The Pampik online store appeared back in 2009 when online shopping was not mainstream. But the idea of delivering diapers right to the door of the new parents took off. Over time, the product range has been enriched with other children's products. Pampik was among the first to develop new ways of working with the target audience with the help of our CDP.
This time we worked on providing a website as a communication channel to increase the sales (focusing on cross-selling and upselling). It was essential for us that the content for each visitor is personalized. On the one hand, it should be as valuable and relevant as possible, and on the other - provide maximum conversion.
This article will tell you how we solved this and raised the product recommendation ROI to 1734%.
Let's start with the secrets of Pampik’s success:
- Fast and convenient delivery. Features like "Quiet courier" (the courier doesn’t ring the doorbell); Free of charge delivery of orders ≤ 30 kg up to the 9th floor in case the elevator is out of order; delivery to the maternity ward in the hospital
- Solid loyalty program. For each purchase, the client receives bonuses - “pampiks”, which can be applied to the next order.
- Effective communication at every stage of interaction with customers and subscribers, implemented through the system. All major trigger chains are configured in the company account, including abandoned carts and abandoned views. As part of the support for the loyalty program, letters are sent about the accrual of “pampiks” and their expiration dates. In addition, sending custom triggers is configured. They are used to respond timely to the buyer's actions or a change in its segment (for example, a change in the age of a child, the appearance of a baby, etc.). One of the best conversion triggers in this series is the reminder to restock diapers.
How we achieved such a high ROI of product recommendations
To introduce product recommendations on the site we enabled the CDP and installed a web tracking script for the behavior of visitors that sends the data about their actions to our system. Using that data the platform generates personalized recommendations that are shown to site visitors.
The selection of products for blocks with recommendations is created with the help of AI. It considers the user's interests and the history of interaction with the site, for example, previously viewed products and categories, previous orders, etc.
Location of product recommendations on the Pampik website
The set of available algorithms solve different problems and depend on the type of page where the blocks will be located
Pampik decided to place blocks with recommendations as follows:
On the main page of the site
Collections introduce visitors to essential assortment deals, and returning visitors are offered products based on their previous activity.
- Popular for you - personalized real-time and history-based search results.
In stock item card
Blocks improve the user experience by saving them time searching for alternative and complementary products and reminding them of a story. For business, these are classic cross-sell and upsell tools.
- “Customers Also Bought”
- “Similar products”
"Similar products" block in the category "Pampers" is formed according to a separate algorithm, considering brand, size, and product line, since these parameters are essential for many buyers.
Out of stock on the product card
Recommendations on such pages help keep visitors reduce their negative experience and generate sales.
- “Customers Also Bought”
- “Similar products” – In-stock items in the same category as the out-of-stock item.
In the basket
The cross-sell block contains relevant products that can be added to the order.
- “Buy with this product”
On 404 page
The recommendations here also help improve the UX and build trust for a new visitor if he followed a broken link.
- “Popular for you”
Thank you for your purchase page
The product block on the thank-you page is another additional opportunity to sell more products to one client.
- “Popular for you”
It’s important
Remember that product recommendations are not set up once and for all. Changes are inevitable both in the company's business processes and in technology. Therefore in our CDP a Customer Success Specialist is assigned to a client implementing CDP functionality and accompanies him at every stage of interaction with the platform
Results
In a year of use recommendation blocks have shown high efficiency. For example the ROI of product recommendations on the site ranges from 341% (at the beginning) to 1734% (at the end of the first year).
The % of the total sales generated by product recommendations goes as follows:
- Buy with this product - 24.8%.
- Block on the 404 page – 0.81%.
- Block on the main page - 47.24%.
- Block "Buy with this product" in the cart – 11.81%.
- Block on the "Thank you for your purchase" page - 0.6%.
- Similar products - 7.18%.
- Similar products in the category "Disposable diapers" – 1.11%.
- Similar products for products not in stock – 6.37%.
In total, blocks with similar products bring about 14.7% of the profit received from product recommendations.
Conclusion
Pampik was among the first to introduce new technologies for interacting with the target audience, and our Customer Success helped the company along the way. This approach, combined with a well-thought-out assortment and a quality customer service system, provides Pampik with a leading position in the market.
Our team is constantly improving product recommendations: acquisition options, appearance, placements, attribution and the algorithms themselves. Data scientists are updating the logic of the recommendation system to make it relevant to the needs, preferences, and requests of each visitor. This means that the customer experience from interacting with the online store is more likely to be positive. Even if you already have recommendations on your site, we can measure their performance against our, so you can choose the best tool!