We have food at home: Turn the data you have into compelling automated campaigns

As a marketer, you have a valuable asset at your fingertips: data. It’s like having a pantry filled with ingredients, each with the potential to create something extraordinary. However, just like having ingredients without a recipe, having data points without a clear strategy can leave you feeling unsure about how to make the most of them. You understand the importance of personalization and automation, but putting all the pieces together to craft impactful campaigns can be a daunting task.

Data-driven marketing goes beyond having the ingredients; it’s about knowing how to use them strategically to deliver personalized experiences, drive engagement, and increase conversion rates.

Bookmark this post as a resource to help you turn those data points into compelling automated campaigns that activate and convert customers. Consider this your personalized recipe book, designed to empower marketers like you to create data-driven messages. Each data point will serve as a key ingredient, and we’ll show you how to combine them effectively to achieve remarkable results.

So, roll up your sleeves and let’s unlock the full potential of your customer data to create campaigns that activate, engage, and convert your audience like never before.

Product inventory data

If you have product inventory data, consider creating the following campaigns:

• Back in stock: Notify customers when previously out-of-stock items are available again.
• Low in stock: Send alerts to customers when their favorited or carted products are running low in stock.
• Price drop: Add urgency to nudge the customer to make a purchase.
• Replenishment: Remind customers to repurchase products based on their previous purchase history.

Browse or cart event data

If you have browse or cart event data, consider creating the following campaigns:

• Back in stock: Send dedicated emails to customers who have browsed or added out-of-stock items, informing them about the availability of the products.
• Browse abandon: Email customers about products they have viewed but haven’t purchased, including personalized recommendations.
• Cart abandon: Remind customers about items they have added to their cart but haven’t completed the purchase.

Order history data

If you have order history data, consider creating the following campaigns:

• Back in stock: Notify customers who have shown interest in specific products when those items are back in stock.
• Buy again: Encourage customers to repurchase products they have previously bought.
• Invitations: Invite customers to exclusive events or promotions based on their past orders.
• Milestones: Celebrate important milestones with customers, such as birthdays or anniversaries.
• Order confirmations: Provide order details and related product recommendations after a purchase.
• Post-purchase: Follow up with customers after their purchase, including personalized recommendations based on their order history.
• Referral program: Encourage customers to refer their friends or network, rewarding them for successful referrals.
• Win-back: Target customers who have not made a purchase in a while with personalized incentives to re-engage.

Customer location data

If you have customer location data, consider creating the following campaigns:

• BOPIS: Notify customers about the option to buy online and pick up their orders in a nearby store.
• Buying affinity time: Trigger campaigns based on customers’ location and weather data to drive purchasing decisions.
• Invitation: Send event invitations to customers based on their geographical location.

Store hours and location data

If you have store hours, location data, or order readiness data, consider creating the following campaigns:

• BOPIS: Inform customers about the specific store location and hours so they can pick up their order. Or, send notifications to customers when their orders are ready for pickup at the chosen store.
• Invitation: Send event invitations specific to the store or event location.

Brand affinity scores

If you have brand affinity data, consider creating the following campaigns:

• Buying affinity time: Deliver targeted campaigns based on customers’ brand affinity scores and their browsing and purchase history.
• Personal offers: Tailor offers and promotions to customers based on their brand affinity scores and purchase behavior.
• Referral program: Leverage customers’ brand affinity scores to identify potential advocates for your referral program.

Subscription status or tier

If you have subscription status or tiers, consider creating the following campaigns:

• Newsletters: Customize newsletter content based on customers’ subscription status or tier.
• Upsell opportunities: Offer personalized upgrade options to customers based on their subscription status or loyalty tier.

Browsing history data

If you have browsing history data, consider creating the following campaigns:

• Browse abandonment: Remind customers about products they have previously browsed, providing personalized recommendations to encourage conversion.
• Personal offers: Deliver tailored offers based on customers’ browsing history, increasing the likelihood of conversion.
• Recommendations: Recommend products based on customers’ browsing history, enhancing their shopping experience and encouraging additional purchases.
• Referral program: Identify potential advocates for your referral program based on customers’ browsing history.
• Win-back: Target customers who have shown interest in specific products or categories in their browsing history, offering personalized incentives to win them back.

Product categories

If you have product category data, consider creating the following campaigns:

• Buy again: Recommend related products or similar items within the same category to encourage repeat purchases.
• Upsell opportunities: Offer customers personalized incentives to upgrade to higher-priced products within the same category.

Favorited products

If you have data on favorited products, consider creating the following campaigns:

• Brand affinity scoring: Leverage customers’ favorited products to determine their brand affinity scores for targeted campaigns.
• Low in stock: Notify customers when their favorited products are running low in stock to create a sense of urgency.
• Win-back: Remind customers of their favorited products as a way to re-engage and encourage them to make a purchase.

Weather data

If you have weather data, consider creating the following campaigns:

• BOPIS: Notify customers about the option to buy online and pick up their orders in a nearby store, for example, the day before rainfall, a sunny day, or a snowy day.
• Buying affinity time: Trigger campaigns based on customers’ location and weather data to drive purchasing decisions.

Delivery date:

If you have delivery date information, consider creating the following campaigns:

• Order confirmations: Provide order details, delivery information, and related product recommendations after a purchase.
• Post-purchase: Follow up with a confirmation, education about their purchase, communication of delivery timelines, or further product or service recommendations that may be relevant.

The campaign strategies above show how each data point can be used to create personalized, targeted automated campaigns that drive customer engagement, conversions, and loyalty. By leveraging customer and business data effectively, marketers can deliver highly relevant messaging that resonates with their audience and increase revenue in the process. And just a friendly reminder that with Cordial, you have the ability to send any of these campaigns. We have all the recipes!

For more in-depth information on these strategies, including examples, the best channels to use, key data points, and tips—check out our Automation Strategies ebook series: 

• Activate: 9 Lifecycle Automation Strategies for Retailers 
• Convert: 11 Lifecycle Automation Strategies for Retailers
• Reactivate: 6 Lifecycle Automation Strategies for Retailers