AI in CRM. What does AI change in CRM tools? | AI in business #67

Introduction to AI in CRM

CRM, or Customer Relationship Management, is a system designed for managing customer relationships. It consists of three main components:

1. Interactive CRM – ensures consistent and satisfying communication across all channels,
2. Operational CRM – responsible for collecting, standardizing, and sharing data about customers and products. Properly utilized, it creates a knowledge base and builds lasting relationships,
3. Analytical CRM – uses advanced analytical models, including AI, to process Big Data and uncover patterns in customer behaviors and market trends. This helps in making better business decisions.

Combined with new analytical capabilities, CRM systems allow personalized communication, customer support through chatbots, and automation of processes, leading to improved customer relationships and experiences.

How AI is changing the CRM landscape: An overview of possibilities

Leading CRM system providers integrate AI solutions that completely transform the way marketing, sales, and customer service departments work. The ways in which AI tools function in customer relationship management vary widely, so let’s take a closer look at three of them that most interestingly leverage the capabilities of artificial intelligence.

HubSpot CRM

HubSpot CRM is an all-in-one AI tool for managing customer relationships. It uses AI to improve marketing, sales, and customer service by quickly finding information and providing comprehensive content writing support.

It also offers tools for automating the creation of websites and newsletters, which is why HubSpot users appreciate the convenience, speed, and attractiveness of the generated content.

Key capabilities of HubSpot CRM related to AI include a website generator that automatically creates pages based on simple instructions and an AI Content Writer that generates content using AI, saving time.

Companies like Trello, Slack, and InVision use HubSpot CRM. Its main benefit is saving time through the automation of routine tasks.

Source: Hubspot (https://www.hubspot.com/)

Salesforce Einstein

Salesforce Einstein is based on advanced data analytics, AI-powered insights, sales recommendations, outcome predictions, and other features leveraging artificial intelligence.

Key capabilities of Salesforce Einstein include:

• advanced personalization – Einstein enables the creation and deployment of AI assistants directly in Salesforce, allowing users and customers to quickly solve problems and work more efficiently. Einstein Copilot is an AI assistant that automates tasks based on predefined skills, primarily aiming to increase productivity.
• Einstein Trust Layer – it ensures customer data security through AI architecture embedded in the Salesforce platform, allowing the use of AI without the risk of data breaches,
• open-source platform — Einstein allows secure usage of any large language model (LLM), such as OpenAI’s GPT-4, Google’s GeminiPro, or models available under open-source licenses like Llama-2 or Vicuna-13B.

Companies like Uber Eats, Gucci, and Accenture use Salesforce Einstein. This solution enables them to quickly resolve customer issues and work more efficiently.

Intercom Fin

Intercom Fin is a chatbot based on OpenAI language models that understands customer queries and provides answers based on technical support content.Intercom Fin, as an AI tool in customer relationship management, allows for:

• reducing customer support inquiries by 60%—thanks to the ability to utilize product knowledge base and advanced language models,
• conducting conversations in 43 languages,
• operating on multiple channels—via the well-known Intercom messenger, as well as WhatsApp and even SMS.

Intercom Fin helped companies like MailerLite increase the percentage of automatically resolved queries from 18% to 29% within a week.

Source: Intercom (https://www.intercom.com/fin)

Personalization of customer interactions through AI

CRM systems gather data about customers and their behaviors. With AI in customer relationship management, data is automatically analyzed to provide personalized communication. This includes:

• personalized recommendations – based on purchase history, interests, demographic data, and other parameters, enabling effective cross-selling and upselling,
• dynamic content on websites – AI in customer relationship management means targeted, personalized content based on user data,
• personalized newsletters – unique, tailored content for each recipient.
• better-targeted ads – displayed to people they truly resonate with.

An example of a company utilizing personalization capabilities in CRM is IKEA. According to a Capgemini report, the Swedish giant employs advanced AI models for customizing newsletters. The system analyzes customer data to tailor content and offers to their needs and interests.

Personalized experiences build trust and enhance customer satisfaction. According to McKinsey, as many as 78% of customers state that they would buy products again from brands that provide personalized experiences. Moreover, a 2022 Twilio study (State of Personalization Report) indicates that a significant 62% of customers would switch goods or services providers if the content was not personalized.

How AI improves segmentation and targeting in CRM

Customer segmentation and precise targeting are the foundations of modern marketing. Artificial intelligence enables significant progress in this area through features such as:

• automatic customer segmentation – grouping based on behavioral, transactional, demographic, and other data,
• machine learning to identify the most valuable customers – big data and predictive analysis help define a group of customers worth special attention,
• real-time analysis of customer sentiments and intentions – with these AI elements in customer relationship management, you’ll discover what your customers think and plan,
• predictive models that determine the likelihood of purchase and churn, and can also suggest additional products that perfectly match the customer profile.

For example, Allegro, the largest e-commerce platform in Poland, uses advanced AI models to segment customers. According to Interaktywnie.com, thanks to machine learning algorithms, Allegro is able to determine customers’ shopping preferences with up to 90% accuracy and target them with personalized offers.

Utilizing sentiment analysis in CRM with the help of AI

Sentiment analysis involves automatically assessing the attitude of a speaker or text author. Natural Language Processing (NLP) models classify opinions as positive, negative, or neutral. Enabled by AI, sentiment analysis allows for:

Evaluating customer satisfaction during conversations—determining if customers are content and assessing service quality.

• monitoring social media and discussion forums.
• tracking product reviews—identifying flaws and issues.
• analyzing customer needs based on phone call transcriptions.
• promptly detecting negative signals from customers and enabling quick responses.

Sentiment analysis is a powerful AI tool in customer relationship management, helping build positive customer relations. Global giants like Amazon and Netflix also employ similar solutions.

Source: DALL·E 3, prompt: Marta M. Kania (https://www.linkedin.com/in/martamatyldakania/)

Intelligent assistants and chatbots in CRM

Chatbots, like Intercom Fin, supporting customer service, are slowly becoming a standard. Implementing them brings many benefits, for example:

• answering customer questions 24/7 via chat, email, or WhatsApp,
• automating simple tasks, complaint requests, or customer orders,
• redirecting to a consultant and smoothly taking over the conversation when the chatbot can’t handle the issue,
• detecting negative customer emotions based on vocabulary or tone of voice and responding appropriately,
• collecting feedback and conducting satisfaction surveys.

Companies investing in chatbots achieve tangible benefits – according to the Juniper Research report, it’s possible to reduce customer service costs by up to 90%. Furthermore, studies indicate that implementing a chatbot can reduce the number of inquiries directed to customer service by up to 40%. This translates into significant savings for the company.

AI in CRM – summary

The technological revolution driven by artificial intelligence and big data processing is changing how we approach building customer relationships. Modern CRM systems not only automate tasks but also help understand customer needs better. This allows for personalized offers and communication, leading to more lasting relationships and satisfying customer experiences, ultimately contributing to business success.

New technologies are here, and their impact is measurable. Estimates suggest a potential 25% increase in sales through personalized approaches (McKinsey). Using these capabilities is essential today to gain a competitive edge in a data-rich and technologically limitless world.

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