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How to Improve Attribution for Your eCommerce Business?

Updated: Jun 12

Improve eCommerce Attribution with Graas' data analytics tool

eCommerce attribution would’ve been so much easier if customers converted every time they clicked on an ad. But this is not the case. They might discover you through an ad, then come across you again through organic socials, and when you think you’ve lost them, they purchase a product by directly visiting your online store. 

Now, where do you attribute this sale? Was it the initial ad, or was it the reel that they remembered? You can’t say for sure. Because there’s still a chance that someone talked to them about your product, which made them buy it. 

So yes, eCommerce attribution is as challenging as it can get. There’s no such thing as 100% attribution in eCommerce, but by following some best practices, we can get as close to the source as possible.

In this blog, we’ll discuss :

Let's dive right in!

5 Ways to Improve attribution for your eCommerce business 

Since the privacy laws have gotten stricter, attribution has become more challenging. However, understanding the performance of your marketing efforts on your sales requires your attribution results to be accurate. 

Here’s how you can improve the accuracy of your eCommerce attribution: 

1. Integrate all your data sources 

Customers interact with multiple touchpoints before making a purchase decision. This data is scattered across various platforms, such as marketing channels, the eCommerce website, CRM systems, and online behavior tracking tools. To improve attribution accuracy, businesses must combine all this data into a unified view. 

Consolidating data from different sources allows you to see the complete customer journey and attribute conversions correctly to the respective touchpoints. Without a unified data view, you may miss crucial interactions influencing the purchase, leading to inaccurate attribution and flawed marketing decisions. 

For example, a customer might see a social media ad for a new pair of shoes (social touchpoint). They click the ad and visit the brand's website (website touchpoint). After browsing for a while, they decide to sign up for the brand's email list to receive a discount code (CRM touchpoint). A few days later, they receive an email with a special offer and click through to the website again (email touchpoint). Finally, they make the purchase. 

By integrating data from all these touchpoints, the business can accurately attribute the sale to the social media ad that sparked the initial interest, even though the email provided the final nudge. 

2. Choose the right eCommerce attribution model 

There are many attribution models, each assigning credit for conversions differently. The choice depends on your business goals, industry, and customer journey complexity. 

Here are some common attribution models to choose from: 

  1. Last-Click Attribution: This model assigns full credit to the final touchpoint before conversion. While simple, it fails to account for the impact of earlier touchpoints that may have influenced the customer's decision. 

  2. First-Click Attribution: In contrast to the last-click model, this approach credits the initial interaction that introduced the customer to the product or service. However, it ignores the role of subsequent touchpoints that nurtured the customer's interest. 

  3. Linear Attribution: This model distributes credit equally across all touchpoints in the customer journey. While it acknowledges the contribution of multiple touchpoints, it may not accurately reflect the varying levels of influence each touchpoint had on the conversion. 

  4. Time Decay Attribution: This model assigns more weight to touchpoints closer to the conversion, under the assumption that they had a greater impact on the final decision. However, it may undervalue the importance of earlier touchpoints that sparked the customer's initial interest. 

  5. Data-Driven Attribution: This advanced model uses machine learning to analyze campaigns and historical sales data and assign credit dynamically based on the patterns and trends it identifies. While powerful, it requires a significant amount of high-quality data and ongoing optimization. 

No single model is perfect; each has pros and cons. You must evaluate your customer journeys and select the most suitable model, regularly refining it as customer behavior or marketing channels change. 

3. Implement cross-device tracking 

Most customers who purchase online use multiple devices. They often switch between smartphones, tablets, and desktops during their purchase journey. 

Cross-device tracking is crucial for accurate attribution as it allows you to stitch together a customer's interactions across devices. 

Without cross-device tracking, you may miss out on crucial touchpoints and fail to recognize the complete path to conversion. For example, a customer may start their research on a desktop, compare products on a tablet while traveling, and eventually make the purchase on a mobile because of ease of payment. 

Strategies for cross-device tracking include using user logins, deterministic matching based on shared identifiers like email addresses, and probabilistic modeling that analyzes user behavior patterns. 

4. Address data quality issues 

Your attribution results will only be as accurate as your data. Incomplete, inconsistent, or duplicate data can lead to flawed attribution results and misleading insights. 

Identifying and resolving data inconsistencies is essential for reliable attribution analysis. This may include standardizing data formats, deduplicating records, and addressing missing or incorrect information across various data sources. 

Ensuring data quality requires robust data cleansing and deduplication processes. Techniques such as data profiling, validation, and rule-based cleansing help identify and fix data issues.

Automated tools and workflows streamline these processes and maintain data integrity, enabling accurate and reliable attribution analysis. Let's explore this in more detail.

5. Use an eCommerce analytics platform for attribution tracking 

Different data sources often present data in different formats, making it challenging to establish connections between them. 

For example, marketing data from platforms like Facebook and Google Ads will be structured differently from data from your eCommerce platforms. Even how metrics are calculated can vary across channels, further compounding the issue. 

As a result, attempting to establish a one-to-one linkage between these disparate data sets becomes difficult. 

When there is no clear one-to-many relationship between data sources, attributing customer actions to their respective sources becomes increasingly tricky. Manually cleaning and integrating data from multiple platforms is time-consuming and prone to errors, which can lead to inaccurate attribution insights. 

This is where an end-to-end eCommerce analytics platform like Graas comes in. Graas automates data integration from all your marketing and sales channels, eliminating the need for manual data wrangling. By consolidating data from various sources, Graas provides a comprehensive view of your customers' different paths before converting. 

Moreover, Graas uses AI-based and data-driven attribution models to identify the impact of each channel on your sales. This granular insight enables you to refine your targeting strategies and reach your audience at the right touchpoints along their journey, resulting in more effective marketing campaigns and optimized resource allocation. 

Tips to manage best and least attributing channels 

Now that you understand how to improve the attribution for your eCommerce business, the job is only half done. 

How you manage your best and least attributing channels ultimately determines your growth trajectory. 

Here are some tips to effectively manage these channels:

5 Tips to manage your best attributing channels 

Your best attributing channels are the marketing touchpoints that consistently drive high conversion rates and contribute significantly to your overall sales. 

These are the channels that deserve special attention and strategic optimization. 

  • Increase budget allocation for top-performing channels to increase their impact. 

  • Continuously test and refine messaging, creatives, and targeting to maintain effectiveness. 

  • Explore expansion opportunities like reaching new audiences or using additional ad placements. 

  • Analyze customer behavior data to identify patterns and insights for further optimization. 

  • Regularly review and adjust bidding strategies to maintain a competitive advantage. 

5 Tips to manage your least attributing channels 

The least attributing channels are the marketing touchpoints that seem to have a minimal direct impact on conversions. 

However, these channels may still be crucial in building brand awareness, educating customers, or nurturing them through the buyer's journey. 

  • Experiment with creative optimization, such as changing ad copy, visuals, and calls to action, to improve engagement.

  • Refine targeting strategies to ensure you're reaching the right audience segments. 

  • Experiment with different ad formats or placements to find the most effective combinations. 

  • Leverage these channels for upper-funnel marketing objectives, such as driving website traffic or social media engagement. 

  • Monitor performance regularly and be prepared to reallocate resources if a channel consistently underperforms. 

Identify the channels that make your customers hit pay! 

There’s no one-size-fits-all approach to attributing sales, but getting the basics right is crucial for improving your attribution results. 

To ensure accurate attribution, the data you use must be clean and unified from all your sales and marketing channels. And Graas does all this for you with its AI-based attribution models. 

And that’s not all. Graas also provides insights and recommendations to ensure that underperforming channels are either discontinued or optimized to produce better results. 


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