This demand generation Tactic is enhanced with product recommendations in the same product category, with incentives for leads, defecting and active customers.

It supports the Revenue objective and contributes to the following strategies:

• Convert leads to first-time buyers
• Convert first-time buyers to active customers
• Retain active customers
• Win back defecting customers
• Win back inactive customers

The prerequisites for the Price drop Tactic to work are the following:

• Web Extend
• Predict

Product view events are sent via Web Extend, and the Product catalog is loaded into Predict. Uploading of product data should happen once per day and the load should be completed before the calculation is scheduled.

• Calculation happens at 11:00 UTC.
• Any Data Platform to Relational Data load after the calculation will replace the previous state, so only fresh data will be stored in the Relational Data database.
• We suggest scheduling the Automation Center campaigns outside of the loading hours.  The approximate loading hours for Price drop Tactic is 11:00 to 14:00 UTC.
• Currently, we use the last 2 versions of the product catalog to feed our calculations. This means the calculation works only if a customer doesn't load their product catalog more than once a day.
  • E.g: the product catalog load is scheduled to run every even hour. In this case, the price drop calculation will compare the product catalogs uploaded at 8:00 and 10:00 and not the changes that happened from one day to the next.
• Product views which are followed by purchase are not filtered out from the calculation.
• Price drop calculation requires at least 2 product catalog uploads in the last 7 days. It uses the price field in the Product catalog to calculate the price drop events.

It always compares to the previously uploaded Product catalog to the current one. After all products with a price drop are listed, the algorithm checks who has an affinity to the products. A consumer considered having an affinity to a product if they checked the product at least once in the past between 12 hours and 90 days ago. We store price drop events only if their value is at least 10%, therefore the calculation filters out all products which have less than 10% price drop or if they are not available. Product views followed by purchase are not filtered out, therefore all contacts who made a purchase in the last 14 days are excluded.

The program looks like this.

The program starts with a Recurring filter node that runs every day and uses a Predict segment that returns all customers who have purchased within the last three days.

The segment filters on contacts who visited a product in the last 90 days which price dropped now. 

1. Please contact your Client Success Manager or Emarsys Support.

2. Emarsys will create your Price drop Tactic in Real Time Interaction.

3. Choose from the following options:

• If your template was created by Emarsys, you do not have to update it. You can proceed to the next step.
• If you use your own template, you need to update it by following the instructions in Updating your template for Product catalog update Tactics.

4. Open your Price drop campaign and add the required tokens to the Repeatable block.

5. Once your campaign is ready, replace the original email campaign with your updated Price drop campaign in the Tactic Real Time Interaction program.

6. Activate your Price drop Real Time Interaction program.