What good looks like, by sector.
Salesforce implementations across the sectors we work in, told the way an architect tells them: the situation, what was built and in what order, what it did, and what it would take to do the same thing for you. Client names are withheld; the numbers are not.
At a glance
- Case studies
- 17
- Sectors covered
- 15
- Client names
- Withheld
- Every story ends with
- The build, and the cost
01
The stories
Fifteen sectors, measured in results.
Filter by sector. Every card carries the three numbers the work is known for; every page walks through the situation, the build in order, and the decisions we would make again.
A North American paperboard and folding-carton manufacturer
A customer portal where packaging buyers track orders, shipments and build requests themselves.
Orders from a legacy system surfaced in Experience Cloud with account-wide sharing, a build-request flow and shipment tracking.
- Order, shipment and inventory status, without a call
- 24/7
- Login model per customer company: everyone sees their company’s orders, and only theirs
- 1
- Fewer “where is my order” enquiries to account executives (Cloudoxia estimate)
- est. 60%
A regulated consumer-products manufacturer selling wholesale to retailers
Salesforce and QuickBooks Desktop kept in step every hour, with nothing re-keyed between them.
Accounts, products and won opportunities synced to QuickBooks customers, items and invoices, with bulk ordering, inventory and dashboards built on top.
- Record types in sync: accounts, products and won opportunities to customers, items and invoices
- 3
- Scheduled sync, replacing manual entry in two systems
- Hourly
- Finance and operations time saved per week on double entry and reconciliation (Cloudoxia estimate)
- est. 8–10 h
The U.S. wealth-management arm of a global bank
Client onboarding cut from weeks to 24 minutes, then meeting prep handed to an agent.
Twenty-six adviser systems consolidated into Financial Services Cloud, and a meeting-prep agent shipped in six weeks on top of it.
- New-client onboarding, previously weeks and 100+ pages of paperwork
- 24 min
- Adviser systems consolidated into one CRM
- 26
- From decision to a live meeting-prep agent
- 6 wks
A multispecialty physician group
Patient intake down from days to five to ten minutes, and cancellations from 40% to 18%.
Patient data unified in Data 360, then agents put on onboarding and self-service so more patients get in, and turn up.
- More patients onboarded per day
- 35%
- Increase in patient satisfaction
- 30%
- Appointment cancellation rate
- 40% → 18%
The engines division of a global industrial manufacturer
Warranty claim processing capacity doubled for a network of 7,500 dealers.
One of the first Manufacturing Cloud builds: a dealer 360 across divisions, warranty on the platform, then an agent piloted on dealer support.
- Claim processing capacity
- 2×
- Dealers worldwide on the direct-to-dealer platform
- 7,500
- U.S. dealers whose satisfaction the programme set out to raise
- 3,500
A family-owned automotive dealer group with 15 sites
One view of customer, driver and vehicle in three months, and 60% less campaign orchestration.
Fifteen dealerships on one record, consent captured as data, and mass mail-outs replaced with journeys triggered from the car.
- Reduction in campaign orchestration
- 60%
- To roll out both clouds and reach one view of customer, driver and vehicle
- 3 mo
- Dealership locations working from the same record
- 15
A global beauty group with 25 consumer brands
Case handling time cut 64% for consumer-care advisers across 25 brands.
Service consolidated across brands and channels into one view of the consumer, replies drafted for advisers, and an agent on order updates around the clock.
- Reduction in case handling time
- 64%
- Brands served from one service view
- 25
- Order updates and shopper verification handled by the agent
- 24/7
A direct-to-consumer household-appliance company with two brands
280,000 agent-led shopping chats in four months, converting at 11%.
Two brands on one commerce platform, with an agent that helps shoppers choose, then handles orders and warranties after the sale.
- Chats handled by the agent in its first four months
- 280,000
- Year-over-year increase in conversion rate
- 6%
- Reduction in customer churn over the same period
- 58%
A national mobile, fibre and TV operator
Answers for 6,000 contact-centre reps in 30 seconds instead of minutes, at 95% accuracy.
An agent inside the service console, grounded on 500-plus articles and live case data, now extending to 10,000 field technicians.
- Contact-centre reps supported by the agent
- 6,000
- Answer accuracy
- 95%
- Extra service appointments a day the field rollout is designed to unlock (target)
- 10,000
A global motorsport championship
Race-day issues resolved 80% faster, with one profile for 24 million fans.
More than 100 fan data sources unified in Data 360, then put to work by agents in service and marketing.
- Faster response to fan service inquiries over chat and email
- 80%
- Higher click-through rates on AI-recommended content
- 22%
- Data sources unified into one profile for 24 million fans
- 100+
A European energy utility
71% of customer cases resolved autonomously, in two languages, inside the utility’s app.
An in-app agent that explains bills, contracts and smart meters in plain language, and can act on what it hears.
- Cases resolved autonomously by the agent
- 71%
- Conversations handled every day
- 1,500+
- Languages served from one agent
- 2
One of the largest U.S. homebuilders
An after-hours sales agent that helps up to 30% of inbound leads book a home tour.
An agent that answers buyers, books tours and creates leads by SMS and web chat, around the clock and within Fair Housing rules.
- Inbound leads helped to make an appointment, even with no live agent available
- Up to 30%
- Appointments the agent is expected to book in its first year (forecast)
- 12,000
- Coverage, picking up where a consultant left off
- 24/7
A private university with an ambitious enrolment target
An admissions agent built to take enrolment from 10,000 to 50,000 students in five years.
A recruitment agent on the website, inside Education Cloud, instead of a form and an eight-week wait.
- Enrolment, the five-year target the programme was built for
- 10k → 50k
- Staff time expected to be saved per website request for information
- $800
- Time for an applicant to hear back, against a sector norm of weeks (target)
- 48 h
A national product-philanthropy nonprofit
Disaster-relief donations routed up to three times faster by a resource-matching agent.
Thousands of truckloads of donated goods a year, matched to the right partner by an agent instead of a five-person team working by hand.
- Faster connection of disaster-affected communities with supplies, up to
- 3×
- Hours a year saved for the five-person matching team
- 1,000+
- Carbon-footprint reduction targeted by routing to the nearest partner
- 20%
A global staffing and talent group
Job-campaign preparation cut by 93%, with an agent that talks to every applicant.
Candidate data unified in Data 360 and agents put across the recruiting lifecycle, from first contact to shortlist.
- Reduction in job-campaign preparation time
- 93%
- Every applicant engaged individually by an agent
- 1:1
- Pre-screening, match scoring and candidate follow-up
- 24/7
The advertising business of a major social platform
Advertiser support resolution down from 8.9 minutes to 1.4, an 84% improvement.
A scripted chatbot replaced with an agent that diagnoses ad-review, billing and pixel problems from the knowledge base and the case history.
- Average resolution time, down from 8.9 minutes
- 1.4 min
- Higher advertiser satisfaction scores
- 20%
- A year given back to live reps
- 760 h
A national flag-carrier airline
Refund turnaround cut from about 14 days to about four hours.
Agents that validate across systems, take the action and draft the reply, on refunds first and then on email resolution, name changes and staff knowledge.
- Refund turnaround time, approximately
- 14 d → 4 h
- Passenger name updates
- 3 d → 30 min
- Agentic initiatives under way across a 140-plus-system estate
- 30+
02
How we work a case
What the stories have in common.
Different sectors, different products, the same four habits. They are how we run an engagement, and they are also how to read the results above.
01
The data model comes first.
Every result on this page sits on a record that was designed before a screen was. Unify the data, model the nouns the business actually uses, then build.
02
One narrow job per agent.
The agents that have a number attached were each given one thing to do, a clear finish line and a human to hand off to. The ones that try to do everything do not appear here.
03
Measured against a baseline.
A figure is only worth printing if there was a before. Where a result was a stated target rather than a measurement, or is our own estimate, the label says so.
04
Sized for a mid-market team.
Each story closes with the three decisions that made it work and the service line each belongs to, so a team of fifty to five hundred people can see what the same outcome takes.
03
On the record
What our clients say on the record.
The stories above carry a sector rather than a name. These are the reviews clients chose to publish under theirs, and the companies that have let us say we worked with them.
Fully understands requirements and implements them into our org quickly and efficiently. The team has been very patient with us as our projects were delayed, and even gave us tips and help without charge. Thanks — will be hiring again.
Cloudoxia took on a very complex set of requirements and executed them well. They asked pertinent questions about the logic behind the functionality, ensuring it worked as expected and to spec. Looking forward to working with the team again.
The team created a custom document generator that saved my company $10,000+ a year in subscriptions. Knowledgeable, easy to work with, persistent about getting the job done, and fair on price.
Worked with
Ask for the references in your sector.
Thirty minutes with an architect who has shipped in your sector. Bring the story on this page that looks most like your problem, and we will tell you what it takes to get there.