Walt Disney was worth $1 billion in the 1960s.
Today, his company is valued at $278 billion.
The secret of his success?
Just like with many other businesses, it’s innovation.
Long gone are the days when Disney was just a traditional theme park. The company had the world’s first computer-controlled thrill ride, radio frequency identification wristbands, and, more recently, AI technology such as animatronics that interact with park guests.
No surprise companies pay attention to AI in business strategies. Entrepreneurs are investing in AI solutions to increase sales, study customer behavior, and become more efficient.
In this guide, we’ve going to talk about the juiciest AI business capabilities:
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Automating business processes
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Creating accurate forecasts (sales, demands, etc.)
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Getting consumer insights analytics.
AI-Powered Business Process Automation
Think of a task that you do at work where you have to do something repetitive. Again, and again, and again. Tiresome. Boring. Demotivating.
AI-powered applications can help businesses automate many repetitive tasks and allow people to focus on more creative things.
Example–
Creation of digital marketing campaigns.
A complete AI marketing solution can cover the entire process, from deep customer segmentation to content recommendations to match the interests of the chosen segments.
Also, machine learning (ML) algorithms can propose campaign variables such as email subject line lengths, headlines, colors, and time of delivery.
How? Natural language generation tools learn brand communication styles and generate texts and content recommendations based on historical campaign performance data.
Marketers are aware of these benefits. This survey of UK marketers revealed their expectations of using AI in email marketing.
Source: Statista
What impact could it have on email marketing campaigns? Well, personalized email subject lines are 26% more likely to be opened while businesses can increase their revenues up to 760% from segmented campaigns.
AI can free up marketers, copywriters, social media researchers, designers, and many other professionals to work on more creative tasks. By taking care of a large share of repetitive business processes, the technology also can increase the overall business efficiency and performance.
Related article: Artificial Intelligence: Fundamentals
AI and Forecasting in Business
Demand and sales forecasting are the best examples here. Two areas where AI’s predictive analytics ability really shines.
Here’s how businesses are taking advantage of this technology.
Improve Retail Demand Forecast Accuracy
Conventional retail demand forecasting systems typically use historical data. That means going through countless sales reports and spreadsheets and compiling predictions while keeping factors like seasonal variations in mind.
AI-based demand forecasting systems increase the speed and accuracy by using data from more sources than the traditional. Almost any type of digital sales document can be analyzed, which takes a lot off the sales team’s shoulders.
Example–
A machine learning algorithm can analyze a wealth of data on sales, product features, and promotional activities and find demand fluctuations based on price changes and other context-specific factors. So, businesses can find out how lowering prices can help increase revenues.
Understand the Likelihood of Hitting Sales Goals with AI Forecasting
Achieving sales and goals is fun, and AI is making it even better. Until recently, sales forecasting was more of a guessing game, but now machine learning can analyze your sales analytics for you.
AI-powered sales forecasting app:
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Collects data about your past sales, both won and lost
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Analyzes data signals like sales meetings, phone calls, emails, free account subscriptions and relates them to sales outcomes
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Predicts sales based on different sales strategies and indicators (number of calls, meetings with potential clients, etc.)
The reports generated by AI could show valuable insights for businesses. For example, a regular analysis of sales data can reveal that the company won’t be able to hit sales goals, and by how many percent.
Related article: Artificial Intelligence: Advanced Principles
AI and Business Analysis
AI greatly expands the role of business analysts by giving them access to more customer insights. Few areas are especially promising: reducing customer churn, impacting customer behavior, and improving online reputation management.
Lower Customer Churn
Customer churn is something that every business is struggling with. It’s unavoidable, so using as many resources as possible to prevent customers from leaving is a must. Business analysts have a major role–they analyze customer data manually to find factors predicting churn.
Machine learning algorithms have changed the way business analysts do their job. For example, if a company has collected 2,000 live chat transcripts from customer support, a business analyst can use an algorithm to find churn predictors.
These predictors could be specific words or phrases, which ML finds in a matter of seconds. Also, the technology does sentiment analysis, so the analysts can understand the experiences of customers better.
Impacting Customer Behavior
AI product recommendation systems are the best example. They look at data about user characteristics, online behavior, and transaction history to come up with personalized product recommendations.
Big retailers are already taking advantage of these systems. Amazon’s product recommendation engine, for example, generates 35% of the company’s $96 billion annual revenues.
Amazon product recommendation engine. Source: Amazon.com
This way, consumer data AI analysis can help to improve sales. By giving relevant product recommendations, businesses can make shopping more enjoyable for their customers.
Data scientists working with customer data analysis can also try different ways to personalize recommendations–the only limit is the customer data that a business possesses.
Improve Reputation Management
AI-powered algorithms can browse through millions of social media posts to inform brands about customer sentiment, engagement, and the overall brand reputation. A social media analyst can build an AI to capture posts, specific keywords, or images mentioning their brand.
The review of branded social media posts is also helpful to define the characteristics of the most popular content. For example, videos can attract more comments and shares than text-only posts–and you can determine why AI goes through tons of data.
The Bottom Line
AI is a part of business innovation that keeps companies competitive. With new insights, they can create more personalized marketing campaigns, automate business processes, generate sales forecasts, and adjust their strategies to engage more customers.