Searchlab Reporting & Analytics
Most orgs have hundreds of reports and three that anyone opens. This work replaces the clutter with a reporting layer that answers specific questions: what is in the pipeline, what changed since last week, and which deals are slipping and why.
Good reporting starts with the report type, which decides what fields and related objects are even available. Standard report types cover common combinations, but the useful questions usually need custom report types, for example opportunities with products and partners, or cases with entitlements and milestones. We build the report types first, so every report after that sits on solid ground.
Inside reports we use the features most teams never touch. Bucket fields group values without creating new fields, row level formulas calculate per record, summary formulas work across groupings, and cross filters answer questions such as accounts with no open opportunity. Joined reports put new business, renewals and service volume side by side in a single view.
Dashboards are built per audience. A rep dashboard shows personal numbers through dynamic dashboards or a running user setting. A manager dashboard shows team coverage, conversion and slippage. Leadership gets a small set of components with agreed definitions. Subscriptions then push the numbers into inboxes on schedule, so nobody has to remember to log in on Monday morning.
For trends over time we set up reporting snapshots, because Salesforce reports show the current state of a record rather than its history. Where questions outgrow standard reporting we assess CRM Analytics, and Einstein features such as opportunity scoring, lead scoring, account insights and Einstein Forecasting, all of which need reasonably clean history before their output is worth trusting.
Everything in Reporting & Analytics
Reporting requirements map
The list of questions each role needs answered, how often, and the decision that follows from the answer. Reports with no decision attached do not get built.
Custom report types
Report types built for the object combinations your questions need, with the right fields exposed and the irrelevant ones hidden to keep report building manageable.
Core report library
A curated set of reports in shared folders with naming conventions and descriptions, replacing the personal report sprawl most orgs accumulate over a few years.
Role based dashboards
Separate dashboards for reps, managers and leadership, using dynamic dashboards or filters so a single build serves many users without duplicating work.
Reporting snapshots
Scheduled snapshots that write report rows to a custom object, giving you week over week pipeline movement and genuine historical trend lines.
Subscriptions and alerts
Scheduled report and dashboard subscriptions with conditional alerts, so a manager hears about a slipping number without having to open the org.
Einstein feature setup
Assessment and enablement of Einstein opportunity scoring, lead scoring, account insights or Einstein Forecasting, where your data volume and history actually support them.
Definitions and folder governance
A written data dictionary for every metric plus a folder and sharing structure, so two dashboards never disagree about what pipeline means.
The process
Question gathering
We interview each reporting audience and write down the real questions and the decisions behind them. Vague requests like better visibility get turned into named, measurable metrics.
Data readiness check
Reporting exposes weak data. We check field fill rates, stage hygiene, close date discipline and ownership before building, then fix or flag anything that would distort the numbers.
Build and validate
Report types, reports and dashboards are built, then validated against a source your team already trusts, so the first number they see matches what they expected.
Roll out and retire
New dashboards launch with a short walkthrough, subscriptions are scheduled, and the old reports nobody opens are archived so the library stays usable.
Questions about Reporting & Analytics
Why do our Salesforce reports disagree with each other?
Usually filters and definitions, not bugs. Two reports use different date fields, different opportunity types, or different owner filters, and both look correct in isolation. The fix is to agree definitions once, write them down, and rebuild the affected reports from shared report types and governed folders.
Do we need CRM Analytics?
Only if standard reporting genuinely runs out. Reports and dashboards handle most sales and service questions and are already included in your licence. CRM Analytics becomes worthwhile when you need to blend Salesforce data with external sources, work with very large volumes, or build guided analytics apps.
Is Einstein scoring useful for a small pipeline?
It needs volume and history to be reliable. Einstein opportunity scoring generally wants a few hundred closed opportunities with reasonable field completeness before the scores mean much. Below that, a scoring formula field based on rules you can explain is more useful and far more trusted by reps.
Can we track pipeline changes week to week?
Yes, with reporting snapshots. Salesforce reports show the current state of each record, so an amount changed yesterday leaves no trace. A scheduled snapshot writes report rows into a custom object on a set day, and your trend reports are built from that stored history.
Ready to talk about Reporting & Analytics?
Tell us where you are stuck. We reply within the hour on WhatsApp, usually sooner.
Or email Searchlabtools@gmail.com