Use Case

​Marketing attribution

Get the complete picture of how your marketing channels are performing

Marketers estimate that they waste an average of 26% of their budgets on ineffective channels and strategies, according to a recent study by Rakuten.

Effective marketing attribution allows you to refine your marketing spend by identifying which channels are converting prospects most effectively.

What is marketing attribution?

Attribution is a process or framework that is used to assign, or attribute, credit to different channels or touchpoints in a customer’s journey, conversion, or purchase decision. These can be micro or macro conversions, depending on the complexity of your attribution model.

Ultimately, every channel plays some role in the decision, but depending on the attribution model you use, some channels get more or less credit than others.

Effective marketing attribution provides insight into the impact of your activity and the platform – meaning you can optimize your advertising and channel effectiveness.

Here are some of the kinds of questions you might be trying to answer within your business:

a) What is the most effective channel for your marketing investment in terms of ROI?

b) What campaigns are driving ROI? How does online spend influence offline activity or conversion?

c) Are marketing efforts having the maximum effect or is there room for optimization?

d) Where should optimization happen?

e) What kind of optimization should be undertaken?

f) How do our channels perform when taking into account cancellations or returns?

Types of marketing attribution

There are many lenses to observe the way prospects move through your marketing funnel and these depend on your strategic objectives. For a deeper dive, see the link at the end of this section.

  1. Single-touch attribution modeling

First-touch Last-touch Last Non-Direct Touch

  1. Multi-touch attribution modeling/Rule-based attribution

Linear Time Decay U-Shaped W-shaped Custom Rule Based

3. Algorithmic attribution

Logistic Regression

Shapley

Markov Chain

Survival Analysis

Custom Algorithmic Attribution

Learn more about the different types of marketing attribution and the relative benefits of each type.

The need for advanced analytics for marketing attribution

Marketers are facing uncertain market conditions, as their budgets and activity are under increased scrutiny. In Deloitte’s quarterly Chief Financial Officer (CFO) study, over half of CFO’s are tilting towards defensive strategies, with cost reduction and cash control listed as their top priorities. Marketers’ budgets are often the first casualty of cost reduction as sales start to drop.

But it is not all doom and gloom. Accurately measuring marketing attribution unlocks a whole host of new opportunities for marketing teams. According to Zoom info, marketing teams that successfully implement attribution see efficiency gains of 15-30% with increased return on investment (ROI) and return on ad spend (ROAS).

Take a deep dive into the technical details of marketing attributionwith advanced analytics.

The challenges of effective marketing attribution

Advanced analytics and AI are allowing certain companies to get an exceptionally accurate picture of the effectiveness of their campaigns. However, these companies have to overcome significant challenges along the way.

Identity resolution

The number one challenge for teams building attribution models is capturing every marketing touchpoint and being able to assign each of them to a specific user. Central to this is the impact of limitations around identity resolution, which is the process of unifying sessions or events to a specific user.

Customization

Each business has a unique context that informs its strategy. Customization of your attribution means taking charge of your data in order to define your own attribution logic to match this strategy. Creating attribution logic that reflects your customers’ journeys (and their touchpoints) is a challenge for many companies, meaning they cannot fully understand their ROI.

Compliance and Data Ownership

One of the most important considerations when extracting data from packaged analytics to build attribution models is compliance. Being able to record the basis for how events are captured, obfuscating some Personal Identifiable Information (PII), and respecting local data processing laws is essential, but again, this poses a huge challenge for many companies.

Learn more about the challenges of marketing attribution as well as how to overcome them.

Data Product Accelerators for marketing attribution

With increasing pressure on marketing teams to do more with less and increasingly complex customer journeys, this Marketing Attribution Accelerator takes you through the creation of this data product step by step. It equips your team with the ability to accurately calculate marketing efficiency and allocate spend accordingly. This is a relatively advanced data product, however, so you will likely need a technical team member to undertake this.

A marketing attribution case study

Animoto, the video-creation tool, achieved more accurate attribution from multi-touch and non-standard user journeys.

This drove a 20% growth in conversions with fixed marketing spend.

Central to this was the ability to attribute orders to various touchpoints, and to set and apply their own business logic. This connected all user touchpoints and involved attributing multiple sources to website visitors with incredible accuracy.

Why choose Snowplow for marketing attribution

Snowplow has a number of significant advantages over other tools when it comes to attributing value to different marketing channels.

The main benefits you get are:

1) A more accurate view of a user journey, over a longer period, and with far more metrics.

2) A fully-compliant solution with a choice of storage destinations, PII obfuscation and GDPR contexts captured with events

3) The ability to track users across devices to capture the full journey

4) Full data sets, circumventing ITP restrictions to get 400 days of data capture on all users, including Safari