The acquisition of new prospects and clients is central to a company's strategy. But how can this approach be made as optimal and genuinely ROI-driven as possible?
At a time when the customer journey has become digitised in many sectors, from the consideration phase to the loyalty phase, via the purchase phase, the internet channel has established itself as essential in the strategy for acquiring new customers.
With the evolution of the internet and usage over the years, acquisition levers that were often confined to Display and SEM have expanded with the arrival of new channels.
The reallocation of marketing department budgets has made it necessary to have better visibility of the amounts invested and the ROI (return on investment) generated by the various channels in which companies invest.
On paper, it seems rather simple thanks to web analytics tools and traffic source tracking, but the calculation of conversions, and therefore the ROI of different levers, turns out not to be such a trivial exercise.
Let's take a concrete example. :
- A web user views an advert for a trip on Instagram, clicks the sponsored post (lever 1) without completing a booking. .
- Three days later, our internet user is «retargeted» by a display campaign (lever 2) which has identified them as a potential buyer.
- Following this display, the internet user signs up for the site's newsletters to be informed of good deals.
- A few days later, our now-identifiable user receives a newsletter presenting the destination they viewed with a related special offer... (lever 3)
- And finally, our online user finalises their purchase and books their trip!
- The investments will certainly have borne fruit, but to what driver do we attribute the source of this purchase: the Instagram post that triggered the first visit, the retargeting advertisement that led to the newsletter sign-up, or finally the newsletter that allowed us to convert our internet user into a buyer? It is precisely this question that attribution allows us to answer.
What is attribution in Web Analytics?
Attribution is the process that allows for the fairest calculation of the marketing performance of the different levers used by a brand. It's the method that helps us understand and measure how each online customer touchpoint contributes to your business objectives. Imagine this process as a referee distributing points among the players who participated in scoring a goal. Even though the goalscorer is decisive in scoring the goal (the final touchpoint), other players will have contributed to this conversion through a succession of assists, in the example from our introduction:
– A discovery on social media (first touchpoint)
– An advertisement on a website via a retargeting campaign (2nd touchpoint)
– One click further on a newsletter (3rd touchpoint)
– And finally, a conversion
The main attribution models
Understanding the different attribution models is essential for effectively measuring the impact of your marketing actions. There are various models, which we present to you below.
If you want to know which is THE model to use, the answer will be: it depends!
This depends on your activity, the sales cycle and its duration, the number of touchpoints required, and so on. In short, each company has a more or less suitable model.
To help you understand and make a choice, we'll provide a very concrete example of a €100 purchase resulting from a customer journey across several channels. Here's how different models would interpret this conversion:
1. The last-click attribution / touchpoint is also called the Last Click model:
Principle: 100% of revenue is attributed to the last channel before conversion.
Practical example:
– A customer discovers your site via a Facebook advertisement
– He's back via a newsletter
– It converts after a Google search
Google receives 100% of credit (€100) as it was the last click that contributed to the attribution
Advantages
– Simple to understand and implement
– Ideal for short sales cycles
– Perfect for measuring the effectiveness of direct conversion channels
Limits
– Completely ignore the impact of other channels
– Can lead to underinvestment in discovery channels
2. Attribution to the first click/touchpoint, also known as the First Click model:
Principle: 100% of the credit is allocated to the first point of contact.
Practical example:
– Touch point 1: Click from Instagram Ads
– Touchpoint 2: Visit from marketing email
– Touch point 3: Final conversion via SEO
Instagram Ads received 100% of the revenue (€100) as it was the first click that contributed to the attribution
Advantages
– Highlights acquisition channels
– Good alternative for evaluating brand awareness campaign performance
Relevant for new markets or products
Limits
– Neglects the importance of the touchpoints that finalise the sale
– May underestimate remarketing channels
3. Linear attribution also known as the linear model:
Principle: Credit is distributed equally among all touchpoints.
Practical example: For a journey with 4 interactions:
– Touchpoint 1: Display advertising: revenue attribution of 1/4, which equates to €25
– Touch point 2: Email marketing: revenue attribution of 1/4, i.e. €25
– Touchpoint 3: Organic search: revenue attribution of 1/4, i.e. €25
– Touch point 4: Direct access: attribution of income for 1/4, i.e. €25
Advantages
– Value all interactions
Easy to understand
Allows for better integration of the multichannel approach
Limits
– Does not reflect the actual impact of each touchpoint
– May overvalue certain minor interactions
4. Allocation by position also called the Position-Based type model:
Principle: Give more weight to the first and last contacts, with a distribution at the points
intermediaries.
Practical example (40-20-40 Model):
– Touch point 1: First interaction: Facebook advert: revenue attribution of 40% which is €40
– Touch point 2: Newsletter: Breakdown of revenue within the 20% allocated to intermediary channels, here 2 (touch points 2 and 3): either 10% or 10 Euros
– Touchpoint 3: Click on a blog article: Revenue split in the 20% attributed to intermediary channels, here 2 (touchpoints 2 and 3): either 10% or 10 Euros
– Touchpoint 4: Last interaction: Search Ads: revenue attribution of 40% which is €40
Advantages
– Balance between acquisition and conversion
Recognises the importance of the first and last touchpoints that led to the conversion
– More nuanced than previous models
Limits
– The weighting can be arbitrary
– Complicate the analysis of intermediate channels
5. The depreciation attribution, also known as the Time Decay model:
Principle: The closer an interaction is to conversion, the more credit it receives.
Practical example for a 7-day itinerary:
– Day 1: Touch point 1: Earliest interaction in time: Display Advertising: Revenue attribution is the lowest, either 10% for example: here €10
– Day 3: Touchpoint 2: Email: Revenue attribution is a bit more important, at 20% for example: here €20
– Day 5: Touchpoint 3: SEO: Revenue attribution is a bit more significant, say 20% for example: here €20
– Day 7: Touchpoint 4: Most recent interaction in time: Direct access: The income attribution is a bit more important, i.e. 20% for example: here €20
Advantages
– Reflects the growing impact of near-conversion interactions
– Relevant for medium to long sales cycles
– Value closing actions
Limits
– May underestimate the importance of initial awareness actions
– Complex to configure (choice of depreciation period)
6. Data-driven models, also known as Data-Driven Attribution models:
Principle: Use of artificial intelligence to analyse conversion paths and dynamically attribute revenue distribution.
Practical example: The algorithm analyses thousands of conversions and non-conversions to determine:
– The relative importance of each channel
– Winning channel combinations
– The most effective interaction sequences
Advantages
– Based on your actual data
– Adapts automatically to changes in behaviour
– Takes account of complex inter-channel interactions
Limits
– Requires a significant volume of data
– Can be complex to interpret
– Higher cost (more sophisticated tools)
How to make the right choice?
To choose your attribution model, we offer a quick analysis framework:
What is the typical length of your sales cycle?
– On average, how many contact points before a conversion?
– What is your main goal: acquisition or retention?
Do you have a sufficient volume of data?
A practical tip: start by Compare the results from different models on your data. The discrepancies between the models will give you valuable insights into your customer journeys.
Here are some pointers to help you:
Your sales cycle
– Short cycle (B2C e-commerce): simple models like last click may suffice
– Long cycle (B2B): favour more sophisticated models that value multiple interactions
Your product/service type
– Purchases made on an emotional basis: focus on the final touchpoints
– Purchasing high-value products or complex services: consider the entire journey with linear or custom models
Your marketing objectives
– Acquiring new clients: make the most of initial contact
– Loyalty: prioritise recent interactions
The impact of attribution on marketing strategy
Attribution isn't just for large corporations with an army of marketers or consulting firms to help them. Attribution can seem like a complex topic, but after a bit of reading, you'll be able to get to grips with it, allowing you to:
Optimise your marketing budget by investing in the best-performing channels
– To understand cross-channel synergies (e.g. how display advertising reinforces your search campaigns)
– Adjust your marketing mix in real time
Attribution is not set in stone. Your models must evolve with:
– Your customers' changes in behaviour
– The emergence of new channels
– The evolution of your marketing strategy
Attribution in web analytics is not just a technical issue; it's primarily a strategic tool for optimising your marketing investments and acquisition strategy. By better understanding the role of each channel in your customer journey, you make more informed decisions. Want to go further? Start by examining your current data with different attribution models. Observe how your perspectives on channel performance change. And remember: the best model is the one that helps you make better marketing decisions.
Discover how our web analytics solution can help you master attribution and optimise your marketing strategy. Contact us for a personalised demonstration.
