Kevel Attribution

What is Kevel Attribution?

Sponsored product attribution refers to the practice of identifying and attributing the influence of sponsored products on consumer behavior and purchasing decisions. In the digital advertising landscape, sponsored product attribution plays a crucial role in understanding the impact and effectiveness of sponsored or promoted products in driving sales and revenue for businesses.

In the context of sponsored product attribution, lookback windows and attribution match types are two important concepts that help advertisers understand and analyze the impact of their advertising efforts. Let's delve deeper into each of these concepts:

Lookback Windows

A lookback window refers to a specific time period during which user interactions with sponsored product ads are attributed to conversions or actions. It determines how far back in time advertisers track and attribute conversions to their ad campaigns. Kevel supports both view-through and click-through attribution:

• View-through attribution: This match type attributes conversions to users who view a sponsored product ad but do not click on it. If a user views an ad and later converts within the designated lookback window, the conversion is attributed to the ad.
• Click-through attribution: In this match type, conversions are attributed when a user clicks on a sponsored product ad and directly completes the desired action, such as making a purchase.

Kevel supports lookback windows of 1, 7, 14 and 30 days. Alternatively, you can select ‘none’ to not perform a specific kind of attribution.

Attribution Match Types

Attribution match types define the criteria used to match user interactions with sponsored product ads to conversions or actions. They determine how closely the interaction aligns with the attributed conversion.

In sponsored product attribution, different attribution models can be used to understand the impact of advertising on consumer behavior and conversions. Among these models, three commonly used ones are same product attribution, same brand and category attribution, and same brand attribution. Let's explore the differences between them:

Same Product Attribution

Same product attribution focuses on attributing conversions specifically to the exact product that was advertised. In this model, the conversion is attributed only when a customer clicks or interacts with a sponsored product ad and subsequently completes a purchase of the same product that was advertised.

For example, if a customer clicks on a sponsored product ad for a specific brand of headphones and then purchases those exact headphones, the conversion is attributed to the same product.

Same Brand and Category Attribution

Same brand and category attribution expands the scope of attribution beyond the exact product to include other products within the same brand and category. In this model, the conversion is attributed when a customer interacts with a sponsored product ad for a specific brand and category and makes a purchase of any product within that brand and category.

For instance, if a customer clicks on a sponsored product ad for a particular brand of running shoes but ends up purchasing a different model of running shoes from the same brand, the conversion is attributed.

Same Brand Attribution

Same brand attribution takes a broader approach by attributing conversions to the overall brand rather than specific products or categories. In this model, the conversion is attributed when a customer interacts with a sponsored product ad for a specific brand and makes a purchase of any product from that brand, regardless of the category.

For example, if a customer clicks on a sponsored product ad for a particular brand of smartphones and then purchases a laptop from the same brand, the conversion is attributed to the same brand.

The choice of attribution model depends on the goals and objectives of advertisers. Same product attribution provides the most specific and granular insights into the direct impact of a particular advertised product. Same brand and category attribution offers a broader view by considering the influence of the brand and category on consumer behaviour. Same brand attribution provides a high-level overview of the effectiveness of the brand's advertising efforts across various product categories.

By considering both lookback windows and attribution match types, advertisers can gain a better understanding of how their sponsored product ads impact consumer behaviour and conversions. These concepts help marketers make informed decisions about their advertising strategies, optimize their campaigns, and allocate resources effectively to maximize return on investment (ROI).

Kevel Ad Server - Attribution Implementation

In order to log purchase data with Kevel, send a server-side event for each purchase completed.

You will send a GET request to a network-specific endpoint following this format, where 123 is the Kevel network ID: https://e-123.adzerk.net/c/123/purchase

The following parameters are required for any attribution set up:

• userKey multiple userKey values are accepted, representing the userKey(s) this customer was seen on in previous ad requests. If you don't have a solution for gathering and sending the different relevant userKey(s) you can leverage Kevel Audience for this purpose
• timestamp (ISO 8601 (eg. 2017-01-19T16:27:20.974Z) but we also support unix epoch time)
• quantity The quantity of items in this transaction (line item of an order)
• price The product price of the line item. The total amount for the line item will be quantity * price

The parameters above are used for Kevel's default attribution implementation, but query parameters may be use-case specific and may include custom information based on your attribution scheme and reporting needs. For example, a retail marketplace company may send Kevel the following:

• transactionId The transaction identifier
• productIdProduct identifier, used to lookup product meta data in the Kevel Catalog
• merchantId Optional merchant identifier, used in Marketplaces to identify the seller

Additionally, you can also send LTV related information on each event, namely:

• ltvQuantity the expected additional quantity of items sold to this customer. As a Retailer, you can decide to send the quantity of the particular item in the line item, or it can be representative of the prorated future number of total items expected to be purchased by the customer
• ltvValue the expected additional sales value sold to this customer. As a Retailer can decide to send the sales value for the specific product in the line item or it can be representative of the prorated future value expected to be spent by the customer. This will not be multiplied by ltvQuantity, it is the total value

Additional product information can and should also be provided via Kevel Catalog. For example, a retail marketplace company may complement product information with fields such as:

• Product details
• Brand identifier
• Main category identifier
• In stock indicator

Sample purchase event fully constructed: https://e-123.adzerk.net/c/123/purchase?userKey=marketplaceshopper-456-abc&transactionId=1234567&timestamp=2022-11-02T16%3A27%3A20.974Z&productId=11982758&quantity=1&price=200&merchantId=12478&ltvQuantity=6&ltvValue=1200

It is important to send a consistent UserKey in both the Ad Decision and the Purchase event request so that Kevel is able to perform a look back to determine whether the purchase can be attributable to an ad view or click (depending on attribution settings defined Flight settings).

Generally, this is done by generating a random UserKey on session start and persisting that locally (local storage, or a cookie). Even if the user authenticates midway through their journey, it is important that the same UserKey is sent in purchase events in order for Kevel to be able to correctly attribute conversions to Ads.

Additionally, if products are sold across multiple markets (with multiple currencies), the price value must first be converted to a single currency (defined by the customer).

When the Kevel Ad Server logs a conversion due to attribution:

• A Server to Server Conversion is logged for the relevant ad using event ID 3. (See Event ID definitions)
• The GMV for the relevant ad is incremented by the value of the price value * quantity value in the purchase event.

Kevel Audience + Kevel Ad Server

For customers using Kevel Audience in combination with Kevel Ad Server, purchase events will instead by synced to Kevel Audience either with the standard event collection approach, or via offline imports. This data will then automatically flow through to Kevel Ad Server for attribution reporting.

End to End Testing Steps

1. Create a Campaign with at least one Flight that has Attribution Settings configured for post-click and/or post-view lookback window and product match.
2. Create one or more Ads in the Flight from step 1 with Attributable Items set. For PLAs this is set automatically using the Ad Template selected in the Create Ads from Products workflow.
3. Make an ad decision request that returns the Ad(s) from step 2. Ensure this request includes a user key.
4. Trigger an impression for the Ad using the event URL returned in step 3.
5. Trigger a click event for the Ad using the event URL returned in step 3.
6. Send transaction data to the purchase event endpoint. Ensure a userKey is included that matches step 3.
7. Receive a response from the purchase event endpoint:
   1. 200: Purchase attributed to an Ad; conversion recored
   2. 204: Purchase not attributable
   3. 400: Invalid request; addition details in response body:
      1. "required parameter missing: expected userKey, timestamp, productId, quantity and price" - If any of the required parameters are missing.
      2. "maximum of 100 userKeys exceeded" - If there are too many user keys.