Artificial intelligence to build customer loyalty


Gamco Team

In today's information-overloaded marketplace, it is becoming increasingly difficult to retain users. For companies, competition is increasing, while for customers there are more and more offers at their fingertips, so more precision is needed to attract and retain them. Therefore, the use of Artificial Intelligence to engage and capture your customers is spreading to design personalized campaigns that get a positive response from the customer and contribute to their loyalty. 

The applications of AI in the field of sales are almost limitless and its incorporation has given a shot in the arm to commercial relationships between companies and consumers. By 2025, according to Statista, AI employment will be worth $126 billion in the United States alone. 

Thanks to AI-based predictive analytics tools, companies are able to understand and anticipate the needs expressed by customers, providing exhaustive knowledge of their preferences and desires, pointing out which decisions, in real time, should be taken to satisfy them and meet their expectations and demands. It is therefore essential to have as a starting point a clear definition of the most profitable possible future scenarios in order to make decisions that will benefit the business.

Companies that are employing tools based on Artificial Intelligence and machine learning in the commercial sphere can obtain, according to data from Harvard Business Review:

  • A 50% increase in the final conversion rate or, at least, in the likelihood that the customer will purchase the recommended product or service.
  • A cost reduction of around 40-60%.
  • A decrease in customer call time by 60-70%.

The most important thing is to have the ability to interpret the huge amount of data from different sources, starting with ERPs and CRMs themselves, and to obtain the most accurate information possible about consumers and achieve their loyalty. In this sense, today's Big Data technologies are capable of processing, integrating and storing data on a large scale. More than ever, companies need to understand and plan for what their customers might do or want in the future.

► You may also be interested in: 10 ways Artificial Intelligence helps businesses

5 strategies to build customer loyalty

To achieve the customer loyalty and build long-term relationships with them, special attention should be paid to the following strategies.

  1. Provision of customer service. The customer must feel valued and listened to at all times. In this sense, it is convenient to provide a service to attend suggestions and give immediate solutions, as well as to have a good after-sales service.
  2. Brand transparency. To generate close emotional connections with the customer, companies must show their values and publicize the initiatives they sponsor or the social causes they support.
  3. Communication campaigns. The main objective is to enhance the company's brand image through the development of actions aimed at developing and maintaining contact with its customers: newsletters, recommendations, events, etc.
  4. Offer unique customer experiences to connect with them. In this way, we will be able to differentiate ourselves from the competition and increase their interaction with the brand.
  5. Loyalty programs. It basically consists of rewarding and rewarding the customer for their commitment to the brand, through, for example, discounts and special promotions.

The loyalty of today's customers, who are increasingly demanding and selective, is one of the key factors in ensuring good business performance. 

It is becoming increasingly necessary to understand consumer behavior. In this sense, predictive analytics through AI allows organizations to know in advance the movements of their customers to make decisions that retain them and make them loyal to their brand, avoiding those weak points that hinder conversion.

The application of these strategies, coupled with the implementation of AI models, will allow companies to predict the best ways to personalize their offers to target selected customers based on their previous orders. AI models can also help plan marketing campaigns and estimate which customers are losing or gaining interest in our products and services.

What does loyalty consist of?

Customer loyalty is a process of developing a positive relationship between the consumer and the company that encourages the consumer to return for further transactions. It is what is called "positive contact", i.e. the gaining of a customer who has previously purchased or acquired a product or service from the company. When this contact is established, we can speak of loyalty.

Why is customer loyalty important?

Because it is necessary to take into account that it is more expensive to acquire a new customer than to keep an existing one. In addition, an existing customer spends a 70% more than a new one. Therefore, maintaining a good relationship with old customers is considered paramount so that trust is not broken.

The relationship with a customer does not end with the conversion of a sale. Once the purchase is satisfied is when a business has to start forging a lasting relationship with the customer, allowing for recurring purchases. Thus, some of the advantages of customer loyalty are:

  • Increased profitability.
  • Enhancing brand reputation
  • Free advertising based on customer recommendations.

In this regard, the churn rate, an indicator of customer churn, has become the main challenge for businesses that are committed to customer loyalty, and for those based on service subscriptions, e.g. many mobile applications and software service platforms. The use of Artificial Intelligence can facilitate the task, as we will see.

Customer churn can occur for a number of reasons:

  1. Natural cause. It occurs when a company cannot avoid customer abandonment because the possibility of retaining the customer has been exhausted or the interest has been extinguished., unless new products or different service lines are added to the catalog.
  2. Alternate consumption with other brands. It occurs when there is a lower recurrence in the orders placed, which may indicate that the customer is trying other brands. In other words: when the customer stops buying with the same assiduity. This is called "hidden abandonment rate". To combat this, the use of predictive tools based on machine learning and Artificial Intelligence can be of enormous help. Businesses will be able to make decisions faster and with a higher degree of accuracy because they will have previously identified, through the analysis of the collected big data, loyal customers and designed a personalized communication to continue counting on their loyalty. 
  3. The customer chooses another brand. Basically because it finds more attractive alternatives (price, design, shipping, after-sales service, etc.).

The relationship between a customer and a company goes through a life cycle. Therefore, analyzing each of the stages of the cycle will provide essential information to carry out marketing actions aimed at satisfying the customer's needs at any given moment..

► You may also be interested in: How do I know if a customer will pay me?

AI to analyze customer behavior

AI models can learn from past data and adjust with the latest known data to, for example, recommend discounts, customized products or services that better meet a customer's needs based on analysis of the behavior of customers with a similar profile.

That is to say, analyzes customer lifetime. Predictive models generated by machine learning and AI decision making therefore determine what actions to take for each customer and according to the phase they are in (acquisition, conversion, growth, retention or reactivation). In this way, companies can answer two key questions:

  1. How can I build customer loyalty?
  2. How can I win back a lost customer?

To build customer loyalty, companies need answers to these questions. Predictive analytics uses customer data to build models that help predict future customer behavior and personalize the customer experience. In this way, companies can predict:

  • Which potential customers will respond to certain offers.
  • What type of products customers will buy.
  • What will be the preferred devices and channels used to access a company's website.
  • Which actions are the most appropriate to retain customers and when to apply them.

In this regard, SAIL (Sales Artificial Intelligence Launch), the sales optimization and intelligent CRM software developed by GAMCO, provides predictive knowledge of what goods and/or services to offer each customer, when to offer them and how to increase sales, through machine learning and data analysis, using the commercial levers and promotions available for customer acquisition and loyalty.

The use of Artificial Intelligence and machine learning in sales enables your business to have a better knowledge of the end customer, being able to monitor it by applying customized sales KPIs and providing suggestions for the optimization of campaigns for their loyalty.

AI for customer churn prediction

The SAIL solution incorporates a module for predicting the abandonment of customers up to 60 days in advance and of products or services by these users.

Through the use of AI, it gathers quantitative and qualitative information that allows detecting behavioral patterns that are repeated in order to improve the understanding of the end customer and avoid the cause of their abandonment.

In this sense, SAIL also allows to improve sales forecasts by processing historical data such as prices, volumes or geographical distribution to convert them into relevant information for demand forecasting. It also avoids customer abandonment by offering products or services that match their real interests, based on their purchase history, discounts applied, participation in promotions, etc.

► You may also be interested in: Artificial Intelligence against delinquency and non-payments in companies

Finally, it significantly improves the efficiency of the sales team by automating many tasks, reserving time for those interactions with a higher probability of success and for talking to the customer and getting to know them better: what their needs and interests are in order to provide them with a better service. On the other hand, sales based on AI resolutions provide salespeople with very useful information on what strategy to follow in order to close a transaction.

5 keys to building customer loyalty through AI

The 5 keys to building customer loyalty through the use of AI tools are:

  1. Automate simple and repetitive tasks. AI makes it possible to collect and segment large data sets in an automated way to generate responses that satisfy customers. Sending personalized emails after an online transaction or purchase is a good example of this. Automating this task saves time and improves the trust relationship with customers.
  2. Accelerate pattern identification: It is possible to recognize recurring trends or attitudes in customers, allowing companies to gain a better understanding of their needs and design specific actions to meet them, such as writing personalized newsletters based on the previous buying patterns of potential customers, avoiding indiscriminate offers and, consequently, possible rejection.
  3. Hypersegmenting customers: Machine learning makes it possible to target precise groups of consumers who share similar attributes and behaviors. This makes it possible to deliver personalized experiences on a large scale. For example, a campaign can be targeted to customers who share the same interests at a given time. The segments obtained by machine learning are dynamic: they follow customer behaviors and are reflected in the data collected from them.
  4. Optimize dynamic content. Through an AI-based analytics engine, it allows you to reach customers through the most appropriate channels and in the most timely manner. The result is a pleasant experience for the consumer and higher levels of satisfaction. With AI, it is possible, based on the analysis of browsing data or purchase patterns on a website, to reconfigure communication with the customer to automatically deliver content that best suits their profile or history. This highly personalized experience ultimately leads to stronger relationships between consumers and brands and makes the shopping experience enjoyable.
  5. Use of chatbots for customer service and purchase guidance services.aimed at customer engagement or loyalty. Rapid advances in voice recognition technologies and voice simulators have driven the growing popularity of "virtual assistants", such as Amazon Alexa or Google. These types of chatbots can handle customer queries and resolve them instantly, although many come configured with static rules and are not fully controlled by AI. With 24/7 availability, GAMCO has created a module within SAIL for promotions optimization to provide a powerful tool for the sales force and chatbots to automatically create promotions that are tailored to customer characteristics. These promotions will have a greater impact on the business and the value perceived by each customer will be more positive Therefore, through the application of AI, users' reactions can be evaluated and personalized offers can be provided in seconds. They can also inform customers about new products, services, events or discounts; they can even send notifications to users about the status of their orders.

Advantages of AI for customer loyalty

The main advantages of predictive intelligence for customer loyalty can be structured around four central axes:

  1. An appropriate and flexible segmentation of the target audience (by all known variables: age, location, interests, etc.), adjusted to the expected needs and requirements. In this way, an incentive can be offered that meets the specific needs of each particular audience segment. Machine learning algorithms analyze customers' past buying patterns to predict their future actions.
  2. In-depth knowledge of customer needs, detecting variations in their needs and preferences over time to better adjust the offer.
  3. Constant monitoring of the relationship between the sales force and the customer, because the predictions made can change substantially based on new data. This is critical for on-site support to the sales force. 
  4. Better decision making that increases the level of customer satisfaction. Artificial Intelligence helps to better understand what customers want, so this knowledge can be used to innovate and design products that meet their requirements.


It is clear that having more customers is not synonymous with more sales, so the main problem is to know how to make profitable the ones you already have and act, as far as possible, on those that are more profitable or have greater future potential. And it is here where the use of Artificial Intelligence to develop actions aimed at attracting and retaining customers becomes valuable. As we have already seen, it is a matter of following the following process:

  1. Identify "premium" or high potential customers.
  2. Define the objective: increase purchase frequency, offer an innovative product range for a specific age group, etc.
  3. Act in accordance with the objectives set, applying the recommendations or suggestions generated by AI: promotions, discounts, price changes, etc.

Thanks to the technology of GAMCOIn addition, companies can estimate customer potential and increase sales by automatically obtaining knowledge and self-adjusting predictive models to improve decision making.

SAIL, commercial optimization and CRM software, allows you to know at all times what products or services to offer, identifying the business opportunities for each customer; to which customer segment to direct your actions, optimizing commercial levers and promotions, according to the type of customer; and how to do it to avoid possible customer abandonment.

SAIL is a proven solution in large companies in the FMCG (Fast Moving Consumer Goods) and distribution sectors, in which commercial channels have been developed, with very significant returns, rapid deployments and no impact on the companies' current systems.

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