Marketing Attribution
Marketing attribution identifies the marketing channels and campaigns that drive sales, leads, and conversions from different touchpoints. For example, it can identify the customer journey from a TV ad, website visit, or social media post to an email click and sales.
There are many different models, such as first touch, last touch, linear, position-based, data-driven attribution, and others shown above.
The promise is to solve every marketer’s most crucial question: What’s working and not? It is the right question but the wrong answer. Here are 7 reasons marketing attribution models don’t work.
1. The customer journey is messy.
The customer journey is generally depicted as a migration through neatly compartmentalized Awareness > Consideration > Action > Loyalty phases. Attribution models place marketing activities on each one. However, the customer journey is neither that clean nor predictable. For example, we may see a TV commercial that creates awareness for further consideration through organic search. Then, when we search online, we read alarming negative reviews. We end the journey. Moreover, the attribution model doesn’t tell us why. It would likely indicate organic search doesn’t work. The channel works, but unfortunately, the product or service doesn’t.
2. Marketing attribution models favor channels that play by its rules.
However weighted, all marketing attribution models place a percentage value on steps along the purchase cycle. Therefore, based on the model, the touchpoints with the highest value will favor that media channel. Let’s look at a few models and see.
3. First-touch attribution models favor awareness channels.
In this model, the touchpoint that first makes you aware of the product receives the highest value. It could be a TV commercial, an organic search query, or a Facebook ad. Regardless, these tactics have an advantage and are generally awareness-oriented. While it could be an offer, incentive, or recommendation is essential for the sale. According to this model, it will receive less value.
4. Last-touch attribution favors the final touchpoint.
Here, the same promotion tactics and conversion ads are now favored over the tactics that may have brought the product to your attention in the first place. This model is set up like most B2B marketing, where a salesperson is the last point of contact and closes the deal. Therefore, he or she feels they made all the difference. And they did, however, not without significant assistance along the way.
5. Data-driven attribution doesn’t show the complete picture
In a data-driven attribution model, the percentage allocation to each touchpoint is dynamically assigned based on the individual user’s data. Although the most sophisticated, it measures only what it’s given. It builds accuracy more slowly. Plans may need to be modified more frequently. For example, this attribution model might assign 15% credit to the social ad, 30% to the organic search, 25% to the email, and 30% to the advertisement before the final purchase. However, it does not measure any influences not online or explain the impact of online content along the way.
6. Marketing attribution models overvalue ads and undervalue the voice of customers.
Whatever model is used, they all come with a bias. Overall, ad spending is required because that is what is essentially measured. Then, emphasis is placed on marketing tactics that receive priority based on the model. They don’t account for the fact that significant influence might come from factors that are not ad-related. Moreover, they overlook perhaps the most effective marketing channel, the customers’ voice.
7. Rules don’t predict business success. Goals, KPIs, and actions do.
Marketing attribution may be the right question to ask. But we all know following a prescribed set of rules is not the path to success. It is more likely achieved by setting clear goals based on quantified improvements within a specific timeframe and a handful of Key Performance Indicators (KPIs). Here’s a way to help by regularly looking at the learning and insights they reveal.
Do these steps help explain marketing attribution and what you should do?
