Optimization for St. Louis companies whose Salesforce org works, but slowly, awkwardly or with dashboards that leadership no longer believes.
Optimization in St. Louis usually means tidying an org that has been extended for many years by different admins and partners. Typical symptoms are reps logging activity in spreadsheets, automation that fires twice and forecasts that finance rebuilds by hand. We start by watching users work, then simplify layouts, consolidate old workflow rules and process builders into Flow, remove duplicate records and rebuild the dashboards leaders rely on. Changes ship in small releases, with short training at your location so each team sees what changed.
Manufacturers here often added Salesforce objects and fields every time a product line, acquisition or new sales channel appeared. The result is record pages with dozens of fields no one fills in and opportunity stages that mean different things in different divisions. Optimization for them means agreeing one set of stage definitions, hiding what reps do not need and rebuilding pipeline and forecast reports so plant and sales leaders read the same numbers.
Consulting, engineering and IT services firms, part of a category worth at least 7.5% of 2024 metro GDP here, depend on Salesforce for pipeline, resource planning signals and client history, yet utilization pressure means partners rarely update records. We streamline data entry to what billing and forecasting actually require, automate follow-up tasks and give practice leaders dashboards that answer their weekly questions without an analyst. Opportunity records then carry the detail billing needs without extra effort.
Advisors, agents and bankers adopt Salesforce when it saves them time with clients. Many orgs in the region were set up for managers and compliance, not for the people meeting customers. Optimization here focuses on quicker household or policy views, fewer clicks to log an interaction and marketing consent that stays accurate, so the org serves both the advisor and the review team. We validate the changes with a few advisors or agents before they reach everyone.
Pull login, record-update and report-usage data first. It shows which teams have drifted back to spreadsheets and which features nobody touches, so the optimization plan targets real friction rather than the loudest complaint in a meeting. It also gives a baseline for measuring improvement later.
It is common to find three generations of automation stacked on a single object in a mature org. Inventory them, map what each actually does and consolidate into Flow one object at a time, testing in a sandbox so nothing a downstream team relies on disappears quietly.
A dashboard is only trusted when everyone agrees what a qualified lead, a closed deal or a resolved case means. Settle those definitions with sales, service and finance leaders first, then rebuild reporting around them. Document each definition where every team can find it later.
How our salesforce optimization works →
Client names are anonymized, and these projects are not specific to St. Louis.
Rarely. Low use is usually a design problem inside the org, not a platform problem. Record pages ask for too much, reports do not match what reps see and nobody retrained people after the last change. We interview a few users in each role, often at your site, and fix the steps that cost them the most time. A rebuild only makes sense if the underlying data model is wrong for how the business works.
Yes, and it is one of the most common tasks in an optimization project. We list every automation on each object, identify overlaps and conflicts, then rebuild the logic in a smaller number of well-documented Flows. Testing happens in a sandbox with realistic records before anything moves to production, and the old automation is deactivated only after the new version has run cleanly.
We weigh each issue by how many people it affects and how much it distorts the numbers leadership uses. Duplicate accounts and broken stage definitions usually come first because they undermine every report. Layout and usability fixes follow, then automation cleanup. You approve the order, and each batch of changes is released and explained to users before the next one begins.
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