Content marketing and analytics provider Parse.ly has rolled out the first generally-available release of Parse.ly Conversions. The solution seeks to help marketers address content attribution challenges of conversion reporting. It allows users to select different attribution models for assigning credit to content. The release also includes features such as labels that can be applied to categorize conversion actions.
“This release includes a conversions report that shows which content converts the most readers, which content contributes to the most conversions (even if it’s not converting directly on the content itself), and which types of conversions content drives best,” the company said in the announcement.
Why we should care
Determining how and which content is contributing to conversions is a challenge for many marketers. Some even have teams dedicated to stringing together data to understand the impact content has on their businesses. As marketing campaigns become more complex and spread across multiple channels — and create data siloes — it can become unclear as to what content or touchpoint actually drives conversions.
Parse.ly’s conversion report aims to provide clearer insight into how users interact with a brand’s content, from a high-level overview of all conversions to a detailed breakdown of its content performance and top referral sources.
Parse.ly also allows users to select one of three different attribution models when building a conversion report: last touch, linear and pages before conversion. The flexibility to select based on a brand’s needs or campaign strategy will be beneficial to multichannel marketers and will benefit users with experimenting with different attribution models.
More on the news:
- Note that the conversions report is not comprehensive just reports data from the past week to provide a baseline.
- Parse.ly supports five standard conversion types and one custom type.
- The company indicated plans to analyze the five standard types as a benchmark for its customers to see how their brand performance compares to the rest of Parse.ly’s network.
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