8 Things You Can Improve Immediately with the Adoption of Artificial Intelligence & Machine Learning

Artificial Intelligence

According to Allied Market Research, the value of the global artificial intelligence market will surpass $169 billion by 2025. By then, the effects of machine learning and AI technology will be felt in virtually all industries. Businesses have invested heavily in research to unlock the possibilities presented by AI and Machine Learning. Not all projects will be successful. MD Anderson Cancer Center famously stopped an AI-assisted cancer-treatment project after it had used $67 million without becoming viable.

More money will go into artificial intelligence and machine learning research around the world. However, there is already so much AI and ML can do for businesses today. If your business is looking to leverage these technologies, here are X things artificial intelligence and machine learning can improve immediately.

1. Improve Revenue through User Recommendation Systems

If your business runs an e-commerce website with tens or hundreds of products, an AI-powered recommendation system can help boost revenue. Recommendation systems display products to visitors based on their needs. The needs are predicted through an algorithm whose input includes past purchases, search history, browsing behavior, age, and so forth. By showing them products that fit their needs, your business increases the conversion rate from visitors. It also improves user experience, which increases the chances of visiting the website again or even recommending it to others.

2. AI-driven Chatbots

Chatbots have been a major iteration in the advancement of user interfaces. Today, artificial intelligence chatbots can have a natural conversation with web visitors. The ability to recognize and understand text means they can solve common problems such as locating information on the website, setting up tickets with the customer-service team, canceling and renewing subscriptions, and so forth. Chatbots reduce the average time to solve problems, which is a big plus for customers.

Chatbots can be implemented on websites and mobile applications too. In both cases, they increase a brand’s engagement with customers, which then provides the opportunity to showcase highly personalized offers to them.

3. Improving Content Marketing through Artificial Intelligence and Machine Learning

How does your brand decide on the content to create? AI systems today can analyze data from online conversations and other sources to recommend the best content to create. For instance, should you be writing case studies or blog posts? What types of videos will do well for your lead generations?  AI systems can also predict which channels will yield the best results.

Data-backed content decisions lead to a higher return on content creation efforts and your content team will realize the best keywords to target at a given point in time.

4. Sentiment Analysis on Social Media

Brands today need to constantly monitor their mentions on social media. It helps to quickly identify trends or concerns people may have about the brand or its products. Fortunately, through AI listening tools, it’s possible to keep a track on people’s feelings about a brand. These tools can aggregate large volumes of unstructured data and give an analysis of sentiment. Certain keywords are associated with satisfaction and vice-versa.

Besides satisfaction, it’s possible to identify trends and respond appropriately. Keeping track of the conversations that consumers are having allows a brand to see how people interact with products. This informs the future developments of the products and innovations around it. Your company can monitor millions of pages from blogs to Twitter to help develop those conclusions.  

5. Making More Accurate Sales Forecasts

AI algorithms can take input from numerous sources of structured and unstructured data to make predictions about the sales of your company. Common inputs include CRM data, sales history from previous years, and competitors’ actions. These predictions inform decisions, such as production and stocking, for a company to help avoid unnecessary opportunity and overstocking costs.

Using analytics on sales data also helps reveal underlying reasons for trends in revenue. A good example would show the effect of an aggressive campaign by a direct competitor. Your business could make an informed decision on how to respond to such a problem. The questions to be asked would be how much revenue has been affected and which type of customers have been swayed. An informed decision with the right messaging would then be implemented.

6. Pricing Decisions through Artificial Intelligence

Your company can leverage artificial intelligence to make optimal pricing decisions with certain goals in mind. The goal might be to expand market share, maintain it, or maximize revenue. Optimal pricing algorithms take in various variables such as time of the year, past price history, your brand reputation, and competitor strength. These algorithms are helpful when your product is available on multiple platforms and markets. You can make objective decisions for each avenue of distribution.

7. Customer Churn Modeling

If your business generates sufficient data, you can build machine learning models to predict the likelihood of customers abandoning your business. This information could be based on clues that your business can use to gauge loyalty. The algorithm can reveal the reasons behind customer dissatisfaction, which helps take action. If a customer is perhaps unhappy with a price bump on a service, a personalized offer or add-on might incentivize them to stay. This approach is common in the SaaS service sector and content streaming services, where when customers cancel subscriptions, they get an offer to get them to reactivate.

8. Fraud Detection through Artificial Intelligence and Machine Learning Models

If your business handles thousands of customer transactions every day, chances are that you are susceptible to fraud attempts. You can use artificial intelligence and machine learning technology to detect anomalous transactions. Companies in the retail and financial services sectors benefit the most from such an application. The large volume of transactions makes it impossible to check every transaction for legitimacy. However, a model for detecting risky transactions reduces the sample size for investigation.

Where Should You Begin?

Where should your company leverage artificial intelligence and machine learning? As long as you generate and can collect data from operations, there are opportunities to turn that data into useful insights. It’s best to take advantage of easy opportunities and automate routine office activities such as processing invoices and sorting emails through importance or urgency. Afterward, there will be higher-level opportunities to take advantage of.

If your organization is agonizing over how to leverage its data, Transcendent Software can help collect, clean, organize and use data to drive efficiency. We can build and operationalize artificial intelligence and machine learning-driven technologies at your company. To learn more, get in touch with us for a consultation.