What is attribution modeling?
March 25, 2020 •DJ Team
A term like marketing attribution modeling may sound a little scary. You may be wondering “Do you need an advanced data science degree to understand it?”
But like so many things in life, once you learn a little about it, you not only realize it's not that complicated. Data attribution models may become your most reliable allies in marketing.
Attribution modeling tools turn what would take endless hours of work into business insight when you need it most.
Attribution is the act of identifying the source or cause of something. For example, you might attribute the increase in customers to those Facebook ads you've been running.
Now, you can replicate what worked from your Facebook efforts to get even better results and reduce the waste on efforts that don't increase customers.
But attribution in digital marketing is rarely simple. The average person may have 20-30 touchpoints with your brand online before they become a customer even if you're a brick and mortar store. Each of these touchpoints did its part to influence the buying decision to varying degrees. So data attribution gives credit where credit is due.
The goal of using marketing attribution is to identify what’s working, and replicate it to optimize your marketing channel performance.
Types of attribution models
Attribution models are designed to deliver business insights. But no two businesses are alike. So you'll find that there are several types of data attribution models to choose from:
- First-touch attribution model: Attributes the sale solely to the first touchpoint made with your brand
- Last-touch attribution model: Attributes a sale to the last thing a person did before becoming a customer
- Linear attribution model: Gives equal weight to every touchpoint on the way to becoming a customer
- Time-decay model: A multi touch attribution model that gives less credit to touchpoints made earlier in the buyer journey.
- Algorithmic attribution model: Employs advanced analytics to determine which touchpoints most influenced the customer
- Markov chain attribution model: an algorithmic attribution model that employs predictive analytics to anticipate the actions of customers based upon data from previous actions of similar customers
If you can predict what customers might do, you know what you need to do to influence customers’ decisions.
Data-driven attribution is more sophisticated than simply first-touch, last-touch, or multi-touch attribution models - and it often delivers better results than said methods. According to Google, “Data-driven attribution gives credit for conversions based on how people search for your business and decide to become your customers. It uses data from your account to determine which ads, keywords, and campaigns have the greatest impact on your business goals. You can use data-driven attribution for website, store visit, and Google Analytics conversions from Search Network campaigns.”
Successful digital marketing uses multi touch attribution, multi channel attribution, and multi-device attribution. That's because chances are that the same customers interact with you on multiple channels and multiple devices.
But what kinds of channels might you need to attribute?
- Social media - Instagram, Facebook, Pinterest, Twitter, YouTube
- Forums - Reddit, Quora, Industry-specific forums
- Review sites - Yelp, Google My Business, WebRetailer
- Search engine results - Google, Bing, Yahoo
- Search and Display ads
- Social media ads
- Competitor sites
- Influencers - YouTube videos, Top 10 blog posts, paid mentions
- Your own website
Ideally, your models should include data from each of these pulled together into intuitive models, so at glance you can see where your highest ROI lies.
Many analytics tools have difficulty gaining true visibility into all these channels, and as such, it can be difficult to get the whole story from one place.
Click here to see how DemandJump combines all your cross-channel marketing data.
Attribution modeling tools
Only advanced marketing attribution tools can deliver linear, time delay, and algorithmic models because they must collect and analyze vast amounts of data from many channels to reach data-driven conclusions. Some of these tools include:
- AdWords Attribution Reports for attribution model Google ads: Find out which touchpoints took place before someone clicked an ad to become a lead or make a purchase
- Google Analytics: Google prides itself on Google's data driven attribution model. It gives website owners access to some really great tools to make more data driven decisions. Create visual sales funnels and other reports to track where your traffic comes from (Facebook, Google, etc.) and how visitors travel through your website to understand better which content should be part of your attribution.
- Facebook multi touch attribution: Works similarly to AdWords but for Facebook and Instagram ads
To varying degrees, these help you analyze and visualize touchpoints. Tools like these place a cookie on the browser of people who visit various channels. They can then follow the browser from site to site. But, of course, you'll only have access to the data that's relevant to you.
Many marketers consult a variety of different attribution models and will want to look at them side by side to understand how different channels fit into their marketing mix and funnel.
For more advanced algorithmic attribution and Markov model predictive analytics, you will need more sophisticated tools. We'd love to help you explore the power of DemandJump's attribution tools and show you the difference they can make in your marketing strategies. See the whole story your customers are trying to tell you when you get your free demo today.
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