Businesses engage with customers through various marketing channels, making it challenging to assess the effectiveness of each channel in driving conversions. Traditional attribution models, such as first-touch and last-touch, have been used to distribute credit for conversions. However, these models overlook the contributions of other channels and fail to provide a comprehensive understanding of the customer journey on their own. Enter the Multi-Touch Attribution Model – a powerful analysis that complements these other attribution models by offering solely looking at the value of each marketing channel as it relates to customer conversions. In this post, I’m going to explain what Multi-Touch Attribution is, how it differs from other attribution models and how your business can benefit from it. Attribution modeling can be daunting, so I’ll ground our discussion in a representative example that you can easily relate to your business.

What is Multi-Touch Attribution?

Multi-Touch Attribution (MTA) is an advanced marketing analytics model that aims to allocate credit to different touchpoints across the customer journey leading to a conversion. Unlike traditional models that solely focus on the first or last interaction, MTA considers all customer interactions with various channels throughout the entire sales funnel.

What does Multi-Touch Attribution tell you?

By examining the customer journey data, marketers identify the various touchpoints that played a part in converting customers and use Multi-Touch Attribution Modeling to compare the respective contribution of each marketing channel to conversions. Multi-Touch Attribution Modeling takes a comprehensive approach by eliminating the focus on the timing of each customer interaction. Instead, Multi-Touch Attribution Models solely looks at whether a channel played a part in a conversion (i.e. whether the customer engaged with that channel) and the frequency that each channel played a part. It then aggregates that data in a complex algorithm that outputs the weighted contribution to conversions of each channel. This analysis provides insights into how customers interact with different channels and the significance of each touchpoint in the decision-making process.

It is important to note again that the Multi-Touch Attribution Model does not consider the timing of channel engagements. Consequently, it may not identify which specific channel directly drives conversions (that is what Last-Touch Attribution Modeling tells us). Instead, it showcases the overall value of each marketing channel in influencing the customer’s final decision to convert.

Contrasting with First-Touch and Last-Touch Models

Let’s take a closer look at the distinctions between Multi-Touch, First-Touch, and Last-Touch Attribution Models:

First-Touch Model
This model attributes the entire credit for a conversion to the first touchpoint a customer encountered. While it may provide insight into initial customer engagement, it neglects the impact of subsequent touchpoints in the conversion journey.

Last-Touch Model
Conversely, the Last-Touch Model allocates all credit to the final touchpoint before the conversion. While this method may highlight the closing channel, it disregards the initial interactions that nurtured the customer’s interest.

Multi-Touch Model
The Multi-Touch Attribution Model bridges the gaps in the First-Touch and Last-Touch approaches by distributing credit to multiple touchpoints throughout the customer journey. It emphasizes the collective effort of all marketing channels in influencing customer conversions.

How does Multi-Touch Attribution help in the real world?

Let’s dive into an example to see how the Multi-Touch Attribution Model can uncover surprising insights for a fictional company, TrendTrove, an online clothing retailer.

TrendTrove conducted a Multi-Touch Channel Analysis to better understand which marketing channels were driving the most conversions. Prior to the analysis, they primarily relied on a Last-Touch Attribution Model, which credited all conversions to their email marketing campaigns. However, after incorporating analysis of the Multi-Touch Model, they discovered a more nuanced picture.

Findings and Learnings

1. Organic Search: The analysis revealed that organic search played a significant role in the customer journey. Pairing this with previous First-Touch Attribution analysis, they discovered organic search often acted as the first touchpoint. Customers frequently discovered TrendTrove’s website through search engines, which sparked initial interest.
2. Social Media: While social media contributed only a small percentage to the last-touch conversions, it played a crucial role in the middle of the customer journey. Many customers engaged with TrendTrove’s posts and ads on various social platforms, influencing their decision to make a purchase.
3. Influencer Marketing: TrendTrove had invested in influencer marketing partnerships, and the Multi-Touch Attribution Model showed that this strategy had a considerable impact on conversions. Customers exposed to influencers’ content were more likely to visit the website and eventually convert.

How TrendTrove Should Adjust Their Marketing Channel Strategy:

Armed with these surprising findings, if TrendTrove adjusts their marketing channel strategy in the following ways, they would be better positioned to achieve more conversions and grow revenue:

1. Content Optimization: If TrendTrove doubles down on their content optimization efforts, focusing on SEO to improve organic search visibility, they would gain more prospective customers. By identifying relevant keywords, creating valuable content, and optimizing their website structure, they would gain more traffic from organic search.
2. Social Media Engagement: Recognizing the value of social media interactions, if TrendTrove increases their efforts on platforms where their target audience is most active, social interactions should increase their lead-to-conversion rates. By engaging with customers, responding to queries, and launching exclusive social media promotions, they would see a significant boost in engagements that help to drive conversions.
3. Influencer Collaborations: Building on the success of influencer marketing, if TrendTrove expands their network of influencers and runs more targeted campaigns, they would unlock another win. By collaborating with influencers whose audiences aligned closely with their target market, they now know they would significantly increase brand exposure and conversions.

The Multi-Touch Attribution Model provided TrendTrove with an eye-opening understanding of their marketing channels’ true value. By pairing Multi-Touch Attribution Modeling with First- and Last-Touch Attribution Modeling, they were able to identify the pivotal role of various touch points throughout the customer journey. Armed with these insights, your business can make strategic adjustments to your marketing channel strategy and achieve more conversions, ultimately growing their revenue, without launching new products or campaigns. This fictional example underscores the significance of adopting Multi-Touch Attribution to gain a deeper understanding of the customer journey and optimize marketing efforts for business success. So, embrace the power of MTA and unlock the true potential of your marketing channels!