The developments in the area of science and technology are constantly changing the business world. As a business owner and an entrepreneur, one needs to gather a better understanding of the technology which goes way beyond the simple smartphone release.
Today people are increasingly talking about artificial intelligence and machine learning. So, what is this and how can it affect the business? Let’s look ahead to find out how these tools can help marketers and businesses to grow and develop.
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Artificial intelligence and machine learning: A conceptual clarity
The terms artificial intelligence and machine learning have been often used interchangeably. But in reality, they are not said to be the same. Actually, artificial intelligence consists of a broader meaning. Artificial intelligence is the idea that machines and computers can complete the tasks that normally require human intelligence to be accomplished.
The theory of Machine learning is said to be a branch of the concept of AI. Machine Learning automates the model building for the purpose of data analysis. The idea behind machine learning is believed that a computer has the potential to learn from the data which it analyzes with the help of identifying patterns. In the end, this technology is able to make decisions without any human assistance.
Machine Learning for the Marketers: Establishing the connection
In the present situation, marketers have been already using machine learning technology for the purpose of assistance in improving their marketing programs and increasing their revenue by optimizing their customer experience.
If a marketer or an entrepreneur does not have control over the marketing pulse, then the business could fall behind the competitors. Even if a company is not ready to implement the technology of machine learning into its business marketing strategy currently, they have to be prepared to do the same in the near future.
Below mentioned are the best 5 ways through which machine learning is reshaping the marketing strategy of modern-day businesses.
1. Better lead scoring accuracy
Lead scoring enables us to rank the prospective customers on a scale that is representing their value to the company. Improving the lead scoring accuracy would help the organization prioritize lead-generation strategies.
In present times, marketing professionals don’t possess the highest level of confidence in their lead-scoring method. But once marketer embraces machine learning marketing into their system, their confidence levels should definitely increase. This is because many of factors go into doing such calculations, and machine learning can help the organization to make them.
Marketers can use machine learning in order to monitor customer behavior. There are algorithms that are written in order to track the aspects such as emails opened, websites visited, Number of clicks and downloads
The consumer’s social score is even an important factor for consideration as well. These feature monitors and even analyzes the way how a user behaves on social networking sites, e.g.:
- The accounts that they follow
- The posts that they like
- The ads that they engage with
Using machine learning technology to qualify prospects is assisting businesses to create more accurate customer profiles, thus improving their marketing strategy.
2. Better predictions of customer churn
The concept of customer churn is also termed customer turnover. They identify the number of customers who have ended their relationship with the company’s business. For the SaaS business, it happens when a customer cancels the service or they unsubscribe from the membership.
The Churn rates have been calculated on the basis of the percentage of customers or subscribers who leave the business within a specific period of time. For an organization to develop and grow, the number of new customers must be greater than its churn rate.
An organization needs to know what the churn rate of their company is, to know how satisfied customers are with the product or service. And it also needs to be able to predict the churn rate so as to reduce it to the bare minimum possible. In order to predict the churn rate, an organization needs to monitor customer behavior.
There is a machine learning discovery model which can make predictions depending on the certain behaviors of the customers. This Machine learning helps to analyze the data on a much bigger scale and gives the marketers information to predict churn as well as prevent it.
3. Beneficial dynamic pricing models
The dynamic pricing strategy lets businesses offer a variety of flexible prices for the products and services they offer. This is a common model in the industries of hospitality, travel and tourism, and the entertainment sector.
With the help of machine learning and AI, a dynamic pricing strategy is able to penetrate the retail industry as well. Generally, this pricing strategy helps to segment the prices based on the customer’s taste and preferences.
The Dynamic pricing concept is even related to real-time pricing, which is when the value of the goods is based on certain market conditions. The sale of an airline ticket is a good example. Fixing the right prices is important for the success of the business.
One can easily generate more and more profits by just focusing on their pricing strategy. Machine learning helps to use regression techniques in order to make market predictions.
4. Analysis of sentiment
The current businesses are not having a large number of face-to-face interactions with the consumers as they’re reaching out to the businesses via online modes. When the customer sends the company an email or a direct message, the business marketer needs to know how the customer is feeling in order to respond appropriately.
Machine learning can do it for the company. The AI technology can easily analyze the text in order to determine whether the sentiment of the message sent to the business by the customer is either positive or negative. The information from the sentiment analysis is currently being used by marketers in order to better understand the company’s online reputation.
5. Enhanced website experiments
A/B testing is considered to be a great technique in order to improve the features of the company’s website, mobile app, as well as email marketing content. While the A/B tests will ultimately give the results to optimize a website, there are some downsides to this method. In order to get to the desired, the company might miss out on some opportunities. Machine learning can help a company in solving this problem by improving its bandit testing.
With the help of bandit testing, a solution with the greatest value gets prioritized. An algorithm of such a test will minimize the missed opportunities and thus make the experiments more beneficial.
Machine Learning and AI technology together can make up a great pair for the purpose of marketing and analysis for the purpose of an enhanced level of service to the customers of the business. It is only when they are used together do, they offer the desired results. They can be used separately but the result may vary depending on the situation and the task at hand.
Thus, it can be seen that Artificial intelligence is definitely here to stay, and it is not going anywhere else. Marketers have already been using machine learning technology in order to change the way that they operate. If a business is aware of how to use machine learning to its advantage, then it can be an extremely valuable tool for the growth of the business.
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