Attribution Models: Achieving Alignment on your Marketing Spend
Today’s marketers have no lack of channels (paid search, display, social media, blog posts, videos, emails, events, direct mail) to execute and measure across what can be a long, multi-touch customer journey. Meanwhile, budgets and staffing have not scaled at the same pace, making it increasingly important to evaluate which channels have the most impact so small teams can focus their resources.
I’ve worked with nonprofits, universities and publishers to adopt attribution models following this 3 step approach:
Step 1: Making the case for attribution
Multi-channel attribution is the practice of evaluating the various touchpoints a consumer encounters on their “path to purchase” and determining which of these channels and messages have the greatest impact. Attribution models give marketers insights into how their budget and resources are best spent by highlighting which channels generate engagements that matter.
To simplify, an attribution model helps data-driven marketers:
Optimize marketing spend, aligning budget with high-performing activities/channels
Align resources to impact, making a case to double-down on high performing activities and/or scale back on with lower impact
While marketers want to be data-driven, they don’t always have access to the data they need to build robust attribution models. In more siloed organizations, this requires making the case for attribution and working across teams in IT/web development, sales, admissions, and/or marketing who hold the keys to data from platforms like a CRM, web analytics, social media management, etc.
Step 2: Selecting an attribution model
There are a number of attribution models, any of which are an improvement over not measuring at all. That being said, selecting the right attribution model is a function of three considerations:
Data: At a minimum, simple attribution models are dependent on web analytics data from platforms like Google Analytics. If CRM data can be layered on, indicating where the customer is on their journey from lead to conversion, more robust attribution model options can be considered.
Customer journey: For high involvement purchases such as pursuing an advanced degree or a new career path, the customer journey may last months or years with multiple touch points along the way. These more complicated journeys benefit from a multi-touch attribution model. For low involvement purchases with fewer touch points (buying a book, signing up for a conference), simpler and more straightforward attribution models are often appropriate.
Scope and scale: Marketing teams with significant budgets, staffing, and more complex multi-channel strategies will want to adopt a robust multi-touch attribution model if possible. For teams with fewer resources focused on a few channels, a simpler, single-source attribution model (see first or last-touch) is often appropriate.
Depending on your organization’s scope and scale, customer journey, and access to data, you’ll want to adopt either a single-touch or multi-touch attribution model.
Option 1: Single-touch Attribution
✔ Low-involvement purchases with fewer touch points on the journey
✔ Smaller teams, fewer channels
✔ Web analytics data
Two common options for single-touch attribution are:
First-touch attribution: The source or channel that a customer first interacted with (ie, a blog post, paid search ad, etc.) gets all the “credit”
Last-Touch Attribution: The source or channel that a customer last interacted with right before purchase (ie, email, event, etc.) gets all the “credit”
Option 2: Multi-touch Attribution
✔ High-involvement purchases with multiple touch points on the journey
✔ Larger teams managing more channels
✔ Web analytics data + CRM data
Multi-touch attribution varies based on approaches to weighting each channel’s role. Here are the most common options:
“OIC” attribution: This model organizes each touch point into 3 actions to elevate the role each channel plays along the journey:
Originator – How they found you
Influencer – What got them to buy
Converter – Where they bought
Linear attribution: This model gives equal weight to all touchpoints a customer interacted with along the journey.
Weighted attribution: This model gives extra credit to those touchpoints that did the most work. This can be difficult to assess. If a customer read several blog posts or clicked several ads, these channels will get more credit than others but without heuristic analysis, this might not reflect the reality of the customer’s experience.
Time-decay attribution: This model gives the most credit to the more recent interactions and the least credit to the earliest touchpoints. With longer customer journeys, the earliest interactions will often generate significantly less credit so it’s important to recognize the implications before adopting this model.
Step 3: Implementing and Acting on Insights
Armed with data from internal CRM, Google Analytics, Hubspot, or other platforms, I work with teams to define the weighting for each of the channels and its influence on conversion. Here’s an example of “OIC attribution” (see below) I developed for a university partner which led to several important insights and actions:
Expand search-optimized content (blog content) given its strong performance as an originator
Optimize email and SMS nurturing sequences as they had the potential to be strong influencers and converters
Scale back on SEM spend except for retargeting (conversion)
Expand targeting accepted students on social media given its potential as an influencer and converter
Contact me if you're interested in applying attribution best practices to your company or organization.