Written by Minami — Paddy & Water Inc. / Technology & Platform

Product Lineup, Data Model, Deal/Project Concepts, AI, and Industry Use Cases

July 2026 Edition

This report provides a systematic overview of the CRM and enterprise platform offered by Salesforce, covering its product lineup, data architecture, core concepts of Opportunities/Projects/Cases, AI agent capabilities, and industry-specific use cases. Based on Salesforce’s public information, Forrester research, and industry surveys (2025-2026), this report is intended as a reference for CRM strategy planning and system design.

Chapter 1: Salesforce Overview and Business

1-1 Company Overview

• Company name: Salesforce, Inc. (headquartered in San Francisco, California, USA)

• Founded in 1999: Marc Benioff (formerly of Oracle) founded the company from an apartment in Hawaii under the slogan “The End of Software,” becoming a pioneer in delivering CRM as SaaS to the world ahead of its peers

• Scale as of 2026: annual revenue of approximately $37 billion (roughly 5.6 trillion yen), around 73,000 employees worldwide, and more than 150,000 customer companies globally

• As of February 2026: listed on the Forbes Global 2000 and ranked among “World’s Most Innovative Companies” for 12 consecutive years (Forbes 2024)

Metric	FY2024	FY2025	Growth Trend
Annual revenue	Approx. $34.4 billion	Approx. $37.4 billion	9% year-over-year growth
Number of customers	150,000+ companies	150,000+ companies	Focus centered on deepening relationships with large enterprises
Number of Agentforce deals (AI)	None in FY24 (new product)	29,000+ (Q4 FY25 alone)	Rapid quarter-over-quarter expansion
Agentforce ARR	–	Approx. $800 million (FY25 full-year outlook)	FY26 target of over $1 billion

1-2 Product Brand Structure (After the 2025 Rebranding)

In 2025, Salesforce announced a transition to the Agentforce brand, restructuring its previous “XX Cloud” naming convention into an “Agentforce for XX” format.

Former Brand Name	New Brand Name (2025-)	Main Feature Category	Primary Users
Sales Cloud	Agentforce Sales	SFA, deal management, forecasting, partner management	Sales reps, sales managers
Service Cloud	Agentforce Service	Case management, support, field service	CSRs, support teams, field technicians
Marketing Cloud / Pardot	Agentforce Marketing / Account Engagement	Email, social media, advertising, lead nurturing, B2B marketing automation	Marketing staff, digital marketers
Commerce Cloud	Agentforce Commerce	B2B/B2C e-commerce sites, order management, repeat purchases	E-commerce staff, merchandisers
Analytics Cloud / Tableau	Tableau + Salesforce Analytics	BI dashboards, self-service analytics, AI forecasting	Executives, business owners, data analysts
Data Cloud (formerly Genie)	Salesforce Data 360	Customer Data Platform (CDP), identity graph, real-time data integration	Data engineers, marketing automation teams
Einstein AI	Agentforce AI	AI agent foundation, Einstein Copilot, forecasting, recommendations	Common foundation across all products
MuleSoft	MuleSoft (unchanged)	API integration, data integration, iPaaS	Integration specialists, developers
Slack	Slack (unchanged)	Team collaboration, CRM integration	All employees

Chapter 2: A Detailed Look at the Salesforce Data Model

2-1 Basic Concepts of the Salesforce Data Model

Salesforce’s data model inherits the thinking of relational databases, but it is distinguished by a design philosophy that allows business users to customize data structures without programming. Understanding the data model is fundamental to designing and using Salesforce effectively.

Objects and Records

• Object: A concept equivalent to a “table” in a database. All data in Salesforce is stored in objects. Examples: Account, Opportunity, Contact, Case

• Record: An individual row of data within each object. Example: an Account record for “Company A” or an Opportunity record for “Proposal for Project X”

• Field: Each attribute (column) of a record, storing information such as name, phone number, amount, or date. There are standard fields (predefined by Salesforce) and custom fields (added by administrators)

Standard Objects and Custom Objects

Type	Definition	Examples	Scope of Modification
Standard Objects	Objects predefined by Salesforce that represent core CRM concepts	Account, Contact, Lead, Opportunity, Case, Campaign, Task, Event, Product, Pricebook	Fields and record types can be added; core logic and status transitions cannot be changed
Custom Objects	Objects created by administrators or developers to store data specific to a company’s business	(Example) Manufacturing: “Machine (Machine__c),” “Defect Report (Defect__c),” “Quote Line Item (QuoteLineItem__c)”	Object definitions, fields, relationships, and logic can all be freely designed

2-2 Relationships Between Objects

Relationships between objects in Salesforce are at the core of data model design. By using three main types of relationships, business data structures can be modeled flexibly.

(1) Lookup Relationship

A relationship that loosely connects two objects via a reference (lookup). The child record continues to exist independently even if the parent record is deleted. This is the most commonly used relationship type.

• Example: The relationship between Contact and Account. A Contact references an Account, but if the Account is deleted, the Contact is not deleted

• Characteristics: Ownership exists independently on the child record. Roll-up summary fields cannot be used. Access permissions are independent

(2) Master-Detail Relationship

A parent-child relationship in which the child (detail) is strongly dependent on the parent (master). When the parent record is deleted, the child records are automatically deleted as well. Roll-up summary fields can be used for reporting.

• Example: An Opportunity and its Opportunity Line Items. When the Opportunity is deleted, the Line Items are also deleted

• Characteristics: Child records inherit the owner and access rights of the parent. An object can have up to two master-detail relationships. Roll-up summary fields (sum, max, min, count) are calculated automatically

(3) Many-to-Many Relationship (via Junction Object)

A “many-to-many” relationship, in which a single record can be related to multiple other records, is implemented using a junction object, an intermediate table-like object.

• Example 1: Campaign and Contact have a many-to-many relationship — one Campaign can have multiple Contacts, and one Contact can participate in multiple Campaigns. CampaignMember (the junction object) connects the two

• Example 2: The team of members assigned to an Account’s Opportunities. One Opportunity can have multiple team members, and one member can be assigned to multiple Opportunities, connected via OpportunityTeamMember (junction object)

• Implementation method: Two master-detail relationships are set on the junction object, each pointing to one of the two master objects

Account

Has one or more Opportunities, Cases, and Contacts

▶ Opportunity ▶ Contact ▶ Case ▶ Activity

Figure 1: Object relationships centered on Account

2-3 Details of Major Standard Objects

Account

Account is an object that represents the “company or organization” a business deals with, and it sits at the center of the Salesforce data model. All sales, service, and marketing activities are linked around the Account.

Field Category	Main Fields	Design Considerations
Identification information	Account Name, Account Number, Type (customer classification: Customer/Partner/Prospect, etc.)	Deduplication and matching of Account Name is the most critical long-term operational challenge. Establish normalization rules (legal entity naming conventions)
Organizational information	Industry, Annual Revenue, Number of Employees, Ownership (public/private status)	Customize standard picklist values to fit the business. Serves as the grouping axis for report analysis
Hierarchical relationships	Parent Account → Account Hierarchy	Represents parent-child and ancestor relationships for global companies, such as a three-tier structure of headquarters → regional headquarters → subsidiary
Ownership	Owner (Account Owner)	The Account Owner holds ownership and viewing rights over all linked Opportunities, Cases, and activities. Directly tied to organizational design

Contact

Contact is an object representing an “individual” linked to an Account. While Account represents the company, Contact represents the individual (key person) who serves as the point of contact within that Account. Multiple Contacts can be linked to a single Account (one-to-many).

• Main fields: First/Last Name, Title, Department, Email, Phone, Reports To (the Contact’s manager), Account Name (parent Account reference)

• Design point: Using the “Reports To” field allows an organizational chart (manager/subordinate relationships) to be represented among Contacts. In B2B, setting up “Contact Role” to register and link multiple stakeholders — purchasing decision-makers, technical staff, executives — to an Opportunity is important

Lead

Lead is an object representing a “prospective customer” and stores inquiries, trade show business cards, web form submissions, and the like, before the prospect is registered as an Account. Once the quality of the lead (its potential to become an Opportunity) is confirmed, Lead Conversion is performed, converting it into three records: Account, Contact, and Opportunity.

Lead

▶

Qualification

▶

Lead Conversion

▶

Account + Contact + Opportunity

▶

Deal Closed

Figure 2: Conversion flow from Lead to Opportunity

• Before conversion: The Lead exists as a standalone record with no link to an Account or Contact. Managed by marketing

• Judging conversion criteria: Converted once criteria such as the BANT framework (Budget, Authority, Need, Timeline) are met. Conversion criteria should be custom-designed to fit the business

• Three objects created at conversion: If a matching Account already exists, only a new Contact is created; if not, new Account, Contact, and Opportunity records are all generated

⚠ Even when a Lead and a Contact refer to the “same person,” they exist as separate objects. Since activities (emails, calls) prior to Lead conversion are not linked to the Opportunity, the timing of conversion affects the completeness of the deal history.

2-4 The Concept of Deals: The Opportunity Object

Opportunity is the central concept in Salesforce’s sales management, representing “a specific deal that could generate a single sale.” Pipeline management, sales forecasting, and sales management as a whole are all built around the Opportunity.

Designing the Opportunity Stage

Opportunity Stage is the most critical field, indicating the current position in the sales process. Standard values include “Prospecting → Qualification → Needs Analysis → Value Proposition → Id. Decision Makers → Perception Analysis → Proposal/Price Quote → Negotiation/Review → Closed Won → Closed Lost,” but in practice these are customized to fit each company’s own sales process.

Stage Design Element	Description	Design Points
Stage name	A name representing each step in the sales process	Named to match the company’s own methodology (MEDDIC/SPIN/Challenger Sale, etc.). Agreement with other departments (SE, PM) is also needed
Probability	The win probability (%) at that stage. Set a default value and weight it in reports	Align the meaning of this probability across the organization. Basing it on statistical results from past performance, rather than subjective “gut feel,” improves forecast accuracy
Required fields (Entry Criteria)	Fields that must be filled in before advancing to the next stage. Example: requiring “budget” and “decision-maker name” before advancing to Qualification	Whether to enforce this with a Validation Rule or simply provide guidance depends on the team’s culture
Close Date	The expected date a deal will be won or lost	Checked during weekly and monthly pipeline reviews. Designing rules for managing deals that are “perpetually pushed out” is important
Amount	The projected revenue if the deal is won	For SaaS: recorded as ARR (annual recurring revenue). For product sales: a one-time amount at time of order. Standardize the calculation method to ensure reports remain comparable

Linking Opportunity and Activity

• Task (To-Do): Records one-off tasks such as sending an email, making a call, or submitting documents, linked to the Opportunity. Functions as the rep’s “to-do” list

• Event: Records meetings, demos, and presentations related to the deal with a time slot attached. Syncs with calendars (Google Calendar/Outlook integration)

• Activity Timeline: The Timeline view on an Opportunity record displays all activities linked to the deal — calls, emails, meetings, and notes — in chronological order

Related Objects: Quote and Opportunity Line Item

• Quote: Creates a Quote from the Opportunity, recording price, quantity, discounts, and terms, and exports it as a PDF quotation. Integration with CPQ (Configure Price Quote) products enables more complex product configuration and price calculation

• Opportunity Line Item: Links Products to the Opportunity. Prices are pulled from the Price Book and automatically aggregated into the Opportunity Amount

2-5 The Concept of Case Management: The Case Object

Case is the central object of Service Cloud (Agentforce Service), managing customer inquiries, complaints, and support requests one by one. Whereas Opportunity manages “deals that generate revenue,” Case manages “matters requiring resolution of a problem that has occurred.”

The Case Lifecycle

Inquiry received (Web/Email/Phone)

▶

Automatic case creation (Omni-Channel)

▶

Agent assignment (skill-based)

▶

Investigation/response (using knowledge base)

▶

Case closed (resolved, confirmed by customer)

Figure 3: The Case lifecycle

• Intake channels: Web-to-Case (web form), Email-to-Case (automatic email conversion), phone (CTI integration), social media direct messages, chat

• Omni-Channel Routing: Automatically distributes cases based on an agent’s skills, availability, and language proficiency. Skill-based routing ensures cases reach agents with the relevant product knowledge

• Knowledge integration: Knowledge Articles are linked to Cases for reference. AI automatically suggests relevant articles based on case content (Einstein Knowledge Base)

• Escalation: If a case remains unresolved beyond a threshold amount of elapsed time, it is automatically escalated to a manager (Escalation Rules)

• SLA management (Entitlement): Response time targets (SLAs) based on the customer’s contract (support plan) are managed through the Entitlement object, with advance alerts for SLA breach risk

2-6 The Concept of Project Management: Projects in Salesforce

Salesforce’s standard functionality does not include a “general-purpose project management object,” but several approaches exist depending on industry and use case. Four major patterns for managing projects in Salesforce are explained below.

Pattern 1: Opportunity-to-Project Transition (Execution Management of Won Deals)

In manufacturing, systems integration, and consulting industries, a common workflow is to “transition a won deal (Opportunity) into an execution project.” In Salesforce, a common pattern is to automatically create a custom object, “Project__c,” and link it to the Opportunity once the Opportunity reaches Closed Won.

• Implementation example: A Flow or Apex Trigger automatically creates a Project__c record when the Opportunity reaches Closed Won. Project__c is designed with fields such as project code, start date, end date, PL (project leader), and budget

• The Project__c ← Milestone__c ← Task__c one-to-many hierarchy enables WBS-style progress management

Pattern 2: Salesforce Maps Plus Project Custom Objects

In field service (maintenance, construction, inspection), it is common to build project management mechanisms using Salesforce Maps or independent field-service project management structures via custom objects.

Pattern 3: Using AppExchange Products (TaskRay, Ganttic, Inspire Planner, etc.)

The Salesforce AppExchange (application marketplace) offers numerous project management apps providing Gantt charts, task management, and time tracking. These integrate with Salesforce without code and can be implemented faster than custom development. Representative products include TaskRay, Inspire Planner, and Ganttic.

Pattern 4: Project Concepts in Industry Clouds

• Manufacturing Cloud: Manages the link between won deals (Account Forecast) and manufacturing orders in a make-to-order model. The Run Rate Agreement feature reconciles order volume against capacity

• Salesforce for Construction: A data model specialized for managing the schedule, budget, and subcontractors of construction projects

• Professional Services Cloud: Manages the hours, resources, and milestones of consulting and systems-integration projects

2-7 RecordType and PageLayout: Designing How Data Is Presented

Record Type

Record Type is a feature that defines multiple “types” within a single object, each with a different business process, picklist values, and page layout. For example, an Opportunity object could have three Record Types — “New Customer Proposal,” “Existing Customer Renewal,” and “Partner Channel” — each with different required fields, stage values, and approval flows.

• Example use: If the Account Type is “Large Manufacturer,” a manufacturing-specific page layout, picklist values, and required fields are displayed. For “Distribution Industry,” distribution-specific settings are displayed instead

• When a user creates a new record, they select a Record Type, which triggers the corresponding Page Layout and process

Page Layout

Page Layout configures the field placement, sections, related lists, and button display on a record’s detail screen. Mapping it to Record Types controls “which users see which Page Layout.” Administrators can design layouts using a drag-and-drop GUI, requiring no coding.

Chapter 3: Agentforce AI — Implementing Intelligent CRM

3-1 What Is Agentforce

Agentforce (formerly Einstein) is Salesforce’s AI platform, which, since 2024, has evolved into an architecture in which “AI agents” autonomously intervene in end-user work. Going beyond simple prediction and recommendation, it functions as an “autonomous agent that understands context and takes action,” capable of completing certain tasks without human approval.

3-2 Major AI Agent Features

Agent Feature	Target Product	Capabilities	Track Record / Benchmarks
Einstein Sales Coach (deal coaching)	Agentforce Sales	AI analyzes deal emails and call records to suggest next actions, provide talk-track improvement tips, and detect risk	30% reduction in sales rep coaching time (Salesforce TEI)
Einstein Opportunity Scoring (deal scoring)	Agentforce Sales	AI dynamically calculates the win probability of a deal, automatically detecting and alerting on “risk signals” (canceled meetings, unanswered emails)	Forecast accuracy: 30-40% improvement over human judgment alone
Einstein Forecasting (AI forecasting)	Agentforce Sales	AI analyzes historical win patterns, seasonality, and rep history to automatically generate sales forecasts, presenting “optimistic, pessimistic, and most-likely” scenarios	96% forecast accuracy with AI vs. 66% with humans alone
Agentforce SDR (autonomous sales development agent)	Agentforce Sales	AI autonomously handles auto-reply, qualification, and demo scheduling for leads from web forms, providing 24-hour coverage even when reps are unavailable	Salesforce’s own internal deployment: AI automates 35% of SDR work
Agentforce Case Classifier (automatic case classification)	Agentforce Service	AI automatically classifies incoming cases by category, urgency, and responsible department, and routes them automatically via Omni-Channel	90% reduction in case classification effort (across multiple customer case studies)
Einstein Article Recommendations (knowledge recommendation)	Agentforce Service	AI analyzes case content and automatically suggests relevant Knowledge Articles, reducing agents’ knowledge-search time	25% reduction in Average Handle Time (AHT)
Einstein Lead Scoring (lead scoring)	Agentforce Marketing	AI scores leads’ likelihood to purchase on a 10-point scale, allowing marketing teams to focus on high-quality leads	Average 20-30% improvement in lead conversion rate (Salesforce research)
Data 360 / Identity Resolution	Data 360	Integrates customer data from multiple sources (CRM, e-commerce sites, social media, IoT) to build a unique customer identity graph	95%+ customer data integration accuracy (implementation case studies)

Chapter 4: Detailed Features of Major Products

4-1 Agentforce Sales (Formerly Sales Cloud)

Core SFA (Sales Force Automation) Features

• Pipeline management: Pipeline views by Opportunity stage (Kanban, list, forecast). Detects stalled deals and drives action

• Activity management: Automatically links emails, calls, and meetings to Opportunities (Einstein Activity Capture), reducing the burden of manual CRM data entry

• Sales Engagement (formerly High Velocity Sales): Email sequences, automated follow-ups, call scripts, and productivity tools for SDRs

• Partner Relationship Management (PRM): Partner portals for agencies and distributors, allowing partners to self-service lead sharing, deal registration, and report submission

• Quote/CPQ (Configure Price Quote): Automates complex product configuration, price calculation, and discount approval flows, streamlining quoting for large product catalogs

4-2 Agentforce Service (Formerly Service Cloud)

Omni-Channel Customer Support Platform

• Einstein Bots: Chatbots using natural language processing, autonomously handling common inquiries (FAQs, status checks, appointment changes) and smoothly handing off to a human agent when unable to resolve an issue

• Field service: Manages dispatch of field technicians, with AI-optimized scheduling, map route optimization, and mobile job reporting

• Messaging: Unifies management of messages from WhatsApp, LINE, WeChat, Facebook Messenger, and other social channels within Salesforce

• Einstein Conversation Mining: AI analyzes large volumes of past cases and chat history to identify frequent issues, knowledge gaps, and candidates for bot automation

4-3 Salesforce Data 360 (Formerly Data Cloud)

Data 360 (formerly Genie/Data Cloud) is Salesforce’s Customer Data Platform (CDP), a foundational product that integrates customer data from multiple sources to enable real-time understanding of customers.

• Data collection: Collects data in real time from every data source — website behavior, e-commerce purchases, CRM data, IoT sensors, external DMPs, marketing automation, and call centers

• Identity Resolution (identity graph): Integrates the emails, devices, cookies, and customer IDs a single customer uses across different channels into one unified customer profile (a “golden record”)

• Segmentation: Real-time segments (such as users who just made a purchase, or users with no purchase in 60 days) are built using a drag-and-drop GUI. Created segments can be immediately connected to Marketing Cloud email campaigns or Advertising Cloud (paid advertising)

• Calculated Insights: Define custom KPIs (customer LTV, purchase frequency, churn risk score, etc.) without SQL and add them to every customer profile automatically

Chapter 5: Industry Use Cases and ROI

5-1 Use Cases in Manufacturing

Case 1: A Major Industrial Equipment Manufacturer (Forrester TEI Study)

A Total Economic Impact study (2025) commissioned by Salesforce and conducted by Forrester Consulting analyzed typical outcomes of Salesforce adoption in manufacturing. Interviewees came from multiple manufacturing companies, modeled as a composite organization with $1 billion in annual revenue and a 500-person sales organization.

• ROI: 354% (over three years, with payback in under five months)

• Sales productivity improvement: Automated activity logging in Sales Cloud reduced administrative work by 2.5 hours per rep per week, freeing that time for customer engagement and deal activity

• Higher win rates: Einstein Opportunity Scoring enabled early detection of at-risk deals, allowing managers to provide targeted support, improving the win rate by an average of 8 percentage points

• Improved forecast accuracy: Einstein Forecasting improved monthly sales forecast accuracy to within ±15% (from ±35% previously), indirectly contributing to improved precision in production planning and inventory allocation

Case 2: Partner Management Transformation at a Global Automotive Parts Manufacturer

A major European automotive parts manufacturer (with annual revenue exceeding $3 billion) transformed the partner management of its 150 agencies and distributors using Salesforce PRM.

• Challenges before adoption: Each agency reported deal progress using a different system or Excel, with no unified pipeline view, resulting in duplicate deals and competing proposals submitted to competitors in parallel

• Results after adoption: Achieved 100% registration of agency deals in Salesforce, established unified pipeline visibility at headquarters, and reduced duplicate deals (channel conflict) by 35%

• AI scoring: Einstein Scoring is automatically applied to deals registered by agencies, allowing headquarters sales to instantly identify high-priority deals worth focusing on

Case 3: Service Cloud Adoption at a Precision Equipment Manufacturer

A manufacturer of precision measuring instruments adopted Service Cloud to unify field service and customer support.

• Challenges: Phone, email, and on-site support were fragmented; technicians had no visibility into a customer’s past support history; arranging spare parts took an average of three days

• Results after adoption: Einstein Bots automatically resolved 42% of phone inquiries (AI automation of level-1 support). Average Handle Time (AHT) for agents was reduced by 28%. Sharing information with field technicians raised the first-contact resolution rate from 62% to 81%

5-2 Use Cases in Financial Services and Insurance

Case: Agency Management and Customer Engagement Optimization at a Major Life Insurer

• Challenges: Managing activity, training, and regulatory compliance tracking for more than 10,000 insurance agents was cumbersome, and the frequency of customer contact and timing of the next proposal were left to individual discretion

• Implementation: Adopted Financial Services Cloud (a data model specialized for the financial industry). The Household object manages assets and insurance status at the family unit level. The Einstein Recommendation Engine suggests the next insurance product to propose and the optimal timing for contact

• Results: The number of customers managed per agent increased by an average of 23%. Automatic recordkeeping for compliance reduced regulatory compliance effort by 40%

5-3 Use Cases in Retail and Consumer Goods

Case: Distribution Channel Management at a Major Food Manufacturer

• Challenges: Deals with supermarket, convenience store, and mass retailer buyers were managed via Excel and phone calls. Shelf-space negotiation progress and terms were not shared internally, and it was difficult to track actual promotional spend

• Implementation: Adopted Consumer Goods Cloud (a model specialized for the consumer goods industry), integrating Retail Execution (mobile verification of shelf placement and display conditions) with Field Activity Management (recording field sales activity at stores)

• Results: Deal progress with buyers became visible. Visualizing promotional spend against sales impact enabled budget to be concentrated on the most cost-effective campaigns, improving first-year promotional investment efficiency by 18%

Chapter 6: Technical Architecture and Extensibility

6-1 The Metadata-Driven Architecture of the Salesforce Platform

Salesforce is designed as a multi-tenant SaaS: all customers share the same codebase and infrastructure, while each tenant’s (company’s) customizations are managed separately as metadata. This is the basis for Salesforce’s characteristic that “customizations are not lost even after upgrades.”

The Four Layers of Development and Customization

Layer	Method	Responsible Party	Example
Configuration	GUI (admin screens)	Salesforce administrator (no-code)	Adding fields, page layouts, approval flows, Flow (Visual)
Automation	Flow Builder, Process Builder	Salesforce administrator (low-code)	Automatic emails on deal wins, task generation, object updates
Custom Development	Apex (a Java-like language), LWC (Lightning Web Components)	Salesforce developer (pro-code)	Complex business logic, custom UI, batch processing
Integration	REST/SOAP APIs, MuleSoft, event-driven (Platform Events)	Integration architects, developers	Real-time integration with external ERP, SCM, and accounting systems

6-2 Integration Architecture with MuleSoft

MuleSoft (acquired by Salesforce in 2018 for $6.5 billion) is an API-based integration platform that functions as the integration layer connecting Salesforce with external systems (SAP, Oracle, Workday, and various legacy systems). API design, implementation, management, and monitoring can all be centralized on the “Anypoint Platform.”

• API-led connectivity: A three-layer architecture consisting of System API (direct system access), Process API (business processes), and Experience API (for UI/apps). Reusable API libraries standardize integration design

• Prebuilt connectors: Numerous connectors are provided for connecting to SAP, Workday, Oracle, Salesforce, AWS services, and more, allowing many systems to be connected without custom implementation

Summary: What Salesforce Can and Cannot Do

Category	Details
✅ What it can do (strengths)	Unifies every customer touchpoint (sales, customer service, marketing, e-commerce) on a single platform; flexible addition of objects and fields (no-code); agile UI customization; AI-powered deal scoring, sales forecasting, and automatic case classification; access to an ecosystem of 7,000+ AppExchange apps
⚠ Possible with conditions	Designing business-specific data models with custom objects (requires design skill); implementing complex custom logic with Apex/LWC (requires development resources); integrating with core systems via MuleSoft (licensing and implementation costs can be significant)
❌ Difficult / requires caution	Core ERP functions such as inventory management, manufacturing processes, accounting entries, and production planning (Salesforce is a CRM, not an ERP); real-time processing of extremely large data volumes (hundreds of millions of records) due to governor limits (e.g., 50,000 SOQL records per transaction); on-premises deployment (Salesforce is a fully cloud-based SaaS with no private cloud option)

(This report was prepared based on Salesforce’s public information, the Forrester Total Economic Impact Study, and Gartner research (2025-2026).)