91% of companies with more than 11 employees use a Customer Relationship Management (CRM) system, compared with 50% of companies employing fewer than ten people. While these tools have become an integral part of the sales processes of businesses, the advances in AI technology impact this solution. As CRM tools become more intelligent, they offer more accurate sales insights and helps companies make better decisions in sales processes. Considering the increased volume of unstructured data and the growing complexity of customer relations/processes, AI technology is becoming a necessity in CRM systems.
However, according to the research by Freshworks, only 12% of CRM users actually use an AI-powered CRM tool in their processes. Many users think that AI-powered tools are too expensive or aren’t extremely useful considering the price today. Thus, we still need to have more time to observe AI’s actual impact on sales processes.
What is Customer Relationship Management (CRM)?
A Customer Relationship Management (CRM) system allows businesses to monitor and analyze their relationships with customers, suppliers, and employees. It aims to increase sales efficiency and profitability by improving and maintaining these business relationships.
By collecting existing and potential customer data, CRM tools can access customers’ interaction histories and sales data. This enables CRM systems to identify the required services and products to improve sales processes. Overall, the software helps businesses understand their customers better. With a better understanding of customers, companies can:
- Develop more effective marketing strategies
- Discover new sales opportunities
- Provide more effective support services
Wikipedia defines CRM as follows:
Customer relationship management (CRM) is one of many different approaches that allow a company to manage and analyze its interactions with its past, current, and potential customers.
Why do businesses need CRM software?
Gartner shares that 65% of a company’s business comes from existing customers, and it costs five times greater to attract a new customer than to keep an existing one satisfied. Thus, it is critical to understand customers better and take accurate actions to maintain strong relationships with them and improve sales metrics.
Sales are becoming more measurable. This might not be that important before the 2000s because most meetings were either face-to-face or on the phone, and the data recording technology wasn’t available, meaning that maintaining relationships mostly relied on the sales skills of workers. However, as today’s sales mainly depend on emails and customer interactions recorded databases, the CRM tools become more useful.
Sales are the biggest challenge for businesses, and CRM makes it easier. Today, businesses leverage these tools to process their customer data and find ways to improve sales channels with the insights gained. As most companies leverage CRM systems now, Gartner also forecasts that CRM will be the single largest revenue area of spending on enterprise software by 2021. From SMEs to large banks and consultancies, most companies use a CRM system to track their sales.
Why should businesses integrate AI into their CRM tools now?
We can provide three main reasons for integrating AI into CRM tools:
The increasing volume of unstructured data that is infeasible to process without AI/machine learning
With the growing amount of transactions, the size of customer data also increases. This increase can help businesses understand their customers better, as they can process more information about them. However, it also means that they need to work more to extract relevant information because the majority of the data remains unstructured. While it is challenging to understand unstructured data, which constitutes around 90% of the total data, AI tools can convert unstructured data to structured data.
After converting to structured data, machine learning algorithms can detect patterns and provide vital insights for businesses. Considering the growing amount of data, AI technology offers scalable solutions for companies and enables them to handle a higher volume of data rapidly and with fewer errors.
The increasing complexity of relationships
Besides the growing volume of data, the business processes and relationships also become more complicated with the increasing transactions. This complexity makes it harder to understand company relationships and analyze customer patterns accurately. According to Xant, sales representatives spend over half of their time spent in CRM for trying to manage CRM tasks more effectively. AI technology can easily surpass this challenge by automating most of these tasks and offering valuable insights.
The increasing popularity
As seen below, the interest in AI-powered CRM tools is expanding since the end of 2016. We can relate this increase to the following reasons:
- The advances of AI enable this technology to be integrated into the CRM tools, and these tools are becoming more preferred by businesses.
- The impact of AI in CRM tools is observed better as processes become more complex, and the amount of customer data increases.
What are some AI applications in CRM?
Interface.ai shares that 87% of sales teams are not satisfied with their CRM. This is due to manual tasks performed in processes or difficulty in using CRM tools. Thus, the integration of AI might help businesses improve their CRM processes and reduce human intervention while performing specific tasks like manual data entry. As a result, employees can focus more on higher value-adding activities and improve their productivity. Here are the main AI use cases integrated into CRM tools:
Sales representatives spend only 32% of their time selling or pitching tasks and 20% of their working hours for managing their CRM-related tasks like producing reports and other administrative duties. Businesses should create more time for their sales teams in sales processes and reduce their workload for their other responsibilities.
During lead qualification processes, AI-powered CRM tools can automate the majority of analyzing needs. They can leverage chatbots and email bots to understand leads’ needs and inform the sales teams to improve their performance. With insights gained from these bots, companies can optimize their sales processes.
Sentiment Analysis during calls
In sales, understanding customer emotions is critical for developing trust with them. As it is harder to build trust without face-to-face interaction, HubSpot Research shares that only 3% trust salespeople. AI can offer a solution to solve this problem. AI-powered tools can analyze customer conversations during calls and assess emotional states using sentiment analysis.
As an example, Cogito offers real-time conversational analyses to evaluate customer emotions, how effective the calls are, and how best to respond to them. According to the company, understanding customers’ emotional states helps businesses increase their revenue per customer by 10%, according to the company.
Accelerated Content Production
With the integration of natural language generation platforms, CRM tools can automatically organize personalized emails, reviews, and client reports. This characteristic can also be used in preparing descriptions for specific products, landing pages, social media posts, and news articles. Wordsmith, developed by Automated Insights, can be implemented in CRM tools and automate employee emails, as seen on this page.
While CRM systems use customer data to understand customers better, AI can discover their needs or desires to offer a personalized experience. Customer data to understand such patterns includes their information like age, gender, region, as well as their sales history and online interactions. As a result, your company can offer a personalized experience to your customers and recommend products based on their needs. Salesforce shares that personalization can improve sales by 10%.
Sales forecasting is one of the most critical and wide-spread features of CRM tools. With AI, these tools can provide more accurate forecasts. AI can detect patterns in customer sales data and offer valuable insights about sales predictions. With these forecasts, businesses can make their plans accordingly and optimize their sales processes.
Predictive Lead Scoring
AI tools can analyze customer sales data, including demographic data, geographic data, activity data, and web behavior, to determine their buying readiness. Companies can analyze won versus lost deals to detect trends that can inform predictive lead scoring methods. Feel free to read our research on the topic to learn more.
Customer Churn Reduction
As most company revenues come from existing customers, it is critical to prevent customer churn for businesses. AI-powered tools can go through customer data to analyze specific patterns and identifying the reasons for customer churn. As a result, companies can take concrete actions to reduce customer churn effectively.
We can group virtual assistants leveraging CRM data in two main categories:
- In-Office Tasks: Virtual assistants can handle simple in-office tasks like managing schedules meetings, taking notes, and notifying follow-ups in a CRM system.
- Intelligent Call Routing: Based on CRM data, AI can interpret natural language queries for customer segmentation and handle customer calls to support call centers in simple customer tasks.
Customer data can include many irregularities, anomalies, duplicates, and other errors, which may cause inaccurate predictions. According to Dun&Bradstreet, 91% of data in CRM systems is incomplete, 18% is duplicated, and 70% is rendered stale each year. To improve decision-making quality, an AI-integrated CRM system can:
- Detect potential issues
- Clean the duplicated data
- Notify the users to correct the errors
- Look for incomplete data in other systems
- Suggest actions to update potentially stale data
While data entry is one of the most repetitive and tiresome tasks in businesses, AI-powered takes it over and allow employees to focus on higher-value adding tasks. Data entry includes entering customer data in the desired format and automatically capturing data from SMSs, calls, emails, images, etc. with document capture, image recognition, and speech recognition technologies.
What are the main benefits?
The main benefits include:
- Increased sales: CRM tools offer valuable insights about customers and help businesses understand their sales processes. With these insights, companies can understand their customers better and develop new strategies that increase their sales. Salesforce shares that CRM applications can increase sales by up to 29%.
- Reduced time and costs: An AI-powered CRM can eliminate manual tasks like inputting and cleaning customer data, which would reduce human errors. By performing these repetitive tasks continuously and without any mistakes, these tools can handle hourlong tasks within a few minutes.
- Improved customer satisfaction: Understanding customers is one of the main challenges of businesses. Thanks to AI analyzing patterns in the customer data, companies can better understand their customers and take accurate actions accordingly. In the end, these actions will increase company revenue and improve customer satisfaction and loyalty.
- Improved employee satisfaction: As AI can handle manual processes, employees don’t need to spend time on manual tasks, reflecting on their satisfaction and performance.
What are the leading vendors that offer AI-powered CRM solutions?
CRM vendor market includes a wide range of solutions to support your business. You can have the sortable list with more than 300 CRM companies on our website. Here are the leading CRM vendors that also leverage AI technologies in their solutions:
- Adobe Sensei
- IBM Watson
- Microsoft Cognitive Services and Dynamics
- Oracle AI
- Salesforce Einstein
- SAP Leonardo
- Sugar CRM
If you have questions about AI-powered CRM software, don’t hesitate to contact us:
CRM usage stats: Getbase
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