How customer experience is changing
Customer relationship management (CRM) systems have been transformed by the power of artificial intelligence, giving companies a smarter way to manage customer experiences. Today, the importance of AI in sales processes cannot be overstated. We looked at how machine learning can be used in CRM systems and how an organization can use it to create workflows that meet customer relationship management goals and expectations.
AI in customer relationship management involves using software, algorithms, services, and best practices to improve customer analysis and actions within a CRM platform. It improves and updates information in real time; creates more engaging customer experiences; increases knowledge for decision makers; and automates various aspects of customer service and work.
With AI in CRM, marketers, salespeople, and service providers can more efficiently manage their daily workflows through automation, integration, and recommendations based on up-to-date performance metrics and recent customer interactions.
Improving customer experience
CRMs use data to improve everything from customer data to customer communications and engagement plans. Here are some of the most common use cases for AI:
Reporting and Predictive Analytics. Artificial intelligence technologies are used to collect relevant and accurate factual data, as well as to obtain more detailed information about customer sentiment and issues that may affect the quality of service.
Creating Custom Content. Generative AI can be used to create dynamic advertising and web content, personalized emails, and other audience outreach that focus on everything from a customer’s global location to their past purchase history and the reviews they’ve left on third-party sites. When content is more personalized, consumers are more likely to feel loyal to a brand.
Automation of work processes. AI can set up complex, always-on automated workflows to ensure customers receive regular, personalized messages that keep them engaged and happy.
Audience segmentation. A task that was often done manually (and tediously) is now performed by bots built into CRMs. Based on the data available for each customer profile, AI can cleverly segment them into sales funnels and reach groups that best match people’s interests and purchase histories.
Sentiment Analysis. Instead of a human combing through third-party review sites, social media posts, and dozens of group chats, AI technology can quickly scan all of these sources to determine overall sentiment and the sentiment of individual customers. From there, it can make recommendations on any larger changes that need to be made or how best to approach a specific customer’s frustrations.
Personalized product recommendations. Once enough data has been collected and identified, CRM AI can generate personalized product recommendations. These can include upsale and cross-sale based on recent purchases or activity. The likelihood of making such deals depends entirely on the relevance and timeliness of the recommendations, two areas where machine learning excels.
Chatbots and virtual assistants. AI-based assistants can be used to support both internal employee work and external interactions with clients. Especially since most of these tools can work 24/7.
Implementing AI into Customer Relationship Management Systems
It is possible to integrate third-party AI technology into your CRM platform of choice, but AI will be more effective at managing workflows if it is offered as part of the CRM from the start.
Nowadays, many CRMs have built-in AI features (automation and workflow management, data analytics and content management, etc.). Therefore, it is advisable to pay attention to studying a potential or installed system to learn about the capabilities already available.
Developing a plan of strategic goals and results
Before you get started with AI and explore its capabilities, identify the customer relationship management goals you hope to achieve with AI. These can be broad and general, but it’s also helpful to set some intermediate, more specific goals that will help you get closer to your desired results.
Start with measurable goals. These will have the greatest impact on your business's customers and profits. For example:
Increase overall customer satisfaction by increasing the organization's Net Promoter Score (NPS) by 10 points over the next eight months.
Use chatbots to resolve 25% of incoming user queries during the first interaction with them. Make this possible within the first year of chatbot implementation.
Increase customer retention by 5% year-over-year by using AI to improve lead scoring, identify churn risks, and develop targeted email campaigns.
Other strategic goals for applying AI in CRM may focus on implementing analytics, customer lifecycle management, task automation, and other areas of the CRM workflow where new efficiencies can be quickly achieved.
Improving Data Quality Before Implementing AI
AI in CRM is primarily focused on the information collected and stored. Therefore, data quality management becomes a priority, which includes cleaning, deduplication, and fact checking. You should also consider whether your data sources are up-to-date and relevant. When working with customer-centric information and customer service, it is important to rely on data from all types of customer service channels, including third-party websites, product pages, social media, phone calls, and customer support chats.
Phased implementation of AI use cases and workflows
Even if you’re working with a very sophisticated CRM system that offers a lot of AI-powered features, it’s important not to get caught up in the hype and instead approach the implementation with careful logic. Start with the most important goals you set out earlier and create a clear project plan for implementing and adopting this AI use case across your team.
The lessons you learn from the initial stages of implementation and change management will prepare you to tackle other aspects of your CRM more effectively and efficiently. Iterative implementation takes time, but it ultimately saves time for most companies because they don’t have to go back and fix recurring mistakes as often.
Performance testing and monitoring
After the initial implementation and implementation, you need to monitor the performance of AI in your CRM system to ensure that it meets your needs and does not create new errors or problems in your workflows.
While actual performance can be measured using usage data in your CRM setup, it’s worth looking at how customers feel about AI-based interactions. Review feedback, especially comments about the quality of AI bots. Make this practice part of your workflow so that you can immediately identify and resolve any issues customers have with non-human support staff or communications.
Transfer control to AI assistants and support specialists
AI still has its limitations, especially when chatbots based on it are in the early stages of training. Customer support staff should remain available at least during normal business hours, as they will occasionally need to take over handling requests.
And for off-hours, it’s worth creating a system where unresolved AI service questions can be escalated to a live support agent. Customers will quickly become frustrated if they feel they can’t reach a real company representative with their more complex questions, especially if the chatbot is giving generic or irrelevant answers.
6 Benefits of Integrating AI into CRM
Integrating AI into your CRM can benefit the business as a whole, key players on the team, and the customers themselves. Here are some of the benefits:
“Smart” and timely analytics. AI can support better data collection and cleaning practices and extract more useful information from it. In essence, it can manage information and its analytics throughout the entire data lifecycle. AI can work in the background across all customer service channels at all times. Having relevant, accurate, and diverse customer data at all times opens up more opportunities for analysis, especially for companies that want to identify and mitigate any risks of customer churn.
Save time by automating your workflow and tasks. Artificial intelligence can write emails and blog posts, handle customer inquiries, and schedule campaigns to reach the right people at the right time. All of these tasks typically require human intervention on a daily or weekly basis, which takes significant time out of a person’s work schedule. As AI is used to automate and take over the most tedious, routine tasks, employees can spend more time working on high-level strategy and loyalty campaigns, which leads to increased sales and helps retain customers.
Income growth potential. Customers who are more satisfied with the support they receive are more likely to become loyal, repeat customers, or even brand advocates. When your brand builds a strong reputation among a loyal audience, you will not only earn more profit, but you will also likely attract more customers who are interested in receiving the same level of attention and care.
A more personalized shopping experience. With the ability to connect multi-channel customer data in virtually any format, AI-powered CRM systems have all the information needed to better personalize the shopping experience. Consumers are more likely to see relevant, targeted ads, receive emails about sales or offers that interest them, and receive support that solves real problems when using products or services. In short, AI provides a personalized experience that is difficult to replicate at such a large scale with limited human resources.
Less spam. AI is often used to target advertising campaigns. Customers will receive fewer spam messages from your organization. They will be happier with the messages they receive from you, and you will likely get more engagement from them.
Real-time support services. AI-powered chatbots are not limited by their working hours. In most cases, they can work 24/7, and this does not require additional costs for the business. At the same time, customers certainly benefit, as they can get answers to many of their most pressing questions at any time of the day. This feature is especially useful for large companies that support customers in different time zones.
Conclusion
For years, people have been afraid of interacting with a “robot” when trying to get the answers they need. While this fear still exists at some level, advances in AI have offered radical improvements, making it increasingly difficult for customers to distinguish between human interactions and AI interactions.
Moreover, AI has reached a point where it can outperform human customer-facing workers in some key areas, including collecting and applying real-time data and automating various customer service and lead management tasks. We can expect AI to continue to rapidly evolve in this sector and in CRM, especially as companies begin to realize greater benefits from its implementation.
