Centralized Analytics with Conversion Tracking and Attribution Modeling


An optimized digital strategy begins with the ability to accurately measure and report the impact of ad campaigns and other digital channels. Analytics reporting is critical to tracking your KPIs and adjusting strategy based on identified goals. Without an iterative optimization methodology, digital strategy is merely a guessing game that wastes a lot of time and money.

Yes, this is a complex topic, but it’s incredibly important. In the interest of simplifying things, we’ll just introduce the basic concepts of centralized analytics, conversion tracking, and attribution modeling.

Centralized Analytics Reporting

Campaigns typically have to deal with a multitude of fragmented analytics reports. You might be reporting metrics from Facebook, ActBlue, Mobilize, an e-commerce platform, NGPVAN, etc. Each gives a glimpse of different KPIs, but none are able to show the big picture of how your digital strategy is performing overall, especially when it comes to analyzing user behavior and extracting actionable insights. By consolidating all of the important user actions (conversions) into a single web property, we’re able to properly measure, interpret, and report data like never before.

Conversion Tracking

A “conversion” is basically any desired action a user might do— for example, a sign up, donation, e-commerce purchase, event RSVP or ticket purchase, a survey or poll response, etc.

Conversion tracking allows us to report metrics such as conversion counts, conversion rate, revenue, conversion value, cost per conversion, and ROI for each channel. These metrics help to make more informed budget decisions for ad campaigns, email, content creation, and other digital marketing efforts.

You can even gain an understanding about which audience segments are driving the most and/or highest-value conversions from each channel. These insights can help to develop the right content and audience targeting strategies for each channel/ platform.

Attribution Modeling

Prior to a conversion, a user may interact with a variety of marketing touchpoints, whether they be ads, search, emails, blog posts, or other digital content. Attribution models allow you to assign partial conversion credit to each touchpoint based on different sets of rules. This allows you to more appropriately determine the ROI of each channel and ad campaign. It’s not enough to only consider a last-click attribution model, ignoring all other ad or content interactions the user might have had on their path to conversion. Testing different models also helps to learn more about your users’ behavior over periods of time.


A multi-channel digital strategy often means multi-action paths to conversion.

Let’s say a supporter visits a campaign’s website, clicks on a Donate CTA button to make a donation on ActBlue. Earlier that day, this individual attended a campaign event that they RSVP’d to after receiving a text message announcing the event with a Mobilize link. They subscribed to the SMS list during an display ad campaign to promote SMS signups.

Without a centralized analytics apparatus, attribution ends with the direct website visit and button click. Analytics reports from ActBlue will know nothing about when the user signed up for SMS, or that they RSVP’d to a recent event on Mobilize. In this user’s path to conversion, the event attendance, the text message, and the original display ad campaign all deserve some conversion credit. But the way campaign infrastructure is typically configured, that donation will be written off as meaningless direct website traffic.

It’s so important to determine the impact, in an actual dollar amount, that each digital channel produces. If a big investment is being made in a certain kind of ad campaign that’s not actually making any discernible impact, it could be a considerable waste of money to continue running those ads. Likewise, if a specific kind of content or ad campaign prove to be performing really well, it might be a good idea to commit more time and money to those high-impact efforts. There’s little use in setting goals or identifying KPIs if you can’t accurately measure what is working and what isn’t.

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