Introduction to Segmentify's Personalized Email Campaigns

Introduction to Segmentify's Personalized Email Campaigns



 Campaigns and Algorithms of Push Module


Everyone has personal email accounts, and everyone receives tens of emails every day. Due to people receiving excessive amounts of daily emails, Segmentify has personalised emails. According to Segmentify's 2018 data, personalised emails tend to increase click-through rates up to 18% and conversion rates up to 5%. Therefore it is clear that personalised emails are a force to be reckoned with for eCommerce success!


Effects of Personalised Email Campaigns


Segmentify’s all email campaigns are listed within 3 main categories:  


  • Recommendation, 

  • Fly Mode,

  • Bulk / Segmented

Winback

Price Drop

If there is a discounted product within the products that each of the visitors viewed before, Segmentify shows these discounted products to the visitors and identifies the minimum discount ratio to be sent. 

The Price Drop scenario is very effective as the price of products that visitors are already interested in is reduced. It is also a very encouraging scenario for visitors to complete their orders.


 Price Drop Email Campaign


Back in Stock

If any of the products that visitors viewed before were out of stock at that moment, Back in Stock works and lets the visitors know when they are back in stock.

Reports show that one of the reasons people decide to buy includes stock availability. 14% of shoppers find it crucial. So, keeping eCommerce website visitors up to date about stocks would be very important.


 Back in Stock Email Campaign

We Missed You

We Missed You works for the visitors that have not been visiting the website for the last n days. The n value is configurable.


 We Missed You Email Campaign


Churn

The Churn algorithm is for the customers who made at least x purchases from the 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 algorithm used here. It finds the favourite categories for each customer and recommends the most purchased products in those categories.

It costs nearly 6 times to get a new customer than it does to keep an existing one. So, it is crucial to remind yourself of personalised products to eCommerce websites shoppers who have made a purchase before but not visiting eCommerce websites for a long time.


 Churn Email Campaign

Growth 

Order Follow Up

The Order Follow Up algorithm works when a visitor makes a purchase. Segmentify sends the related bundle of the last purchased product 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 eCommerce websites. And it can also identify how many emails will be sent on a monthly/weekly/daily basis.

Repeat customers spend 3x more money than new customers. This scenario is a very effective cross-sell method. 


 Order Follow Up Email Campaign

New Arrivals

This algorithm works for visitors who have visited eCommerce websites for the last n days. With these all-new arrivals, personalised products are recommended for each visitor based on their browsing/purchasing history. The email will be triggering when products that are new in the Segmentify system are listed from the Monday of the previous week until the campaign is sent. 


New Arrivals Email Campaign

Top Sellers

Top Sellers algorithm shows the top seller products in the store. It aims to show the most popular products to visitors and direct them to purchase these items. It works for visitors who have viewed at least one product in the last week.

According to a Nielsen Report, 83% of consumers trust product recommendations from their friends and family, which can be used to the eCommerce websites advantage by using this “Top Sellers” scenario for the email marketing strategy.  


 Top Sellers Email Campaign

Birthday

The Birthday campaign is a mix of Smart Offers, New Arrivals, and Discounted Products algorithms. Additionally, it is possible to customise the number products that will come from these algorithms. 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 works.


This scenario makes the website’s visitors feel special as Segmentify knows their previous behaviours and tastes. 


For this campaign to work, birthDate:'dd.MM.YYYY' must be sent on the integration side. 

 

 Birthday Email Campaign

Retention

Abandoned Cart

The Abandoned Cart algorithm works when a visitor adds a product to the basket but leaves the website without purchasing. Within this scenario, it can simply identify how many emails the Segmentify account will send on a daily/weekly/monthly basis per user. 


It is exceptionally effective as a sales recovery tactic. Some reports suggest that 75% of shoppers abandon their carts. And most of them plan to come back. Hence, sending a personalised email and reminding yourself in the right way may become very effective.



 Abandoned Cart Email Campaign

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 is used in this campaign. It offers visitors the best products based on their browsing history. Within this scenario, you can simply identify how many emails will be sent on a daily/weekly/monthly basis per user.


 Last Visit Alternatives Email Campaign


Nice to Meet You

The Nice to Meet You scenario works for the newly registered visitors, aiming to convert them to customers by completing their purchases.

The user must sign up in order to send Nice to meet you by email. Therefore, this scenario is triggered by the signup event and also requires email information.


 Nice to Meet You Email Campaign


Last Visit Reminder

The Last Visit Reminder algorithm works by reminding customers of the products they have visited before. The Personalised Last Visited Products algorithm is used here. Emails are sent to remind the user of the last visited product.


Last Visit Reminder Email Campaign

Fly Mode Email Campaigns

Fly Mode Campaigns offer the opportunity to send emails 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.


Fly Mode Email Campaign Page

Bulk / Segmented Email Campaigns

Bulk / Segmented Email Campaigns offer the opportunity to send emails to all customers or micro-segments. Our customers can inform their users about updates on their favourite categories. 

As Segmentify, we try not to use the Bulk / Segmented Email campaigns unless we have to. Because the effect could be less according to personalised campaigns since all users are contacted and is more costly. 

Bulk / Segmented Email Campaign Page


Other Algorithms

Discounted Products

This algorithm shows the discounted products. The products, which are purchased or viewed on a daily, weekly, or monthly basis, return as a recommendation. The algorithm catches the price drops of all products and recommends them.

Spotlights

This algorithm shows the most popular products. The most popular products are determined by Segmentify Rock Score. It aims to show the most popular products to visitors and direct them to purchase these items. 

From this algorithm, products can be requested on a daily, weekly, monthly time frame basis.


In this algorithm, the time frame recommended by Segmentify is “monthly”. If there is no special case, a "monthly" time frame can be used.

Last Purchased Product

This algorithm brings each user’s last purchased products. The aim is to help customers with speeding the purchase process who buy repetitive products (such as toilet paper, bottled water). Here, it can also return products that are not in stock as recommended.


The Last Purchased Product algorithm also returns products that are not in stock by default.

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