can apply this strategy in the retail industry as well. Basically, this approach will be help full in section or segment-based prices.
There are many real-time examples that are suitable for this environment. Buying a ticket for the airline is one of the best fil of this. The cost of a ticket is dependent on Fare History, Number of the previous buying, choice of seat, location on country, route and peak days, etc.
This is not a new thing in marketing but machine learning helps companies for implementing this model. Using Regression technique to enable market prediction. It is also helpful for sales estimating and forecasting. This forecasting enhances the price structure based on past experiences.
Sentiment Analysis
Wherever you are involved in real-time conversation with someone else, it’s easy to understand things because you are talking face to face. From less talk, you understand more because of the involvement of body language, tone, and expressions.
As a resultant, you have knowledge of how much anyone satisfied with you or disagreed with you. But nowadays the trend is Digital Communication and sometimes you are missing to get actual understanding.
The customer reached us using Online medium and not face-to-face interaction is available. When the customer sends an email or any message, it’s very hard to get an idea about sentiments but machine learning can do it with high accuracy.
AI & ML can examine the text and tells the sentiment in the form of positive or negative. It’s mean happy or unhappy.
The marketers use the Sentiment Analysis technique to know about the reputation of the business in the online community. It also helps to a better understanding of the product’s popularity. You can also use machine learning to read customers’ emotions and social media trends. In 2020 this field is very popular.
Targeted Advertising & Customer Personalization
Machine learning can be very helpful for marketers when they target ads. The results are more efficient. Without technology maybe your ads are good but they are not hitting the right audience. With the help of artificial intelligence and ML, you can find the right viewer and good interaction with your ads.
The prediction based algorithms can forecast your product content type and popularity of your product in which customers have. The unique user can find for your product or service. You can also apply the filter as per your choice
- Age: 25-50 (Specify Your Product. Is it Adult Product? )
- Location: New York City (Maybe you can deliver only specific locations.)
- Gender: Male/Female (Is your product is related to Makeup?)
- Language: English/French (Is your support available in only English?)
Chatbots
Web-based live chat can increase by 90% plus customer satisfaction rate. Recent studies tell that if you have online chat then 60% of customers have return frequency.
A chatbot is a system based on artificial intelligence that you have not required any physical human. The computer automatically understands queries and respond at the same time.
You can also integrate Facebook chatbot on your website.
There are some eye-catching features of chatbots. Have a look.
- Much improvement in existing online support system through chatbots.
- Chatbots analyze user messages and can judge the mood using sentiment analysis which is discussed in the upper section.
- Chatbots can reduce your traditional support queue time and wait.
- Customers can stay longer on your page.
- At the same time issue can be resolved.
- 24 X 7 is available.
Conclusion
Machine learning does not end in the future, it’s increases day-by-day. Marketers already use this in his domain and you can also.
If your company is not active and not ready for implementation then you must aware of this technology. Job is temporary knowledge is permanent.
If you have a grip on this you can use it in inter disciplines. Like you can use this Machine learning in marketing and sales and Machine learning in marketing automation etc.
You have an excellent opportunity if you want to gain “64 FREE Online Courses offering by Harvard University”
I hope you have a better understanding to “How can machine learning be useful in marketing?”