


Use artificial intelligence to personalize and optimize interactions with customers
Artificial Intelligence (AI) is revolutionizing how marketers and customer-facing business sectors engage and interact with customers. In fact, in today’s competitive world, data science is helping to rewrite business dynamics as it can personalize the customer journey with precision that was not possible before. Today, the future of every company is tied to the customer journey. Research shows that 88% of U.S. marketers report measurable improvements from personalization, and 44% of consumers say they become repeat customers after a company personalizes their shopping experience. What’s more, businesses see an average 20% increase in sales when using personalized AI experiences.
In fact, customer personalization is not limited to selling products or services to customers. It must transcend. Highly personalized customer service can help brands exceed customer expectations, resulting in higher Net Promoter Scores (NPS). This will help reduce customer churn and increase sales/cross-sell opportunities. For personalization to be effective, it requires systematic and ongoing effort and the participation of all team members. To be successful, you must invest in data, technology and people.
How Artificial Intelligence Can Help
Personalized AI can help businesses improve customer experience, increase sales and revenue, and improve their marketing efforts. We recommend four main initiatives for you to deploy artificial intelligence and data science into personalization:
(1)Customer login
Use the help of algorithms to engage customers in the initial stage for long-term use With your product or service, you can improve retention rates, increase referrals, and reduce abandonment rates.
(2) Next best action calculation
By using a dynamic decision-making strategy that uses all customer data to find the best next action for (potential) customers, you can improve your customers’ Satisfaction, leading to higher conversion rates and revenue.
(3) Cross-sell and up-sell of products/services
By recommending products or services that suit users’ interests, you can increase the likelihood of users purchasing, thereby increasing revenue.
(4) Churn prediction and prevention
Based on dynamically calculating the percentage of exiting customers within a predefined time interval and deploying prevention strategies to prevent churn, you can ensure a close relationship with customers and revenue Long-term relationship.
The impact of deploying personalized AI can be measured by:
- Improving overall revenue and revenue per customer - up to 25%.
- Higher product and service conversion rates - up to 20%.
- Higher Marketing ROI - 2x to 3x.
- Higher customer satisfaction – significant improvements.
- Lower churn rate - up to 30%.
- Improve customer experience and brand experience.
*Please note that the benchmarks and numbers mentioned in the article are based on DAINStudios’ internal research and client projects.
Industries Benefiting from Personalized AI
While personalized AI can benefit a wide range of industries, including e-commerce, consumer and industrial goods manufacturing, retail, finance, healthcare, and more, But specific applications will vary based on individual business needs and goals.
For example, manufacturers and retailers can interact directly with consumers and use artificial intelligence to understand customer needs and recommend products based on their browsing and purchase history, thereby increasing overall basket value.
In the healthcare industry, personalized AI can be used to provide personalized services, such as providing information or assistance tailored to customer needs. In the financial industry, personalized AI can be used to provide personalized financial advice and recommendations, for example by analyzing a customer's financial history and providing recommendations on investment or savings options.
Starting the journey of artificial intelligence
Starting the journey of personalized artificial intelligence means preparing the business to be data-driven. While all of the following steps are important, none of them work without data.
Getting data to build a machine learning model means bringing the data together and activating it. Centralizing data will help bring all data to one location in a high-quality manner, such as CDP. Activating data means taking action on the output of machine learning models to gain real, tangible value for customers and the business. There are also activities that businesses need to focus on:
?Determine the specific goals the company hopes to achieve with personalized AI. This can include goals such as improving customer experience, increasing sales and revenue, or improving marketing efforts.
?Collect and activate the data of the company's customers. This may include data about their preferences, behavior and interests. This data can be used to train personalized artificial intelligence and provide personalized experiences to individual customers.
? Select and implement a personalized AI platform that fits your company’s needs and goals. The specific platform or tool will depend on the company’s needs and goals, and integrating personalized AI with the company’s existing systems and processes, such as a customer relationship management (CRM) system or marketing automation tool, will be key to success.
?Monitor and evaluate the performance of personalized artificial intelligence to ensure that it achieves its intended goals and objectives. This may involve tracking key metrics such as customer satisfaction or sales revenue and making adjustments as needed to improve the performance of personalized AI.
Making the impossible possible
Overall, the real benefit of using artificial intelligence and machine learning in marketing, sales, and customer service is making the impossible possible. Calculate optimal results faster in complex environments, detect patterns, and optimize particle behavior invisible to the human eye. Personalized AI is a game changer and competitive necessity for any business today.
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