From automation to sentiment analysis, AI is transforming the modern CRM. In this post, we take an in-depth look at AI in CRMs and see how the technology is transforming one of the most important tools in your tech stack.
Salesforce - Best for AI CRM Automation
- Forecast management
- Email marketing automation
- Einstein AI
1. Personalized Recommendations
While 85% of businesses believe they’re offering personalized experiences, only 60% of consumers agree.
CRMs with built-in AI capabilities use the extensive data collected on leads and customers to make hyper-personalized recommendations.
AI can pull data on the entire customer journey, using machine learning to understand every interaction leads or customers have with your brand — from calls with sales reps to blog comments.
In doing so, AI can get a 360-degree view of each customer, developing an understanding of their behaviors, preferences, and barriers to converting.
With an in-depth view of leads and customers, a CRM AI can make personalized recommendations for each lead and customer — showing marketing and sales teams the best way to them.
AI can also make personalized purchase recommendations and identify upsell and cross-sell opportunities. Zoho CRM’s AI Zia and Salesforce‘s Einstein are great examples.
These AI tools analyze customer behavioral patterns to make personalized product recommendations for users at the ideal stages in their customer journey, for example.
2. Sentiment Analysis
Sentiment analysis is one AI-powered capability you should look out for when choosing or switching CRMs. This combines natural language processing and text analysis, empowering AI to efficiently analyze a customer’s intent, emotional tone, and level of urgency.
Sentiment analysis is particularly useful when it comes to customer service. Customer service teams can use CRM with AI using sentiment analysis to provide immediate responses to queries.
Take an AI chatbot on a company’s homepage, for example, AI can use sentiment analysis to interpret a customer’s emotional tone and the urgency of their message.
From there, it can either provide basic front-line support or reroute more serious cases to available agents. By using AI CRMs in this way, you can reduce customer response times.
This will ultimately improve customer satisfaction and free up your reps to focus on more engaging, higher-level tasks. Several popular CRMs provide built-in AI chatbots powered by sentiment analysis.
The most popular of the bunch is Salesforce‘s Einstein. You can use Einstein to provide automated responses to customers via chat that mirror the tone, intent, and content of your customers’ queries.
Einstein can pull up relevant, historic customer data from your CRM and use it to personalize customer interactions.
3. Enhanced Data Analytics
By 2025, the amount of data generated, gathered, copied, and consumed is set to reach 190 zettabytes. Right now, companies have a host of information on their contacts, leads, customers, and teams.
But without AI, this wealth of data is difficult to manage and mine for valuable insights. Modern CRM’s AI functions use machine learning to analyze large amounts of data for actionable insights.
AI can make data-informed suggestions based on historic and real-time data on customer, contact, and lead interactions and team workflows.
Beyond Zoho and Salesforce, Pipedrive’s personal AI assistant is another good example. You can use it to mine data on your deals, contacts, and emails — using it to gain invaluable new insights.
These CRM AI assistants can deliver insights into your team’s performance, highlight your most valuable deals and track email opens, for example.
With this, the AI can provide recommendations on how you can improve sales success and productivity — allowing you to:
- Better understand your metrics
- Predict high-probability deals, and
- Prioritize the right tasks in your workflows
4. Predictive Lead Scoring
In the past, sales teams manually scored leads — giving them less time to focus on closing deals. Thanks to AI, they can automate this with help from machine learning and natural language processing.
You can use AI within your CRM to automatically prioritize leads based on the pool of data on the entire customer journey — from email conversations to page visits.
Top CRM services allow companies to use predictive lead scoring to better understand which leads to prioritize, automate follow-ups, and close more deals.
HubSpot, one of the best AI CRMs, for example, uses machine learning to analyze thousands of data points, helping sales teams qualify their leads.
Impressively, the system becomes more effective over time. Ultimately, this creates a self-optimizing system for lead scoring.
5. Enhance Operations
When integrated with your CRM, AI can improve operational efficiencies by automating routine tasks that can end up eating into your sales and customer service reps’ day.
For example, you can use AI to automate data entry and follow-ups, giving your customer-facing teams more time to focus on more complex and interesting tasks.
Take Zoho’s CRM, for example, which makes brilliant use of AI to automate workflows. You can trigger workflows once a certain action has been taken by a lead or member of your team.
This allows you to automate tasks like setting up demo calls and sending out welcome emails to leads who have just signed up for your newsletter.
Conclusion
Salesforce - Best for AI CRM Automation
- Forecast management
- Email marketing automation
- Einstein AI
AI has had a transformative impact on CRMs — both for internal teams and for prospects, leads, and customer experiences. Thanks to AI CRM software, you can:
- Create highly personalized customer experiences
- Automate lead scoring, and
- Enhance your processes and productivity
What does the future look like for AI and CRMs? AI is developing at an incredible pace. Over the next year or two, we predict that AI will be able to analyze and extract even vaster amounts of data.
Ultimately delivering more refined insights on leads and customers and intelligently utilizing this data to enhance predictive analytics, personalized product recommendations, and workflow automations.
