Multi-Touch Attribution in Ecommerce Marketing: Everything You Need To Know

Ecommerce has exploded over the last decade, with global retail ecommerce sales reaching $5.8 trillion in 2023. However, the online world moves fast, and consumer attention spans seem to get shorter by the day. Companies that don't have their fingers on the pulse of digital marketing strategy will quickly be left behind.

One way to stay in the game is by using advanced analytics to understand your customer's journey. Doing so enables you to credit marketing efforts properly through multi-touch attribution, which is vital now. Top brands are implementing sophisticated models to see where budgets are best spent. These models reveal which channels drive buying choices and how to refine each step to maximize conversion.

This guide will explore everything needed to leverage MTA. Read on to take your ecommerce marketing up a level. Let's start by clearly defining the foundation.

What Is Multi-Touch Attribution?

In digital marketing, attribution means giving credit. It usually pertains to a desired action during various touchpoints along the customer journey. The action could be a purchase, newsletter sign-up, ebook download, or any other conversion label.

Marketing attribution enables scoring each touchpoint's impact in driving the conversion. For example, a shopper’s journey may include:

• Clicking a Google Shopping ad
• Reading online reviews
• Seeing a product on the Instagram of an affiliate
• Clicking an on-site retargeting ad
• Buying the product

MTA means granting partial credit to multiple touchpoints in this sequence. Each channel and interaction gets a slice of the revenue based on its influence.

Single Touch Attribution Limits

This approach differs from single-touch models, which give 100% of the credit to one event. Marketers have historically relied on “first-touch attribution” or “last-touch attribution.”

The first touch often overrates early actions like branded searches. Yet, most buyers aren’t ready to buy at first exposure. More progression down the funnel usually comes first.

The last touch has the reverse issue - outsized credit for the final pre-conversion click. This ignores earlier influence guiding users to this point.

Neither tells the full story. Today, buyers take winding paths with extensive research before converting. They may need to see many brand messages over weeks before eventually purchasing. Specifically, the average seems to be around eight touchpoints before a sale. 

Single-touch models miss the cumulative impact of multiple exposures across complex journeys. Multi-touch accounts for every step towards conversion. It gives brands vastly better data to enhance ecommerce customer retention rates and budgets.

Business Impact of Multi-Touch Attribution Marketing

Speaking of customer retention strategies for ecommerce and budget, that's where MTA truly shines. Deploying multi-touch methodology elevates ecommerce marketing and key business performance markers:

Understand Channel Performance

The core benefit is accurately gauging channel performance grounded in hard attribution data. You can use it to quantify revenue and conversions generated by all major sources. Think paid search, organic, referrals, social ads, affiliates, etc.

Lift the hood even more to see attribution analytics for specific search terms, campaigns, or creatives. Identify your most and least efficient customer acquisition sources based on truthful ROI.

Optimize Marketing Spend

Seeing clear channel impact enables smarter paid budget decisions. Shift dollars away from poorer performing areas towards higher converting traffic sources.

Cut wasteful platforms failing to drive attributable value. Instead, double down on proven winners surfaced via multi-touch data signals. This dynamic multi-touch attribution analysis gives clear budget optimization guidance.

Boost Conversions

Beyond overall optimization, MTA also uncovers opportunities to increase conversions within each channel. Through journey mapping, you gain visibility into friction points and drop-offs.

You'll spot where shoppers lose interest, bail on carts, or fail to convert. Then, you can tweak pages, navigation, on-site experience, and funnels based on leakage insights.

Identify. Target. Fix.

Recognize Most Valuable Customers

Ecommerce brands can also filter multi-touch data by audience to reveal value. Assess channel performance for VIPs vs bargain hunters. Examine by geography and acquisition source. And see which channels deliver big lifetime value customers with high repeat order rates over months or years. Then, tailor your ecommerce retention strategy to their preferences.

Types of Models

We’ve discussed why MTA is indispensable for ecommerce. Now let’s explore popular ways to put this into practice:

There are two core model architectures:

1) Rules-based fractional

2) Algorithmic machine learning

Rules-based MTA is the simpler option, guided by pre-defined rules that are often set by the marketer. Algorithmic options can be more complex. They shift channel values automatically based on changing performance data.

Here's an overview of the most common choices:

Even Attribution

In even attribution, conversion credit gets split into equal parts across all touchpoints. Each step along the journey receives an equal percentage of the revenue or credit. Regardless of type, sequence order, or logical weighting.

Even distribution makes sense early on before you have sufficient data to inform differential weights. It offers a starting point until analytics can confirm appropriate valuations.

• Pros: Simplistic and easy to implement. Gives partial credit to all channels automatically.
• Cons: Fails to account for inherent differences in value between touchpoint types. 

Fractional Attribution

Here, marketing analysts define a custom fractional value or weight tied to each touchpoint type or marketing channel. You might determine that the first touch gets 20%, the last touch gets 30%, referring domains get 10%, etc., based on in-house heuristics.

It makes sense once preliminary performance data is available. Use it to guide channel weighting decisions and rules configuration.

• Pros: Easy to understand and modify. Logic can be customized by analysts without reliance on black-box statistical modeling.
• Cons: Still relatively static and not responsive to changes in channel influence over time. Weight selection introduces some subjectivity and guesswork.

Linear Attribution

Linear attribution is a simple variation of weighted methodology that looks at the sales funnel as a four-step process. Depending on where the lead enters and exits the funnel, multiple touchpoints receive a linear fraction of the credit.

Linear minimizes subjective human bias before analytics can confirm the relative impact.

• Pros: Easy to set up out of the gates. Gives partial credit without overweighting specific steps before data confirms appropriate percentages.
• Cons: Harder to differentiate between significant interactions versus less meaningful engagements.

Position-Based Multi-Touch Attribution

Channel valuations are determined based on sequence position relative to the conversion event. Typically, common configurations weigh the first touch, last touch, and middle touchpoints differently. It could be:

First Touch: 20-30%

Middle Touchpoints: 10-20% total

Last Touch: 40-60%

Of course, analysts can customize fractional allocations across sequence positions. It is applicable once preliminary data shows sequence-based differences in attribution. The last touch likely does deserve heavier credit in many businesses.

• Pros: Allocates more value to final interactions vs early impressions based on user behavior data. Still maintains some first-touch credit.
• Cons: Difficult to distribute middle touchpoint allocation. The final click is often influenced by earlier interactions, even if immediately preceding conversion.

Time Decay Attribution

In time decay, channel credit accumulates over time. Later touchpoints always receive increased influence valuation. Earlier interactions earn lower attribution. The recency of exposure has a magnifying impact on attribution scoring.

It helps account for those with longer, more complex buying journeys across multiple sessions.

• Pros: Dynamically updates scoring over time without arbitrary rules configuration. Attempts to capture recency effects.
• Cons: Can significantly underweight early interactions and mid-funnel activity. These might plant seeds for eventual conversion.

Incremental Attribution Analysis

This multi-touch attribution analysis focuses on quantifying the “incremental lift.” That means the boost generated from a particular marketing activity or spend allocation. It uses statistical measurement and MTA tracking.

It compares conversion rates during periods when you are running certain campaigns versus periods when paused or absent to isolate true incrementality. That makes it perfect for quantifying campaign ROI and fine-tuning budgets. 

• Pros: Helps prove incrementality and ROI rather than just correlate. Fixes over-attribution biases common in standard multi-touch models.
• Cons: Requires robust analytics and properly structured statistical tests. Customers may get exposed to other messages during the test duration.

There are pros and cons to both rules-based and algorithmic options. Many brands start with simpler fractional methods. They focus on a few channels while they build data history and internal expertise. From there, shifting towards flexible machine learning models powered by deep conversion history unlocks superior predictive intelligence over time.

Implementing Attribution

Ready to get started with multi-touch attribution marketing and improve your ecommerce KPIs? First, let’s summarize the key requirements for implementation:

Install Marketing Analytics Platform

The foundation is enterprise-level marketing analytics software with attribution modeling capabilities. Popular options include Google Analytics, Adobe Analytics, Salesforce DMP, Oracle Bluekai, and more.

Integrate With Marketing Channels

Tag and connect all the multiple touchpoints feeding your sales funnel. You can use multi-touch attribution tools like UTM codes, tracking links, or other parameters. Capture granular interaction event data across channels.

Feed Conversion Data

Pipe granular interaction events and final sale/conversion data into your analytics platform. This enables mapping full sequences to outcomes. Access journey reports mapping each individual’s path to purchase.

Select & Implement Attribution Model

Choose your preferred model based on the use case, resources, and analytics maturity. Consult rule-based vs algorithmic model overviews in the previous section. Then, connect the chosen model to your analytics platform and marketing activation channels.

Analyze, Report, and Optimize

Like any initiative, you'll want to continuously analyze attribution reports. Keep an eye on every channel's influence on conversions. Digest insights and share with internal stakeholders. Brainstorm campaign optimizations to improve performance.

Attribution Best Practices

To ensure optimal impact, consider these proven tips:

Phase Channel Integration

Avoid getting overwhelmed trying to integrate and analyze all marketing channels at once. Start with 2-3 high-priority paid channels like Google and Facebook to prove initial attribution models. Then, expand over 6-12 months.

Maintain Tagging

Tagging marketing channels and campaigns enables accurate attribution data. And that's what you want flowing into your analytics measurement. Don’t just tag some links while excluding other key funnels. Embed multi-touch attribution tools into your ESP for automatic campaign tracking codes.

Breakdown of Reporting By Segments

Build multi-touch reports that break out more than conversion rates. There are other metrics across various dimensions, like

• Geography
• Device type
• Traffic source tier
• Seasonal peaks
• And more.

Comparing performance by segments improves decision-making.

Appoint Project Owner

Designate a respected marketing ops leader to own attribution strategy and evangelize cross-departmentally. It's a good idea to create recurring dashboards for transparency. Consider self-serve access to data for other managers to explore themselves without bottlenecks.

Executive Buy In

Likewise, educate leadership early on multi-touch concepts. Have analytics leaders present attribution dashboards directly to key business stakeholders. Secure buy-in and input on optimization from the top down before rolling out changes.

Benchmark Performance

Leverage industry KPI benchmarks for metrics like CPA and ROAS to better contextualize model lift vs niche averages.

Conclusion

Today’s hyper-competitive ecommerce demands retention in marketing and agility. Continuous optimization based on data is one of the best ways to stand out. Multi-touch attribution marketing equips brands with intelligence to refine strategy on the fly.

By connecting every step to conversion, you gain visibility to optimize budgets. You learn more about channel mix, segmentation, and creatives for a performance edge.

If you're still wondering how these KPIs compare to your competitors, Varos can help. Book a demo to see how our benchmarking platform can help you capture market share through data-driven decisions.

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About the Author

Sarah Clowes-Walker 

Head of Marketing at Varos

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