ROI 807%: Cascade Campaigns, Automated Campaigns, Pop-ups, and the FOAM Loyalty Program

FOAM is an online cosmetics store with delivery in Eastern Europe and a beauty store. It offers premium niche brands with a strong reputation and boosts new local cosmetics developers.
Business scale. 
70.000 customers in the database
author
Gleb Aitov,
co-founder of FOAM
Goals
Manage communications in a single windowIncrease email channel revenueIncrease website conversionIncrease the subscriber base  
Solutions
We switched to the marketing automation platformWe conducted an RFM analysis to personalize bulk and launch trigger campaigns and initiated cascade campaignsWe launched stories on the website, data-collecting pop-ups, and personalized widgetsWe launched an omnichannel loyalty program

IT stack. 

ERP, Marketing Automation Platform
Results
ROI 807%18.9% — the average share of email channel revenue in total revenue9.6% — the average share of trigger campaigns revenue in total revenue

Time to value. 

9 months
Noteworthy features
We launched recommendations of related products based on their active ingredients
The following case study is from Mindbox, the original brand behind Maestra’s technology
FOAM marketing specialists were using three different services only to send emails. At the same time, the way the emails were designed left much to be desired, analytics were scattered across different systems, and the campaign preparation required the constant participation of developers. The plan was to launch a loyalty program and personalize the website, which would lead to an inevitable increase in the number of services used.
To avoid this issue, FOAM decided to implement a marketing automation platform. As a result of the integration, the company has been able to achieve the following:
  • Marketing and developer teams now spend less time on tasks;
  • Customers are segmented based on frequency and recency of purchases (after an RFM analysis was carried out);
  • An automation map was created including non-standard automated campaigns — e.g., a reminder that a shampoo the customer had purchased would soon run out, or that the customer would need to buy sunscreen to give their vitamin A a boost;
  • The website was personalized, an ETA timer was added for deliveries and a free delivery counter was added to the cart;
  • An omnichannel loyalty program was launched.

Results

  • 807%
    ROI of marketing automation
  • 18.9%
    Average share of email channel revenue in total revenue
  • 9.6%
    Average revenue share of trigger emails in total revenue

ROI 807%

To calculate the ROI, we took data from January to September 2021. We have not disclosed the figures at FOAM’s request. Calculation formula:
807% — ROI from the Mindbox platform. This means that each dollar invested in the platform brings FOAM $8.
18.9% — the average share of email channel revenue relative to the total revenue
Data from the “Mindbox Summary report on campaigns,” Last-click attribution
9.6% — the average share of revenue from trigger campaigns in total revenue
Data from the “Mindbox Summary report on campaigns,” Last-click attribution

What has changed with the introduction of the marketing automation platform?

Before the platform was implemented
After the platform was implemented
Bulk, automated, and transactional emails were sent from three different systems. There was a separate service for text messages.
Emails and text messages are sent from a single window.
The emails looked different because of the new layout. It was difficult to make automated emails look nice, although this is critical for the beauty sphere.
All brand communications are in a uniform style.
Emails and text messages were prepared with the help of layout specialists and programmers.
Campaigns are prepared without developers. If the text and images are ready, it takes 10 minutes to prepare and send an email campaign.
There was no single analytics source. The data had to be collected from different services.
Unified analytics. Even if a campaign took place in both email and SMS channels, its results can be evaluated in one report.
Active referral program for purchasers. The loyalty program was only a plan.
Launched a loyalty program.

How to segment the audience of bulk email campaigns

Bulk campaigns include news, useful articles, and promotional materials. At the same time, the customers receive no more than four emails per week. If they made an order or received a series of trigger emails, they are excluded from bulk campaigns, which prevents them from unsubscribing. Customers are segmented based on RFM analysis. They are evaluated based on the recency and frequency of their purchases, their average order value, as well as their interaction with emails. Periodically, different content is sent to active users and those who do not open emails. For example, we send news to active users, while churned users receive promo codes and personal recommendations. Those who have not responded to communications for a very long time are placed on stop lists and excluded from campaigns.

An email with a discount and a survey

This was sent to customers who had made an order in the last six months, but did not place another one in the past three months:
Open rate
Click rate
Conversion rate (measured using last-click attribution)
19.5%
3.1%
0.1%
Image
Customers are also segmented by region. The residents of large cities are sent content related to the beauty store, such as news and special promotions.

Invitation to an in-store party

Open rate
Click rate
Conversion rate (measured using last-click attribution)
20.4%
1.7%
0.01%
Image

An email about a discount for used packages

Open rate
Click rate
Conversion rate (measured using last-click attribution)
17.6%
0.4%
0.1%
Image

How to use product recommendations in bulk email campaigns?

Almost all campaigns use product recommendations.
Image

A/B test of product recommendations

Email with recommendations:
Open rate
Click rate
Conversion rate (measured using last-click attribution)
13.3%
0.8%
0,1%
Email without recommendations:
Open rate
Click rate
Conversion rate (measured using last-click attribution)
12.9%
0.6%
0,01%
Recommendation widgets can’t be added to emails aimed at focusing on a particular brand or new products.

An email regarding new brands in the store

Open rate
Click rate
Conversion rate (measured using last-click attribution)
21.5%
1.4%
0.1%
Image

An email regarding discounts on “Don’t touch my skin” brand

Open rate
Click rate
Conversion rate (measured using last-click attribution)
18.5%
2.7%
0.3%
Image

How to talk about promotions in cascade campaigns?

Big sales are held from time to time. For example, in August and September, they were stylized for music festivals. At this time, customers received email communications almost every day. Those who did not open email were “caught up” with text messages:

An email regarding the Beauty Rhythm Fest promotion

Open rate
Click rate
Conversion rate (measured using last-click attribution)
14.4%
1.7%
0.2%
Image

Text message regarding the Beauty Rhythm Fest promotion

Click rate
Conversion rate (measured using last-click attribution)
15.6%
0.5%
Image

How the automation map was improved

Welcome series. Previously, the store had a short welcome series consisting of two emails: DOI and emails with a 10% discount. Now the sequence has been significantly expanded and made more comprehensive:
Image

Double-Opt-In (DOI) email

This is sent to confirm registration:
Open rate
Click rate
Conversion rate (measured using last-click attribution)
62.6%
44.1%
11.1%
Image

Reminder to confirm subscription

This is sent two days after an unconfirmed subscription:
Open rate
Click rate
Conversion rate (measured using last-click attribution)
29.7%
4.7%
0.4%
Image

An email with a 10% discount and recommendations

This is sent if the user left their contact details in the pop-up on the website:
Open rate
Click rate
Conversion rate (measured using last-click attribution)
75.3%
12.7%
3.3%
Image
Abandoned category and product view, and abandoned cart. We launched campaigns for an abandoned category and product view, as well as an abandoned cart. Product recommendations help to return customers to the website.

Abandoned product browse

Open rate
Click rate
Conversion rate (measured using last-click attribution)
36%
2.7%
0.2%
Image

Abandoned cart

Open rate
Click rate
Conversion rate (measured using last-click attribution)
34.8%
5.9%
1.7%
Image

Abandoned product category view

Open rate
Click rate
Conversion rate (measured using last-click attribution)
38.4%
2.4%
0.2%
Image
Related products recommendations. The customers’ purchases say a lot about them, and FOAM uses this knowledge to make a suitable offer. This means that if the customer has sensitive skin, they will be offered specialized products for this issue.

An email regarding sun protection

This is sent to those who bought cosmetics that contain acids, vitamin C, and vitamin A:
Open rate
Click rate
Conversion rate (measured using last-click attribution)
31.5%
1.8%
0.1%
Image

An email regarding hair accessories

This is sent to those who bought hair care products:
Open rate
Click rate
Conversion rate (measured using last-click attribution)
33.8%
2%
0.1%
Image
A reminder that the purchased product is running out. We can roughly calculate how quickly certain products run out. For example, shampoo is consumed in 60 days. This information was added to the product feed, from where it gets into Mindbox. Then we set up a trigger campaign. When a person buys a product, the system waits, and then seven days before the expected date when the product is supposed to run out, it sends an email with an offer to buy it again.

Reminder that the shampoo will end soon

Open rate
Click rate
Conversion rate (measured using last-click attribution)
42.4%
3.3%
0.8%
Image
Reactivation. Based on RFM analysis, the audience was divided into groups by frequency, recency, and order value. Each group received an email reminding them about the brand and offering them a 15% discount:
Image

An email with reactivation discount

Results in the “Customers that are churning” segment:
Open rate
Click rate
Conversion rate (measured using last-click attribution)
27.4%
6.7%
0.3%
Results in the “Lost regular customers” segment:
Open rate
Click rate
Conversion rate (measured using last-click attribution)
22.9%
3.3%
0.3%

How the website was personalized

Stories, pop-ups, embedded blocks, and widgets are launched on the FOAM website in order to collect customer data and increase conversion. Product recommendations are used both in email campaigns and in the online store. “Wheel of Fortune” for collecting email addresses. Customers who are not subscribed to the store’s communications see the “Wheel of Fortune” pop-up. At the same time, it does not distract from purchases as it does not appear on the product page and in the cart.
  • 9,7
    thousand customers have left email addresses in 2 months
  • 8,8%
    pop-up conversion
A pop-up for collecting the date of birth. When we launched an automated campaign with a birthday promo code, it became necessary to collect the customers’ dates of birth. Therefore, customers with a subscription were displayed the following pop-up:
  • 3
    thousand customers have indicated their birthday in 2 months
  • 19,5%
    pop-up conversion rate
Stories. In stories, we talk about promotions and products, we observe active ingredients and the problems of customers that these products can solve.
ETA timer. Fast delivery is one of the advantages of the store. Orders placed before 16:00 will be delivered on the same day within the city. Therefore, customers from the specific cities see how much time is left to place an order to receive it today. Other users don’t see the timer.
Image
Free shipping counter. Delivery in the store is free if the order value exceeds $80. Embedded blocks and widgets help customers understand how many products they need to add to the cart to get free delivery.
Image
Product recommendations. Embedded blocks and widgets with recommendations are added on the main page, in the product card, and in the cart.
Image

Why is the loyalty program being restarted?

Previously, FOAM only had a referral program for purchasers. One of the reasons for switching to Mindbox is the opportunity to develop our unique loyalty program. As a result, we launched a tiered point loyalty program. When buying, the customer receives points that they can start spending in a week. Points can be used to pay for up to 99% of the purchase. Additionally, customers received discounts on their birthday and on their favorite products. At the same time, the loyalty program is omnichannel — the customer can get bonus points in the beauty store, and spend them in the online store, and vice versa.

An email regarding the accrual of points in the loyalty program

Open rate
Click rate
Conversion rate (measured using last-click attribution)
50.8%
8%
0.8%
Image

An email regarding the transition to a new level in the loyalty program

Open rate
Click rate
Conversion rate (measured using last-click attribution)
53.7%
10.4%
0.9%
Image

How do we plan to develop direct marketing?

  1. Run NPS surveys in email campaigns to track customer satisfaction.
  2. Modify recommendation widgets in the cart, and make them more personalized. Add recommendations to the blog. As a rule, authors mention products in articles, but they also want to add recommendations that will offer related products.
  3. Create more personalized pop-ups, for example with related products or information regarding promotions. Add a warning that the product is running out of stock.
  4. Redo the promo page on the website. Currently, this is a set of banners. We are going to make a full-fledged page and automate shares using our ERP. By adding a promotional product to the cart, the customer will see a pop-up with an offer to perform a target action (add the same product for the second time or another product of this brand) and receive a discount or gift.
  5. Launch a bot on the website that will ask questions and recommend products based on the answers.
  6. Restart the loyalty program so that it motivates customers to return.