Smart Recommender Analytics

For all Web Smart Recommender campaigns on your website, Insider collects and visualizes usage metrics to show the impact on revenue and engagement performance of these campaigns. Smart Recommender Analytics presents revenue breakdowns that include both direct and discovery aspects, as well as user engagement journey breakdowns (from first impression to product purchase), as overall summary metrics.

You can also find campaign analytics, product analytics with product-algorithm relationships, and product category analytics, which enable you to generate merchandising insights.

You can also find answers to the following questions:

To see the performance of Smart Recommender Campaigns with specific metrics and detailed reporting, navigate to Reports > Smart Recommender Analytics to reach this dashboard.

Personalize metric calculations: The Attribution Window

The Web Smart Recommender aims to " create a product purchase” that can happen in days or weeks after the user engages with a recommended product. The time between these two actions is dynamic and can be adjusted at any time.

To see the performance of Smart Recommender campaigns, Insider offers a dynamic setup that allows you to customize the “time allowed between an engagement (click) and the goal action (purchase),” known as the Attribution Window.

The attribution window enables you to see the true performance. For instance, consider a fast-moving goods retailer where customers complete purchases on the same day or even in the same session. However, a customer of a furniture retailer can complete their order in 14 days or even in a month. If both companies use the same 7-day attribution window, the recommender analytics won’t include the furniture customer's purchase of a recommended product on the 10th day after the click. Therefore, you won’t be able to see the actual performance. Hence, select the window span that suits your customer behavior to tailor your analytic metrics calculation according to your end-users' behavior.

The attribution window is the time allowed for an end user to complete the purchase of a clicked product. It can be the same session, 1 day, 7, 14, or 30 days.

Session-based: The session starts when the user lands on the website and is terminated after 30 minutes of inactivity. Campaigns and products with click and purchase logs sharing the same session ID will be counted as a session-based conversion. Insider sends one viewable impression of the event per session. However, a user can have multiple clicks, add items to carts, and make purchases from the same campaign within the same session.
1 Day: The purchase must be completed within 24 hours of the click event.
7 Days: The purchase must be completed within 7 days of the click event.
14 Days: The purchase must be completed within 14 days of the click event.
30 Days: The purchase must be completed within 30 days of the click event.

How is the attribution window applied to direct revenue?

Events	Click	Purchase	Revenue
Day 1	Product 1
Day 5	Product 2	Product 1	Revenue 1
Day 8
Day 13		Product 2	Revenue 2
Day 25	Product 3	Product 3	Revenue 3

Product 1 was clicked on day 1 and purchased on day 5, indicating that the end user took 4 days to complete the conversion funnel.
- Revenue 1 will be added to direct revenue when you select a 7-, 14-, or 30-day attribution window.
Product 2 was clicked on day 5 and purchased on day 13, which means it took the end user 8 days to complete the conversion funnel.
- Revenue 2 will be added to direct revenue after selecting a 14 or 30-day attribution window.
Product 3 was clicked on day 25 and purchased on the same day, but not during the same session, which means it took the end user one day to complete the conversion funnel.
- Revenue 3 will be added to direct revenue when you select a 1-, 7-, 14-, or 30-day attribution window.

Filter your results

To narrow down the Smart Recommender Analytics, you can filter your results thanks to the date picker and the Filters button.

You can apply page type, platform type, and campaign status filters. These filters enable you to list campaigns on the same page and across different platform types to make a fair comparison.

You can also view the campaign summary in different statuses after filtering your results.

Revenue Performance

Through direct and assisted revenue metrics, you can visualize the "discovery” and “direct attraction” effects of Smart Recommender separately.

Direct Revenue is the total value of the recommended products purchased directly by clicking on the product links in your campaigns within the days selected from the attribution window. As the attribution window increases, more time will be allocated for a click to become a conversion, so a higher direct revenue value is expected.
Orders with Recommended Products are the number of checkouts containing at least one recommended product. You can compare this number with your total checkout count to see how recommendations are infused into your orders.
Assisted Revenue, also known as discovery revenue, shows the total value of products not recommended but purchased within the same session after clicking on product links in your campaigns.

Engagement Performance

The user's journey, which begins with the first click interaction with a Web Smart Recommender and concludes with purchasing a recommended product, is visualized using a funnel structure on the Product Engagement Funnel.

Product Impressions: Once the campaign container enters a user's viewport, one impression log is sent for each visible product. So, if five products are visible on the screen, Insider sends five impression logs to the campaign. When the sixth product appears on the screen after the user clicks an arrow, Insider sends one more impression log for the newly visible product.
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Impression only counts when the campaign appears on the screen, not when the page loads.
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Product impressions are unique to each session. If a user sees the same product from another campaign or from the same campaign on a different page in the same session, it won’t be counted as an impression.
Product Click-through Rate (CTR) is the number of clicks on the recommended products divided by the number of viewable impressions on the recommendation carousel.
- Product Clicks: The click event is triggered when a user clicks on a recommended product, redirecting them to the product detail page or adding it to the cart and wishlist. The product clicks can be anywhere on the product card, including the image, CTAs, description, etc.
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  Clicks are not unique to a product or session. All clicks that a user makes on a product, even if it's the same product in the same session, are counted as clicks. If a user clicks on a product 10 times within the same session, whether from the same or different campaigns, all 10 clicks are counted.
Product Add-to-Cart Rate: The number of add-to-carts divided by the total product impressions of that campaign.
- Product Add to Carts: The add-to-cart event is counted when a user clicks on the Add to Cart button, either from the product detail page or directly from the product card on the recommender carousel, as long as the product was initially clicked via the recommender carousel and the action occurs within the attribution window.
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  Add-to-carts are not unique; they are based on SKU quantity. This means that each SKU added to the cart will be counted as an ATC. For example, if a user clicks on product A from the widget and adds three units to their cart, Insider counts this as three add-to-carts from that campaign.
Product Conversion Rate (CR)is the sum of purchased recommended products (direct conversions) divided by the sum of viewable impressions.
- Product Purchases: The number of product purchases that are clicked from the recommender carousel and complete the checkout event during the attribution window.
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  Purchases are not unique; they are based on SKU quantity. This means that each SKU purchased will be counted as a purchase. For example, if a user clicks on product A from the widget and purchases three units of product A during checkout, Insider counts this as three purchases from that campaign.

You can also view those metrics daily, weekly, or monthly on the timeline.

Campaign Analytics

The campaign analytics table enables you to create relations between Smart Recommender campaign parameters, such as page type, algorithm, and other relevant metrics, and performance.

You can compare the results to see which algorithm performs the best on your category or cart page. You can also see the breakdown of variants within a campaign, along with its performance metrics, which allows you to select the best-performing variant and improve your campaign strategies.

The main rows in the table are the Web Smart Recommender campaigns, and the nested rows are the variants within each campaign. To look at the variant performances of a campaign, click on the main row, and variants will be listed in the nested part.

Important Note on Variant Product Metric Collection
A user might click on a red shirt from the Web Smart Recommender campaign. Then, they can change the size or color of this shirt and proceed the journey with the blue color of the recommended shirt. In this case, Insider compares the clicked and purchased products to make sure that they have the same group code and are variants of each other. Consequently, add to cart and purchase logs of the variant product (blue shirt as in the example) will be added to the originally recommended and clicked product’s (red shirt as in the example) metrics. In essence, even if the user substitutes the recommended product with a variant, the revenue and engagement metrics associated with the variant will still contribute to the overall metrics. This approach ensures that no revenue is lost in the process.
For example, a user is recommended the L size of a t-shirt. After going to the detail page, the user decides and purchases the M size. In this case, the sale of the M size is written to the overall recommendation revenue and the campaign revenue which has recommended L size product.

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The Winner Algorithm determines the winning variant based on the highest direct revenue generated. If two variants have not generated any revenue, their Click-Through Rates (CTRs) are compared. In the absence of any clicks, Impressions are compared to determine which variant has created the highest visibility for your products.

Top 100 Product Analytics

In addition to the campaign analytics, recommendations also provide insights regarding product performance. The Product Analytics table shows the top 100 products that have generated the highest revenue in descending order.

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You can refer to the FAQ for more information on product analytics.

You can see the revenue generated by product sales and your users’ engagement (impressions, clicks, adds to cart, and purchases) with that product using different recommendation algorithms. In addition to the performance metrics, the product analytics table provides transparency into the performance of algorithm-product relations. This feature offers more insights into how an algorithm performs for a specific product or which products generate more engagement than others.

When you click on a product in the product analytics table, you can view the algorithms that recommended it and generated revenue. In other words, trending, most popular, and other contextual algorithm outputs will be clear to help you gain insights into which products are more valuable to your users.

Category Analytics

One of the Smart Recommender's most powerful abilities is enabling users to discover and engage with various categories.

Seeing the number of products recommended from that category and the total revenue generated from the sale of recommended products, category analytics can help you understand which element of your taxonomy performs best in recommenders, especially in terms of revenue and Click-through Rate (CTR).

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Do not sum all the revenue or other metrics in this table. This table is generated by attributing a metric collected for a product to all categories within the product's category tree. For example, a shirt has three categories: Top Wear, Short Sleeves, and Shirts. If a user clicks on or purchases a product, all categories associated with that product receive the same metric. Therefore, when a user interacts with a shirt, the "Top Wear", "Short Sleeves", and "Shirts" categories receive one click.

You can also refer to the video below to walk through the Smart Recommender Analytics:

Export your results

You can create single and recurring reports for your Smart Recommender Analytics. While exporting, the overall page filters you applied are shown on the export modal. You can change them if you like.

Single Report: The report is generated immediately with the filters applied on the page and shown in the “Reports” drawer, which you can access later. Single reports are stored for one week and then deleted from the created reports section.
Recurring Report: The recurring report type offers recurrence settings in the drawer modal. You can adjust the frequency, report range, recurrence period, and start date. Together with the applied filters, the configuration of the recurring report setting is complete.

Change in the calculation method for Impressions

To improve metric accuracy and help you better interpret the performance of your Smart Recommender campaigns, making more informed decisions, some subsequent changes have been applied to Smart Recommender Analytics.

To find the details and timeline of the implemented changes, refer to the Impressions Calculation in Smart Recommender.