Artificial Intelligence In Customer Analytics: There’s a mantra in the business world: KNOW YOUR CUSTOMER. On the one hand, this is an increasingly pressing need.
On the other hand, given the amount of information available, it is becoming almost impractical. In this article, you will find out how to solve this problem using Artificial Intelligence in Customer Analysis.
There was a time when the most successful strategies focused on offering products to everyone on a large scale. After all, the offer was small, and the competition was almost non-existent. It was enough to announce features and functionalities to sell.
Currently, the most effective campaigns are customer-focused. This involves market analysis, segmentation, and targeting to deliver something satisfying real needs and desires. That is a higher value that differentiates you.
In addition to features and benefits, the consumer is interested in how the product is manufactured and sold, if there is an environmental impact, if there is labor exploitation, and if it is associated with social and humanitarian causes, among other factors.
Until Then, So Good! So What’s New?
It happens in parallel with a technologically profound technological advance that triggers a revolution. And not just any revolution, no.
It is the 4th Industrial Revolution, promoting digital, biological, and physical technology fusions. In the same way, it prints social, economic, and demographic changes, and it strongly impacts how people do business.
Undeniably, one of the most representative advances in this process occurs with Artificial Intelligence. Computers, in addition to being faster and more efficient, correlate facts and develop new knowledge.
And it is this ability to process a large volume of data allows the implementation of gradually more segmented and personalized strategies in customer analysis.
How Can Artificial Intelligence In Customer Analysis Help You?
Indeed, smart computers are a reality. This happens due to Machine Learning, a form of Artificial Intelligence. It helps companies get to know their customers better, provide more effective service, and create more lasting relationships.
Regardless of size and activity area, companies need to invest in customer experience. That keeps him satisfied and close, meeting his needs and anticipating his aspirations.
In addition, this tool allows you to analyze customers who do not buy with you. With this information, you can carry out a predictive analysis to identify those who can go to the competition and act to avoid loss.
Likewise, it is also possible to determine the factors that make consumers resistant to loyalty. Another important analysis is that of customer turnover. All of this impacts retention marketing strategies and improves customer relationships.
After segmenting the customer base with the help of Artificial Intelligence, you can start targeting strategies and actions. Here are some:
Loyal Customer Strategy
They usually represent most of the company’s revenue and deserve special treatment. In this sense, he invests in the relationship, sends exclusive newsletters, forms a friends club, and offers discounts or advantages he values.
Increase customer contact points, monitor deliveries and the level of satisfaction, offer personalized products and services, set up loyalty programs, and humanize service. Also, value after-sales service and constantly update your profile information to detect possible changes in behavior patterns.
Be alert if customer information shows a frequency, recency, or average ticket drop. He is likely meeting his needs with the competition. In this case, the action is punctual and surgical. Find out what your objections are and act on them urgently.
This is the universe of Inbound Marketing. In summary, define the customer profile that your company needs to attract. Organize all actions around it. Produce original and exclusive content to help you overcome your pain. Create Landing Pages to capture it.
Most problems that cause wear and tear in the relationship with the customer arise in customer service.
What Are The Concrete Benefits For Your Company?
As noted above, technological advancement with cloud computing and mobile platforms keeps everyone connected and produces valuable data. They need to be processed and transformed into valuable information for the business.
Doing this manually is impossible. Therefore, the importance of Artificial Intelligence in customer analysis. Here are 6 concrete benefits:
On the one hand, this broad connectivity facilitates customer contact. On the other hand, it can become a threat. Given the intensity and speed with which we communicate, a positive experience is highly valued, with customers commenting and referring us. However, the reverse is also true. A negative experience goes viral much more strongly and quickly. And this is one of the main reasons for your company to use Machine Learning to ensure this does not happen.
An omnichannel company operates on multiple communication channels. The hyper connected customer requires a different approach, which assumes answers with qualified information in real-time and on the platforms where he chooses to be present. Therefore, Artificial Intelligence allows language adaptation and adaptation to different channels, improving the quality of the experience.
Who has not spent hours in long queues waiting for service? This is in public and private services, physical stores, and the companies’ SAC s. Intelligent and interconnected systems remove this terrible experience from the customer’s day-to-day life and enhance the service capacity.
This is the greatest benefit of applying Artificial Intelligence. By automating processes, information, and repetitive tasks, time is better used. The impact is immediate in reducing costs and increasing productivity.
Integrated Data Analysis
Intelligent systems evolve to support an increasing amount of data. They process and make available to companies unique information about customer behavior. These, in turn, are integrated with other systems – such as the CRM, for example – from where previously established strategies can trigger actions.
The intelligent system generates a database fed back by Machine Learning, which provides a permanent improvement process. Thus, the digital transformation gradually develops solutions more suited to customer profiles, more humanized, and focused on the satisfaction experience.