Marketing attribution for SaaS companies is the analytical process of determining how much or how little marketing efforts impact desired business outcomes, such as sales pipeline or closed-won Annual Recurring Revenue (ARR). In this comprehensive guide, we will explore the various models of marketing attribution, the tools available, and common pitfalls to avoid.
The Most Common Attribution Model Used in SaaS
Last-Touch Attribution
Last-Touch Attribution is one of the most prevalent models in SaaS marketing. This model assigns all credit for a conversion to the last interaction a customer has before a conversion.
Last-Touch Advantages:
- Simplicity: Easy to implement and understand, making it a go-to for many marketing teams.
- Insight into the last marketing interaction: Provides insight into the last ad or asset someone saw before taking an action, such as submitting a demo or contact request. This is a key data point for SaaS marketers.
Last-Touch Disadvantages:
- Inflated Impact of lower marketing funnel tactics: By assigning all credit to the final click, last-touch attribution often misrepresents the role of lower funnel tactics like SEO and paid search ads. When prospects are already interested—having seen ads, read content, or discussed solutions with peers—their next step is often to search for the company or solution on Google. This click is more about how prospects do research than the effectiveness of a static, yet last-touch reporting makes it appear as though search engine marketing was the primary driver of the deal.
- Misleading Resource Allocation: This overstatement of lower funnel tactic impact can lead to underinvestment in the channels that actually generate demand and spark interest in a brand. For instance, content marketing, social media engagement, and podcasts may be undervalued, even though they play an important role in nurturing leads through the buyer’s journey.
Relying solely on last-touch attribution can lead to misaligned marketing strategies and budget allocations, as it overlooks the cumulative effect of multiple touchpoints that contribute to a final decision.
Other Marketing Attribution Models Used In SaaS
First-Touch Attribution
First-Touch Attribution credits the initial interaction a customer has with your brand. This model is valuable for understanding how awareness is generated, but it can overlook the effectiveness of subsequent touchpoints. For example, if a customer first learns about your product through a blog post but later converts after seeing a paid ad, first-touch attribution would not capture the full journey.
Time Decay Attribution
Time Decay Attribution assigns more credit to interactions that occur closer to the conversion. This model acknowledges that recent touchpoints are often more influential in the decision-making process. For instance, if a customer engages with multiple pieces of content over time but ultimately converts after clicking a recent email, this model would give more weight to that email interaction.
Data-Driven Attribution
Data-Driven Attribution employs machine learning to analyze multiple touchpoints and assign credit based on their actual contribution to conversions. This model provides a more nuanced understanding of customer behavior and is increasingly favored in the SaaS landscape. By analyzing patterns across various customer interactions, this model helps marketers identify which channels are most effective at driving conversions.
Influence Attribution
Influence Attribution assigns 100% of the value to each touchpoint. For example, if a deal is worth $1.2 million in ARR and paid search, social media, and email all had touchpoints, each channel would be credited with influencing the entire $1.2 million. This can lead to an inflated perception of each channel’s effectiveness, as it does not break out the value contributed by each touchpoint.
Attribution Tools Used By SaaS Companies
To effectively implement marketing attribution, SaaS companies often rely on various tools. Below are some common attribution solutions that SaaS companies leverage to support their marketing attribution programs:
- Marketo Measure (formerly Bizible): Ideal for B2B marketers already using Marketo, this tool offers multi-touch attribution capabilities.
- HubSpot: Provides built-in attribution tools for tracking customer interactions, making it a good choice for those already using HubSpot.
- Factors.ai: Focuses on B2B SaaS companies, linking revenue data to marketing efforts for clearer insights into ROI.
- HockeyStack: Rapidly growing in popularity, this tool combines analytics and attribution for a comprehensive view of customer journeys.
- Google Analytics: A free tool that offers basic attribution models. However, to maximize its effectiveness, you need to enable it by pushing your opportunity data into it, including estimated and closed-won revenue or ARR values.
- Ad Networks: Platforms like Google Ads and LinkedIn provide insights into paid campaigns. Similar to Google Analytics, you need to push your data into these platforms to take full advantage of their attribution capabilities. This includes integrating opportunity data to ensure accurate tracking and reporting.
These tools help automate data collection and analysis, allowing marketing teams to focus on strategy rather than manual reporting. The right attribution tool can significantly enhance a company’s ability to track and optimize marketing performance.
The Blindspots of Digital Attribution
Despite the advantages of digital attribution, like the ones mentioned above, there are significant blind spots that can hinder effective marketing strategies. Many companies rely solely on digital attribution tools, which can lead to incomplete data and a skewed understanding of customer behavior.
Measurable Interactions vs. Qualitative Insights
Digital attribution models often focus on measurable interactions, such as clicks or conversions, but they can miss out on qualitative factors that influence buying decisions. For example, a prospect might hear about your product through a current client, which happens often in SaaS businesses. However, if that prospect ultimately converts after clicking a display ad and then a paid search ad, digital attribution will only credit the display and paid search ads. This approach overlooks the earlier mention of your product by the client, which played an important role in building interest and trust.
Much like the issues caused by last-touch attribution, a sole reliance on digital attribution tools can lead to misallocation of budgets and resources. Marketers may over-invest in channels that appear to drive conversions while neglecting the foundational efforts that initially sparked interest.
The Role of Self-Reported Attribution
Self-Reported Attribution is a method where prospects provide feedback on how they discovered your brand or product. This can be done through forms or direct questions during sales conversations. One of the most popular ways to collect this data is through an open text field on contact forms that asks, “How did you hear about us?”
By asking customers how they heard about your brand, you can gain insights that digital attribution tools may overlook due to their inability to track certain interactions.
For instance, if a customer indicates they learned about your product through a social media post, it highlights the importance of that channel in their decision-making process, even if it wasn’t a captured digital touchpoint.
Incorporating self-reported attribution can bridge the gaps left by digital systems, providing a fuller picture of how various marketing efforts contribute to conversions.
This multi-faceted approach ensures that all touchpoints are considered, leading to more informed decision-making and better resource allocation.
Why You Need Multiple Attribution Models
Throughout this guide, we have talked about several attribution models, their upsides, and their downsides. The truth is, no single attribution model works well for every use case. Just like a mechanic needs multiple tools to diagnose a car, marketers need various attribution models to understand which parts of their marketing are working.
If your linear model, last-touch model, and self-reported model all agree, that is a strong indicator of performance. Conversely, if all three of those models disagree, that is also a valuable insight into potential gaps in your understanding of buyer behavior.
Your marketing attribution models should help you identify which parts of your marketing are effective and which aren’t. Do not make decisions based on just one model. Instead, use a combination to get a clearer picture of your marketing.
