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Looker vs. Tableau: An In-Depth Data Analysis Showdown 2024

By: Don Hall
10 April 2024 at 10:00

Key takeaways

  • Tableau specializes in creating visualization dashboards and has pre-made templates. It’s cost is based on a per-user license and is ideal for smaller businesses.
  • Looker is a browser-based intelligence software that can also operate on mobile. Looker’s cost is on a per-month basis and while it is more expensive than Tableau, it offers more extensive features.

When comparing Looker vs. Tableau, two of the most popular business intelligence (BI) software tools on the market today, it’s crucial to have the facts laid out as clearly as possible before making a decision.

Business intelligence software executes data preparation and management, data querying, predictive analytics, and many other analytical tools that help managers make better decisions based on BI outputs. We will look at the features of each BI software tool to give readers more insight into which product will best fit their companies.

TechnologyAdvice is able to offer our services for free because some vendors may pay us for web traffic or other sales opportunities. Our mission is to help technology buyers make better purchasing decisions, so we provide you with information for all vendors — even those that don’t pay us.

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Google Looker logo.

Looker

Overall Score

4.16/5

Pricing

3.13/5

General Features & Interface

3.75/5

Core Features

5/5

Advanced Features

4/5

Integration & Compatibility

5/5

UX

3.75/5

Pros

  • Powerful data modeling
  • Scalable to handle large datasets
  • Highly customizable
  • Free tier

Cons

  • Cost
  • Mixes reviews on customer supper
  • Limited data security due to cloud hosting

Looker is a cloud-based Business Intelligence (BI) platform purchased by Google in 2019. Designed to offer insights and analytics, its strength lies in the powerful data modeling layer. This layer emphasizes a “single source of truth” model, ensuring accurate metric readings by consolidating information from various sources onto one dashboard.

Looker’s data modeling allows users to define intricate information and create reusable models. These can be used throughout the platform, ensuring data consistency and accuracy. This approach streamlines data exploration, giving users confidence in the displayed data.

The 23.4 release introduced the Looker Studio Connector and Connected Sheets for all Looker-hosted instances. This enhancement allows users to access and analyze Looker-modeled data, expanding the platform’s capabilities. Another feature, the Performant Field Picker Labs, offers refined search options for large Explore field pickers.

Data Exploration and Discovery: Looker allows users to explore and discover data in real-time using an intuitive interface that requires no SQL knowledge.

Customizable Dashboards: Users can create and share interactive, customizable dashboards that offer a comprehensive view of business metrics.

Integrated Workflow: Looker integrates seamlessly with other tools, enabling users to embed insights directly into business workflows and applications.

Data Modeling Layer: The LookML modeling layer enables users to define business logic centrally, ensuring consistency across all analytics.

Collaborative Data Analytics: Looker supports collaboration by allowing users to share data insights with team members through links, dashboards, or scheduled reports.

Real-Time Data Insights: Looker provides real-time insights, enabling businesses to act on the most current data available.

Embedded Analytics: Organizations can embed Looker’s analytics capabilities into their own applications to offer data-driven experiences.

Robust Security and Compliance: Looker offers enterprise-grade security features and compliance certifications, ensuring that data remains safe and secure.

Looker business intelligence Dashboard view.
Looker business intelligence Dashboard view.
Looker dashboard.
Looker business intelligence Dashboard view.
Looker business intelligence Dashboard view.
Looker business intelligence Dashboard view.
Tableau logo.

Tableau

Overall Score

4.34/5

Pricing

3.13/5

General Features & Interface

3.75/5

Core Features

5/5

Advanced Features

4/5

Integration & Compatibility

5/5

UX

3.75/5

Pros

  • User-friendly interface
  • Excellent data visualization capabilities
  • Ability to blend data from multiple sources

Cons

  • Slow performance when working with large datasets
  • Additional software required for advanced data cleaning

Tableau is a data visualization and business intelligence (BI) tool designed to help users interpret and understand their data.

Through its interface, users can create visual representations like dashboards, reports, and charts from raw data. The software allows for data integration from various sources, from databases to cloud services. Over time, Tableau has been adopted by many due to its straightforward features and ability to handle complex data sets. With each release, including the 2023.1 update, Tableau introduces modifications and improvements, reflecting feedback and the changing landscape of data analysis.

  • Data Visualization: Tableau excels in creating powerful, interactive visualizations that help users understand complex data intuitively.
  • Drag-and-Drop Interface: The drag-and-drop interface allows users to easily create visualizations and dashboards without the need for advanced technical skills.
  • Data Blending: Tableau enables users to combine data from multiple sources into a single view, providing a holistic perspective.
  • Real-Time Data Analysis: Users can connect to live data sources and perform real-time analysis to make timely decisions.
  • Dashboard Sharing and Collaboration: Tableau allows users to share dashboards and collaborate with others, enhancing teamwork and decision-making.
  • Mobile-Friendly Dashboards: Dashboards in Tableau are optimized for mobile devices, ensuring accessibility and usability on the go.
  • Advanced Analytics and Calculations: Tableau offers built-in tools for performing advanced analytics, such as trend analysis, forecasting, and statistical modeling.
  • Integration with Other Tools: Tableau integrates with a wide range of data sources and tools, including cloud services, databases, and spreadsheets, making it versatile and adaptable.

Looker vs. Tableau: A detailed comparison

Business intelligence software has many tools to provide insightful details managers can use. However, to get the most out of one of these tools, managers need to know the company size, the types of charts and graphs needed, and the business analytical requirements.

With that data in hand, one can use this comparison as a tool to help make your final decision the right decision. 

Looker vs. Tableau: Commonalities

Looker and Tableau are both comprehensive, flexible, and scalable solutions that prioritize user accessibility and collaboration. While they each have their unique strengths and weaknesses, these core commonalities make them leading choices in the realm of business intelligence software:

Looker and Tableau both offer an array of BI tools to help businesses make informed decisions using advanced Machine Learning (ML) concepts.

Both platforms are incredibly user-friendly.

You don’t need to be a data scientist to navigate through them; they’re built for everyone from the intern in the marketing department to the CFO. This universal appeal is what makes them so indispensable.

It’s like having a universal remote for all your data sources.

Integration is another area where both stand out. Whether your data lives in the cloud, in SQL databases, or even in good old Excel sheets, Looker and Tableau make it a easy to pull that data in.

Let’s talk about scalability.

Looker and Tableau have engineered their platforms to be highly scalable so they grow alongside your business.

Tableau offers a distributed server architecture that allows you to add more server nodes as your data and user base expand. This means you can handle larger data sets and more concurrent users without sacrificing performance.

Looker leverages an in-database architecture, allowing it to push queries to the database itself. This ensures that as your data grows, you can scale your database resources to maintain high-speed analytics. Both platforms also offer cloud-based solutions, providing the elasticity to quickly scale up or down based on your needs.

Both tools are big on teamwork.

They offer nifty collaboration features that make it easy to share insights, annotate findings, and even distribute reports. It’s like a virtual huddle for your team, where everyone gets to contribute to the game plan.

Also read: Tableau Alternatives

Looker vs. Tableau: Key differences

Looker is fully deployed as a browser-based intelligence software with no desktop installation requirement. In addition, Looker offers a mobile app solution. Tableau is a desktop-based platform with a Tableau license for cloud access but with limited cloud capabilities. Looker uses its version of structured query language called LookML with pre-built Looker Blocks. Tableau uses a spatial file connector to create maps.

While those are substantial differences, when it comes to team-facing features, the two titles serve the same overall purpose.

What are the key features of Looker?

Looker business intelligence dashboard presenting data and analytics.
Looker dashboard.

Looker offers several key features that will enhance the ability to view data in real-time, build applications with embedded analytics, and provide proactive insights with instant alerting for quicker decision-making. Here are some of the key features of Looker:

SQL-based type language used for data modeling and complex data analysis.

Used to create unique applications or modify existing applications with embedded analytics.

Allows users to develop reports in ad-hoc or governed data environments, which allows for data analysis in ad-hoc and governed data environments.

Looker API is used for calling data while providing a secure RESTful API that allows users to create custom applications, workflows, and scripts that can automate tasks.

Looker is owned by Google and is built on their cloud infrastructure that is available as a service to allow users to manage their Looker instances.

Predefined and pre-built code that expedites the development of applications, workflows, and analytics.

A development platform that helps developers build Looker applications while automatically performing some of the necessary steps to save time.

Looker has a mobile solution for any Internet-connected mobile device that users can access using a QR code or biometric authentication.

Provides expected authentication and access controls that help businesses stay within compliance regulations.

Interface code that helps developers create filter controls like radio buttons, sliders, and tag lists, which can be embedded in applications or dashboards.

What are the key features of Tableau?

Tableau business intelligence dashboards shown on desktop, tablet, and mobile.

Tableau’s focus is on creating sophisticated visual representations of data. As a result, Tableau allows users to quickly analyze large amounts of data that can be converted into reports. Tableau has a heavy focus on dashboards, but here are some other key features of this BI solution:

Offers a wide variety of visual objects and text elements that can form stories or provide multiple views, layouts, and formats using the available filters.

Provides instant data sharing for quick reviews of dashboards and data visualization.

The ability to connect to live data sources or extract data from external sources allowing a user to access data from multiple sources without limitations.

A primary feature that allows users to create a wide variety of data visualizations.

Pre-installed map information on cities, and the maps can contain geology layers.

Tableau has a foolproof security system that uses authentication and a permission methodology for user access and data connections.

The ability to create views to be seen on iOS and Android devices.

Allows users to type a query about data using their natural language and the ability of this feature to respond with text or a visual representation as an answer.

Uses time series forecasting by selecting historical time-stamped data

Looker vs. Tableau: Pricing

Looker pricing:

  • Platform pricing: Looker offers three editions—Standard, Enterprise, and Embed. The Standard edition costs $5,000 per month with a pay-as-you-go model. Enterprise and Embed editions require you to call sales for an annual commitment.
  • User licensing: Looker offers three types of user licenses—Viewer ($30/user/month), Standard ($60/user/month), and Developer ($125/user/month). These fees are consistent across all editions.

Tableau pricing:

  • License tiers: Tableau offers three tiers—Creator, Explorer, and Viewer. The Creator license is $70/user/month for the cloud version and $35/user/month for on-premise. The Explorer license is $42/user/month for cloud and $20/user/month for on-premise. The Viewer license is $15/user/month for cloud and $10/user/month for on-premise.
  • Enterprise package: Tableau also offers an enterprise package with custom pricing.
  • Additional Costs: Some users have noted that Tableau may require additional tools for data extraction, adding to the total cost.

Key takeaways

  • Looker offers a more customized pricing model, allowing for tailored solutions. Tableau offers fixed pricing tiers, which may or may not suit all organizational needs.
  • Both platforms offer tiered user licensing but differ in costs and capabilities.
  • Tableau provides upfront pricing, whereas Looker requires you to engage with their sales team for most of their offerings.

Looker vs. Tableau: Feature comparison overview

As you can see, Looker and Tableau have different key features available to users. This section will look at some of the expected features of a business intelligence and data analytics software solution.

FeatureLookerTableauAdvantage
Data VisualizationLooker provides a dynamic dashboard filter feature that can filter for data visualization types and specific users or groups. Looker also has a mapping feature to aid in chart creation.Tableau specializes in visualization dashboards and infographics. Tableau provides pre-made templates and has a wizard feature that helps non-technical users.Tableau business analytics logo.
IntegrationLooker integrates with big data platforms and databases and can execute queries without extracting dataTableau has over 200 connectors that can connect to multiple sources such as RDBMS, spreadsheets, Presto, SQL Server, Cloudera, Hadoop, Amazon Athena, and SalesforceTableau business analytics logo.Looker Logo
Data ModelingLookML is a data modeling tool that is reusable and flexible. LookML has pre-built modeling called Looker Blocks used to build sophisticated query analytics  Tableau uses snowflakes and dimensional data models that help improve the performance of queriesLooker Logo
ReportingProvides basic reporting templatesUsers can build customized reports with extensive connectors to create dashboards and reportsTableau business analytics logo.
SpeedLooker is slower, and users may need several hours to share a reportAllows a user to create visualization reports in short periodsTableau business analytics logo.
Advanced AnalyticsLooker pre-built code blocks are configurable, and LookLM allows for a deeper analytical review of dataTableau does not have pre-built code blocks, but it is more configurable than LookerLooker Logo
SecurityLooker provides an admin panel to change security settings and 2-factor authenticationTableau allows a user to protect reports and dashboards, but not with the detail of LookerLooker Logo
Mobile SupportLooker’s mobile app allows you to view data using any browser with an Internet connection. Emails and chat sessions are available too. Users can log in using a QR code or biometricsAndroid and iOS devices can use Tableau’s mobile web applicationLooker Logo
PricingFor a company, $5,000/per month, but Looker offers a variety of business plans depending on sizeTableau’s creator license cost per user is $70/per month, and for a viewer, it’s $15/per monthTableau business analytics logo.

Looker vs. Tableau: Which BI software is right for your business

The best BI solution is subjective since every company’s situation differs slightly. For example, a company that uses Salesforce may lean towards Tableau since Salesforce purchased Tableau four years ago. Any company heavily invested in using Google products may lean towards Looker. Just because a company uses Google or Salesforce products should not be the basis for a decision.

Other factors to consider are the existing infrastructure, analytical data needs, and storage preferences, whether cloud or local, are only a subset of reasons why a company may choose one BI product over the other.

How to choose between Tableau vs Looker

A business need for a BI software solution was identified as a requirement. Next, the company generates a list of requirements on why BI software is needed. These requirements vary from company to company, but they are the driving force behind choosing a BI solution. Finally, decision-makers are on track to make the right decision using the key features and the comparison overview along with additional research.

Looking for the latest in Business Intelligence solutions? Check out our Business Intelligence Software Buyer’s Guide.

Frequently Asked Questions (FAQ)

When comparing Looker vs Tableau, know both are powerful BI tools, but they serve different needs. Looker excels in data modeling and integration with SQL-based databases, while Tableau is known for its advanced visualizations and ease of use. The choice depends on your specific requirements.

The downside of Looker is its reliance on SQL for data exploration, which can be a barrier for non-technical users. Additionally, its pricing can be prohibitive for smaller businesses, and it may require more setup and customization compared to other BI tools.

Looker is expensive due to its robust data modeling capabilities, enterprise-level features, and deep integration with SQL databases. The cost reflects the advanced functionality, scalability, and customization options it offers to large organizations.

Yes, Looker is owned by Google. It was acquired by Google in 2020 and is now part of the Google Cloud ecosystem, enhancing its integration with other Google Cloud services.

Tableau is better for users seeking intuitive, visually rich analytics with minimal setup, while Looker is preferred for those needing strong data modeling and SQL-based querying. The best choice depends on your business needs and technical expertise.

Tableau uses a distributed server architecture to manage increased data and user loads, whereas Looker relies on in-database processing to scale alongside your database resources.

The post Looker vs. Tableau: An In-Depth Data Analysis Showdown 2024 appeared first on TechnologyAdvice.

The Best AI CRM for 2024

28 May 2024 at 16:50

Businesses constantly seek innovative ways to understand, engage, and retain customers. AI-powered customer Relationship Management (CRM) software facilitates this by blending artificial intelligence and customer relationship management. This breakthrough addition to sales software promises to transform how companies interact with their clientele.

At its core, an AI-powered CRM system integrates artificial intelligence capabilities with traditional CRM functionalities. It’s not just about storing customer data anymore; it’s about analyzing, predicting, and automating real-time interactions. 

As AI is becoming an integral factor in the software we use daily, we decided to curate a list of our top picks for AI CRM solutions:

Software Spotlight: HubSpot
HubSpot’s AI capabilities are transforming CRM from a reactive tool into a proactive, strategic asset for businesses.
HubSpot logo.
  • Embedded directly on your website, chatbots understand user behaviors and predict needs, offering instant, personalized solutions without human intervention.
  • The AI website builder can create an aesthetically pleasing, SEO-optimized site with just a few prompts.
  • By analyzing your business’s tone, audience demographics, and content preferences, HubSpot’s content assistant helps in crafting blog posts, emails, landing pages, and ad copies that resonate with your target audience.
  • HubSpot’s AI features include enhanced reporting tools, providing detailed sales forecasts and analytics.
This is a paid placement. However, our team of experts approved it as an appropriate product and our content remains editorially independent.

Our choices for the top AI CRM software

HubSpot CRM: Best free AI CRM


Pros

  • Automatic lead scoring
  • Email optimization
  • Versatile chatbots
  • Content recommendations based on preferences and behaviors
  • Sales forecasting

Cons

  • Some advanced AI features are only available at higher price tiers
  • Unexpected results and incorrect predictions reported
HubSpot logo in dark blue and orange with spikes coming from the letter O.

Our Rating: 4.6/5

Lead scoring: HubSpot’s AI assigns scores to leads based on their conversion likelihood, aiding sales prioritization.

Email sentiment analysis: The tool gauges email sentiments to categorize them as positive, negative, or neutral.

Chatbots: Customizable chatbots in HubSpot handle inquiries, schedule meetings, and qualify leads.

Content recommendations: The AI recommends content based on a visitor’s website behavior, enhancing engagement.

Sales forecasting: HubSpot predicts future sales trends using past data, assisting in strategy planning.

Free plan available

Paid plan starting at $45/user/month

HubSpot offers a user-friendly interface that seamlessly integrates AI-driven features, enhancing the efficiency and accuracy of sales and marketing processes. 

The AI-assisted lead scoring system is particularly noteworthy, as it automatically prioritizes leads based on their likelihood to convert, ensuring that sales teams focus their efforts where they matter most. Additionally, the platform’s email sentiment analysis provides invaluable insights into customer sentiments, allowing for tailored communication strategies. Including predictive lead scoring, customizable chatbots, content recommendations, and sales forecasting further cements HubSpot’s position as a leader in the CRM space. These advanced features, combined with its availability at no cost, make HubSpot CRM an unbeatable choice for businesses seeking an AI-enhanced CRM solution without the hefty price tag.

Pricing: 5/5

General features and interface: 4.6/5

Core features: 5/5

Advanced features: 4/5

AI and automation: 3.8/5

Integration and compatibility: 5/5

UX: 4.8/5

HubSpot is a developer and marketer of software products for inbound marketing, sales, and customer service. Founded in 2006, the company’s software has been adopted by businesses worldwide to “attract, engage, and delight customers,” according to HubSpot. 

HubSpot’s journey began with a focus on inbound marketing, a strategy that aims to attract customers through content and interactions that are relevant and helpful. Over the years, the company expanded its product suite to include CRM, sales, and service hubs. The introduction of AI into its platform was a natural progression, given the increasing importance of data-driven decision-making in modern business.

Freshsales: Best for AI-powered chatbot tools


Pros

  • “Freddy” AI automates sales process
  • Affordability compared to competitors
  • Multi-language support
  • Built-in telephony

Cons

  • Free CRM does not include AI capability
  • Fewer integrations compared to competitors 

Our Rating: 4.3/5

Visitor tracking: Monitors website user journeys, providing insights into how potential customers interact with your online presence.

Real-time customer service: Engages with customers in real-time, answering queries and providing instant support.

Automated email campaigns: Automated marketing campaigns, ensure timely and relevant communication with leads and customers.

360-degree customer profiles: Provides comprehensive profiles of customers, including insights into previous interactions.

Lead qualification and intelligent insights: Qualifies leads based on various parameters, ensuring that the sales team focuses on high-potential prospects. It also provides intelligent insights to guide sales strategies.

Automated triggers: Automatically triggers actions such as sending welcome emails, making calls, or sending notifications based on specific customer behaviors or milestones.

Free plan available for up to 3 users

Growth Plan: $9/user/month billed annually or $11/user/month billed monthly

Features: Contact, deal & account management, tasks, appointments, notes, activity dashboard, rename modules, basic custom fields, product catalog, workflows (20), visual sales pipelines, multiple sales pipelines (10), sales goals, data storage (2 GB per user), two-way email sync, sales sequences (5 per user), custom reports, website tracking, built-in phone.

Pro Plan: $39/user/month billed annually or $47/user/month billed monthly

Features: All features from the GROWTH plan plus advanced custom fields, workflows (50), sales sequences (10 per user), predictive contact scoring, and live chat.

Enterprise Plan: $59/user/month billed annually or $71/user/month billed monthly

Features: All features from the PRO plan plus workflows (100), sales teams (max 100), data storage (100 GB per user), sales sequences (25 per user), AI-powered deal insights, WhatsApp Business, AI-powered forecasting insights, transactional emails, custom modules, dedicated account manager.

The primary reason for this selection is Freshsales’ integration of Freddy AI, a state-of-the-art artificial intelligence system to enhance customer interactions. Freddy AI automates routine tasks and offers predictive insights, making the sales process more efficient and data-driven. Furthermore, Freshsales’ AI chatbot capabilities excel in real-time customer engagement, providing instant support and nurturing leads outside regular business hours. The platform’s seamless integration capabilities mean the chatbot can access customer data in real time, offering personalized responses based on past interactions and preferences. Additionally, the intuitive interface and robust analytics tools of Freshsales make it easier for businesses to track chatbot performance and optimize strategies.

Pricing: 4.8/5

General features and interface: 4.6/5

Core features: 5/5

Advanced features: 3.1/5

AI and automation: 3.8/5

Integration and compatibility: 4.2/5

UX: 4.5/5

Freshsales, developed by Freshworks, is a CRM solution that offers tools that streamline the sales process, from lead management to email and event tracking. 

Its chatbots are designed to engage customers in real time, providing immediate responses to queries, offering support, and nurturing leads around the clock. This ensures that businesses remain responsive to potential opportunities at all times. Freshsales boasts the inclusion of Freddy AI, a sophisticated artificial intelligence system. Freddy AI not only automates routine tasks but also delivers predictive insights, enhancing the efficiency and data-driven approach of the sales process. Its ability to access real-time customer data allows for personalized interactions, making each engagement more meaningful and tailored to individual customer needs.

Pipedrive: Best for AI sales suggestions


Pros

  • Chatbot provides extensive communication tools
  • AI enhances lead capture and data collection
  • AI sales assistance

Cons

  • No free version
  • Less comprehensive than larger competitors
Pipedrive logo.

Our Rating: 4.3/5

AI-powered sales assistant bot: Provides next-step suggestions by analyzing sales data to enhance salespeople’s productivity.

Performance-based tips: Uses algorithms to offer insights and tips for improving the sales workflow.

Notifications and insights: Centralizes all notifications, enhancing transparency and team collaboration.

Progress updates: Offers AI-powered insights on performance trends through graphical representations.

Activity-based suggestions: Reacts to user activity with quick tips and data for workflow optimization.

Automated sales expertise: Sends intelligent notifications, insights, and advice to streamline the sales process.

Essential: $24/user/month 

Advanced: $44/user/month 

Professional: $64/user/month 

Power: $79/user/month 

Enterprise: $129/user/month

Pipedrive’s AI-Powered Sales Assistant Bot can analyze vast amounts of sales data and provide actionable next-step suggestions. This feature not only enhances the productivity of sales teams but also ensures that no potential lead or opportunity is overlooked. 

Pipedrive’s performance-based tips, driven by sophisticated algorithms, offer invaluable insights that guide sales strategies and decision-making. The centralized notification system further ensures that sales reps are always informed and aligned, fostering efficient collaboration. The platform’s progress updates, presented through intuitive graphical representations, provide a clear view of performance trends, enabling teams to adjust strategies in real time.

Pricing: 3.6/5

General features and interface: 4.6/5

Core features: 5/5

Advanced features: 3.1/5

AI and automation: 4.3/5

Integration and compatibility: 4.6/5

UX: 5/5

Pipedrive is a leading CRM platform emphasizing ease of use, visual sales pipelines, and effective lead management. What truly sets Pipedrive apart, however, is its integration of advanced AI features and tools. The AI-Powered Sales Assistant Bot analyzes sales data in real time to provide actionable next-step suggestions, ensuring that sales reps are always focused on the most promising leads and opportunities. 

The platform also boasts centralized notifications and insights, keeping sales reps informed and aligned, and its progress updates give a clear snapshot of performance trends.

Zoho CRM: Best for broad AI capabilities


Pros

  • AI chatbot assistant
  • Smart sales forecasting and other predictive tools
  • Filter deal records based on AI predictions
  • Talent assignment based on prediction scores
  • Conversational AI

Cons

  • Limited storage 
  • No option for white labeling or re-branding
zoho crm logo

Our Rating: 4.2/5

Generative AI: Zia, powered by ChatGPT, can autonomously generate business emails and social media posts.

Ticket answering: Zia can automatically respond to customer support tickets.

Meeting summaries: Zia is capable of creating concise meeting minutes from discussions.

OpenAI integration: Zia integrates with OpenAI to enhance its content generation capabilities.

Native AI capabilities: Zia offers built-in AI tools that seamlessly integrate with the Zoho ecosystem.

Privacy emphasis: Zoho ensures AI operations prioritize user data privacy and security.

Standard: $14/user/month 

Professional: $23/user/month 

Enterprise: $40/user/month 

Ultimate: $52/user/month

Zoho CRM’s AI assistant has multifaceted features, ranging from autonomously generating business emails to responding to customer support tickets. The integration with OpenAI further amplifies Zia’s content generation capabilities, making it a powerful tool for diverse business needs. Additionally, Zia’s ability to create concise meeting summaries ensures that key discussions are never missed, streamlining team communication. The platform’s native AI tools, designed to integrate with the Zoho ecosystem seamlessly, offer a holistic approach to managing and analyzing data.

Pricing: 3.9/5

General features and interface: 4.6/5

Core features: 4.5/5

Advanced features: 3.1/5

AI and automation: 4/5

Integration and compatibility: 4.4/5

UX: 4.3/5

Zoho’s Zia AI is an intelligent assistant designed to enhance the capabilities of the Zoho ecosystem. As an integral part of Zoho CRM, Zia offers predictive sales analytics, lead scoring, and even sentiment analysis to gauge customer feelings based on their interactions. Beyond CRM, Zia’s capabilities extend to automating routine tasks, offering smart solutions based on data-driven insights, and even assisting in content generation. The AI is designed to learn from user interactions over time, continuously improving its suggestions and automating more tasks. Zia can also answer queries, provide real-time notifications, and generate reports, making it a versatile tool that aids in various business processes.

Zendesk Sell: Best for AI lead management


Pros

  • Centralized customer communications
  • Omnichannel support
  • Customer support AI chatbots
  • Automated lead nurturing
  • Mobile accessibility

Cons

  • Lacks advanced AI predictive analysis
  • Limited email template customization
Zendesk Sell logo

Our Rating: 4/5

Lead scoring: Utilizes AI to prioritize leads based on their conversion likelihood, ensuring sales teams focus on the most promising prospects.

Sales forecasting: AI-driven predictions provide insights into future sales trends, helping teams prepare and strategize.

Email sentiment analysis: Analyzes email content to gauge the sentiment of the communication, allowing sales reps to tailor their approach.

Automated data entry: Reduces manual data input by automatically populating lead and deal information from various sources.

Smart notifications: AI-driven reminders and alerts ensure timely follow-ups and actions on important tasks or deals.

Recommendation engine: Offers suggestions on the next best actions to take with leads or deals based on historical data and predictive analytics.

Sell Team: $19/user/month

Sell Growth: $55/user/month

Sell Professional: Price: $115/user/month

Sell Enterprise: $169/user/month

Zendesk Sell’s AI-driven lead scoring system ensures that sales teams prioritize leads with the highest potential, optimizing both time and resources. Automated lead nurturing, encompassing email and SMS, ensures consistent and personalized engagement, enhancing conversion rates. Furthermore, its predictive sales forecasting offers invaluable insights into future sales trends, enabling proactive strategy adjustments. The platform’s intuitive design, complemented by features like email sentiment analysis and smart notifications, empowers sales teams to deliver tailored interactions, fostering stronger customer relationships.

Pricing: 3.6/5

General features and interface: 4.5/5

Core features: 4.1/5

Advanced features: 3.1/5

AI and automation: 4/5

Integration and compatibility: 4/5

UX: 4.7/5

Zendesk Sell is a dynamic CRM offering a blend of traditional CRM functionalities and advanced AI capabilities. At its core, Zendesk Sell streamlines the sales process, ensuring leads, contacts, and deals are efficiently managed. What sets it apart, however, is its AI integration. 

The platform boasts an AI-driven lead scoring system that intelligently prioritizes leads, ensuring sales efforts are directed towards the most promising prospects. Automated lead nurturing, facilitated through AI, ensures personalized and timely engagement with potential customers. Predictive sales forecasting, another AI feature, provides invaluable insights into potential sales trends, enabling teams to strategize proactively. Features like email sentiment analysis offer a deeper understanding of customer interactions, allowing for more tailored communication.

What is AI CRM?

Artificial Intelligence Customer Relationship Management (AI CRM) integrates machine learning and other AI technologies into CRM software to automate, enhance, and optimize customer relationship management processes. It enables businesses to analyze vast amounts of customer data in real time, offering predictive insights, automating routine tasks, and personalizing customer interactions. 

AI CRM can intelligently prioritize leads, forecast sales trends, and provide chatbot support, among other functionalities. By harnessing AI, CRM systems become more proactive, helping businesses anticipate customer needs, streamline operations, and ultimately drive sales and customer satisfaction. The integration of AI into CRM represents the next evolution in customer relationship management, making it more efficient and data-driven.

How does AI work in CRM?

AI in CRM works by leveraging machine learning, natural language processing, and predictive analytics to enhance customer relationship management. It sifts through vast amounts of data to identify patterns, trends, and insights that would be challenging for humans to detect. For instance, AI can analyze customer interactions to predict which leads are most likely to convert, helping sales teams prioritize their efforts. It can also automate routine tasks, such as data entry or lead scoring, improving efficiency. 

Chatbots, powered by AI, can handle basic customer inquiries 24/7, ensuring immediate response. Predictive analytics can forecast sales trends, helping businesses strategize effectively. Furthermore, natural language processing aids in sentiment analysis, gauging customer feelings from their communications.

Benefits of integrating AI into CRM

Integrating AI into CRM offers a plethora of benefits that enhance business operations and customer relationships:

Enhanced lead scoring: AI can analyze vast amounts of data to prioritize leads based on their likelihood to convert, ensuring sales efforts are directed efficiently.

Automated routine tasks: AI can handle repetitive tasks such as data entry, appointment scheduling, and follow-up reminders, freeing up staff for more strategic activities.

Predictive analytics: AI can forecast sales trends, customer behaviors, and potential churn, enabling businesses to strategize proactively.

Personalized customer interactions: AI analyzes customer data to tailor marketing campaigns, product recommendations, and communications to individual preferences.

24/7 customer support: AI-powered chatbots can handle basic inquiries round the clock, ensuring immediate response and improved customer satisfaction.

Sentiment analysis: By analyzing customer communications, AI can gauge sentiments, helping businesses address concerns and capitalize on positive feedback.

Enhanced data analysis: AI can sift through vast datasets, extracting actionable insights that can drive decision-making.

Improved efficiency: With AI handling data analysis and automation, CRM processes become faster and more streamlined.

Reduced errors: AI minimizes human errors in data entry, analysis, and prediction, ensuring more accurate outcomes.

Continuous learning: As AI systems process more data, they continually refine their algorithms, improving performance over time.

Real-world applications

Einstein GPT (Salesforce):

Salesforce’s Einstein GPT is a generative AI technology that enhances the CRM platform’s capabilities. It processes real-time data, performing over 1 trillion predictive analyses every week. Its integration with platforms like OpenAI further amplifies its AI capabilities, enabling businesses to refine their consumer engagement strategies.

Generative AI for Call-Center CRM (IBM Consulting):

Bouygues Telecom, a mobile phone company, collaborated with IBM Consulting to boost its call center operations using generative AI. IBM introduced generative AI models for automatic call summarization and topic extraction. This integration updated the CRM with precise and actionable insights, leading to over $5 million in savings and a 30% reduction in call operations.

Use cases of generative AI in CRM

Answering simple requests: Generative AI can autonomously respond to basic CRM queries, such as details about a customer’s last purchase or address updates.

Shipping process control: It can manage shipping processes by generating optimal shipping routes based on real-time data, predicting potential shipping issues, and auto-generating customer updates about their order’s shipping status.

Payment automation: Generative AI can craft payment-related communications tailored to each transaction or client. For instance, it can auto-generate polite reminder messages for overdue invoices.

Recommendation system: By analyzing a customer’s purchase history and preferences, generative AI can suggest products they might be interested in, enhancing personalized marketing efforts.

Data collection: Generative AI can auto-populate CRM fields with minimal input, streamlining data entry processes for sales and service teams.

These real-world applications and use cases underscore the transformative potential of integrating generative AI into CRM systems, offering businesses innovative tools to enhance customer interactions and streamline operations.

Measuring ROI of AI CRM

Integrating Artificial Intelligence (AI) into Customer Relationship Management (CRM) systems has been a game-changer for many businesses. But how can companies effectively measure this integration’s Return on Investment (ROI)?

Enhanced customer interactions: With most CRM users seeking AI or machine learning capabilities when choosing software, the improved customer interactions resulting from AI integration can be a significant metric. Track customer satisfaction scores, Net Promoter Scores (NPS), and customer retention rates before and after AI implementation.

Operational efficiency: AI can automate routine tasks, freeing up employees for high-value work. Measure the time saved on tasks like data entry, lead scoring, and customer query responses. For instance, Bouygues Telecom reduced call operations by 30% with AI integration.

Sales forecasting accuracy: AI-enhanced CRMs, like Salesforce’s Einstein GPT, can perform predictive analyses, improving sales forecasting. Compare the accuracy of sales forecasts before and after AI integration to gauge improvements.

Increased sales and upselling: AI-driven recommendation systems can suggest products based on a customer’s purchase history. Monitor the uptick in sales and the success rate of upselling campaigns post-AI integration.

Cost savings: Track cost savings resulting from AI-driven efficiencies. For example, IBM’s generative AI models led to savings of over $5 million for Bouygues Telecom.

Data-driven decision-making: AI can provide actionable insights from vast datasets. Measure the increase in data-driven decisions and the success rate of strategies based on these insights.

To effectively measure the ROI of AI in CRM, businesses must set clear benchmarks before implementation and continuously monitor performance metrics post-integration. By doing so, they can understand the value AI brings to their CRM processes.

The future of customer relationships

As we stand on the cusp of a new era in customer relationship management, integrating AI into CRM systems heralds a transformative shift. No longer are CRM systems mere repositories of customer data; they are evolving into intelligent platforms capable of proactive decision-making, predictive analytics, and personalized customer interactions. 

The fusion of AI with CRM is not just enhancing operational efficiency; it’s reshaping the very fabric of customer relationships. Businesses can anticipate customer needs, tailor interactions with unparalleled precision, and foster deeper, more meaningful connections. As AI advances, we can expect even more nuanced and personalized customer experiences, solidifying its role as an indispensable tool in shaping the future of customer relationships. 

In this landscape, businesses that embrace and integrate AI-driven CRM solutions will undoubtedly lead the charge, setting new standards for customer engagement and satisfaction.

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AI CRM Frequently Asked Questions (FAQ)

An AI CRM is a Customer Relationship Management system that uses artificial intelligence to automate tasks, analyze customer data, and provide insights, enhancing customer interactions and sales processes.

CRM leverages AI to enhance customer interactions, predict sales trends, automate tasks, and provide personalized marketing insights.

You should look for a CRM with AI to optimize customer engagement, streamline operations, and make data-driven decisions efficiently.

Three examples of AI in CRM are chatbots for customer service, predictive analytics for sales forecasting, and personalized marketing automation.

AI is transforming CRM by automating routine tasks, providing actionable insights through data analysis, improving customer engagement, and enhancing decision-making with predictive analytics.

The future of AI CRM includes advanced personalization, predictive analytics, and deeper integration with other technologies, driving more efficient and effective customer relationship management.


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