Multi-channel and multi-screen browsing is the nature of the current digital economy. Consumers are likely to have engaged with your marketing initiatives on several channels and devices before they commit to a purchase.
Attribution models that contribute towards the dynamics between channels and devices allow analyzing the full journey to purchase or a call to action and attribute the right credit to each event, making marketing spend decisions for digital leaders, far more accurate and financially viable. Digital attribution is one of the core fundamentals for a successful digital marketing transformation.
Digital attribution is the set of events based on user actions. These events or set of actions contribute in some manner to the desired digital marketing results. Each of these events is assigned values according to its importance in marketing and its impact on consumers. Digital attribution specifies what combination of events involves users in the desired behavior, mostly referred to as conversions. Leveraging Digital Attribution and make data-driven decisions is foundational to digital transformation.
This article covers the basics of digital attribution from a marketing angle as a quick read for executives and digital transformation leaders.
The current application of attribution marketing has emerged from the transition of marketing from traditional to digital ways. The field is highly affected by large data collected through digital channels such as online surveys, social media data, conversion, emails etc.Its main purpose is to quantify and study the effects each advertising impression leaves on the purchase decision of the user. Subsequent to analyzing and studying what influences customers more, marketers optimize media for conversions and compare the importance of different media channels for marketing, such as E-mail, affiliate marketing, social media networks, display ads, and others.Analyzing the whole conversion path across the whole marketing mix eliminates the accuracy challenges of analyzing data from isolated marketing means. Usually, attribution statistics is utilized by marketers to map future ad promotions and campaigns by evaluating which media assignments (ads) were the most cost-efficient as shown by metrics like CPA (effective cost per action).
Models of attribution
Rapid growth and popularity of digital advertisement and online marketing have concluded in a large amount of user data for tracking, ROI and effectiveness of conversions. These new tendencies have affected the way marketers measure the effectiveness of marketing and advertising. The trends have also opened a new door to development of new marketing metrics that are CPI (cost per impression), CPC (Cost per click), CPA (cost per acquisition/action), and click-through conversion. For this reason, a number of attribution models have emerged with time since the explosion of data and devices have boosted up the creation of attribution technology. Digital attribution is very important because it assists advertisers in analyzing behaviors and responses of customers.
The types of attributions are:
Single source attribution
Also known as single touch attribution, allocates all credit to the single event or action, for instance, the last channel used to show the ad, last click or initial click. Single attribution model does not justify and contribute to all elements involved in creating results. This is the reason model isn’t considered verified and accurate especially by Google.
Fractional attribution
This attribution model comprises of consumer credit, U-curve models, and equal weights. Here equal weight based models assign the same amount of credit to all media channels and media mix, consumer credit involves studying guesswork or past experiences of customers to assign credits, and whole credit is allocated to first and final click in U-curve where idle actions are ignored across conversion path.
Algorithmic attribution
This model of attribution utilizes proprietary algorithms to allocate conversion among all touch points before conversions with the help of auto scripts to locate where credit is unpaid. Model is started from very first event level and assesses converting and non-converting paths crosswise all media channels. After that weights are combined to figure out hidden associations and correlations inside marketing.
These are the high-level attribution models that can make your marketing data more meaningful and useful in your digital transformation journey.
Which attribution model do you think that fits your business better? Let us know at the comment section!👇
And if you want to collaborate, please contact us dropping an email to info@haensel-ams.com or clicking here.
The original text was posted on March 24, 2019. You can read the full article here.
