Marketing attribution has grown in complexity over the last decade-plus, thanks in part to an unprecedented proliferation of new advertising platforms and new content types. Getting attribution right is not just an onerous endeavor, but the no. 1 pain point facing today’s marketers –– more challenging than getting organizational buy-in, budget, audience insights, or proper technology.
If you’re new to marketing measurement, that may sound like bad news. This is going to be tough. But if you’re a veteran, you may be encouraged to hear of that sweeping struggle. You’re not alone.
Whether you’re a novice or a master of marketing attribution, there are a handful of common pitfalls marketers fall into when seeking to prove the efficacy of their marketing efforts. Falling into any one of these can lead to bad data, which can inform bad decisions that ultimately spoil the very efforts you’re trying to measure.
Here are a handful of attribution pitfalls you want to avoid when measuring your marketing:
Poor or undefined UTM usage
Urchin tracking modules. That’s what UTM stands for. We talk about UTMs so often in marketing that we are not only prone to forget what the acronym even stands for… we’re also susceptible to improper usage.
Here’s a quick-hit list of other UTM best practices:
- Be consistent with your naming conventions
- Be specific with your naming conventions
- Be clear with your naming conventions
- Use a question mark (?) to begin the UTM parameter
- Use an ampersand (&) to separate queries in a URL string
- Use Google Analytics-recognized mediums
- Use the mandatory utm_source parameter
- Use lowercase tags
- Use plus (+) signs to create spaces (however, ‘+’, ‘-’, and ‘_’ are all acceptable)
- Remember parameter hierarchy: source, medium, campaign, term, content
- Don’t use UTMs for internal linking
The easiest way to muddle your attribution is to be inconsistent or incorrect with your UTM usage. Using UTMs for internal linking, for example, will break a session into a new visit and strip original source/medium data for that user. And using an unrecognized medium will create a bunch of clean up work down the road and pollute the picture your attribution is meant to paint.
Forgetting about referral exclusions
Think of your website like a department store, with each page and section representing a different department. If you’re in Google Analytics and you see your own site as a referring source for a visit to a page, you’ve forgotten to exclude your own site as a referral. This is sort of like visiting the shoe department at Nordstrom and, when asked to fill out a survey after your purchase, writing “Nordstrom” as your answer to the “How’d you hear about us?” question. That’s not going to be too helpful to the store’s marketers. And neither is your own domain as a referring source.
But how does this happen?
Generally, visits that mark your own site as a referring source occur as a result of long, idle sessions, which Google Analytics considers expired by default. When a user revisits a page on which their session has expired, a new session begins. The referring source for that session? Your site, if you have not excluded it.
And that’s a big deal. Take inventory of the open tabs on your screen as you read this. How many have been open for longer than 30 minutes? Shamefully, I have over 20 on my computer. If I ever get back to them, I’m probably messing up some marketer’s attribution data when I revisit the page –– double-counting my session, giving credit to both the Google search or email campaign which actually drove me there, as well as the site itself, which saw me go idle before revisiting the page.
Double-counting conversions without identity resolution
As we explain in our post, “What is multi-touch attribution?” identity resolution is “the narrative glue for multi-touch attribution.”
Identity resolution is the process of assigning, capturing, and joining datasets based on a unique identifier. Without an identity resolution system, marketers have no way to associate a website visit (touchpoint one) made by Sally on Monday with a subsequent inbound phone call (touchpoint two) by Sally on Friday.
Most attribution marketers use an existing analytics or other marketing tool’s unique identifier for tying together multiple touchpoints from the same person. For example, Google Analytics assigns a Client-ID to each website visitor. This GA Client-ID is then retrieved and captured by other applications on a website that capture leads.
Without identity resolution in place, marketers are susceptible to double-counting their conversions. It’s critical to unify all interactions an individual has with a business, online and offline.
Still gleaning from last-touch models
Our marketing world is more omnichannel than ever before. People bounce from channel to channel, device to device freely.
A last-touch attribution model ignores this reality. It doesn’t give marketers a view how multiple touchpoints worked together to generate a purchase or site conversion.
There are better, more objective models available out there that marketers can start gleaning from today.
Here’s an overview of attribution models >
In CallRail, you can see every touchpoint in the buyer’s journey in the following attribution models:
First Touch Model: 100% credit to the first touchpoint a customer engaged with.
Lead Creation Model: 100% credit to the last touchpoint before a customer calls/texts one of your tracking numbers or submits a form and becomes known to your company as a raw lead.
50/50 Model: Split credit evenly between the First Touch milestone and the Lead Creation milestone, 50% on each.
Qualified Model: 100% credit to the last touchpoint before a customer is scored as a qualified lead. Leads can be scored manually or through CallScore.
W-Shaped Model: Credit is split evenly between the First Touch milestone, Lead Creation milestone, and the Qualified milestone. Each of these touchpoints receives one-third attribution credit in this model.
Ignoring critical conversion points
We polled 300 marketers about the challenges they’re facing today. While 96 percent of them agreed that “Attribution is critical to informing and optimizing my marketing decisions,” a much smaller number had attribution modeling in place to accommodate all conversion points.
As an example, only 57 percent were attributing specific phone calls to their marketing efforts via a call tracking tool like CallRail.
Without a full view of all possible conversion points, online and offline, marketers could be missing out on key insights about their marketing performance.
The post 5 Marketing attribution pitfalls marketers must avoid appeared first on CallRail.