Optimization for Orlando orgs where agents juggle cluttered screens, duplicate guest records and reports that disagree with the property systems they summarize.
4.95/5 from 92 AgentExchange reviews Salesforce Select partner since 2017 138 certifications, client case studies
Optimization in Orlando usually focuses on the people who use Salesforce most intensively: service agents, reservation teams and group sales staff. We watch how they work, measure which fields and screens they skip, and simplify layouts so common tasks take fewer clicks. Duplicate guest and customer records are merged under agreed rules, overlapping automation moves into maintainable Flows, and service and sales reports are rebuilt so managers can trust handle times, conversion and pipeline without exporting everything into a spreadsheet first.
Hospitality agents handle large volumes of short interactions, so every extra field on a case layout costs real time. Optimization for resorts and restaurant groups trims case and contact screens to what agents need, adds quick actions for common requests such as date changes and refunds, and fixes routing so the right team sees each case first. Managers then get queue and resolution reports that reflect how work actually moves.
Retailers often hold marketing lists, loyalty data and service history that never quite match. We deduplicate customers, standardize how stores and channels are recorded, and rebuild segments so journeys stop reaching the wrong people or the same person twice. Reporting is reworked around repeat purchases and service contacts per customer, giving merchandising and marketing teams a shared picture of who their most valuable customers are, and which stores serve them best.
Optimization for Retail & Consumer Goods →Digital technology is one of the Orlando Economic Partnership's target industries, and the region is also known for simulation and gaming work. Growing firms in this group often built Salesforce quickly and now carry unused fields, abandoned stages and dashboards nobody opens. We cut the org back to the process the team runs today, consolidate automation and rebuild pipeline reporting so founders and sales leaders finally look at the same numbers.
Usage data shows which fields go blank, but sitting with reservation and service agents shows why. A morning of observation often reveals extra tabs, copy-and-paste steps and workarounds that no report captures, and those drive the most useful layout changes.
Merging duplicate guests or shoppers affects loyalty balances, marketing consent and service history. Decide which record wins, how consent is combined and who reviews borderline matches before any merge runs, because an overly aggressive merge is harder to undo than a duplicate.
Front-line teams in hospitality and retail change often. Pair each round of optimization with short, role-based guides and recorded walkthroughs that new staff can use later, so the simplified process survives the next hiring wave instead of drifting back to old habits.
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Client names are anonymized, and these projects are not specific to Orlando.
Start with the handful of tasks agents perform most. We time those tasks, count the clicks and screens involved, and look for steps agents skip or complete elsewhere. The first changes are usually small: fewer required fields, a consolidated case layout, quick actions for frequent requests and better default routing. When the common path becomes faster than the workaround, agents stay in Salesforce even on the busiest days.
Usually because they are counting different things. Marketing audiences may include subscribers who are not contacts, duplicates that reports merge, or consent rules applied at send time. We trace how each number is built, align definitions with your marketing and service leaders, clean the underlying records and rebuild the key reports and segments. Any gap left after that has a known cause your team can point to.
It is one of the best preparations. An AI agent answering guests relies on clean case history, accurate knowledge articles and clear routing, the same things optimization improves for your human agents. We tidy the case model, consolidate automation, review knowledge content and tighten permissions, so an Agentforce pilot starts from a service process that already works well for people.
Last reviewed September 26, 2026.
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