While some marketers may think they have little need for upgrading their attribution models because their KPIs may not be always acquisition , there’s still plenty of reason why an upgrade should be considered: increased accuracy in reporting results; more accurate predictions based on past data; less waste of time, money and resources; better visibility into the customer journey across multiple channels in today’s more complex media environment.
Namely, the days when a marketer could accurately track a visitor with a cookie are over. Consumers today bounce around from channel to channel, device to device all day long, making it next to impossible for them to be followed via cookies on any single browser or device, as well as for brands not only to know which ads drive sales but also whether those sales were generated by an impression seen weeks prior or just that morning by a banner ad. This is where Multi-touch attribution models come in.
How are current Attribution models not feasible in a post-cookie world?
The spaghetti journeys and complex behavior makes complex multi-touch attribution models the sought after analytics option for marketers. In the ever-changing world of marketing attribution models, cookie matching is no longer enough to track consumers and their behaviors.
What is cookie matching?
It’s a process of matching user identity across digital devices and platforms to measure the return on investment for digital marketing campaigns. Before cookies became part of the standard web, online advertising was all about impressions – no one really knew if those impressions resulted in sales. Cookies changed that with the ability to store information about a consumer so that it can be used over time without making them re-enter their info each and every time they visit your site.
So what is multi touch attribution? Multi-touch attribution models will take past behavior into account when determining future interactions – how many times someone saw an ad before actually clicking through as well as how long they were exposed to multiple ads as part of your campaign. These models use predictive analytics based on past purchases.
While this method was once thought that a match between two cookies meant the same consumer, modern technology has now made this assumption obsolete. With the advent of mobile devices and changing ad-placement patterns, marketers must now adapt to new models which take into account how real consumers behave.
With a post-cookie world in mind, it is important for marketers to adopt new attribution models that can give them insights on where their consumers are coming from when they purchase products. Cookie matching has traditionally been used by marketers as an attribution model, but this method still leaves out a considerable amount of data about consumer activity and does not allow attribution between channels or devices. Adopting complex multi-touch attribution models instead can help solve these issues.
Multi-Touch Attribution Models access to data across multiple touchpoints
Data across all touchpoints explains the multitude of behaviors that take place before someone buys any product. No matter which method you choose, all multi-touch attribution models are meant to help marketers determine the impact of their marketing investments at granular levels by assigning credit for a KPI event (e.g., conversion, lead, etc.) to one or more touchpoints.
The most common forms of tracking are:
Click-based attribution models where each ad impression or ad click is attributed to a brand touchpoint. The challenge with this model is that today’s consumers can interact with brands in many different ways such as browsing the site, clicking on an email link, etc., but the cookie won’t last long enough to track users across these multiple channels. In fact, a recent study found that only 23% of people that visit your site will be tagged by a cookie.
For example: You have two ads: one for insurance and another for finance. A person visits your finance page then clicks through to see details of the car insurance product via email. This occurs after they read an article about car insurance on a news publication that convinces your prospect to act upon the same.
The same consumer then searches for a specific model of car they are interested in. They land on your site and discover that you have the car they want at a reduced price.
But, with browser cookies, you cannot track the journey of the visitor with such accuracy nor with any data that can support the details. That’s because the browser restrictions that support data privacy and user preferences kill cookies which can no longer provide relevant information about the user or visitor. You will not even know the fundamental difference whether the person visiting is a new user or an existing customer.
Server-side tagging used to design and fully implement multi touch attribution models.
In order to implement a multi-touch attribution model, marketers first need to tag all the touchpoints where people interact with a brand. These tags are added either server-side or client side. In general, using server-side tagging has greater accuracy since it does not rely on any cookies and gives accurate results across devices and browsers. With server-side tagging, a unique identifier is created when an ad impression occurs which can then be used to attribute every subsequent interaction that person has with that company’s ad spend. Such identifiers can take many forms such as user id, IP address, screen resolution, browser type or mobile carrier IDs.
Setting aside the technological challenges: The cookie model is out of date.
The entire digital marketing landscape relies on cookies and their ability to follow a user’s behavior across multiple sites and platforms, but this is coming to an end. Cookies are too restrictive in terms of privacy and preference. Even though tracking cookies store information for 24 months, this serves as no benefit if you cannot connect it to any relevant data or use that data to generate actionable insights. For example, consider a customer who visits your site, looks up a new car online … they have an existing coupon for $500 off the price of the car they want… but then they leave without buying anything.
Server side tags also allow for better privacy protection as they do not leak information out onto the internet like cookies do. For example, if you use server-side tags on your site, then users can’t track other sites that you visit or see what sites link back to yours since all of the information is stored only on your own server instead of their browsers. With cookies, there is no such thing as “private.”
Continue with the multi-touch attribution model in the post-cookie world.
Cookies can’t be used for multi touch attribution models, but server side tags have no such limitation and allow you to see where each customer came from. If you store all of this data only on your own servers instead of in browsers then users won’t even know that they’re being tracked since there is nothing stored about them anywhere else – it’s completely private! Use our server-side tag manager (like Google Tag Manager) so that you can track visitors with ease without sacrificing their privacy or security. It also works perfectly with any marketing platform as well as with other analytics tools.