AI AGENT TEMPLATE
An AI agent that emails dormant bike rental customers (no booking in 90+ days) with a personalized rebook offer. Converts 3–5x cold rate.
Bike rental customers are two-mode: locals who rent occasionally and tourists who rented once during a trip. Both modes respond well to pre-season reactivation, and both are usually neglected entirely. The local forgot about you until they're planning the family weekend ride; the tourist will only come back if you're still in their head when they're planning the next trip to your city.
The Pre-Season Bike Customer Reactivation Agent reaches both cohorts with differentiated messaging. Six weeks before your peak season, the agent pulls every customer from the last 24 months, segments them (local vs. tourist based on address or behavior, by bike category), and drafts personalized emails referencing their specific prior rental with a returning-customer discount and early-season booking incentive.
The tourist-segment work is where outsized ROI typically lives. A tourist who had a great time on your rental last July is a 20-30% rebook prospect for next July — if they hear from you at the right moment. The right moment is their trip-planning window, which for most destinations starts 3-5 months before arrival. Email lands, brand is remembered, direct rebook follows, acquisition cost is zero.
Below is the full agent spec: trigger date, tools, segmentation logic, default copy, and how to configure offer structure and cadence for local vs. tourist customers.
"Every Monday, segment customers who have not booked in 90+ days but did rent within the prior 12 months. Compose personalized emails referencing their last rental (dates, bike type). Include a pre-filled rebook link and 10% returning-customer discount. Throttle send at 200 per day."
Paste this into Dash Agents. Dash reads the prompt, picks the right tools, assembles the logic, and creates a ready-to-run agent in seconds.
The agent uses the standard Dash Agents tool library. Every tool call is logged.
On trigger, the agent runs these steps in order. Any step can be customized by re-prompting.
Customers with most recent booking 90+ days ago AND a booking within the prior 12 months. De-duplicate, exclude unsubscribes.
Casual recreational, multi-visit, families, tour participants, e-bike riders.
Attach each rider's specific last rental(s): dates, bike type, notes.
Per rider: URL opens with last setup pre-filled.
Warm, references last visit, delivers link + 10% discount.
200 per day to protect sender reputation.
Opens, clicks, rebooks per segment.
Customizations by re-prompting in plain English: change the trigger timing or conditions, adjust the recipient list, tune thresholds, modify tone, add approval gates, connect additional channels (SMS, WhatsApp) if available. Run in approval mode for the first week to build confidence before switching to autonomous.
Structured automation beats manual follow-up in three ways:
Set this agent up on your first week. Run in approval mode for five days while you watch the outputs, then flip to autonomous. The ROI compounds across a full season — a quiet automation that simply does the right thing, every time, without anyone having to remember.
The highest-leverage tactic is a warm personalized email to riders who have gone dormant (90+ days since last booking) referencing their prior rental, with a pre-filled booking link and a modest returning-customer discount (10%). Personalization drives 10–15% conversion — dramatically better than generic "we miss you" blasts. Run it on a rolling weekly cadence, not a single annual blast — that way you catch lapses early instead of waiting for an opening-day push.
Dash Agents handle the repetitive work so your team can focus on customers. Start your free trial and build your first agent in minutes.
