Case Study · Shine and Sparkle
From missed calls to a marketing system that runs itself.
Hannah Brees runs Shine and Sparkle, a commercial and residential cleaning business. She came in for help saving time on marketing. We left her with three AI workflows that handle data, inbound calls, and customer outreach — and her team got 40 hours a month back.
40 hrs/mo
Freed up by the outreach automation alone
3 workflows
Data analysis, inbound, and outbound — all automated
0 missed
Cira, an AI voice receptionist, now answers every call
The challenge
Disconnected tools, missed calls, and a VA stuck on lead nurture.
Shine and Sparkle was already running on multiple systems — a marketing app, a sales tracker, house-cleaning software, and spreadsheets bridging the gaps. The tools worked individually. Together, they didn't compound. The team was burning hours on the seams between them, and Hannah knew leads were leaking out the edges.
Tools that didn't talk to each other
Marketing lived in one app. Sales tracking lived in another. House cleaning operations ran on a third. Spreadsheets bridged the gaps. None of it compounded — every report meant exporting, copy-pasting, and manual reconciliation.
Missed calls leaking revenue
Calls came in faster than they could be answered. Each missed call was a lead that either reached a competitor or fell off the radar entirely. Hannah and her team were already maxed out doing the cleaning work itself.
A VA spending most of their time on lead nurture
The virtual assistant's day was eaten by manual outreach to inbound leads — the kind of follow-up Hannah wanted but couldn't scale. Even with the VA's help, follow-up was inconsistent and customers slipped through.
No systematic outreach to existing customers
Past customers and one-time customers stopped hearing from the business. No upsell cadence, no win-back campaign, no reason for a one-off cleaning to become a recurring contract. The marketing engine was reactive, not active.
Hannah came in for "help me save time on marketing." The actual problem was that her marketing wasn't a system at all — it was a stack of tools and a person running between them.
What we built
Three AI workflows. One marketing system.
The audit found three places where AI would compound for Shine and Sparkle. We shipped them in priority order and tied them together so the system runs without anyone driving it manually every day.
Claude for sales and financial analysis
Showed Hannah how to use Claude to pull the data that mattered: churn rate, sales lists, segmentation, financial reporting. Reports that used to require an export-and-spreadsheet ritual now happen in a conversation.
Cira on the phones
Stood up Cira — the AI voice receptionist we built (hicira.com) — to answer inbound calls, capture lead details, and route urgent calls. Missed calls dropped to zero. The VA's time on call triage and lead intake disappeared overnight.
Voice-trained outreach cadence
Built an automated outreach system trained on Hannah's voice — so the messages going out to current customers, past customers, and one-time leads sound like her, not like a template. Includes upsell offers for existing accounts, win-back campaigns for churned customers, and warm-touch sequences to keep one-time clients aware of the business.
A marketing system, not a tool stack
The work wasn't "add three more apps." It was tying the data, the inbound, and the outbound into one system that runs without anyone driving it manually every day. Hannah's job became reviewing what the system did, not running it.
How we worked
Discovery. Custom report. Implementation. Hands off.
The engagement followed the same arc as every Smart Operator audit: 45-minute discovery call, custom report with the workflows that would compound, and implementation against the 4-day quick-start plan. Hannah's engagement extended into the implementation work because she wanted the systems built, not just recommended.
Discovery
Walked through Hannah's actual week — where time leaked, what tools she already had, what work the VA was doing, where leads were coming in and going dark.
Custom report
Delivered a written report identifying the three workflows that would compound: data analysis, inbound triage, and voice-trained outreach. With a 4-day quick-start plan she could run from Day 1.
Implementation
Stood up Claude for the analysis side, Cira on the phones, and the outreach cadence. Trained the cadence on Hannah's voice so the messages don't sound like template marketing.
Hands-off operation
The system runs without Hannah managing it day-to-day. She reviews what it produces and makes calls; the work itself happens whether she's at her desk or not.
The outcomes
Hours back. Leads kept. A marketing engine that doesn't need a driver.
40 hours a month back from outreach automation alone
That's the conservative number — Hannah's own line, dialed back so the claim stays credible. The actual savings across all three workflows are larger. Either way, it's hours that came directly off the team's plate without anything dropping.
The VA freed up for higher-value work
Instead of spending most of the week on manual outreach and call triage, the VA can focus on the parts of the business AI shouldn't touch — the human-judgment work that actually needs a human.
Outreach that sounds like the business owner
Voice-trained automation means existing customers don't get spammy templates. They get messages that read like Hannah wrote them — because the system was tuned on how she actually talks.
A repeatable system, not a one-time fix
Upsells go out on a cadence. Past customers get win-back attempts. One-time clients stay warm. The marketing engine moves whether Hannah is on a job, on a call, or at her kid's soccer game.
“I knew I was losing leads because we couldn't keep up with follow-up. Bryan looked at how my business actually worked and gave me a plan I could run on day one. The outreach automation alone freed up 40 hours a month on my team.”
Hannah Brees
Owner, Shine and Sparkle
The takeaway
The work isn't adding more tools. It's tying the right ones together.
Hannah didn't need new software. She needed her existing work to stop running on a person and start running on a system. That's what an AI Tools Assessment finds — the workflows that will compound when AI handles them, the order to install them in, and the day you start seeing time back.
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