Multi-Touch attribution model for Shopify: What it is and How to do it

Read Time 21 mins | Written by: Attribuly

 

The customer's journey spans many devices and touchpoints before resulting in conversion of products. Marketing needs to understand what content consumers have to receive to create positive outcomes. This is a guideline for deciding how and when to allocate advertising. If marketers understand the impact of different touchpoints on conversions then they can effectively spend the same amounts of money on similar touchpoints and divert money to the channels that have no effect.

There are a lot of attribution models to measure the impact of touchpoints. You may question, I use Shopify analytics, what is Shopify's attribution model?

What is Shopify's attribution method and the issue?

Shopify Analytics' Marketing Reports feature two attribution models to assess credit for conversion events. The first is Conversion by First touch attribution, which provides all the recognition to the initial touchpoint; while Conversion by Last touch attribution assigns full credit of conversion to its concluding contact point.

Shopify attribution measures conversions based on the last clicked interaction, disregarding any credit to direct channels. This means that it will attribute credit for a conversion to the most recent click and its corresponding keyword, even if prior visits were from people who directly navigated to your eCommerce store. 

The problem with this approach is that conversions today are often influenced by multiple touchpoints. This makes it difficult to understand how each touchpoint contributes to the overall customer journey, preventing marketers from optimizing their marketing channels effectively. Furthermore, you need to understand every customer's conversion journey so you can keep on improving your full customer experience. But currently, the data is unavailable. 

 

Why you need independent attribution software? 

1. Track campaign performance and its ROI

As your store continues to grow, the need to effectively allocate your budget becomes a major challenge. In order to maintain a positive marketing ROI, it is crucial to carefully monitor your marketing performance using accurate metrics. Attribution software is an ideal tool for monitoring these metrics across various channels, allowing you to respond quickly and avoid wasting your budget. Wasting budget is one of the top reasons why brands fail, so it is important to stay vigilant and make informed decisions based on accurate data.

2. Understand the customer buying process

Understanding the customer buying process is not only crucial for driving awareness, consideration, and conversion, but it is also essential for delivering a great user experience. By gaining insights into how customers navigate through their journey, businesses can tailor their marketing strategies to meet their needs at every stage.

When businesses understand the customer buying process, they can identify pain points, optimize touchpoints, and make informed decisions about where to allocate their marketing budget. This understanding allows them to create a seamless and personalized user experience that ultimately leads to higher conversions and customer satisfaction.

The Difference Between Multi-Touch Attribution and single-touch attribution Models

Multi-touch attribution models assign credit to more than one touchpoint during the buying process. For example, a user may have seen a Facebook ad on social media and then clicked on a paid Google search ad before making a conversion. With multi-touch models, each of those interactions would be assigned some credit for the eventual sale. This is different from single-touch models which only assign credit to the first or last interaction that occurred during the purchase journey.

Benefits of Multi-Touch Attribution

Multi-touch attribution model helps marketers get a better understanding of where their ads are working and which channels contribute to conversions in order to allocate budget appropriately across various channels and campaigns. It’s important for marketers to understand how different touchpoints contribute towards conversions because it can help them make more informed decisions and optimize campaigns for better results.

More and more touchpoints are required to convert customers. So collecting customers' conversion journey becomes essential to measure touchpoints' contribution. A multi-touch attribution model gives marketers the ability to understand how these points are connected and helps them make informed decisions about where their budget should be allocated for maximum return on investment (ROI).

"Customer journey is important for me to understand my customers. Especially how my customers interact with different campaigns across touchpoints such as Google, Facebook and Influencer campaigns. " From Alan, TexTale

Types of Multi-Touch Attribution Models

There are lot of models to determine how credit is given to touchpoints. Because in a customer journey, there may be different devices, browsers, campaigns working together. So Shopify merchants need to understand which campaign is the key contributor in the conversions.

1, Linear multi-touch attribution model

The linear attribution model gives equal credit for all touchpoints in a conversion. This is the most basic model which assigns credit to each interaction based on its position in the user's journey, regardless of the impact each touchpoint has.

For example, there are 3 touchpoints before a conversion: Tiktok ads, Tiktok influencer marketing, LinkedIn ads. In a linear model, 3 touchpoints receive 0.33 conversion each.

2. U-shape attribution model

The U-shaped multi-touch attribution model is a kind of position-based attribution model. It gives more credit to the first and last touches of conversion while assigning less weight to any touchpoints in between. This model is great for recognizing the search and other channels that typically drive the majority of conversions.

For example, there are 6 touchpoints before a conversion: Facebook ads, Tiktok influencer, email, Reddit social media, Google organic search, and referral. In a U-shaped model, 2 Touchpoints (Facebook ads and Referral site) receive 0.4 conversions each while Tiktok influencer, email, Reddit social media, Google organic search receive 0.05 each.

3. Time Decay Attribution Model

The time Decay multi-touch attribution model gives more weight to touchpoints that are closer to the conversion. It assigns most of the credit to the touchpoint nearest to a conversion and lessens as you go further away from the conversion. This helps give marketers insight into how quickly customers convert after being exposed to their marketing message.

All above models belong to rules-based multi-touch attribution models, meaning the weight is pre-defined. There are also models that adopt machine learning.

Algorithmic or data-driven multi-touch attribution models

Rule-based multi-touch attribution models assign credit to touchpoints by using pre-defined rules, algorithmic or data-driven multi-touch attribution models use data science and machine learning to determine the weight of each touchpoint. These models can be more accurate in assigning weights as they are based on actual user behavior.

Which attribution model you should choose?

 The attribution model you choose has a significant impact on how you allocate your budget and is closely tied to your growth strategy. If your goal is to maximize conversions, the last click attribution model is ideal as it attributes all the conversions to the last touchpoint. However, this approach may pose challenges for achieving a high growth rate due to limited investment in the awareness and consideration stages.

Alternatively, if you have a growth mindset and are focused on expanding your business, the First click model may be the ideal choice for you.

Attribuly chooses Linear as the default attribution model since it's a balanced choice. 

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Benefits of Multi-Touch Attribution

If you're an eCommerce marketer, multi-touch attribution models are incredibly essential for assessing the impact of your digital campaigns. These models provide a much more comprehensive and individualized view than traditional single-touch modeling approaches that merely take into account aggregate metrics.

By utilizing multi-touch attribution, marketers gain a much greater understanding of their customer's journey and are better able to customize messaging to reach consumers on the right channel at the right time. Armed with this granular data, it becomes easier for marketers to identify audiences across channels and pinpoint each user's marketing needs more accurately. In today’s world where people have become experts in avoiding marketing messages, using data-driven approaches like multi-touch attribution is key to meet your customer's expectations.

Not only does multi-touch attribution enhance the customer experience, but it also helps marketers increase their return on investment. By providing insight into which campaigns are most successful and least successful, this solution can not only reduce sales cycles, but also empower brands to make more informed decisions with fewer yet more impactful marketing messages.

What is multi-touch attribution vs marketing mix modeling (MMM)

Multi-touch attribution and marketing mix modeling (MMM) are two distinct yet related approaches to measuring the effectiveness of different channels, campaigns, and ad placements.

While both methods can help marketers understand how their efforts contribute to conversions, there are some key differences between them that should be taken into consideration when devising an overall strategy.

Multi-touch attribution models assign credit to more than one touchpoint during the buying process while MMM looks at a variety of factors including channels, campaigns, pricing strategies and other variables in order to determine which ones have had the most impact on sales or leads.

By understanding these differences between multi-touch attribution and marketing mix modeling (MMM), marketers can make better decisions about where they should allocate resources for maximum return on investment (ROI).

The attribution challenges Shopify merchants are facing

1. Lack of accurate data

The privacy policy, ad blockers, IOS 14 updates are changing the way merchants collect customer data. Attribution software can't work without accurate data. For Shopify merchants, The new Shopify web pixel should be the best option to collect data.

For WooCommerce and other platforms, try to upgrade tracking with first-party cookie and collect as many as first-party data as possible. 

2. More and more marketing channels

Are you exploring the potential of new marketing channels like TikTok and Facebook Shop for your store? As you venture into multiple channels for promotion, you may encounter the complexities of attribution.

How to get started with multi-touch attribution

How to get started with multi-touch attributionFor Shopify merchants, it's essential to understand the customer journey, and choose an attribution model to connect marketing campaigns and their conversions. We have seen some high-growth brands build their flywheel based on 3 points:

1, Experiment campaigns based on combination of ( Creatives, copies, audiences)
2, Get multi-touch attribution analysis and customer level conversion journey.
3, Scale the hign performance campaigns and turn off the bad one.The attribution report is critical, since brands need this data to make decisions of campaign optimization. All the tactics can't run well without great data.

Step #1: Deploy Marketing Analytics Software

There are lot of marketing attribution apps for Shopify merchants. Some best matches should have deep integration with Shopify to make sure you can easily deploy.

Step #2: Capture your marketing data

To get customer behaviors raw data, you need to insert tracking snippets. These snippets track most customer conversion events such as page view, add to cart, checkout start, payment info and finish purchase.

Managing tracking snippets can be complicated. Attribuly has released a code-free solution, which integrates with Shopify pixels & customer events. This future-oriented solution can save lot of work for browser side tag management.

Furthermore, you may also get conversion events from Shopify server-side tracking. Because some orders could not be triggered at browser-side. For example, the recurring orders.

Step #3: marketing channels integration

To understand detailed customer sources, you need to connect different channels. By integrating with Google ads, you can get what key the customer clicked, ad spend and ad level ROAS. Integrating with Facebook ads, you get what ad the customer clicked, as well as ROAS.

So by integrating your first-party data including historical data, you get an accurate insight of blended or single ad performance. This important data is key to make sure you don't spend money to the wrong campaigns.

You can also connect to klaviyo, uppromote and all your touch points. 

Step #4: Set up conversion goals

Setting up a conversion goal is an important step when setting up attribution analytics for Shopify e-commerce businesses. A conversion goal allows marketers to track the customer journey and understand how their marketing campaigns are contributing to sales or leads. It can also help them identify which channels, campaigns, and ad placements are most effective in driving conversions.

Most brands set up goals for different products at different stages. You will find this setup easy if there is integration with Shopify. What you need to do is just select the event type and products you want to put into the goal. Then the software will automatically finish the rest.

Step #5: test different attribution models

Marketers targeting consumers with short sales cycles and limited contact points( typically fashion) can easily identify messages that spark or finish the sale by utilizing first or last-click attribution models. Still, neither of these approaches allows marketers to evaluate how successful other interactions across the customer journey are.

For marketers needing to communicate with consumers over a longer sales cycle and more touchpoints prior to conversion(typically product with high price), there are moulti-touch attribution models that can identify the most effective steps.

For advertisement, you can view a blended ROAS across marketing platforms, to view overall return. Or dive into single ad ROAS to find the best-performing campaigns. The ROAS will be changed according to multiple models you select.

You may want to check every conversion's customer journey. So you get a rich insight into the customer portrait. With some external customer information, such as social information. You will have a clear understanding of your audience's portrait.

You may have a lot of campaigns in testing, so you will scale the best-performing one. In the long run you invest money in all the performing campaigns so your ROAS keeps in a stable and high level.

Step #6: check conversion paths

Conversion paths give you a bird view on some most important routes that your customer convert. So you may invest more routs with the highest conversion rate, and conversion value. Aware that using different models with result differently.

Conclusion

Multi-touch attribution tools are invaluable for Shopify merchants who are looking to maximize their ROI in the crowded e-commerce space. By understanding how their customers interact with various channels and campaigns throughout the customer journey, marketers can make more informed decisions about how to allocate marketing investments and resources. Additionally, by carefully evaluating their data and experimenting with different models, they can further refine their strategies and ensure that they are getting the most out of every dollar spent. With the right approach, multi-touch attribution can be an effective way for Shopify merchants to understand their customers’ behavior and maximize their marketing ROI.

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