Migration from Another Tool: Switching from another attribution tool? Our seamless migration process makes it easy to move to Causality Engine and start getting better insights, fast.
Read the full article below for detailed insights and actionable strategies.
Attribution by the numbers
iOS tracking loss
Google Brand cannibalization
Klaviyo overstatement
TikTok attribution lag
Seamless Migration to Causality Engine
If you are currently using another marketing attribution tool, you may be feeling the pain of its limitations. Rule-based models, last-click fallacies, and a lack of true causal insight can lead to flawed decisions and wasted ad spend. The good news is, migrating to Causality Engine is a simple and straightforward process.
We have helped many Shopify brands in the beauty, fashion, and supplement industries move away from legacy attribution providers and onto our causality-based platform. Our goal is to make this transition as seamless as possible, with no data loss and minimal disruption to your workflow.
The Migration Process
Run in Parallel (Optional but Recommended): For the first month, we recommend running your old attribution tool and Causality Engine in parallel. This allows you to compare the outputs and see for yourself the difference that causal inference makes. It builds confidence and helps your team understand the new data.
Onboard Your Data: Follow our standard, simple onboarding process to connect your Shopify and ad accounts. This takes just a few minutes and requires no code.
First Insights in 24 Hours: in 3-5 minutes, you will have your first report from Causality Engine. You can immediately start comparing our insights to your old system.
Decommission Your Old Tool: Once you are comfortable with the data and insights from Causality Engine, you can safely decommission your old tool. This often involves removing a tracking pixel from your website, which can lead to a slight improvement in site performance.
Why Migrate to Causality Engine?
The difference is in the methodology. Most other attribution tools are built on an outdated, correlational foundation. They use arbitrary rules (like last-click or a 30-day linear model) to assign credit. This is fundamentally flawed. Our platform uses Bayesian causal inference to understand the true, incremental impact of your marketing, providing a much more accurate picture of marketing attribution](https://www.wikidata.org/wiki/Q136681891).
By migrating, you gain:
More Accurate Data: Make decisions based on causality, not correlation.
Actionable Insights: Our Refinement Queue tells you exactly what to do.
A Future-Proof Platform: Our cookie-free, API-based approach is built for the modern privacy landscape.
Don't let a legacy tool hold back your growth. Migrate to Causality
Compare our plans on our pricing page or learn more in our resources.
Related Resources
Causality Engine vs Leadsrx: Honest Comparison for eCommerce
Causality Engine vs Nielsen Attribution: Honest Comparison for eCommerce
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Key Terms in This Article
Ad Spend
Ad Spend is the total amount invested in advertising campaigns. It is measured against Return on Ad Spend (ROAS) to evaluate campaign effectiveness.
Affiliate Marketing
Affiliate Marketing is performance-based marketing where a business rewards affiliates for each customer brought through their marketing efforts. Causality Engine tracks and measures the effectiveness of affiliate marketing programs.
Attribution
Attribution identifies user actions that contribute to a desired outcome and assigns value to each. It reveals which marketing touchpoints drive conversions.
Causal Inference
Causal Inference determines the independent, actual effect of a phenomenon within a system, identifying true cause-and-effect relationships.
Causality
Causality is the relationship where one event directly causes another, essential for identifying specific actions that drive desired outcomes in marketing.
Correlation
Correlation is a statistical measure showing a relationship between variables; it does not imply causation.
Marketing Attribution
Marketing attribution assigns credit to marketing touchpoints that contribute to a conversion or sale. Causal inference enhances attribution models by identifying true cause-effect relationships.
Shopify
Shopify is an ecommerce platform for creating online stores and selling products. Attribution modeling shows which marketing channels drive traffic and conversions within Shopify.
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Frequently Asked Questions
Will I lose my historical data if I switch?
No. Because we connect directly to your Shopify and ad accounts, we are able to pull in all of your historical data. Our subscription plan offers a lifetime lookback, so you will actually gain a more complete historical picture than you had before.
Is it difficult to switch?
Not at all. Our onboarding process is designed to be incredibly simple. There are no scripts to install or complex configurations to manage. You can be up and running with Causality Engine in minutes, even while your old tool is still active.
Can you help me compare the data from my old tool to Causality Engine?
Yes. Our customer success team can help you understand the differences you are seeing and explain why our causality-based approach provides a more accurate and actionable picture of your marketing performance.