Blog
Research you can act on.
Research and perspective on customer data, marketing measurement and applied AI.
- 26 articles
- Revenue intelligence
- AI readiness
- Applied AI
Anthropic Claude Dashboards: measure whether win-back offers work
Claude Dashboards can turn plain-language prompts and live data into dashboards. For appointment-based businesses, the useful question is whether a win-back offer brings clients back for completed visits.
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AI readiness3 min readSalesforce on personal AI agents: safer repeat booking
Salesforce’s discussion of customer-side AI agents raises a useful question for appointment businesses: could an assistant rebook a client without guessing about services, availability or policies? Start by defining a safe booking path and the information an outside agent is allowed to use.
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AI readiness3 min readGoogle Gemini enterprise AI agent: a human-approved routine for membership renewals
A practical guide to evaluating AI-assisted renewal follow-up while keeping member data, staff approval and booking records under your control.
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Revenue intelligence3 min readZenoti cross-location loyalty: what to verify before benefits travel between branches
Cross-location memberships could make it easier for clients to use benefits at another branch, but the supplied sources do not confirm Zenoti offers this feature. Here’s what multi-location operators should check before building retention plans around it.
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Revenue intelligence3 min readMindbody AI Insights: find missed second-visit opportunities
Mindbody’s AI Insights can point to clients who may be drifting away, but a risk flag is not proof that someone missed a second visit. Use it to focus your review of booking history and test whether a personal follow-up leads to rebooking.
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Revenue intelligence3 min readAWS contextual bandits: measure whether AI follow-up earns second visits
An AWS post reports mixed results from AI personalization in a product-acquisition funnel, not appointment retention. Here’s how to apply its measurement lesson to first-visit follow-up and repeat bookings.
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Applied AI3 min readSalesforce’s Listen Labs deal: find out why clients don’t rebook
Salesforce has agreed to acquire Listen Labs, a customer-research platform that uses AI agents.
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AI readiness3 min readBefore clients use an AI booking agent, test the awkward cases
A polished demo cannot tell you how an AI agent will handle a cancellation, an unavailable service or a booking change. Build a small test set and check accuracy, cost and handoffs before clients rely on it.
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Revenue intelligence3 min readEnrich client records with fields that change a decision
A longer client profile is not automatically more useful. Choose a few signals—such as lifetime value, preferred services and time since last visit—that help your team decide what to do next.
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AI readiness3 min readIs AI search bringing in bookable demand?
AI mentions and referral visits can show visibility, but they do not prove that new bookings came from AI search. Track them alongside inquiries and completed appointments, then use a comparison period or attribution experiment before assigning revenue credit.
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Revenue intelligence3 min readJudge acquisition channels by client value, not lead volume
More leads or a short-term conversion lift can look promising, but neither tells you whether a channel is paying off over time. Compare channels by the value of clients who book and return against what it costs to acquire them.
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AI readiness3 min readMake reviews part of your AI search visibility
AI assistants may draw on what others say about your business, not just the claims on your website. Start by checking how they describe you, then use recurring review themes to improve the client experience and make your services easier to verify.
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AI readiness3 min readMap your booking, payment and marketing systems before adding agents
AI agents are beginning to connect with business tools, but more connections make clear system ownership important. Map which platform owns each record and what an agent is allowed to read or change before putting it to work.
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Revenue intelligence3 min readReplace the spa newsletter blast with rebooking segments
A general newsletter can miss the moment a client is ready to return. Group clients by the service they had and how long it has been since their visit, then test messages that fit those needs.
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Applied AI3 min readUse AI to organize customer feedback, not replace listening
AI can help group call notes, survey responses and reviews into useful themes. A person still needs to check the original feedback and decide what to change.
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Revenue intelligence3 min readAn AI visibility score is not proof of new bookings
AI visibility scores can show whether your business appears in a selected set of generated answers. To understand whether that exposure matters, track qualified inquiries and booked appointments too.
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Applied AI3 min readCan a data agent show which clients drive revenue?
A practical way to test AI analysis against your booking and POS records—without mistaking a plausible client segment for a verified one.
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AI readiness3 min readCan AI search describe your local business accurately?
Run a simple baseline across ChatGPT, Gemini, Claude and Perplexity. Check whether the answers name your business, describe it accurately and reflect the services you offer.
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AI readiness3 min readClean your booking and POS records before connecting an AI agent
AI follow-up and recommendations depend on the client and visit history behind them. Before letting an agent act on that history, reconcile duplicate profiles, service names and visit statuses.
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Applied AI3 min readCompare AI models by workflow cost, not headline price
A lower price per AI request does not necessarily mean a lower cost for your business. Compare models on the same real task and include staff review, retries and the cost of mistakes.
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Revenue intelligence3 min readFrequent visits do not tell the whole loyalty story
Visit frequency is useful, but it does not show the full shape of a client relationship. Look at service mix, consistency and lapses before deciding who needs a reward or a check-in.
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AI readiness3 min readGive AI agents only the access they need
An AI agent should be able to do its assigned job without having broad access to your business. Here’s how to think about permissions, prompts and system-enforced limits before connecting an agent to booking or customer information.
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Revenue intelligence3 min readMeasure booked-appointment CAC before shifting budget to AI search
A report on AI use for local services may be a reason to improve your tracking, not proof that AI search deserves more budget. Measure inquiries, first-time bookings and acquisition cost by source before deciding what to change.
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Applied AI3 min readTest AI phone agents on the calls that cost you bookings
An AI phone agent’s reported resolution rate won’t tell you how it will handle your booking rules or callers. Start with a narrow test and judge it by completed bookings, appropriate staff handoffs and errors.
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Revenue intelligence3 min readUse booking patterns to make smarter next-service suggestions
Your booking history can help you spot useful service pairings, but frequency alone is not enough. Start with relevant sequences, add clear eligibility rules and test a small number of suggestions.
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