「einstein」の検索結果

Configuring and running Pipeline Inspection in Sales Cloud: enabling the feature, mapping forecast categories into the inspection view, Days in Stage and other deal-change metrics, and pipeline review cadence for sales managers. Use when designing or improving how a team monitors deal health and pipeline movement. NOT for the Revenue Intelligence app, Einstein deal insights, or forecast-accuracy dashboards — use admin/revenue-intelligence-setup. NOT for forecast types, quotas, or forecast hierarchy setup — use admin/collaborative-forecasts. Keywords: pipeline review, coverage ratio, stage conversion, slippage, stale deals, days in stage, LastStageChangeInDays, LastStageChangeDate, AgeInDays, PushCount, ForecastCategoryName, enablePipelineInspection, PipelineInspMetricConfig, OpportunitySettings, review cadence, commit call.

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Configure CRM Analytics (formerly Einstein Analytics) app sharing, dataset-level permissions, row-level security predicates, sharing inheritance, and license assignment. Trigger keywords: CRM Analytics security, row-level security predicate, dataset permissions, analytics sharing inheritance, Analytics Plus license. NOT for OWD and sharing rules — use admin/sharing-and-visibility. NOT for predicate design across many datasets — use architect/analytics-security-architecture.

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Use when creating or managing CRM Analytics datasets: configuring dataflows, scheduling refreshes, selecting fields, handling date types, managing row-count growth, or troubleshooting stale or broken datasets. Triggers: 'dataset creation', 'dataflow schedule', 'dataflow quota', 'date field not filterable', 'dataset row limit', 'CRM Analytics data refresh', 'field type mismatch in dataset'. NOT for making an existing dataset smaller or faster — use data/analytics-dataset-optimization. NOT for choosing between Reports, CRM Analytics and Tableau in the first place — use admin/einstein-analytics-basics.

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Identify, score, and prioritize Salesforce AI use cases before any implementation begins — opportunity identification, Impact-Effort matrix scoring, feasibility evaluation across Technical/Operational/Data/Risk dimensions, and ROI framing. NOT for the license checks and enablement steps once a use case is approved — use agentforce/agentforce-service-ai-setup or agentforce/agentforce-sales-ai-setup. NOT for making the data model AI-ready — use architect/ai-ready-data-architecture.

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Use this skill when planning user adoption, structuring Salesforce training materials, drafting release communications, or running a change impact assessment for a Salesforce rollout or update. Triggers: user adoption plan, training materials, release announcement, change impact, go-live communication, communication plan, training plan by persona, adoption metrics, LoginHistory adoption report, PromptAction, training sandbox, go-live checklist, post-go-live feedback, super user program, pilot group. NOT for org deployment mechanics or sandbox promotion — use admin/change-management-and-deployment. NOT for adoption of an Agentforce or Einstein AI feature — use admin/ai-adoption-change-management. NOT for configuring the in-app prompts themselves — use admin/in-app-guidance-and-walkthroughs.

日本語の概要は準備中です。原文の説明を表示しています。