How OWOX BI Built & Optimized a Custom Marketing Attribution Model for SaaS Business

SaaS businesses have a more complicated customer journey than most of the e-commerce businesses. Repeated payments longer sales cycle and the sales funnel with a lot of touchpoints: organic, ads, blogs, webinars, free trials, sales calls, email marketing, and so much more. It’s not easy to track the whole customer journey: more steps, and most conversions happen in the CRM system instead of a website.

Moreover, businesses use a lot of different ways to acquire and retain customers, including offline channels like phone calls, conferences, and meetings. The challenge here is that you need to know which of your efforts worked out, attracting customers and making them become your regular ones.

OWOX BI noticed this SaaS B2B challenge back in 2018, and that prompted us to create our own machine-learning funnel-based attribution model, that was extremely successful for B2B SaaS businesses.

Note: This article was originally published in August 2019 and was completely updated in February 2024 for accuracy, new details and because things are changed a bit.

B2B marketing attribution is the analytical process of evaluating and assigning value to marketing touchpoints contributing to a customer's journey toward conversion or sale. This comprehensive approach entails the following:

• Meticulously tracking the user's journey to understand their interaction with various marketing channels,
• Scrutinizing each touchpoint along the customer's path to discern which ones effectively lead to the desired actions,
• Fine-tuning marketing tactics based on these insights bolsters the overall return on investment and improves future marketing strategies.

Saas Marketing Attribution modeling presents unique challenges for enterprises, especially newer ones that often expand through referrals and non-digital avenues. When digital marketing enters the mix, attributing conversions can become complex and opaque, as there's typically no dedicated person overseeing analytics, making interpretation challenging. Therefore, such companies must establish their analytics infrastructure early, despite initial growth not driven by conventional marketing methods.

Marketing attribution for B2B SaaS differs significantly from e-commerce, unfolding in two distinct phases, each separated by the point of a demo or trial signup:

This phase encompasses the customer's journey from their initial interaction to the point where they sign up for a demo or trial. This is a critical phase in the B2B SaaS marketing attribution context as it sets the stage for further engagement, unlike in e-commerce or B2C, where the journey might end with a quick purchase.

Tools like Google Analytics 4 or another website tracking system track conversions up to the demo, focusing on various paths leading to Marketing Qualified Leads (MQLs) and SQLs.

The emphasis here is on tracking interactions that involve exchanging contact information, like downloading resources or signing up for webinars, rather than on immediate sales.

However, there are challenges in this phase, such as the misuse of conversion goals, lack of proper redirections to "thank you" pages after signups, and the complexity of managing numerous conversion goals, particularly in larger organizations.

After the demo or trial, the journey continues for a potentially extended period, often spanning several months, as the prospect moves from being a Sales Qualified Lead (SQL) to an actual customer. This phase is crucial due to the typically longer sales cycles in B2B SaaS.

This phase shifts focus to the CRM systems, pivotal for larger enterprise SaaS companies. It involves tracking the conversion path from trial signup to customer conversion, a process complicated by data management issues and the depth of tracking required.

Large companies might use CRMs like Salesforce, Pipedrive, Zoho, Pardot, or HubSpot for detailed attribution tracking, while smaller companies might need less complicated CRM platforms.

The key takeaway for businesses, especially large enterprises with extended sales cycles, is the importance of selecting a CRM system that can provide detailed insights into every touchpoint, from the demo or trial signup to the final conversion into a customer.

In today's competitive SaaS landscape, B2B marketing attribution is a pivotal tool for success. It's not just about tracking metrics; it's about understanding the impact of each marketing effort on your business goals.

Let's look at some points of why SaaS marketing attribution is important.

• Enhances ROI Analysis: B2B marketing attribution in SaaS provides detailed insights into which marketing efforts yield the best return on investment, allowing for more efficient allocation of resources.
• Improves Customer Journey Understanding: It enables a deeper understanding of the customer journey, identifying key touchpoints and influencing factors in the decision-making process.
• Facilitates Data-Driven Decisions: Attribution models help make informed, data-driven decisions, reducing guesswork and enhancing marketing strategy effectiveness.
• Optimizes Marketing Channels: By understanding which channels are most effective, businesses can optimize their marketing mix for better engagement and conversion rates.
• Supports Personalized Marketing: It aids in creating more personalized marketing strategies by understanding customer preferences and behavior patterns.

In short, we collect data on all the user touchpoints on their way through the funnel.

Next, we evaluate the probability of users passing on to the next funnel step. If the step is more difficult to pass, the efforts that lead users through it get more value.

But it’s vital to track every phone call and meeting in a CRM system and evaluate every step of the user journey to get measurable results.

Like many other B2B SaaS companies, our client’s customers interact with them outside the website.

They developed quite a comprehensive system for tracking that:

1. The sales department works with their potential customers, holds product demos, and assists in choosing proper plans.
2. Customer success specialists provide tech support and help users improve their experience using our client’s products.
3. Product specialists train and consult customers, providing solutions to achieve business goals.
4. Designers, developers, and product managers work on improving the UI and UX of the products, as well as creating new features and updates.
5. Event managers organize conferences, meetups, and other types of events.

Due to so many teams involved in the user journey, finding out whose input was the most valuable at every step of the funnel is quite challenging. It’s also difficult to discover what stage of the customer journey requires more time and effort, which can be easily skipped.

If you try to evaluate every team’s contribution separately, you’ll surely attribute more revenue than you get because the same deal can be considered for each department.

If your business is subscription-based, the first and the following payments matter to you. So, the value of the acquired customer should be measured by the first payment along with the customer LTV. Moreover, businesses normally use multiple tools to attract and retain customers, with different teams involved, and it’s important to know their contribution.

That’s why we decided to combine two approaches when building a SaaS attribution model for our client, the first payment and the predictive LTV, after considering possible ways to distribute value among the funnel steps. We suggested that the value of the first payment should decrease in the following months. Due to this, the customer value gets measured and then redistributed after every next payment, depending on how much effort every team spends on each user step.

To calculate the marketing attribution model, we used the value of the predictive LTV and deduct the value of the payments we already got. For example, if the money obtained from a customer’s predictive LTV is $1,500, and he or she pays $100 monthly 3 times in a row, the value of the first payment would be $1,200, which is $1500 — (3x$100). In case we talk about 6 months instead of 3, the value of the first payment will be $900, which is $1,500 — (6 x $100).

We defined and distributed all customers events based on the company's engagement area. This is how we got 40 types of events within 5 categories:

1. Marketing: SMM, PR, content marketing, webinars, PPC, еmail marketing.
2. Events: ticket purchases, conference website visits.
3. Sales: demo presentations, personal emails, calls, meetings, chats.
4. Product: all of the products in the line of our client
5. Customer success and Support: personal emails, solved tickets, chats, and meetings.

The choice of attribution model was obvious. We used machine learning full-funnel attribution model somehow similar to Data-Driven attribution and Custom attribution but way more manageable to suit the business needs.

It helps in the contribution of each channel on sales and channels' mutual interaction. Also, it’s perfect for complex non-linear funnels. This model calculates the possibility of transfer from one funnel level to another and distributes the value due to the rule: the less the possibility is, the more valuable the efforts forcing the client to make this step are.

The website data is collected with OWOX BI Streaming, we also collect all of the advertising cost data to BigQuery as well as the client’s third-party data: SalesForce, Intercom, Gmail, Calendar, and Zendesk.

That’s why we brought all data together in Google BigQuery, in order to merge and evaluate correctly.

To track how our audience overlaps across domains, we used OWOX User ID similar to clientID in GA4. We also analyzed project-level events and tracked User ID along with Project ID. It is necessary to do that, as in B2B business, a product can get tested by one job title during the trial period, though purchased by another job title from the same company.

Moreover, the sessions that lead a customer through more difficult steps should get more value and increase with the step complexity. The attributed revenue should match the real revenue obtained by a business.

To look at the data from a different angle, we built 3 reports.

The first one below demonstrates how actual and predictive revenue and the actual and planned costs are attributed to each department.

Due to the long user journey our client has, it’s important to take note of the predictive revenue. This allows us to measure the contribution of all the efforts that lead the customers along the funnel.

Those numbers are given as an example.

For instance, you can see that the most predictive costs are attributed to the Product department, though it also drives the most of actual and predictive revenue.

The second report is based on the same data, demonstrating ROI for each department.

The report above demonstrates that only some of the Product teams have positive ROI. This means that the team’s processes should be optimized to boost the overall Product department performance.

The third one visualizes our client’s efforts to actual and predictive value and contains metrics from previous reports. You can see the metrics of the first report by month on the top graph, while the circle diagrams show how revenue is distributed among departments. The bar chart allows you to see the ROI by department.

This report shows, for instance, that you should pay more attention to the Product and Sales departments and help them streamline their work.

Having evaluated the performance of every department, you can realize how efficient is each of the marketing channels and understand how to make more out of the channels that pay off.

This case is designed to help you better understand how different departments contribute into the overall success, find narrow gauges of your complex B2B sales funnel, and boost the effectiveness of all the channels involved in the sales process.

You can also ensure that all of the touchpoints, including the offline ones, are credited correctly (by your rules).