Technology has always altered the retail shopping experience. There are many consumers who inhabit digital omni-channel age where people are using their laptops, smart phones and tablets to compare research and make purchase decisions. Many startups and companies are investing in paid media advertising in order to increase the signups, downloads, sales, customer acquisitions and leads. For every user it is important to figure out which attribution model is the right fit for their situation. On the basis of these questions, how many marketing channels do you use? How long is your marketing channel in execution? In this post, we will deliver into 11 attribution models and explain the benefits and drawbacks of each.
The first touch model offers 100 of the credit to the marketing effort driving a visitor to your website for the very first time. Since it gives you all the credit based on a single touchpoint, it will emphasize an individual part of the funnel. In such a situation, the first touch model lays emphasis on the top of the funnel marketing channels driving awareness.
The first touch model is also very much susceptible than many other single touch attribution models to the mistakes from technological limitations. The problem is if you are making use of the conversion tracking in business to business marketing, the duration between first touch and the conversion can be a bit longer than the usual 30 to 90 day expiration on the tracking cookie. So many times, this model is actually attributing credit to the first touch which is within the cookie expiration window and not the first touch.
In a nutshell, first touch model is a single touch model which is easy to implement, however is susceptible to channel technology limitations.
The lead conversion touch model can be confused with the ‘first touch’ model. That is mainly because in a marketing analytics system built around the lead generation like some marketing automation platform, the website session where lead was created is the first session where data is measured and tracked. In such systems, if the true first touch was something anonymous, it is something that didn’t exist.
The advantage of the lead conversion touch model is this that it helps in understanding what marketing channels drive lead conversions. This is vital, but it is also like a small part of the entire consumer journey. In a long B2B customer journey, there is enough to market than just the lead conversion and giving 100% of the entire credit to it. It simplifies the marketing role in the consumer journey.
The key appeal of the last touch model is this that it simplifies the model for attribution system to measure. While measuring and crediting the complete creation of sales opportunity on the basis of the last touch, the analytics technology has little time window for an error to take place. In long B2B buyer journeys, the time duration from last touch to the conversion is shorter than one say, the first touch or the lead touch. This plays a role because many tracking cookies have 30 or 90 day expiration. If conversion does not happen in any case within that window, the marketing channel data will not be in existence. By attributing 100% of the credit to the last touch, this expiration window becomes superfluous as no time lapses between the last touch as well as the conversion.
This is a little bit more useful than the last touch model, just because it eradicates the limitations of the direct data.
When it is about web and marketing analytics, direct data is a very big pain. Traffic attributed to the direct is specifically defined by the marketing analytics because any time a visitor enters the URL manually. But in reality, about every marketing analytics product consider any visitor who does not have a referral source directly. A common behavior getting classified as Direct is traffic from the untagged social ads, social posts or untagged emails. Instead of having its own filter; direct becomes the catch-all bucket for the traffic which hardly qualifies for any other filters.
In simple words, direct data is almost misleading. The key upside of the last Non-direct touch then is that you neglect the troubles of direct channel data.
This is again the catch-all bucket for channel particular attribution models. Search markets will wish to use the last adwords touch model. Social marketers who wish to show their value will use default last default Facebook touch model or Twitter’s default last Twitter touch model.
Remember that by touch it means the touch before whatever conversion you configured the analytics to measure out. This could be the opportunity conversion, lead conversion or whatever you set it up to be.
The benefit is this that these models commonly come standard with their channel – Facebook insights make use of the last Facebook touch model, Adwords Analytics uses a last Adwords touch model and lot more.
The negative is this that each of these models is tremendously on the basis of their own channel and overvalues their respective impression. If you make use of these attribution models differently, and later on aggregate them into the single report, you would double count or triple count the conversions. For instance: if a visitor click on the Facebook ad on Monday and then an Adwords ad next day and then converts, both last touch Facebook model and Adwords Last touch model will claim 100% of the conversion credit.
Linear is the most simple of the multi-touch attribution models. It allocates credit by applying credit to every single touch in the buyer journey. The affirmative is, it is a multi-touch model giving credit to the marketing channels throughout multiple stages of the funnel.
The negative side is, it does not take into consideration the potential for different impact of marketing touches. For instance, if a prospect spend two days at a single user conference and then goes home and then again visit your website 20 times through direct and then converts, your user conference is about to get 5% of the credit, even though it did most of the heavy lifting. On the other hand, it will get around 95% of the credit.
The time decay model is a multi-touch model that offers more credit to the touch points near to the conversions. It assumes that when it is close to the conversion, the more influence it leaves on the conversion.
The problem with this assumption is it will never give a good amount of credit to the top of the funnel marketing efforts as it will always be away from the conversion.
The U-shaped model or so called position-based model is one of the great multi-touch attribution models for marketing teams that pay attention on lead generation. It is a multi-touch model tracking every single touch point, instead of giving equal credit to the touch points like linear model. It lays emphasis on the importance of two major touch points: the anonymous first touch that got the visitor inside and the lead conversion touch. These are the two touches that get 40% credit each and the leftover touch points equally divide the remaining 20%.
The lower side to this model is it does not consider marketing efforts beyond any lead conversion. This is something that makes it an ideal model for the leads reports or for marketing the organizations that do not do marketing targeted to prospects beyond the lead stage.
The W-shaped model takes the concepts of U-Shaped model to the opportunity stage. For many organizations it is the end of the marketing funnel. Moreover to give an extra emphasis to the unknown first touch and the lead conversion touch, the W-shaped model also lays stress on the opportunity creation touch. These three key touchpoints get 30% credit each and 10% split among the leftover touchpoints.
While spreading the credit with such a distribution, the W-shaped model highlights three key funnel transitions that market the impacts in the customer journey.
If one takes it even a step further, the complete path model also account for marketing beyond the opportunity stage. Instead of two key stages represented in the U-shaped model or three key stages in the W-shaped model, the full-path model adds one more key stage which is customer close.
In this type of model, each touchpoint at the four key stages gets 22.5% of the credit and remaining 10% is divided equally among the left over touchpoints.
While it may appear like more major touchpoints is a better and more accurate representation of the consumer journey, this model is appropriate just for marketing organizations that do marketing to existing sales opportunities. Most of the organizations, until there is extreme alignment between the sales and marketing teams, wish to let their AEs control the messaging and conversation when they are trying to close the deals. So, before you try to adopt such type of attribution model, ensure that you sync with your sales team.
The last attribution model is to have the data scientist build up custom or algorithmic attribution model matching best to the customer journey particularly to your buying process. While analyzing your existing customer data, you can see which marketing channels have got an outsized impression or if there is any specific step in the customer journey which is important.
This is apparently the most difficult and time consuming model to build up, maintain and use but it may also offer you the most accurate representation of your marketing’s impact on the consumer journey.
Are you ready to learn more about your attribution models? Let us know in the comment section below.