Suomi
Français
Deutsch
Polski
Forecasts leave too much to guesswork
When forecasts depend on spreadsheets and individual judgment, sales and operations teams struggle to agree where to focus. Late changes can disrupt inventory and resource plans.
Salesforce Einstein Consulting That Turns Predictions into Business Value
Plan sales with clearer insight. Reduce manual case triage. Give your teams more time to act. Routine Automation implements predictive analytics and case categorization in Salesforce—from data readiness and a focused pilot to integration and ongoing improvement.
Where Is Your Team Losing Time and Revenue?
Start with the decision or service bottleneck that costs your business the most. We connect each use case to a practical workflow and a result you can measure.
Manual triage consumes service capacity
Reading and categorizing every incoming request takes time before anyone starts solving the issue. Growing queues put more pressure on the same support team.
Cases reach the wrong team
Inconsistent categories can send requests between queues. Customers repeat their issue while agents reconstruct the context and ownership.
The Business Value We Build Toward
Agree the business measure before building the solution. These are pilot objectives we validate against your baseline.
More capacity for customer care
Move repetitive classification out of the agent’s way so support staff can spend more time investigating and resolving requests.
Measure: triage time and manual touches per case.
Better informed commercial decisions
Give sales and operations teams a shared view of predicted outcomes and the factors associated with them, so they can focus follow-up and planning.
Measure: prediction error against your current baseline.
Less friction in service delivery
Use consistent case fields and configured routing to reduce avoidable transfers and make ownership clearer from the start.
Measure: reassignment rate and time to the appropriate queue.
Make Predictive Intelligence Part of Daily Decisions
We implement CRM Analytics and Einstein Discovery around the question your team needs to answer. The deliverable is a usable decision workflow: relevant data, evaluated predictions and insights available where people work.
See which factors matter
Connect relevant datasets and explore the factors associated with your chosen outcome. Give decision-makers context alongside a score; statistical relationships do not establish causation.
Focus attention where it can help
Assess use cases such as renewal likelihood or expected sales value. Place evaluated predictions on Salesforce records or in the workflow that guides follow-up.
Validate value before expanding
Compare predictions with your existing baseline using held-out data. For forecasts, test the future periods your team needs to plan. Agree the action a useful result should trigger.
From Incoming Request to the Right Service Team
Reduce the work between receiving a case and starting the right response. We connect case categorization to your service process, with review rules for uncertain results.
Define meaningful categories
Align case fields with the teams and decisions they serve. Review historical labels so the model learns from useful examples.
Recommend case fields
Configure Einstein Case Classification to recommend supported values from case subject and description. Evaluate representative requests before rollout.
Apply and route
Set confidence requirements for supported automatic updates. Connect accepted values to Flow and queue or Omni-Channel routing rules.
Improve service performance
Review corrections, unclassified cases and transfers alongside triage time. Use the findings to refine labels, thresholds and workflow rules.
Hire Routine Automation to Implement Your Einstein Use Case
Bring us a forecasting challenge, a growing service queue or an existing AI setup that is not delivering useful results. We will scope the data, implementation work and success criteria with you, then prepare a project estimate.
Readiness and project scope
A defined use case, data and licensing review, integration needs and pilot acceptance criteria.
Pilot and implementation
Model or classification configuration, workflow integration, representative testing and user handover.
Improve an existing solution
Review weak predictions, inconsistent categories or routing gaps, then agree a focused improvement plan.
Choose the Approach That Fits the Business Need
We help you select the implementation around the work to be done, the quality of your data and the cost of operating it. Confirm product entitlements and usage charges before committing to a rollout.
Predictive case classification
A candidate for consistent, repeatable categorization when historical labels are reliable and the category set is stable. Evaluate training eligibility and confidence behavior in your org.
Flow with Prompt Builder
Consider a prompt-driven workflow when message context needs interpretation against defined labels. Validate structured output and permitted values before updating Case.
Agentforce service workflows
Consider Agentforce when categorization also needs knowledge retrieval, a resolution attempt or a human handoff. Scope actions and escalation around that broader task.
Predictive Analytics and Service AI in Practice
See how we have applied predictive analytics to retail forecasting and Agentforce to service triage and electronics support. Explore the business challenge, implementation approach and results documented for each project.
Retail Forecasting: Salesforce Analytics Implementation
U.S. retailer used Salesforce Einstein’s AI analytics to revamp sales forecasting, resulting in 30% better accuracy.
Automating Case Triage and Resolution with Salesforce Agentforce
A US retailer uses Agentforce in English and Spanish to triage service requests, attempt knowledge-based resolution of eligible cases, and route uncertain issues to human support.
Assisting First-Tier Electronics Support with Salesforce Agentforce
An electronics manufacturer uses an Agentforce Employee Agent to analyze support requests, find documented troubleshooting guidance, and support escalation when first-tier troubleshooting cannot resolve a case.
A Clear Path from Business Problem to Working Solution
Start with a scoped pilot and an agreed measure of success. We estimate delivery after reviewing the data, access and integration work your use case requires.
Agree the business case
Choose one decision or bottleneck, record its current cost or workload and define the result needed to justify further investment.
Prepare and build
Review data quality, feature eligibility and licensing. Configure the selected solution and its integration with Salesforce workflows.
Test with your team
Evaluate representative examples, exception handling and business measures. Agree where a person reviews results before automation proceeds.
Launch and improve
Hand over the workflow, train users and monitor performance. Refine the solution as case patterns and business priorities change.
Salesforce Einstein FAQs
We scope and implement predictive analytics and case categorization in Salesforce, including data readiness, configuration, workflow integration, testing and handover. We also review and improve existing implementations. Share your use case to receive a project estimate based on your data and requirements.
CRM Analytics provides data preparation, analysis and dashboards. Einstein Discovery adds models that predict defined outcomes and suggest possible improvements. Discovery requires an eligible license; we confirm your entitlement during scoping.
No. Predictive classification recommends case field values from patterns in historical cases. Agentforce can support a broader workflow with knowledge retrieval and actions. The right choice depends on what must happen after a case is categorized.
Eligibility depends on the selected feature, segment and supported fields. Salesforce documents a minimum of 400 eligible closed cases created in the past six months for classification segments, while its architecture guidance recommends more history for stronger performance. We check current requirements and category coverage in your org; eligibility alone does not establish quality.
Supported predictions can feed configured automation. Priority needs agreed business rules, and routing needs queue or Omni-Channel configuration. We define when a recommendation may be applied and when a person must review it.
We set evaluation criteria and estimate delivery after reviewing your data and workflow. Accuracy varies with label quality, data coverage and the prediction task. A published customer result is evidence for that implementation, not a forecast for yours.
No. The architecture follows the feature and data sources involved. We assess whether Salesforce data and existing integrations are sufficient before recommending a Data 360 implementation.
Ready to Put Your Salesforce Data to Work?
Tell us which decision needs better insight or where case handling slows down. We will help define the first implementation scope and prepare an estimate for your project.
