Audience Analytics

Prospects Vs Returning Customer trending over timeFebruary 05, 2024

Prospecting vs Retention

Validated Audience Traffic over time

You can now understand your Prospecting vs Returning and your traffic scoring on a daily basis.

For all of our customers, at $0, you can now:

  1. Get Event Match Quality (EMQ)  scores directly from Meta over time.
  2. Measure Meta Paid user site visitors against Purchases and further split by New or Returning Purchase [Audience, not Attribution].
  3. Measure returning customer visits to Intent ratios tunnels.
  4. Using your retention audience to understand seasonality. Your 1P Audience is the best guidance of others like them are ready [on Meta].

Here's the Deal with Cross-Channel Traffic: Why It's Tricky

Most spenders are looking to optimize cross-channel performance because they feel blind to how traffic performs within the channel. Click metrics provide insight into long-lived customers who came via paid media but converted during their consideration time. However, understanding how these metrics contribute back to future traffic is key.

Such diagnostic analytics do not exist today with any multi-touch attribution (MTA) because only a channel (like Meta) can provide such metrics. Currently, Meta provides only a 24-hour snapshot of such a metric (EMQ).

EMQ Scores

Free Audience Insights for everyone; courtesy of Meta

Blotout now offers detailed and verified metrics (via Meta) for any Blotout customer for free, and these can be generated even for customers not actively using our system. Imagine having your EMQ scores represented as a graph; that's precisely what this is. You can now track how much paid Meta traffic is converting versus how much retention traffic is converting, side by side over time, between your top of the funnel and actual purchases.

What You'll Gain

The benefits of diagnostic analytics are threefold:

  1. Understand if you are having a good day and double down (or vice versa) [Check every AM].
  2. Identify errors that may be difficult to diagnose otherwise.
  3. Suppression on a sale day.
  4. Use retention metrics to understand seasonality—ultimately, your first-party (1P) traffic is a good indicator of whether others like them are ready to purchase.

How Analytics Turned the Tide During BFCM for this $100M+ GMV Brand [Case Study]

During BFCM (Black Friday Cyber Monday), one customer's retention traffic was dropping significantly; despite their largest sale. While this is acceptable for heavily suppressed customers and normal during the low season, it was far outside the standard deviation during the BFCM. The charts, showcasing Meta-verified metrics, clearly showed the drop—a detail that could have easily been overlooked by any other analytics platform.

Retention Scores

When we spoke to them, it turned out that there was an error in their Meta campaign, and they were heavily suppressing traffic after their first sale (human error). Once informed, they immediately turned off the suppression, enabling traffic to jump back to normal levels. Without Audience Analytics, identifying the root cause of this issue would have been very challenging.

The challenge: New Sports Drink Uptick [Case Study]

When paid performance drops and it is unclear whether it's related to data issues, general consumer behavior, or just timing, analytics stored for multiple years can be invaluable. You can capture general seasonality trends and also build your own time-series analysis for your brand.

Paid Traffic

The chart above, available only via Blotout, shows the percentage of paid Meta traffic at the top of the funnel versus paid Meta traffic for conversions. This is a key metric worth tracking daily, and Blotout does this automatically for you. Essentially, this is a time series of your EMQ that Blotout tracks and has access to.

In the time series example above, the customer clearly had a couple of bad weeks until 1/19 when the purchase (Conversion) traffic overshot the PageView (Top of Funnel), and we sent an alarm suggesting they increase spend—this is reflected in the chart, enabling them to take advantage of expanding spend.

How Blotout Ensures Analytics Validation

By using our partnership status with Meta, we are now able to validate our audience daily using Meta EMQ scores in a privacy-preserving manner. This ensures that advertisers receive a precise score for how many actual users who were previous customers were present and how many truly anonymous users visited.

Unlike traditional Customer Data Platforms (CDPs) that merely send data outward, whether they stream, transform, and provide data to growth or other channels, the future of data also includes an entry point to those streams, forming a continuum. We have been using the incoming signals to begin isolating them to understand how to create an incremental value chain.

Why Blotout is Different Than Any Other Platform?

The ability to utilize Server-Server signals in a two-way sharing process is a brand new concept. As privacy erodes identity, Blotout (aka Signal Loss) is already working towards implementing machine learning (ML) that will enable us to recover multi-party signal isolation, facilitating privacy-preserving signal sharing over time.

Blotout was born out of the necessity to address the growing challenge of transferring data between parties, especially with the increasing focus on moving data from advertisers to walled gardens. We firmly believe that this process should be bidirectional, and the analytics generated from Meta serve as a prime example of value creation in this context.

Blotout Analytics Wants You!

Every D2C company should be using this and checking it daily. If you are a Blotout Customer, login and scroll down to get analytics.

It's $0 to get started. Schedule a demo?

If you are not a Blotout customer:

  1. Connect your B Pixel
  2. Connect your Klaviyo
  3. AND let it RIP!

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