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Triple Whale’s Total Impact Attribution Model

Triple Whale’s Total Impact Attribution Model

In a rapidly changing digital landscape, marketers face new challenges in understanding and optimizing their campaigns. In this article, we will explore the state of marketing attribution, the rise of first-party and zero-party data, and unveil Triple Whale's Total Impact Attribution Model – a game-changing solution for the future of marketing. Buckle up and get ready to dive into the next wave of marketing attribution.

So…How Can We Track Attribution Today?

The marketing attribution landscape experienced a BIG transformation after the release of iOS 14.5. Apple's App Tracking Transparency (ATT) framework dramatically altered advertisers' ability to track user data by requiring users to opt-in for app tracking, instead of being automatically enrolled. This forced marketers to adapt to diminished data granularity and shift focus toward developing alternative, privacy-centric attribution models.

Attribution using first-party data gained traction because enabled marketers to adapt to the changing privacy landscape by tracking customer behavior and interactions with a brand’s owned channels, such as its website or app.

(Enter Triple Whale and other first-party attribution solutions)

With first-party attribution, marketers can take a more holistic approach to attribution, considering the overall customer journey that a customer takes before making their purchase.

While on the subject, it's important to address one more type of data that is critical to the evolution of marketing attribution: zero-party data.

What is Zero-Party Data?

Zero-party data is a type of data that customers intentionally and proactively share with a brand. This information goes beyond what can be inferred from customer behavior and includes personal preferences, opinions, and interests.

Unlike first-party data, which is collected through customer interactions with a brand's owned channels, zero-party data is voluntarily given by the customer. Post-purchase surveys (PPS) are an excellent example of how zero-party data can be collected. Curious to learn more on PPS and zero-party data? Check out our blog on the subject here!

Alright, we've discussed first-party and zero-party data, but what is the future of marketing attribution? We believe that the future of marketing attribution will be shaped by a combination of first-party data and zero-party data, supercharged with the help of machine learning and artificial intelligence. We're calling this Total Impact Attribution. Let’s jump in.

The Total Impact Attribution Model

Triple Whale’s Total Impact Model is a holistic approach to marketing attribution. The new gold standard.

Click-based attribution only tells part of the story. Total Impact provides a more comprehensive view by using a multitude of data points to determine the impact of prospecting channels like TikTok and Facebook on a business.

Total Impact gives clarity on advertising investments, which tactics are working or not, and provides insight for future marketing tests.

First-party data + Zero-party data + Proprietary algorithm = Total Impact Attribution Model

The model works by analyzing the customer journey from the initial touchpoint to purchase and beyond. It takes into account a wide range of factors, including survey data, ad impressions, clicks, website visits, email opens, and more.

By combining this data, the model can identify which touch points have the greatest impact on customer behavior and help inform your future marketing efforts.

The future goal of this model is to continuously learn and adapt as new data becomes available. This means that we can provide increasingly accurate insights over time, helping businesses stay ahead of the curve and make data-driven decisions.

Total Impact vs Other Attribution Models

When to use the different attribution models:

Total Impact: Utilize the Total Impact Model if you want to visualize the weighted success of your marketing sources, channels, campaigns, adsets, and ads

  • Total Impact is similar to an MMM, where aggregate data is used to determine which channels and campaigns are responsible for the most revenue to your store over a period of time.

Triple Attribution: Best for understanding the total value of click-based revenue attributed to every channel and making day-to-day decisions on your ads. Use this model to review Order Overlap between channels to better understand how many customers are interacting with multiple channels prior to placing their order.

  • Triple Attribution assigns 100% order credit to any channel that the customer clicked on prior to purchase. For example, If Customer A spent $100 with you and clicked on a Facebook Ad + a Google Ad, we will attribute the $100 order to both Facebook and Google. This is valuable in understanding the total revenue a single channel, campaign or ad drove to your business.

Triple Attribution + FB Views: Triple Attribution + FB Views should be used when specifically analyzing Facebook Ads

  • With this model, we combine Triple Pixel attributed orders with View-Through conversions + conversion value provided by the Facebook API

Linear All/Paid: The Linear Model should be used when you want to analyze all of your marketing channels, sources, etc. on an equal playing field

  • The Linear model gives equal conversion value credit to every source, channel, adset and ad that Triple Whale tracked a click from prior to purchase.

First Click: The First Click model should be used when trying to understand which channels or ads are driving the initial interest in your product/brand as well as understanding which channels are creating interest vs assisting in interest (linear all). Oftentimes, First Click channels or ads are the drivers for creating awareness in your product or brand.

Last Click: The Last Click model should be used when trying to understand which channels or ads are clicked last, prior to the order being placed. Oftentimes, these channels or ads are the “trigger” for converting an interested buyer into a customer.

Total Impact & Lighthouse

Triple Whale’s Lighthouse uses AI to detect anomalies, surface insights, and deliver tactical recommendations to make your store more profitable. Simply stated: it’s the smarter way to build your brand.

Total Impact Reports are one of Lighthouse's several key alerts, empowering store owners to unlock the true impact of their marketing mix on a daily, weekly, or monthly basis. As you can see in the visual below, the Total Impact Report includes a clear visualization of total ROAS, spend, and revenue, as well as a breakdown of how each channel contributes to the total impact. “Other” indicates a marketing channel with no allocated spend; you can view which channels this includes in the Pixel tab.

How Do I Get Total Impact To Work For Me?

First-party data via Pixel and zero-party data via a post-purchase survey are necessary to power the Total Impact Model. If you don’t have a post-purchase survey yet, you can:

  1. Install Triple Whale's free post-purchase survey.
  2. Connect or sign up for one of our partner Post-purchase survey tools.
    - Sign-up with Kno
    - Sign-up with Fairing

If you are not yet using Triple Whale, Fairing and KnoCommerce are two great PPS options for ecommerce brands. And they are both tech partners with Triple Whale! As you can probably tell, we are super pumped about the value of zero-party data. If you want to read more on the topic, check out our blog post on Zero-party Data and Post-Purchase Surveys.

As we navigate this wild world of data privacy and ever-shifting marketing landscapes, we have to learn to adapt and innovate. Looking ahead, we are excited about the potential that the Total Impact Attribution Model has for marketers and businesses alike, enabling them to make better data-driven decisions and create meaningful connections with their customers. So let's jump in and ride the next wave of the ongoing evolution of marketing attribution! 🌊🤘

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266 N 5th Street, Columbus OH 43209