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B2B marketing attribution: the mastery of investing our efforts and money.

Updated: May 4

The modern marketing landscape is constantly changing, and with budgets becoming increasingly tighter, we must make sure our investments are spent wisely.


Attribution is a practice that helps us understand which channels and campaigns are effective and which are not to make more informed decisions about where to allocate our efforts and money. And while making decisions, we should strive for an unbiased, data-driven approach rather than relying on gut instinct and personal experience. Without it, we risk throwing our resources in the dark and hoping something sticks.


This is why attribution must be a key part of every marketing leader's vocabulary; to make the most of our investments, we need to understand what drives conversions and revenue. Understanding attribution is the ultimate level of our marketing performance and analytics journey that I have been writing about before.


So, let's talk about why attribution is necessary and why it must be a priority for marketing leaders.


In this blog post, we will address the following areas:

  • What is marketing attribution?

  • What can attribution help with?

  • The difference between B2C and B2B attribution

  • Different approaches and attribution models- rule and data-based models.

  • Data as the necessary prerequisite

  • The importance of touchpoint and the buyer's journey

  • The complexity of the B2B buyer journey

  • How to model the B2B journey?

  • What should we attribute f0r (revenue, pipeline, opportunities, funnel conversion)?


Marketing attribution is a practice that includes crediting touchpoints and analyzing campaign performance.


To me, attribution is a practice consisting of several areas, including

  • Understanding the importance and contribution of marketing channels. This is a critical step before assigning credit.

  • Evaluating marketing campaigns and activities according to different attribution models. By understanding what drives conversions (leads, opportunities, or even which ones get revenue credits), we can make more informed decisions about where to invest our efforts and money.

  • Reporting and analytics.

A more systematic approach to marketing attribution should result in better marketing spend


Marketing attribution is one of the essential tools and practices for marketers. It supports our efforts to optimize marketing spending and allocate resources more effectively. It also helps understand the customer journey and identify opportunities for improvement.

It helps marketers understand which marketing activities are most effective in driving conversions and revenue and how different channels and marketing campaigns work together to drive business results.


Regardless of how we tackle attribution (emerging attribution technologies, B2B attribution platforms, Excel, Marketing CRM, Google Analytics, and Data Studio), when doing attribution right, we should expect the following benefits:

  • Understand the importance and impact of a particular marketing channel/touchpoint within the journey

  • Understand which campaigns create the strongest awareness

  • Understand what mix of channels drives the best conversions-leads

  • Understand which conversion points have the most substantial ROI

  • Which channels are the overall best contributors

The attribution journey usually starts with assigning credit to various touchpoints and channels.


An essential part of marketing attribution is assigning credit for marketing outcomes to the various touchpoints and channels that contributed to those outcomes.

There are several different approaches to assigning credit, including last-click attribution, which gives credit to the last touchpoint before a conversion; first-click attribution, which gives credit to the first touchpoint; and multi-touch attribution, which assigns credit to multiple touchpoints based on a predetermined set of rules.


Attribution models include predefined rule bases and data-based models.


The first and multi-touch models are the so-called rule-based models. Rule-based attribution is a method that assigns credit to different touchpoints and channels based on predetermined rules. This can involve giving equal credit to all touchpoints, giving more credit to certain touchpoints (such as the last touchpoint before a conversion), or using other rules to distribute credit. Rule-based attribution is usually based on our assumptions or heuristics rather than actual data.


On the other hand, data-based attribution is a method that uses data and analysis to assign credit to different touchpoints and channels. This can involve analyzing the user journey, looking at how different touchpoints and channels contribute to conversions, and using statistical models to assign credit based on the data. Because it is based on data, the promise of data-based attribution is to be more accurate and more tuned to a particular B2B buyer's journey.


This does not mean, however., that rule-based attribution does not have its place, as you will see below.


B2B and B2C marketers often select different attribution models.


Attribution can be applied to B2B and B2C, but there are differences in how it is used and the most effective approaches. While B2C marketers often go with a single-touch attribution model, B2B marketers usually use a multi-touch model.


In B2B marketing, the customer journey may be longer and more complex, with multiple decision-makers and touchpoints involved. As a result, multi-touch attribution may be more useful in B2B marketing, as it allows marketers to assign credit to multiple touchpoints and channels that contribute to a conversion.


In B2C marketing, the customer journey may be shorter and more straightforward with a single decision-maker. In this case, last-click or first-click attribution may be all that is needed as they focus on the last or first touchpoint before a conversion.


Overall, the most effective approach to attribution will depend on a business's specific goals, audience, marketing mix, and the data and tools available to measure and analyze marketing performance.


The key to proper B2B marketing attribution is data.


An essential piece of the attribution exercises is data, so data collection is a necessary first step. If you are interested in a complete metrics journey, you are welcome to read the "B2B marketing performance, Part II- from zero to a B2B marketing metrics hero.""business'sbuyer'sbuyer'slet'sleader's article.


When talking about data needed for attribution, in particular, B2B Companies can use the following techniques to ensure the data:

  • UTM. To have an unbiased view of how customers interact with your business, you must use unique links for every channel, campaign, and content.

  • Cookies and scripts. They are necessary to track the journey of prospects across all digital assets.

  • Traffic forensics. Using tools that allow you to understand which Companies visit your web is important in a B2B setup with multiple buyers, even without conversion to named leads.

  • Lead Conversion. Landing pages and marketing CRM are critical to turning anonymous visitors into named prospects.

  • Opportunity conversion. For pipeline and revenue-based attribution, it is crucial to integrate the marketing CRM and tools with Sales CRM and other tools used by sales teams.

  • Offline events. Gathering and importing data from excel or other formats into Marketing CRM is crucial.

Attribution is heavily related to marketing technology


Disclaimer: I am not using any specific marketing attribution technology, but I have talked to several companies and got the demo of solutions such as DreamData, and Windsor AI.


I encourage everyone to get a demo of these and similar tools and evaluate whether they can provide additional value to the tools and practice currently in place. The reason why we are not yet using these tools (we do plan, however):

  • The volume of our ad spending is not on the level

  • The volume of opportunities generated is at the moment at the level when we can have a good overview of all aspects related to attribution by using existing tools integrated into each other

  • we are using the following tech stack for attribution: Snitcher, HubSpot, Google Analytics

  • we are also importing offline data from several "sources" into HubSpot to minimize the dark funnel

Digital B2B companies like SaaS are well-equipped to leverage attribution.


Marketing organizations that work predominantly with digital data, including B2C and Saas B2B offerings, are well equipped to dive deep and well into attribution. Digital businesses already have access to a wealth of data that can be used to measure and attribute marketing efforts accurately.


The biggest challenge for B2B organizations regarding attribution is the lack of data. Many B2B Companies rely heavily on offline channels such as industry events, and this organization must combine online and offline touchpoints and data to get an unbiased view.


Such an organization must also ensure that such data includes not only marketing data but also data such as Sales CRM data.


The power of attribution is in finding your perls


Let us assume we are running several different Google Ads marketing campaigns (could be either B2C or simple B2B).


How would we use attribution here to evaluate the effectiveness of our spending?

For example, if we are interested to understand which campaign generates the most awareness, we would assign all the credit to the first touch and evaluate and compare campaigns using the first touch model. If we look at image 1- campaign 4 performs the best in this regard.


Similarly, we can use the last touch model to understand what generates the most conversions or leads i.e. closes more leads or provides the strongest funnel. If we look at image 1- campaign 1 performs the best in this regard.

And last and most importantly, we can compare each campaign's ROAS- return on marketing spending.

Based on this, we can better adjust our spending. What can we learn from comparing several campaigns based on different models?

  • Campaign 4 attracts the most new visitors but has the worst return

  • Campaign 2 barely makes any sense as it performs badly with regard to leads and closing deals and should probably be shut down. If there would not be attribution - as it has the second best ROAS, it is a Perl we need to invest into.

  • Campaign 3 has the best ROAS, but it is the one that has been optimized already.



Image 1 - Campaign and model comparison

Key to B2B marketing attribution is understanding the buyer's journey.

A buyer's journey is the journey a prospect undertakes before becoming a client. Especially in B2B, the journey is quite buyer-driven, which means that there are several defined activities (sometimes quite formal) the buyer's team must accomplish during the process. In comparison to B2C, there is little the vendor can do to change the journey i.e. drive the journey by stimulating the need and closing the deal.

A B2C journey can be a linear journey consisting of a series of standard digital marketing touchpoints. For this kind of journey, the marketing effort can be "as simple" as forming a lookalike audience from existing clients, putting out an ad, taking orders, and shipping out your physical or digital product.

The complexity of the buying journey and activities within the B2B space makes attributing (assigning proper credit across the journey) and measuring marketing effectiveness a bit more challenging.

Just my own example when I purchased a subscription for our marketing software:

  • Read a blog for specific software on the vendors' partner page

  • I visited the website and read several blogs

  • I asked my team to co-research alternatives, talked to several local partners

  • I asked for a demo (several months later) and had several discussions with the vendor

  • Presented the case for CRM and automation and got it into the budget for the next fiscal year.

  • Once the time came, several discussions with the vendor again before closing the deal

This is not the most complex form of a B2B purchase, but even this one went through a specific process and took weeks rather than days. The more complex and more expensive the purchase is going to be, the more people will be involved, and the longer and more complex the buying process is going to be.

Modeling the B2B journey: a bit more multidimensional, group buying, offline influences, different journeys, and long times to value

A more complex journey means more marketing touchpoints between your brand and a potential customer and more interactions across the entire customer journey. This includes digital and offline, direct and indirect (your partners), and dark channels.

According to research from Marketo, we are talking tens of engagements and hundreds of touches- "While the exact buyer journey is unique to every company, data shows that, on average, B2B buyers engage 36 times before deciding to make a purchase, with some journeys."

In my experience, it can well be 100 in case of dealing with complex enterprise deals. I love this Gartner image, as it shows the whole complexity of the buying cycle and indicates the many touchpoints a potential client has with the brand.

A more complex journey also means that it is going to be more difficult to figure out the impact of these touchpoints, and the more we should start considering attribution tools, including B2B marketing attribution software and revenue attribution platforms.


B2B touchpoint complexity includes indirect and offline channels and dark funnel

In the hybrid B2B world, your customer journey may include the following touchpoints and channels:

  • Google, LinkedIn, display and banner ads

  • Live events, including panel discussions and prospect conversations

  • Blog posts and other types of content

  • Webinars

  • Analyst briefings

  • Comparison portals

  • e-mail

  • Direct LinkedIn outreach

  • Referrals and word of mouth


What I also find it useful when discussing and evaluating touchpoints is the different roles they play within the marketing mix, including:

  • Awareness generation: not all touchpoints contribute to awareness. Webinars and e-mail, for example, are rarely first touches with your prospect.

  • Intent: not all touchpoints show clear intent. Google search and demo requests are something opposite to a display ad.

  • Dark funnel: in B2B, there are lots of dark funnel (touchpoints we have no data from) that we need to consider to get a complete picture. Analysts are critical for enterprise B2B, but there is no way to get some data about it. What one can do is interview the client and integrate it as offline data.


A simple approach to model your B2B journey

The B2B complexity should not force us to give up. Just the opposite. The more complex the client journey, the less our intuition and calculation capabilities will be of help. You should try to design a non-linear workflow of touchpoints and a model that comes as close to reality as possible. It can look something like Image 2 below. Image 2 is an example of a simple B2B journey across different touchpoints (and buyer roles) based on an actual opportunity. While green arrows represent entry points and paths, the numbers represent the sequence of events.


Image 2 - Customer journey across touchpoints

You can do something similar as a test. Just outline and document your prospect journeys and then ask your sales and marketing teams to run a couple of recently won deals or opportunities through the journey to better understand the importance of different touchpoints. This is an essential exercise that will let your teams understand the role of different touchpoints and make communication about the journey easier.


Switch to tech once your start running volumes of data points


As you see, the journey map and the model can be made manually. However, if you run tens of campaigns that are mostly digital, then it makes sense to consider using technologies. The tech will not only make your life easier but also make you smarter; several technology vendors offer tech to make your "data-based attribution" models and custom journeys.


In general, good tech would do this by:

  • It would integrate and automate data collection across all your marketing channels, including your social advertising, Marketing, and Sales CRM, website user behavior, and more. Different vendors provide different out-of-the-box integrations; what is missing can usually be integrated via Zappier

  • Based on this data, it would design your attribution models. With AI methods, many tools can figure out your specific connections and patterns and create custom models. Almost all tools provide standard models such as 1st, last touch, and linear.

  • Export data to BI or use proprietary tools to make sense of the data. Dashboards and reports that get you insights into conversions, ROI, and times spent in different phases

The Complexity of B2B marketing attribution: a time between touches can be so long that we do not have data.


B2B sales processes can often be lengthy, meaning there's plenty of time between different stages, such as when someone contacts you and when they buy from you.


As outlined in the CEO metrics blog, one of the important metrics is "time to value," which can, in B2B, be quite long. Once we have the journey modeled and technology in place, we can measure different journey times.


Image 3 is an example of a dashboard you can implement to get a grip on this important metric. This can be done with the proper use of marketing CRM, however, dedicated tools to offer more and better actionable insights.


Image 3 - Customer journey stages view of the CMO dashboard

The Complexity of B2B marketing attribution: it is not about a single journey, it is about a buying team


The other thing increasing the attribution complexity is that there are many stakeholders involved in each stage of the buying process. A B2B customer is usually an organization rather than a single person. It involves multiple people who may be working together during the buying process. Indeed, where the individual who starts the process is very unlikely to be the one making the decision or signing the deal.


This is why there are different rows with different user roles in Image 2.


I wrote about the difference between B2B and B2C to some extent. If not before, the difference becomes apparent when discussing this part of the attribution. It is much easier to define the attribution model for B2C than B2B.


This makes it extremely difficult to know whether your efforts led directly to a sale. In fact, according to Gartner, only about 20% of companies manage to track attribution. There are no simple answers to marketing attribution.


We should tune campaigns and channels for conversion, sales funnel, and revenue.


We always measure the performance of channels/campaigns towards a specific goal.


Ideally, it is the generated business (i.e. sales revenue). However, it can be other goals,Revenue such as the sales pipeline and the number of "serious" conversions (Marketing and Sales Qualified leads). As mentioned in our metrics discussions, it is ok to start the metrics journey with some simple metrics and introduce more business-oriented ones as you go.


Whatever the case, it is essential to define the proper goals and start thinking about the right metrics and data collection methods. However, attribution is a practice for more mature metrics. Thus, I would advise something like table 4.


Metric

Attribution

Traffic

No

CPC

No

Conversions

Conversion, at minimum, should be an articulated intent, someone leaving contact details, or even better, registering a demo (this is usually how I would advise defining an MQL)

Sales pipeline

Attribute for spend/generated value of proposals.

Revenue/ROAS

Attribute for generated revenue.


Table 4 - attribution goals

In conclusion, B2B marketing attribution is a complex process that requires careful consideration of all the touchpoints between a company and its potential buyers, the selection of the proper model, and the decision about technologies. It is important to define the goals of the attribution model and to select the right metrics and data collection methods to optimize for cost per relevant conversions, spend/generated sales pipeline, and spend/generated revenue. With proper planning and execution, B2B marketers can master the art of investing their efforts and money in the right areas.



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