Advanced Attribution: How Custom Models Work in Elly Analytics

Elly Analytics offers advanced attribution and can customize attribution models to fit your business model and marketing mix. In this article, we will explain why it’s important to understand how attribution works in your marketing performance reports and how attribution in Elly Analytics differs from Google Analytics’ attribution.

A major issue with relying solely on Google Analytics is its Last Click attribution model, which attributes a conversion to the last visit regardless of its source or the interactions that preceded it.

This can lead to misguided decisions regarding the effectiveness of advertising. With fewer conversions assigned to paid channels and non-brand campaigns, you might think ads perform worse than they actually do. Based on this, you might allocate budgets suboptimally, missing out on potential returns. This can result in a lower ROI from advertising and a loss of revenue that could have been earned by funding campaigns and ads that actually perform well.

This is where considering an alternative like Elly Analytics can be advantageous. Elly Analytics provides fully customizable attribution models that offer a deeper, more nuanced analysis of the customer journey. By using these custom models, Elly Analytics has been shown to reduce the percentage of conversions incorrectly attributed to channels like Direct, Organic, and Mailings from 30% down to 10%.

Below, you will find screenshots from Google Analytics and Elly Analytics, illustrating the impact of adopting a more accurate attribution model.

How Google Analytics Attributes Leads

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How Elly Analytics Attributes Same Leads

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To better understand this issue and the importance of tailored attribution rules, let’s examine typical customer journey scenarios and explore how Elly Analytics handles attribution differently.

Example #1

A customer spots your ad on a search engine or social media platform, clicks on it, but isn’t ready to convert just yet, so they leave. A few days later, they remember your brand and search for it by name, visit your website again, and fill out a hand-raise form.

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Google Analytics credits this lead to the Organic Search channel. However, this search would not have occurred without the prior ad.

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Therefore, the Last Ad Click attribution model in Elly Analytics is ideal as it credits leads to the last ad click.

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Example #2

A similar scenario unfolds where a customer clicks on your ad but does not convert immediately. They leave, and upon revisiting through a branded search ad, they fill out a hand-raise form.

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Google Analytics assigns this lead to the Branded Search campaign. Yet, the branded ad click stemmed from the initial non-branded ad exposure.

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Here, Elly’s custom attribution rules ensure the lead is correctly attributed to the last non-branded ad click.

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Example #3

You invest in content marketing to answer frequently asked questions from your target audience. A customer seeking answers visits your content page, but leaves after finding what they needed. Later, they return by searching your brand and completing a hand-raise form.

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Though Google Analytics assigns this lead to the Search channel, the interaction with your content was crucial.

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The Last Paid Click attribution model in Elly Analytics can attribute the lead to either the last ad or the last content page visit.

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Example #4

After initially interacting with an ad, a customer departs but later encounters a retargeting ad, clicks it, and completes a hand-raise form.

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Google Analytics credits the retargeting campaign. However, this last website visit would not have occurred without the prior ad.

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Here, Elly’s custom attribution rules ensure the lead is correctly attributed to the last non-retargeting ad click.

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Example #5

A customer discovers your ad on Instagram and clicks on it, leading them to subscribe to your newsletter filled with special offers before leaving. A few days later, they receive an email from you with a tailored special offer, click the link within, visit your website again, and fill out the hand-raise form.

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Although Google Analytics would attribute this lead to the visit via the email link, we understand the crucial role played by the initial Instagram ad in initiating this customer journey. Even if Google Analytics supported a First Click attribution model — which it doesn't anymore — it would still trace this lead back only to the email link, due to the separate browser environments typically used for Instagram and email links. This results in no recorded visits prior to the one from the email in Google Analytics' view.

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Therefore, Elly Analytics' Last Ad Click attribution model is invaluable, as it can integrate these disparate interactions into a cohesive customer journey by tracking through the customer’s email address.

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Example #6

A customer engages with a search or social ad but leaves unconverted. Later, influenced by an influencer’s ad featuring a discount code, they search for your brand, visit your site, and sign up for a trial using that code.

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Although Google Analytics attributes this to the last website visit, the influencer’s impact was decisive.

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Elly Analytics’ ‘Last Ad Click with Discount Code Priority’ model effectively links this trial back to the influencer ad.

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Example #7

A customer interacts with an ad, visits your site, and fills out a hand-raise form, but the CRM already lists them under a partner.

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Google Analytics inaccurately attributes this to advertising.

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Elly Analytics’ custom models can correctly assign this lead to the partner instead.

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Example #8

A customer responds to your ad, but right before filling out a hand-raise form on your site, they visit through an affiliate link.

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Google Analytics would attribute this lead to the affiliate, but we know the original ad brought them.

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The Last Ad Click model prevents affiliates from unfairly claiming leads that should rightfully be attributed to your own marketing efforts.

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Let’s Summarize

Google Analytics and similar tools usually credit the last source visited before a conversion, often overvaluing Organic Search and Email channels, and also Branded Search campaigns. This can lead to poor budget decisions, as fewer conversions get credited to paid channels and non-brand campaigns. You might end up thinking ads are doing worse than they really are, leading to less optimal budget allocation and lower revenue.

Elly Analytics improves attribution in two ways:

  1. It links together sessions across all browsers and devices where the individual has identified themselves at least once (for example, by subscribing to a newsletter, signing up for a webinar, or logging in). This capability allows Elly Analytics to accurately attribute conversions across the entire customer journey, unlike common platforms such as Google Analytics.
  2. It can establish custom rules for attribution that consider the customer journey, leading to a more accurate assignment of leads.