Arrives while they are looking
A night-owl client's copy of the newsletter lands around when she is actually checking email, rather than sitting buried under other messages by the time she gets to it hours later.
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In build
The whole team
Nineteen specialists, each with a defined job and an honest status label.
See all nineteenThe business's emails get opened more often because they arrive when each subscriber is actually checking their inbox, instead of everyone getting mail at the same fixed hour.
Works with
What it does
Patri looks at a contact's past open-time history and schedules that contact's copy of a campaign to arrive during their personal high-engagement window, within a range the owner sets. Contacts with no history fall back to a sensible default send time.
A freelance graphic designer sends her monthly newsletter to past clients at 9am sharp every time, because that felt like a sensible business hour to pick when she started — except a fair few of her clients are night owls who check email properly around 10pm, well after her newsletter has already scrolled past a dozen other messages sitting above it in their inbox by the time they finally look.
Send time optimization looks at each contact's own past open-time history and schedules that contact's copy of the campaign to land during their personal high-engagement window instead, within a range the designer sets. A contact with no history yet — someone brand new to the list — falls back to a sensible default time rather than being left unscheduled or guessed at randomly.
Patri runs this directly on the platforms your customers already use — no separate app for them to install.
How it works
Each contact's history of when they have actually opened previous emails is tracked over time, gradually building a picture of their personal best send window rather than assuming everyone behaves the same way at all.
A business chooses the outer bounds this can operate within — say, between 7am and 10pm — so a contact's personal window still falls inside hours the business is genuinely comfortable sending during, at all times without exception.
One campaign is broken into many individual scheduled sends, one per contact, each timed to that contact's own best window rather than every recipient receiving the same message at the identical fixed hour every time.
Someone with no open-time history yet is scheduled at a fallback hour chosen to be reasonable for most people, until enough of their own history builds up to compute a genuinely personal window instead of a default one.
Why it matters
A night-owl client's copy of the newsletter lands around when she is actually checking email, rather than sitting buried under other messages by the time she gets to it hours later.
The designer does not need to separately track or guess which clients prefer mornings versus evenings — the system computes each contact's own pattern from their actual behaviour over time.
A brand-new contact with no history yet still gets a sensible default time immediately, rather than being skipped or scheduled at random while their personal pattern is still building up.
The detail
Splitting one campaign into many individually timed sends multiplies the number of scheduled jobs behind the scenes — a list of a few hundred contacts becomes a few hundred separate dispatches instead of one. Every dispatch still has to run through a global suppression check at the moment it fires, not only when the campaign was first queued, because a contact could unsubscribe hours after the campaign was scheduled but before their personal staggered slot arrives. Optimising for open time cannot weaken that safeguard for even one recipient in the stagger.
This feature reads open-time history from a tracking pixel, and open tracking has become a genuinely unreliable signal — Apple Mail Privacy Protection and similar features now pre-fetch images for a meaningful share of recipients, registering an 'open' the moment the email arrives rather than when a person actually looks at it. A contact's computed best window is only as accurate as the underlying open data, and for a recipient whose mail client pre-fetches aggressively, that window may reflect delivery timing more than genuine reading behaviour.
A new contact's fallback hour is a reasonable default, not a personalised choice, and stays that way until enough real open history accumulates to compute something better — there is no shortcut beyond the contact actually opening a few emails over time. A business expecting immediate personalisation for every contact from day one will find the newest subscribers on any list are, quite reasonably, sent at the same default hour for a while, which is expected behaviour, not a gap.
Industry use cases
12 industries where Patri applies this directly.
A software reseller captures demo requests through a signup form; Patri enrolls each lead in a welcome-and-nurture automation while the sales manager reviews and approves the first broadcast to a larger prospect list before it sends.
See the b2b sales playbookA regional NBFC branch collects customer email consent at account opening; Patri stores that consent record and later sends a fixed-deposit rate update only to customers whose consent record is on file, routed through a manager approval step first.
See the banking and finance playbookA D2C skincare brand connects its online store; when a shopper adds a serum to cart but leaves, Patri's recovery automation sends a reminder a few hours later without any manual action from the brand's small team.
See the beauty and cosmetics playbookAn online exam-prep platform enrolls every new trial signup into a welcome series that introduces study resources over the first week, while a separate automation checks in on students who have not logged in for two weeks.
See the education playbookAn independent designer adds a signup form to their portfolio page; Patri captures each new subscriber's consent and sends a two-email welcome sequence introducing recent work.
See the freelancers and consultants playbookA physiotherapy clinic uses a welcome sequence for new patient inquiries and a quarterly newsletter reviewed by the clinic owner before sending, since Patri flags AI-drafted health claims for manual approval.
See the health and wellness playbookA modular-furniture retailer connects its catalogue site; a visitor who views a wardrobe configuration but does not request a quote receives a follow-up email a day later through Patri's recovery automation.
See the home decor and furnishing playbookAn agency managing five retail clients keeps each client's contact list and consent records separate in Patri, with every draft campaign routed through the account manager's approval before it reaches that client's subscribers.
See the marketing agencies playbookA brokerage captures site-visit inquiries through a signup form; Patri enrolls each inquiry in a nurture sequence that shares similar listings over the following weeks, while a broadcast to the full buyer list still needs the principal broker's sign-off.
See the real estate playbookA restaurant collects email addresses through a QR-code signup form at checkout; Patri sends a monthly offer email to that list and automatically suppresses anyone who unsubscribes from future sends.
See the restaurants and food playbookA salon connects its booking system; clients with no visit in the last two months are automatically enrolled in Patri's re-engagement sequence, which pauses immediately if the client books a new appointment.
See the spas and salons playbookA travel agency's package-inquiry form feeds into Patri, which sends a short sequence of destination highlights over the following days and a follow-up if the traveler started but did not finish a booking request.
See the travel and tourism playbookMore from Patri
The business gets a professional-looking email out to its list without hiring a designer or writing code.
Learn moreThe business sends fewer, more relevant emails and avoids annoying subscribers who do not care about a given message.
Learn moreThe business nurtures leads and customers on autopilot — a welcome series, a re-engagement sequence — without anyone remembering to hit send each day.
Learn moreNew subscribers and customers get an immediate, on-brand introduction instead of silence after they sign up.
Learn moreThe business wins back revenue and engagement from people who started something (a cart, a booking, an inquiry) and did not finish.
Learn moreThe business finds out which subject line or message performs better before committing the whole list to one version.
Learn moreQuestions
No — a contact with no history is scheduled at a sensible fallback hour rather than being skipped or left unscheduled, and that fallback hour is used until enough real open behaviour accumulates to compute a genuinely personalised window for them instead of the default one. There is no delay to a new contact's very first send while their pattern builds up over time.
Yes, and this is checked for directly — every individual staggered dispatch runs its own suppression check at the moment it actually fires, not only when the whole campaign was first queued. This matters specifically because staggering spreads individual sends across hours or even a full day, giving more time for a contact's status to change before their personal slot arrives.
It is only as accurate as the underlying open-tracking data, which has become a less reliable signal for a meaningful share of recipients since some mail clients now pre-fetch images and register an open the instant an email arrives rather than when someone actually reads it. Treat a contact's computed window as a reasonable, data-informed estimate rather than a precise, guaranteed read of exactly when they check their inbox.
Yes — the business sets the outer bounds this operates within, such as never before 7am or after 10pm, so a contact's personal computed window still stays inside hours the business is actually comfortable sending during. The optimisation works within that range rather than overriding it, however strong a particular contact's own pattern looks on paper, and no exceptions get made for individual contacts.
The rest of your stack
No rip-and-replace — send when subscribers are most likely to open works alongside the systems already running your business.
Coming soon