9 Ways AI Is Driving Decision-Making In Business

For any business, making the right decisions - big or small is critical for success. However, with the fast-changing context in which business decision-making occurs today, most companies need help to keep up. According to a Gartner survey, 65% of decisions are more complex now than three years ago.

In modern-day business, especially digital business, leveraging Artificial Intelligence (AI) to boost decision intelligence can help bring better business outcomes and speed up decision-making.

Some key areas where AI can make an impact for more effective and consistent outcomes are decision augmentation, decision support, and decision automation. In addition, many internal operations, such as scheduling and follow-ups, can also be managed by AI systems with little human intervention.

Nine ways AI drives better decision-making in businesses

1. Boosts CRM efficiency

Customer Relationship Management, or CRM, is call center software that helps businesses manage interactions and relationships with existing and potential customers. Research shows that sales professionals spend up to 17% of their time manually entering data, equivalent to nearly one workday every week!

By adopting a CRM, relevant data can be entered into the system to eliminate the hassle of manual data entry, effectively saving time. In addition, AI can make targeted recommendations for your sales team based on the data fed into your CRM.

In addition, AI supports your sales team's ability to sort through disparate customer databases and forecast the complete customer cycle, irrespective of their contact channel, such as emails, chatbots, etc.

While humans are prone to decision fatigue, AI-powered algorithms are engineered to process large amounts of data within minutes to provide relevant insights. Even better, they do so without the risk of exhaustion or burnout!

2. Assistance in customer support for next best actions

With the increasing role of AI in business operations, its use in customer experience (CX) also grows parallelly. A Talkdesk report suggests that 85% of CX professionals recognize the importance of AI and automation, including the risks of not leveraging their potential.

One of the critical roles of support teams is to deliver efficient customer support within the shortest time. However, if relevant data is scattered across multiple storage systems, availing the correct information at the right time becomes a huge challenge. Here's where AI-driven cognitive decision trees can come to the rescue.

Decision trees are tree-like support tools that present a clear pathway to a decision as a flowchart. They use a step-by-step guided workflow system to provide your support agents with the next best action depending on the customer's input.

Cognitive interactive decision trees software effectively empowers customer service agents. It reduces their time to sieve through overwhelming information by making contextual knowledge readily available to the agents. This way, support agents can deliver quicker and more accurate resolutions to customers, improving the agent and customer experience.

3. Strategic marketing decision-making

In today's dynamic market space, decision-making is more complex than ever. Understanding your customer's needs and pain points is challenging; aligning your product to meet those needs is another ball game altogether. This is why understanding your customer's behavior and their customer journey has become a crucial focus for every business.

By generating AI-driven algorithms, you can analyze your customer's browsing history to reflect on their search interests. Accordingly, these insights will help you create targeted and customized marketing campaigns. You can also target product recommendations and send personalized emails depending on the customer insights obtained.

4. Sentiment analysis to understand customers better

For any successful business, knowing what your customers feel about your brand and product is crucial for business success. Customer feedback can be collated from social media, surveys, product or service reviews, and more, providing direct insights about your customer's thoughts and feelings. 

However, with data increasing daily, manually tracking this feedback is impossible. So here's where AI-driven sentiment analysis can help you identify priority or urgent issues for resolution. 

Accordingly, you can route tickets to your support team for quick problem resolution. Simply put, sentiment analysis with AI can help you understand human emotions better with the help of machines.

5. Augmented analytics for reliable data

According to Gartner, augmented analytics is the next disruptive solution in the data and analytics space. Augmented analytics uses machine learning and AI to assist data preparation, analysis, and visualization to help businesses make better and faster decisions.

With meticulously analyzed and reliable data, stakeholders and decision-makers can make well-informed decisions to drive overall business efficiency. Augmented analytics allows you to track all organizational data to give you a clear picture of sales, projects, campaigns, and anything you gather data on.

With real-time data-driven insights, decision-makers can take actionable steps toward building bulletproof business strategies.

6. Biased-free performance assessment

In traditional performance assessment methods, managers are responsible for sharing reviews of their employees' performances. From rating performances to providing actionable feedback and training recommendations, managers have a lot on their plates.

The assessment process is even more taxing when managers are expected to do this for a large group of employees. This could result in decision fatigue, personal errors, or human bias.

Contrary to the traditional assessment, an AI-driven performance management system is entirely data-driven. It continuously collects data from performance management systems, eliminating the possibility of errors in the data collected. This helps managers provide objective feedback to employees.

7. Automation to boost workflow efficiency

Many businesses are automating mundane or repetitive tasks to allow employees to focus on more critical work. Using AI in automation enables companies to streamline processes, reduce costs, and boost productivity.

For instance, robotic process automation or RPA allows businesses to automate repetitive tasks such as data entry, invoice and order processing, report generation, and more that are performed manually.

Additionally, AI can analyze data and decipher customer patterns to improve your team's efficiency by streamlining workflows and eliminating time-consuming chores. 

It can predict results based on data trends, empowering organizations to choose wisely when allocating resources, managing inventories, and more. This lowers the possibility of human errors and guarantees that resources are used wisely.

8. Personalization for better CX

Using AI algorithms, customers can be divided into groups based on their actions and preferences, allowing brands to offer tailored recommendations, promotions, and customer service.

AI-powered Natural Language Processing (NLP) tools can examine customer interactions with companies, such as chats with customer support agents or reviews of products, to spot trends and learn more about their preferences.

Chatbots with AI capabilities can communicate with customers and offer tailored support based on their preferences and actions, increasing customer happiness. For example, using customer data analysis, AI can suggest tailored content to customers, such as articles or videos, based on their tastes and interests.

9. Customer journey mapping

Businesses can improve the customer experience by mapping customer journeys with AI to identify pain points and development opportunities. By proactively supporting customers and spotting possible problems before they arise, AI can lessen the likelihood of adverse experiences. In addition, by segmenting customers based on their behavior and preferences, AI enables companies to offer specialized assistance and suggestions.

AI can collect and analyze customer data from various sources, including social media, online reviews, and customer assistance interactions. Then, the customer journey can be mapped using these data's insights into consumer behavior, preferences, and pain spots.

AI can analyze customer feedback and sentiment to find areas where the customer experience needs to be improved. The customer experience can be enhanced by using this input to tailor the customer journey. Specific customer journey procedures, like customer support interactions or product recommendations, can be automated with AI. This can increase productivity and free up resources, enabling businesses to concentrate on giving customers a better experience.

Summing up

AI's unique potential in data-driven decision-making is its ability to teach itself. The more data it has to analyze, the more it learns and gets better. Unlike humans, who are prone to decision fatigue and burnout, AI does not have this problem. On the contrary, AI can power through noise and complexity to provide accurate results.

This is not to say that AI will completely replace humans in decision-making processes in the future, but rather that humans and AI have their place in the process. AI is only a tool to assist humans in providing deep insights into various aspects of a business.

AI can boost business processes such as boosting CRM efficiency, workflow automation, strategic marketing decisions, sentiment analysis, elevating customer experiences, and customer journey mapping in their day-to-day business operations to maximize productivity.

By using AI to automate more repetitive and mundane tasks, your employees now have the bandwidth to spend more time and energy on more critical and high-cognitive tasks for overall operational efficiency.

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