Audience Recipes That Drive Engagement

Audiences are only as good as the way you use them. The win isn't building one giant list, it's matching the right message to the right customers so your campaigns feel relevant instead of spammy. Here are proven segments to build, the fields behind them, and how to put each to work.

Why Segmenting Beats Blasting Everyone

Sending the same message to your whole list trains people to ignore you, and burns the opt-ins you worked to earn. Targeted messages land better, keep your unsubscribe and opt-out rates low, and protect your ability to reach customers at all. A handful of well-chosen audiences will out-perform one big blast almost every time.

High-Value Audiences to Build

Each recipe below notes who it captures, the fields to build it from, and how to use it. (For the mechanics of building one, see Creating a Custom Audience.)

• Win-back / lapsed shoppers. Customers who haven't ordered in a while. Build from Performed event (hasn't ordered online recently) or Computed trait (total order count plus Last active from App engagement). Use it for a "we miss you" message with a reason to return.
• VIPs / big spenders. Your most valuable customers. Build from Computed trait: Total spend or Avg ticket size above a threshold. Use it for early access to drops, loyalty perks, and first dibs on limited stock.
• Cart abandoners. People who added items but didn't check out. Build from Cart activity (cart total above zero, recent Last cart update) or Performed event (Abandoned cart). Use it for an automated reminder in Notification Settings, one of the highest-ROI messages you can send.
• First-timers. New customers with a single order. Build from Computed trait (Total order count = 1) or App engagement (recent First app open). Use it for a welcome nudge toward a second purchase, when loyalty is still forming.
• Category or brand loyalists. Customers who keep buying a certain category, brand, or strain type. Build from Performed event (Purchased category / brand / strain type). Use it for targeted drops, brand spotlights, and cross-sells (flower buyers → a new flower arrival).
• Channel-ready lists. Customers you're actually allowed to message on a given channel. Build from Contact trait opt-ins (Push / SMS / Email opt-in). Layer one of these into other audiences so a campaign only reaches people who said yes.
• Pickup vs. delivery preference. How customers like to shop. Build from Computed trait (Delivery order ratio, Pickup/curbside order ratio). Use it to tailor offers to each habit.
• Engaged but not buying. App-active browsers who haven't converted. Build from App engagement (high Total app sessions) plus a low Total order count. Use it for a first-order incentive.
• Medical patients. Build from Contact trait (Has medical card) for med-relevant messaging, handling this data carefully and per your state's rules (see the compliance note).

Layer Rules for Sharper Targeting

The best audiences usually combine conditions. Set the match to all and stack traits: high total spend and no order in the last 30 days gives you a high-priority win-back list worth a stronger offer than a generic lapsed customer.

Use Is in audience and Is NOT in audience to build on what you've already made, for example, target VIPs while excluding anyone already in an active campaign audience, so you're not over-messaging the same people.

Keep Your Audiences Healthy

• Don't over-message. Use exclusions so the same customers aren't hit by every send.
• Refresh and rename. Audiences are rule-based and update on their own, but names and intent drift, so keep them clear and retire ones you no longer use.
• Watch what converts. Check Orders Over Time and Top Selling Products in Analytics after a campaign to see which segments actually drove sales, and lean into those.

A Quick Compliance Note

Cannabis messaging is regulated and the rules vary by state. Only contact customers who've opted in on each channel, follow your local rules on SMS and email consent and on advertising promotions, avoid health or medical claims, and handle medical-patient data appropriately. When in doubt, check your state's regulations. DopeTech can't give legal advice on what's allowed in your market.