Why Businesses Should Integrate Their Apps with Machine Learning?

A technology that vows to bring massive changes to the data led world is Machine Learning. Apps integrated with Machine Learning are entering our everyday lives and delivering smarter mobile-centric solutions.

ML makes mobile platforms more user-friendly, improves the customer experience, maintains customer loyalty, and aids in building consistent omnichannel experiences.

In this article, we discuss the seven most lucrative use cases of machine learning for small businesses. Let’s take a closer look at how integrating Machine Learning tools can enrich small businesses:

1. Gives a Personalized Touch

With the continual learning process of ML, small businesses can serve the most customized options for their users by analyzing the revealed data from their behavior. Based on the information collected, you can classify your customer and apply an individual approach to each customer group.

With Machine Learning you can interpret:

• Who your customers are
• What they desire
• What they can afford
• What hobbies, preferences, and pain points they have
• What words they’re using to talk about your products

Machine Learning lets you provide users with the most relevant and enticing content and convey the impression that your app is talking to them.

2. Enhanced Search Experience

Machine Learning solutions let you optimize searches in your app, adapt the tone of your content, and provide the most relevant and enticing information to your users. Thus the searching process for users becomes more comfortable and less burdensome.

The latest apps allow you to collect data about your customers from search histories and common actions to rank products and services. Hence, come up with the most relevant search results.

Machine learning algorithms learn from customers’ queries and prioritize the results that matter the most to a particular person. Cognitive technology also helps to group articles, DIY videos, FAQs, documents, and scripts into a knowledge graph to provide smarter self-service and immediate answers.

3. Visual and Auto Recognition

With the data world progressing at high speed, providing a creative and pleasant user experience has gained even more importance. Through neural networks, apps integrated with ML tools recognize different words for enabling translation and detect various faces.  

Machine intelligence allows businesses to enhance the app with a built-in translator, as machine learning supports real-time speech translation. Thus, customers can successfully communicate within the app without third-party online translators.

Chatty AI assistants that can cheer customers up and hold conversations at 2 a.m. are examples of ML tools that are used to entertain customers. This is largely helpful in making the experience seamless and less time-consuming for the end users and to keep the users engaged.

4. Deep User Engagement

Machine learning tools empower small businesses to offer solid customer support, a range of advanced features, and entertainment that provides customers with an incentive to use your app on a daily basis.

Small businesses should integrate ML tools at the initial stage itself so that they are ready for the heavy traffic and customer engagement at the later stage. Machine learning systems can quickly analyse large sets of data and make decisions in real time.

Popular app Snapchat uses machine learning and augmented reality to let customers revamp their pictures with funky filters. The app’s camera detects a customer’s face, localizes the facial features, and adds filters responsively.

5. High Level of Security Standards

Apart from being a useful marketing tool, machine learning can also serve as a valuable security tool. Machine learning helps identify if your app is vulnerable to security threats and thus helps in preventing frauds. The analysis of GPS traces and usage patterns through ML tools assist a great deal in uncovering various suspicious activities.

With Machine Learning, small businesses can also implement ongoing app monitoring, eliminating the need for constant control. It aids in determining access rights to the customers and detect and ban any suspicious activity taking place.

Machine Learning systems can shield your customers from previously unknown malware attacks in real time, whereas traditional apps can resist only known threats.

6. Predict User Behaviour

Small businesses can understand a user’s preferences and behavior patterns through machine learning applications and scrutinize different kinds of data:

• Age
• Gender
• Location
• Search Requests

This data is useful to improve the performance and effectiveness of your app and keep the user hooked to your app. ML integrated apps can also generate individualized recommendations that keep the customer engaged and increase the time spent on your app.

For example; you find out that males under the age of 40 actively use your app more than females. Based on this knowledge, you may either take action to attract a female audience or target your entire marketing campaign at men.

7. Optimized Ads Delivery

The tricky part of advertising is directing the right kind of ads towards the right audience. Machine learning helps to generate ads drawing on data about each customer’s unique interests and buying propensities.

With Machine Learning technology, small businesses can predict how a customer will react to a given promotion and thus can display ads to only those customers with a higher rate of interest in the displayed product.

Target display advertisements and personalized messaging can be more accurately managed by integrating ML technologies, and marketers can avoid tiring customers by showing ads of products they have just bought.

 

Summing Up

Developing a mobile application and integrating it with ML technology can help small businesses get an edge over their competitors and expand their client base starting from their initial phase.

Artificial intelligence and machine learning technology have the potential to revolutionize marketing, and most businesses have already adopted this technology.

If you wish to build an app that creates real value for your customers, Machine Learning can be a safe bet to embed, to contribute towards your goal.