Introduction to Segmentify Push Scenarios

Introduction to Segmentify Push Scenarios


Push Notifications are indispensable for eCommerce today. Push campaigns that serve different purposes can increase the conversion rate considerably since they are campaigns that directly reach the customer.


At this point, Segmentify offers a wide variety of push campaigns.


The campaigns offered by Segmentify are as follows.

Double-Step Push Permission Prompt

The Push Permission Prompt campaign is the most critical campaign for other push campaigns to work. When the user visits the website while this campaign is active, push notification permission must be received from the website. 

If the user answers "allow" to the permission question from the campaign and the browser, push notifications will be able to reach the user.





Push Recommendation

Push Recommendation campaigns offer the opportunity to send personalised push notifications for any period of time with Segmentify algorithms.





Bulk / Segmented Push

Bulk / Segmented Push Campaigns offer the opportunity to send push notifications for all customers or micro-segments. With this campaign, customers will be able to receive pushes from their favourite categories and be informed about updates.



Fly Mode

Fly Mode campaigns offer the opportunity to send push notifications for any specific user behaviour. It is triggered along with any behaviour (event) of the user. Campaign content can be selected on the panel and all algorithms can be used.



Winback Campaigns

We Missed You

We Missed You scenario works for the visitors that have not been visiting the website for the last n days.

If the visitor has a browsing history, the Smart Offers algorithm finds the top 5 favourite categories for each visitor and recommends the most purchased products from those categories. If the visitor does not have a browsing history, the most popular products are sent to that visitor.




 

Churn

The Churn scenario is for the customers who made at least x purchases from a store previously and have not been visiting for the last n days. The purchase number and the number of non-visiting day values are configurable. Smart Offers is the working algorithm here. It finds the top 5 favourite categories for each customer and recommends the most purchased products in those categories.



Price Drop

If there are discounted products in the products that each visitor has previously viewed, these discounted products are shown to the visitors and the minimum discount rate is determined according to these products.



Back in Stock

If any of the products that visitors viewed before were out of stock at that moment, this algorithm works and reminds the visitors when they are back in stock.



Growth

Order Follow Up

This algorithm works when a visitor makes a purchase. The related bundle of the last purchased product is sent after n days of their order. The personalised Complementary Products algorithm works here. It offers customers the best products based on their taste and their last orders on the website. 




New Arrivals

This algorithm works for visitors who have visited a website for the last n days. With these all-new arrivals, personalized products are recommended for each visitor based on their browsing / purchasing history. When the push will be sent, products that are new in the Segmentify system are listed from the Monday of the previous week until the campaign is sent. This algorithm updates itself once a week.




Birthday

Smart Offers algorithm is used by default for this campaign. In this campaign, the birth data of all users who have permitted at the time selected from the panel are checked to see if they have birthday data. On the day of the user's birthday, the campaign is implemented.





Top Sellers

Top Sellers scenario sends the top seller products in the store. It aims to show the most popular products to visitors and direct them to purchase these items.

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Retention

Nice to Meet You

This algorithm works for the newly registered visitors, aiming to convert them to customers by completing their purchases.




Abandoned Cart

Abandoned Cart aims to increase the effectiveness and conversion of the Cart Abandonment scenario. While the algorithm was sending a single push with the same content to those who leave the product in their cart, Segmentify aims to increase the CTR of the push and conversion rate by making it a push series.



  • 1st Push: In this push notification, a randomly selected product will be displayed among the products added to the cart.

  • 2nd Push: This push reminds the shopper of the last product the customer added to the cart.

  • 3rd Push: With the Alternative Products algorithm, the alternative product of the last product added to the basket will be sent.

  • 4th Push: If there is still no purchase, the coupon code will be sent at the last push. There is also a popup option here that will show the coupon code on the page when the end-user goes to the website after clicking on the push notification.




Last Visit Reminder

This algorithm works by reminding customers of the products they have visited before. The Personalised Last Visited Products algorithm works here. Push notifications are sent to remind the user of the last visited product.



Last Visit Alternatives

The Last Visit Alternatives scenario works when a visitor views a product and leaves the website without any basket action. For these visitors, the most related products are recommended after a specific period. The Personalised Alternative Products algorithm works here. It offers visitors the best products based on their browsing history. 





It was mentioned in the campaigns that there are algorithms that can be used together. These algorithms are listed below:
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  • Smart Offers: A personalised machine learning algorithm that recommends products based on best-matching categories and behaviour of the current visitor during the last visit.

  • Top Sellers: An algorithm that recommends the top-selling products from the current product category or category of current product or the overall e-commerce site.

  • New Arrivals: A machine learning algorithm that recommends new arrivals from the e-commerce site.

  • Last Visited: An algorithm that reminds visitors of all products they have visited during their lifetime on all platforms of the online shop.

  • Last Purchased: An algorithm that recommends the last products visitors have purchased in their last session.

  • Spotlights: A machine learning algorithm that intelligently sorts all the products on an e-commerce site.

  • Discounted Products: An intelligent algorithm that catches the price drops of all products and recommends them to the customers.

  • Predefined Products: A straightforward algorithm that recommends the products pre-defined for each product.


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