Suppose you're a SaaS business and leverage Google Ads, Facebook Ads, Bing Ads, SDRs (sales development representatives), outbound e-mail, blog articles, affiliate marketing, and more to promote your business.
Suppose a customer finds out about your business through a Facebook ad and visits your social media pages to learn more about your business. Finally, they make a purchase using an affiliate link.
So, how do you know which marketing method led the customer to make the purchase decision or what role each marketing touch played in influencing the customer to purchase a product?
This type of situation is where revenue attribution comes into the picture.
But what exactly is revenue attribution? Why is it important? What attribution models, either single touch or multi-touch, should you be using? How can you implement revenue attribution modeling correctly?
Let's find out.
What is revenue attribution?
Revenue attribution, also known as marketing attribution, is the process of apportioning revenue to the various marketing and sales activities that contribute to earning it. For a company to effectively measure and optimize its revenue-generating efforts, it must accurately attribute revenue to each marketing and sales touchpoint.
Revenue attribution involves collecting and assembling data about customer journeys to gain vital insights into how each aspect of marketing influenced a customer to make a purchase decision.
There are several different attribution models, and the attribution model utilized should align with the business questions. Revenue attribution takes advantage of attribution models to assign credit to the various touchpoints in the customer journey.
Businesses can use predefined single-touch or multi-touch attribution models to carry out revenue attribution. They can also use custom attribution models if they have a specific goal or need related to revenue attribution.
Why is revenue attribution necessary?
In any business, it is crucial to understand where revenue originates. There are several reasons why businesses need to know how revenue is attributed. It can help identify which products and services are most popular among customers, track the marketing campaigns' effectiveness and allocate resources more effectively.
By understanding where the revenue comes from, businesses can make better decisions about how to grow their business.
How can businesses use revenue attribution to their advantage?
Businesses can use accurate revenue attribution to their advantage by connecting marketing activities to revenue and deals at both a strategic and tactical level. With the proper data setup, marketers can understand which marketing channels, activities, campaigns, ad groups, and ads result in revenue and deals. By allocating their marketing budget more effectively and improving their return on investment, businesses can further scale their revenue and maximize their profits.
It can also help businesses understand which marketing campaigns are most effective and generate the most revenue to focus their efforts on them. For example, suppose many new customers in their sales pipeline are coming from online ads, specifically LinkedIn. In that case, they can focus more on digital marketing than traditional marketing.
There are some common challenges with revenue attribution. These include:
- customers not interacting with all marketing channels and
- not all deals are attributable to marketing channels.
However, businesses can overcome these challenges by
- using web tracking, including google analytics, to capture customer activity
- combining web tracking data with other first-party data in CRM systems, data warehouses, and
- survey-based self-reported attribution, and
- using probabilistic methods for estimating the marketing contribution from offline channels such as direct mail or television.
It is crucial to have complete and accurate reporting for businesses to understand how marketing initiatives are turning into pipeline and revenue. Without accurate attribution reporting, companies are flying blind, and their marketing budgets are being spent more on gut instinct rather than hard data.
How should a business go about implementing revenue attribution?
The ideal implementation approach and technology selection should align with the company's goals, sales cycle length, and mix of demand generation strategies. For longer sales cycles such as B2B, it’s essential to collect data starting with the first touch and for the entire customer journey to the closed/won stage.
Generally, businesses will need to collect first-party tracking data and combine it with other first-party data to understand where their customers are coming from, how they interact with the brand, and what channels result in deals. Once this data is collected and normalized, businesses can use it to assign marketing credit for revenue generation to specific channels.
Marketers should consider a build vs. buy decision to analyze marketing activity beyond first and last touch tracking models. Multi-touch attribution platforms can handle this data-intensive endeavor, and businesses can make informed decisions about where to allocate their marketing resources to achieve the greatest return on investment (ROI).
What are some common challenges with revenue attribution?
Businesses can face several challenges with revenue attribution models that can impact the project's overall outcome. Some of the common challenges include:
Establishing reliable revenue attribution data
One of the initial and most common problems with revenue attribution is establishing reliable and accurate customer journey data. To accurately track marketing channels, businesses need to collect and combine data on how users interact across the customer journey from multiple sources.
This data can come from customer relationship management (CRM) systems, web tracking, marketing automation software, and other data sources. Once this data is collected, it needs to be cleansed, normalized, and combined into a single location before businesses can start to draw conclusions about which marketing activities turn into deals and revenue and where to optimize marketing efforts.
Revenue attribution platforms help businesses understand their customers and the marketing initiatives that influence them. This data can improve marketing strategies and shorten sales cycles.
Defining and tracking milestones and conversions in the customer journey
Another common challenge with revenue attribution is that businesses need to define and track conversions and milestones that lead to a conversion. A conversion could be a sale, a lead, or any other desired action that a user takes and gets tracked in a first-party reporting system.
In addition to conversions, B2B businesses should also define and track key milestones that roughly track to deal stages, such as the first touch, lead creation, opportunity creation, closed/won events, and other deal stages.
Milestones and conversions are synthetic events with data attributes inserted into the customer’s journey dataset. An Opportunity, a milestone event example, can be created in Salesforce and included in a customer’s journey, and marketing activities can be associated with milestone and conversion events. Businesses should track synthetic events, such as milestones and conversions, in their customer journey datasets to understand how marketing activities progress a deal.
Defining the credit in attribution models
Once conversions and milestones are defined, businesses need to decide how much credit to give each marketing touchpoint, milestone, and conversion in the customer's journey. Attribution modeling is the process of assigning credit or value to each marketing touchpoint.
There are many ways to assign or attribute credit, but the most common methods are linear, last touch, first touch, u-shaped, and position-based. Both rules-based and data-driven attribution models can provide insights into different aspects of the business.
How can a business overcome these challenges by establishing accurate revenue attribution?
While businesses can encounter challenges with establishing reliable revenue attribution, they can easily overcome them by taking steps in the right direction. Some of them include:
Leveraging revenue attribution software platforms
To overcome data collection challenges, combining data, data cleansing, and data normalization. B2B and B2C businesses will have slightly different requirements to prioritize in a revenue attribution platform.
Revenue attribution systems give you the ability to see all of your enhanced marketing data in a single place, along with the ability to analyze that data and help increase sales revenue. You might want to synchronize the enhanced marketing data with your data warehouse for further analysis based on your company's analytics capabilities.
Establishing a conversion tracking model
The marketing and sales teams should establish a revenue attribution model related to conversion and milestone tracking that aligns with your revenue attribution platform. Your attribution platform should make it possible to label attribution events such as marketing campaigns, online conversions, sales interactions, customer calls, conferences, and self-reported attribution.
Labeling key events
With the correct data for analysis and a set method for labeling key events, marketing attribution can help to align your marketing and sales departments by allowing you to combine data from both departments throughout the sales funnel, beginning with the first touch and through conversion.
What are some benefits of accurate revenue attribution?
The ability to accurately attribute revenue to marketing channels is essential for many reasons. Some of the significant benefits include:
Understanding the most-effective revenue attribution channels
First, it can help businesses understand which marketing channels, campaigns, keywords, targeting, and ads are most effective at generating deals and revenue. This knowledge can help companies to allocate their marketing budget more effectively.
These data insights help businesses improve their investment return. By understanding which marketing initiatives drive revenue and deals, companies can optimize their marketing to align more closely with revenue growth.
Making informed decisions
Second, it's also beneficial to establish shared responsibility and offer data-driven decisions to align revenue generation goals with sales and marketing teams rather than just sales.
This approach can help build a more effective and cohesive go-to-market motion. Attribution data can synchronize with go-to-market systems to enhance sales efficiency.
Identifying the best-rewarding marketing efforts and activities
Third, businesses should also consider sales velocity when considering revenue attribution models. Sales velocity measures how fast a company can sell its products or services.
With accurate attribution data to better understand which marketing activities have the highest sales velocity, marketers can leverage these insights to drive predictable revenue growth.
Identifying fraudulent activity
Finally, accurate revenue attribution allows businesses to identify fraudulent activity or discrepancies in their sales data. By identifying and correcting these issues, companies can improve their bottom line by ensuring that all their revenue is correctly attributed.
What steps can businesses take to improve revenue attribution?
Businesses can take a few easy steps to improve their revenue attribution process. These include:
Define the business goals and objectives
A revenue attribution strategy requires the right people, processes, and technology. As a first step, defining the business goals and objectives is essential to planning the people, process, and technology needed.
"What are you hoping to achieve with your marketing efforts?"
“What share of revenue are you expecting marketing to contribute?”
“How will better revenue attribution improve your business performance?”
Once you know the objectives, you can better align your attribution strategy to help you reach those goals.
Centralize Sales and Marketing Customer Journey Data
Accurate revenue attribution requires collecting high-quality customer interaction data across marketing channels, be it online channels like landing pages, blogs, or social media, or offline channels like telemarketing, print ads, and trade shows.
Collecting and centralizing data from the entire customer journey promotes transparency amongst teams and enables insight-led revenue-influencing decisions. This valuable dataset allows a better understanding of what tactics are working and which should be adjusted to meet company goals.
The data integration process begins with the unification of data from multiple sources to generate advanced insights. After customer journey and marketing data have been collected, enhanced, and normalized, go-to-market teams can leverage this data to make decisions and improve business performance.
Ensuring that your integration tool has data normalization capabilities is crucial, as different departments rely on various data sources and prioritize contrasting naming conventions for their KPIs.
Normalizing data combines different naming conventions from multiple data sources to create more coherent data fields and can be implemented manually or through automated means.
Ultimately, successfully centralizing sales and marketing customer journey data puts you in the best position to unlock additional revenue.
How do changes in privacy laws impact revenue attribution?
New privacy laws have significantly impacted accurate revenue attribution and shifted towards a more privacy-centric relationship with consumers. Reliable revenue attribution relies on data from multiple sources to track and attribute revenue accurately.
As a result of consumer and regulatory pressure, companies have adopted higher and more stringent standards for protecting and managing consumer data over the last two years. Between initiatives such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), many believe the United States will soon enact a GDPR-like regulation. Several state and data laws are already making their way through Congress.
At the start of 2020, Google announced it would remove third-party cookies by the end of 2023. This change will likely significantly impact marketers, as the absence of third-party cookies reduces ad platforms' ability to target users effectively. Removing third-party cookies will likely have far-reaching consequences for the entire online ecosystem.
With an evolving privacy environment, brands must rethink their data collection strategy. Marketers should shift their focus to collecting first-party data from their customers in a way that complies with privacy laws. This approach will allow them to make better data-informed marketing decisions and understand their customers' needs and interests.
Accurate revenue attribution requires businesses to collect data from their marketing and sales activities and the various channels that generate revenue throughout the customer journey. Companies must also establish a first-party, privacy-compliant data strategy for attributing revenue. With this framework, businesses can ensure that they more accurately measure and attribute revenue to their marketing efforts.
Don’t know where to start?
At Sona Labs, we specialize in revenue attribution and marketing data unification. We help companies collect first-party data, aggregate it in a unified warehouse, and streamline their data for analysis. With our synchronization capabilities, data warehouses, CRMs, and visualization software updates as often as you need. Schedule a call to learn how you can get more granular insights and a complete overview of your marketing performance with us.