AI for Business Growth
Artificial intelligence is not just the future of your business — it’s a technology you should implement as soon as possible to increase your competitive advantage, profitability, customer satisfaction, and almost all business outcomes. If you’re wondering how artificial intelligence can accelerate your business growth, this article is for you. You will find many
practical examples that you can use to improve your business results.
AI in Business: Why Should You Invest in This Technology?
The importance of AI is growing, and every entrepreneur knows that digital transformation is inevitable.
PwC predicts that AI will cause the GDP to increase by up to 14.5% by 2030. The same research shows that AI could contribute as much as $15.7 trillion to the global economy.
This increasing impact of AI is caused by many business drivers such as:
- Work automation
- Reducing operating costs
- Increased productivity
- Improving customer experience and customer retention
- Boosting consumer demand
- Increased profitability
- A growing number of employees
While this last factor may seem like nonsense, there are indications that AI will increase the number of jobs.
According to the World Economic Forum, almost 85 million jobs worldwide will be replaced by AI by the year 2025. However, this new technology will help create around 97 million new ones.
More and more companies are deciding to implement AI to help them meet their business objectives. Half of the global business leaders said that their companies have already adopted AI in at least one business function. If your business isn’t one of them yet, let’s move on to specific solutions you can implement to improve your business outcome.
4 Ways AI Can Help You Achieve Desired Business Outcomes
There are many ways AI can improve a company’s business results. It all depends on the type of business, the size of the company, and the organisation’s work culture. But no matter where you apply AI, if you do it right, you will see results in a short period. Here are some examples of how AI can help your business.
- Automation of the Most Repetitive Tasks
Let’s start with something you’ve probably heard before. AI, especially machine learning-based systems, allows you to automate the most repetitive, time-consuming, and tedious tasks.
One example would be a case study of the online retailer. The company needed to find a solution that helped streamline the listing and managing of new merchandise. They wanted to automate most of the process to spend time growing inventory.
To help them, we built advanced software based on machine learning and computer vision using both image and text recognition. Our solution automates every step of the product listing process. It can auto-edit images, scan barcodes, or categorise product types. As a result, the software reduced the workload by 22%. The AI-powered system enables their employees to do more ambitious and exciting tasks and spend more time improving the business.
This type of solution can save you a lot of time, but it can also make your employees more engaged and happy at work. Their work will no longer be boring and monotonous, which can help improve employee retention and reduce turnover in the company.
- Increased Revenue From a Recommender System
Did you know that Netflix’s recommendation engine is worth $1 billion per year? According to the Netflix team, “consumer research suggests that a typical Netflix member loses interest after perhaps 60 to 90 seconds of choosing, having reviewed 10 to 20 titles on one or two screens. The user either finds something of interest or the risk of the user abandoning our service increases substantially.” Netflix executives think they could lose at least $1 billion yearly if their subscribers don’t get a proper recommendation.
Netflix’s case is just one of many examples that shows the importance of a recommendation system on business outcomes.
Without recommender systems, the e-commerce industry practically wouldn’t exist today. So let’s talk about another giant: Amazon. Did you know that hyper-personalized product recommendations account for as much as 35% of the company revenue?
If you’ve browsed their site, you may have noticed the different ways they recommend products:
“Your recommendations” — various products from different categories recommended for you. They are the offers you’ve been browsing before, increasing the possibility of your click and buy.
“Frequently bought together” — suggestions based on the products you are browsing that lead to an increased order amount. For example, if you are looking at a smartphone screen protector, the recommendation will show you cases, headphones, or other accessories compatible with that product.
“Your recently viewed items and featured recommendations” — similar offers to ones you’ve browsed before to get you a choice and help you find an item you may be interested in.
“Browsing history” — a list of products you’ve browsed in the past.
“There is a newer version of this item” — a recommendation to check out the listing of a more upscale version of the product you’re looking at.
These recommendations and others are based on a database analysis of your browsing history, other users’ preferences, product information, buying patterns, etc.
Another exciting way to recommend products is through personalised email marketing campaigns based on users’ buying patterns interested in a similar outcome. Such messages sent by Amazon are usually based on a person’s browsing history and recommend a list of similar products that you may be interested in. For example, if you’ve recently been browsing for a MacBook, you may receive a list of Apple’s most popular laptops in the first email. In the second email, Amazon will send you recommendations of popular third-party laptops that you might like.
These strategies significantly improve the marketing team’s key performance indicators and overall sales.
- More Informed and Data-Based Decision Making
Artificial intelligence can extract business value from data. More than half (54%) of company executives admit that artificial intelligence significantly impacts the decision-making process.
By analysing data on customer behaviour or market trends, you can make more informed and data-driven business decisions based on facts, not hunches. Surely you’ve heard about predictive analytics. It’s a powerful technology that allows you to plan your marketing or sales roadmap and set KPIs or business metrics. Based on advanced statistical algorithms, millions of pieces of relevant information are analysed in real-time to help you make the best decision for your business.
For example, an AI-driven system can be integrated into a CRM, enabling sales teams to automatically generate valuable information, such as which customers will bring the company the most profit and which are most likely to churn. Armed with this knowledge, salespeople can focus their time and energy where it matters most.
Moreover, AI-driven decisions can be made automatically by the system and, thus, support the employees’ work. A great example of this is using predictive analytics in the retail industry. The global leaders in this sector implement AI in crucial parts of the value chain, and regional companies follow them. The benefits include marked improvements in forecasting, inventory management, and efficiency. Companies can use AI to predict trends, optimise logistics operations, set pricing, and offer personalised promotions. Some can even forecast customer needs, sending their products without waiting for order confirmation. All stakeholders can benefit from this solution.
- A Better Understanding of Customer Needs and Satisfaction
Computer vision is one of the fastest-growing elements of AI. A widespread application of this technology is face recognition in smartphones or face filters used by social networking applications.
What business outcome improvements can computer vision bring to your company? For starters, computer vision can help you sort products or categorise documents. It can save time by sorting through invoices or other documents — even collected in paper form. But we’d like to focus on a less obvious use of computer vision: helping you understand customer needs and improve customer engagement.
Computer vision can provide customer emotion analysis. An interesting example is a study conducted by researchers from Ibn Tofail University. They used a facial expression classification that identifies various smiles, frowns, eyebrow raises, and more to predict the decision-making by customers. They used a database that contains 213 images of facial expressions of 10 Japanese female models.
Their study shows that this information can predict the customer’s preferences for products. According to the researchers, this technology can be applied, for example, in virtual stores. They mentioned that a company used eye gaze detection to find their customers’ point of gaze and then detect which products draw their attention.
At first, they collected data from a video camera. Afterwards, the system processed the data of face and emotion detection. Finally, it analysed and found emotions that generate business values.
What does it mean for your business?
It means that computer vision can help marketers determine the needs and satisfaction of consumers with face expression analysis. It can optimise the effectiveness of advertising campaigns and achieve desired business outcomes. According to the researchers, the critical value for the enterprise can be extracting business intelligence about how consumers perceive the product.
Using computer vision in this way is rather innovative. However, considering the dynamic pace of development of this field, we can be sure that it will already be widely used in a few years.
Ready to Improve Your Business Outcomes With AI?
There are plenty of ways AI can improve your business. Choose the best one for your needs and enjoy the benefits of this fantastic technology. Please schedule a consultation with our AI experts and find the solution to help you achieve your desired business outcomes.