Product
Shift is the guest-facing side: review management, with real-time conversations and retention offers in development. Lift connects that guest experience to business intelligence — check averages, selling behavior, and financial performance — so managers can understand what happened and what to change.
01 · Guest Experience
How do guests tell us about a visit?
A location-specific survey opens in the browser — no guest app. Guests rate the visit, identify it by check number and visit date, select the issues that mattered, and add comments where the flow asks for them. Configured public-review destinations are supported.
Feedback arrives already connected to the check.
How is the guest experience doing overall?
A scoped view of survey ratings, sales and check value, staff-associated ratings, recurring Shift Issues, and a Review Breakdown by rating group — with the selected location and date range always visible, and missing data shown as missing, never as zero.
Read the room in one glance, then open the visits behind it.
Conversation view implemented · live outbound messaging not yet validated
What do we say back?
An inbox built for review and conversation: the feedback on one side, the visit behind it in the middle — check, items and modifiers, server account, and reservation context where a verified link exists — and the reply on the other.
Follow up with the visit in front of you.
Shared workspace layout in development
How does the team coordinate privately?
A separate internal channel for staff discussion of a guest concern or operational matter, with linked case and visit context — clearly labeled so internal talk is never confused with a message sent to the guest.
Keep guest messaging and team talk apart.
Verified return and recovered-revenue evidence are future
Did we actually win the guest back?
Review recovery activity and distinguish open and closed cases from evidence a guest actually returned. A closed case is an administrative state, not a retained guest. Verified return visits and recovered-revenue evidence remain future capabilities.
See what was tried, and what is actually known.
02 · Team Coaching
Where would recognition or coaching help most?
Category selling across the team, separated from simple workload totals: category leadership, items per guest, average and median context, and each person's strengths and largest supported opportunity.
Spot the example worth sharing with the team.
Redesigned V2 view in refinement alongside the original
How do I prepare a useful one-to-one?
Selling behavior, guest feedback, and worked-role context in one review: a selling-versus-feedback chart, category summary, primary and additional opportunities with named qualified peers, and a clear 'why this goal' explanation. A Coaching view hides restaurant-dollar figures and shows estimated additional tips.
Coach the role the person actually worked.
Dedicated per-role dashboard in development
Which servers consistently produce a complete check?
The monitor in development shows how servers stack up against your own recipe — for example, an entrée, an appetizer, a dessert, and a drink. Required groups and alternatives define a complete check per role. Compare eligible-check rates alongside feedback and check averages; unsupported checks are excluded, not scored as failures.
Find a selling habit worth coaching — or recognizing.
Shared role setups implemented, pending activation
What should each role focus on?
A searchable role list with a focused editor: primary priorities, additional opportunities, excluded categories, and each role's Perfect Check recipe — so a bartender and a server are never measured against the same list.
Set the priorities once; let every review follow them.
03 · Sales & Visits
Can I inspect the visit instead of reconstructing it?
Reservation activity and recorded orders and checks in one operational view: deterministic OpenTable–Toast links where the shared identifier exists, guest counts, visit timing, and per-source data freshness. Unmatched records stay visible — never silently guessed.
Review the period without exporting anything.
Is a higher total just more guests?
Guests served, net sales, average net check, and net sales per guest by person or POS account, with sorting and filtering. Shared or unconfirmed accounts are labeled as such — an account row is not automatically one person's performance.
Compare volume and normalized measures side by side.
04 · Setup & Definitions
Do the reports speak our menu's language?
Map Toast sales categories and menu groups into meaningful reporting categories — appetizers, entrées, desserts, alcoholic and non-alcoholic drinks — with bulk mapping and clear visibility into incomplete setup.
Consistent analytics start with consistent categories.
What assumptions sit behind the comparisons?
Configure the minimums and assumptions used in comparisons and projections — qualification thresholds and the estimated tip assumption — with definitions that explain how a change affects results.
A configured target stays a coaching choice, not a promise.
What exactly does this number mean?
A searchable, categorized reference index using the same definitions as the in-product information dialogs — so every metric carries one clear population: location, period, unit, and eligible records.
One number, one clear meaning, everywhere.
Start with a review that needs attention, a check-average gap, or a Perfect Check coaching question. See how the connected workflow could save investigation time and inform retention-focused action. Value from day one is our goal, not a guaranteed payback claim.
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