How Artificial Intelligence applied to CRM improves customer experience

Companies are increasingly aware of the importance of properly analyzing and managing the huge amount of data they store on a daily basis to ensure their productivity. Therefore, companies are obliged to build a "healthy data culture" if they want not only to grow, but also to survive the market and their own competition.

In this regard, the Artificial Intelligence applied to a company's CRM helps to understand and interpret the information collected, obtaining a complete real-time view of all the company's interactions with its current and potential customers. The goal is to create stronger and more effective relationships at every stage of the customer interaction process.. This translates into a smooth and fast relationship between the brand and the customer that will increase productivity, company revenues and customer satisfaction and loyalty.

Because the main challenge for any company is to invest its time in finding new ways to increase revenue while reducing costs and minimizing risks. Extracting relevant information from the various channels - databases, social networks or customer browsing histories - to generate new business opportunities, detect trends and anticipate consumer needs, has become practically an obligation to survive in today's changing market. It is clear that AI-powered CRMs are revolutionizing the way we do business..

In this direction he points out SAIL (Sales Artificial Intelligence Launch)The intelligent commercial software developed by Gamco, which allows, based on a company's customer information (CRM and ERP), to optimize the commercial channels in order to:

  • Attracting new customers.
  • Development and follow-up of current customers.
  • Loyalty, avoiding customer churn. 

► You may also be interested in: SAIL: Intelligent trading software

Why does a company need to use AI in its CRM? 

CRM (Customer Relationship Management) is a software that records and integrates in a single database all the interactions that occur between a company and its customers. In other words, it gathers customer information from numerous sources and uses this information to improve customer relationships.

A CRM can be implemented in any company, regardless of its size. It is usually a SaaS that is adaptable to the requirements of each company and, combined with AI, guarantees greater productivity. One of the main benefits of their integration is that they facilitate and speed up business decision making.

A CRM is designed to understand and design strategies or actions to get the most conversions or sales from a company's customers. The main function of a CRM is to collect information through emails, orders, address books and form submissions. In this way, behavioral patterns can be defined to help create specific offers for different customer segments.

With the implementation of artificial intelligence, CRM performance has improved exponentially by providing a complete view of the user experience from acquisition to retention, contributing to a more robust and successful business strategy. A CRM optimized with AI allows a company to identify areas in which it can improve its customer service to make the customer experience as satisfactory as possible.

In this sense, the automation of certain tasks is key to achieving objectives. This has a lot to do with the software's ability to perform both administrative and data analysis tasks, which, in addition to saving time, reducing costs and optimizing a company's efficiency, contributes to generate insights valuable to personalize the customer experience in each and every channel, preferably digital, reducing decision bias.

In this way, uncovering new growth opportunities and identifying trends at an early stage or in anticipation of complex market dynamics. Therefore, combining a CRM with artificial intelligence optimizes both the sales process and the customer experience. 

Summarizing, Artificial intelligence applied to CRM uses structured data processing, natural language and machine learning algorithms to help companies better understand their customers and identify new business opportunities..

However, it must not be forgotten that one condition sine qua non is to train AI to behave efficiently in different conditions and/or scenarios over time, rather than following rigid or general instructions. As a CRM becomes more and more intelligent, it provides more valuable and accurate information to make better decisions and optimize sales processes.

It must be taken into account that nowadays we are all, to a greater or lesser extent, much more informed than a few years ago, and we tend to trust the information we obtain, mainly online, about any product and/or service before making a purchase. Therefore, it is essential for a company to identify which processes and decisions motivate customer purchases in order to increase sales and improve customer satisfaction.. And this is where an AI-optimized CRM can make a difference.

CRM Types

According to their main functionality, we can find three basic types of CRM. 

  1. Operational CRM. Designed to automate sales, analytics, service and marketing tasks. Stores data on both customers (contact data, demographics, consumption habits, etc.) and employees.
  2. Analytical CRM. Focused on the collection and analysis of relevant information from customers in order to improve the service provided to them.
  3. Collaborative CRM. Designed for companies to have a more fluid internal communication and to integrate different work teams, so that all employees have access to the same customer data.

Benefits of applying artificial intelligence to a CRM

In this section, we will focus on the main benefits of optimizing CRM management through artificial intelligence.

However, before listing the benefits, it is useful to keep in mind that for the implementation of AI algorithms in a company's CRM to be effective and deliver better results, it is necessary to first identify the different data sets that exist -and that can be combined - to draw a complete map of customer typology and respond appropriately to the unique needs and preferences of each customer.

In this way, through data analysis and machine learning, interactions with each customer can be personalized, based on, for example, their purchase history, demographic group or browsing behavior.

Optimization of new customer acquisition

The use of artificial intelligence has proven to be a highly valuable resource in the creation of strategies to attract and capture new customers, as well as to generate qualified leads. Its ability to analyze vast amounts of data and extract relevant information has become an essential ally in this process.

When it comes to designing strategies to capture customers and generate qualified leads, artificial intelligence is positioned as the perfect ally. The combination of acquisition and remarketing campaigns together with customer clustering allows the design of more focused and precise campaigns, converting visits into successful sales.

One success story of the positive impact that artificial intelligence has on these strategies is the Gamco's SAIL solution. Thanks to this innovative solution, significant increases in the conversion of new leads have been obtained, with estimated increases between 15% and 25%. This achievement clearly demonstrates how the efficient implementation of artificial intelligence can translate into tangible results and significant improvements in conversion rates.

► You may also be interested in: Qualified lead generation for new customer acquisition using AI

Increased sales

This is one of the most obvious and valuable benefits for any company. Thanks to AI, the volume of data processed is much greater. This data, properly analyzed, is transformed into knowledge, i.e. accurate information on, for example, purchasing trends. Basically, this information is channeled to make better decisions and optimize the sales process, as well as campaigns and customer communication.

For example, when deciding whether to offer a discount to our customers, AI analyzes multiple variables, such as seasonality, the customer's socioeconomic profile, previous discounts or the evolution of the competition, in order to set the discount that best suits the market in a given period or timeframe.

Task automation and time optimization 

AI increases the CRM's ability to perform certain tasks with greater speed and accuracy than humans. It therefore enables an increased degree of automation of repetitive or routine processes, such as data entry or retrieval, which significantly reduces employees' manual work and errors. This translates into higher productivity and satisfaction for employees, who can focus on higher-value tasks, such as building customer relationships and optimizing their sales funnel.

Likewise, the virtual assistants or chatbotsThe new software solutions, which are now available on the market, play a very important role in automating administrative tasks or basic support functions, as well as in boosting employee productivity.

Chatbots that are properly trained can answer frequently asked questions, provide product recommendations, track orders, manage contacts, take notes and even process simple transactions.

In summary, allow increasingly realistic customer service conversations to be held in real time, significantly improving response times. For example, in the banking sector it is already commonplace for chatbots to take care of resetting a password without the need for human intermediation.

In this regard, more and more companies are replacing email with chatbots that enable real-time two-way conversations to engage customers. Instant responses to customer requests are the foundation of good customer service.

Sentiment analysis for loyalty

A happy customer is a loyal customer. Therefore, Knowing the emotional state of customers allows for a more effective communication strategy.to act proactively and optimize the customer experience. In this sense, AI tools can capture, analyze and visualize how customers perceive products and services.

For example, the use of chatbots makes it possible to analyze and assess customer conversations and identify and evaluate their emotions, including satisfaction and frustration. Understanding customers' emotional states helps companies increase their revenue per customer by 10%.

Optimized customer segmentation

AI-powered CRMs ease the segmentation process of your customer data into defined categories. They allow, therefore, to create very specific audience segments, according to the objectives or results that the company needs, taking into account geographic and demographic data, as well as psychographic, behavioral or sentiment analysis data. 

By better understanding its customers, a company can personalize the interaction and thus the effectiveness of the expected actions, whether it is the follow-up of an order or the sale of a product or service. For example, AI is used in marketing to generate personalized messages or experiences based on each type of customer. 

Improved customer experience

In relation to the previous section, there is no doubt that reaching a deeper understanding of the customer's demands is a key factor in generating an affective brand-customer bond. In this way, the customer feels understood. It is therefore not just a matter of satisfying their specific needs with individualized offers, but of reinforcing their loyalty and commitment for the future, with actions designed for this purpose.

This is called "hyperpersonalization of the experience"and is key to implementing customer loyalty strategies. By gaining a deep understanding of customer needs, companies can recommend specific products based on their demands. 

The development of improved applications, with more intuitive and user-friendly interfaces, also plays an important role in improving the customer experience. This ensures a high-quality experience that will undoubtedly contribute to improved conversion rates or sales.

Reduction of customer churn rate

This section is closely related to improving the customer experience. AI tools can identify patterns and trends in the reasons for customer churn, thus the company can act in a predictive manner and establish strategies aimed at reducing the abandonment rate. In any case, it should not be forgotten that it is easier and, above all, less costly to keep a customer than to acquire a new one. 

Optimization of sales strategies

By being able to estimate or predict the behavior of their customers, companies can design customized actions containing materials and proposals of quality and interest to them. 

Thanks to the application of AI in a company's CRM, data can be kept better optimized, avoiding, as far as possible, inaccurate predictions. In this way, it enables the detection of potential problems and suggests tailored actions to solve them. For example, if you find incomplete or duplicate data in a database, you can go to other channels to update or delete it.

Disadvantages of AI-based CRMs

Despite the undeniable benefits of artificial intelligence in enterprise CRMs, there are also some disadvantages to consider that can hinder its proper integration.

Data bias

AI algorithms can produce results that are incorrect, inaccurate or far from market reality if they are fed with biased or incomplete data coming from different channels and/or campaigns. So the results projected by AI will only be as good as the data used, its readiness for training with machine learning algorithms and its integration with sales channels. .

Lack of human interaction

Although it is clear that automation saves time and reduces costs for companies, the lack of human interaction with customers can negatively affect the experience of some customers, so this component should not be neglected. Chatbots, for now, are only capable of generating generic responses, so other alternatives must be provided to customers, such as access to a telemarketer or a brand representative In this way, dehumanizing commercial relationships is avoided.

Cybersecurity risks

Working with sensitive customer data, CRMs can be vulnerable to cyber attacks, so companies must take precautions to protect that data.

Conclusion

More than 90 % of companies with ten or more employees use a CRM to optimize their processes and become more efficient. This gives an idea of the important value of customer relationship management systems for companies. Therefore, by integrating artificial intelligence into these CRMs, companies are able to improve data entry automation and data analysis processes.

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