What is multi-touch attribution?
Multi-touch attribution is a marketing measurement method that takes multiple online and offline touchpoints along the customer journey into account, and then assigns credit to each based on varying logic per business.
Offline touchpoints include television (excluding smart TV), radio, print (e.g. billboards, coupons, and direct mail), in-store, call centers, and sales calls.
Online touchpoints are divided into paid, owned, and earned media across digital properties.
Paid media includes search, display, social etc, while owned media refers to websites, emails, demos, content marketing such as blogs, and your brand’s social media accounts. 3rd party social media and blog mentions are examples of earned media, as is press coverage.
In multi-touch attribution, touchpoints can be weighted equally or proportionally, depending on the model used (more on this below).
Single-touch vs. multi-touch attribution
Single-touch can refer to both first or last-touch attribution.
First-touch assigns full credit to the first known point of contact with your brand in the consumer journey, whereas last-touch gives all the credit to the last known touchpoint.
Of course neither attribute across the entire user journey, so why would a marketer choose to use them?
First-touch for branding
If you are focused on introducing your brand and widening the top of your funnel then you may opt for a first-touch attribution model. That is because it’s relatively easy to implement and delivers insights on how customers discover your brand.
Last-touch for conversions
Conversely, last-touch attribution focuses on the bottom of the funnel and what factors helped convert the user, which is after all, the essence of performance marketing.
Multi-touch for a complete view
Multi-touch takes a more holistic view and covers the entire funnel, delivering insights across the user journey. Let’s explore this in more detail.
Benefits of multi-touch attribution
Clearly, both first and last-touch attribution ignore the reality of a modern consumer journey (5-20 touchpoints on average, remember?); That’s where multi-touch attribution comes in. It takes a more sophisticated approach to mapping the journey, and offers a number of other benefits.
Multi-touch attribution addresses the complexities of the actual customer journey
We mentioned above that the customer journey is complicated by multiple devices, channels, and touchpoints. MTA helps to overcome some of these complexities by reflecting, more accurately, the actual user journey.
The better the representation of reality, the better the understanding of where influence lies and which combination of touchpoints are performing the best.
Having a more accurate picture of the user journey and the touchpoints along the way will help you better customize your messaging, meeting consumers on the right channel(s) at the right time.
Multi-touch attribution eliminates biases
Allocating credit along the length and breadth of user journey means you are not placing undue importance on the first or the last touchpoint. Instead you are able to allocate credit using data to support any argument over the influence of a touchpoint in the path to conversion.
For example: let’s say a consumer first sees one of your paid ads on Facebook, searches for your brand on Google, you remarket them on a news site, and then they go back to Google to search for your specific product and purchase.
Who’s to say that the paid touchpoint (the first) should get credit over search (the last touchpoint)? Or vice versa? That’s where an MTA model can save the day by making sure each channel gets its fair share of the success.
Multi-touch attribution enables agility
Multi-touch places all of the data in one model so there is no need to jump between reports trying to identify the value of a touchpoint. The result of having increased agility is the ability to adapt and pivot your strategy according to the insights gained.
For example, say a large chunk of your marketing budget was dedicated to a bottom-of-the-funnel promotional email campaign. However, your MTA model showed that a social media campaign towards the top of the funnel is proving to be very successful at getting prospective customers to click through to your mobile site and purchase.
With these insights you were able to see the impact of the social media campaign at increasing conversions. As a result you pivot your strategy and place more emphasis and spend on the social media channel, and less on the email campaign, to maximize your Return on Investment (ROI).
Multi-touch attribution prevents bleeding marketing budgets
The risk of misunderstanding your customer journey means that you may be blind to which combination of touchpoints are delivering the highest ROI, and equally important which are underperforming.
Multi-touch attribution offers the insights needed to know when to reduce your marketing spend on the channels that aren’t delivering, and to leave more budget for doubling-down on the ones that are.
How to choose the best model for your business
When it comes to multi-touch attribution, there is no one size fits all approach.
Ultimately, it will depend on the specific KPIs for your app and your campaign. For example, if you’re measuring the number of app downloads then the time decay model may work best. But if you’re measuring LTV you may want a model that covers more touchpoints even after conversion such as the full path model.
Before you decide which model to use it’s crucial to determine your KPIs and then decide which model is the best fit.
You should also test out different models and see which one aligns most closely with your strategy. If one model doesn’t work, try another until you get the insights you need.
Finally, compare the results between the different models and see where you can optimize for improved results.
We have discussed how the various multi-touch models allow marketers to assign credit in more sophisticated ways. However, for a truly holistic view, MTA should be combined with Marketing Mix Modelling (MMM). MMM is traditionally used for budget planning and strategic purposes and takes a top-down approach to attribution modeling. Conversely to many digital attribution models that rely on user-level real-time data (or as close to real-time as possible), MMM insights are aggregated and referred to as part of quarterly or even annual strategic conversations.
MMM accounts for a number of other influencing commercial factors beyond marketing and advertising, ranging from macroeconomic conditions, to seasonality and even the weather.
For example, we saw in 2020 that app downloads climbed 33%, which was largely attributed to COVID-19 lockdown measures and people being asked to stay at home. Using MMM, which accounts for the pandemic in its calculations, helps marketers assess the impact of external influences and can be used for strategic planning.
Using both MTA and MMM together adds to the agility we mentioned earlier. Marketers are able to see both sides of the coin : the strategic side with MMM, and the tactical side with MTA.
For example, is a 10% discount code sent via a push notification on a taxi ride app better received in a rainstorm or during a heat wave? The data attained through MTA combined with the insights on external factors will help marketers make smarter decisions.
5 steps to implement multi-touch attribution
1. Determine your KPIs
As we mentioned above, your KPIs will guide your strategy. If your primary goal is user acquisition then you may choose a different model than if you’re measuring LTV or the uninstall rate. Defining what you’re measuring will help guide which attribution model is best suited to your needs.
2. Clean your data
Today, most organizations store customer data in a CRM system, but if not maintained and cleaned regularly, your data could end up causing you problems.
Do a thorough audit of your data to ensure it meets your quality standards. Make sure you fix missing contact fields, remove duplicate data, ensure data is inputted into the correct field, and correct typo’s or other inaccuracies such as out of date job titles or companies.
Poor data can leave holes in your analysis and lead to incorrect assumptions and ultimately wasted budgets.
With the introduction of iOS 14 and other privacy measures, the quality of your data and the safeguards you implement around it have never been more important.
In fact, data quality was cited as the biggest barrier to revenue attribution success (43%) globally, so making your data clean early on in your attribution process will pay off in the long run.
Use an analytics software that can identify the role of each touchpoint to analyze the data once it has been collected. Doing so will help make it easier to identify any insights and address app campaigns that require optimization.
4. Optimize on-the-go
Continually review the metrics and assess if any channels are underperforming. If you find this to be the case then adjust your campaigns accordingly. Your attribution should always reflect your business goals. If your goals change then you may need to optimize or regroup and try a different attribution model.
5. Apply insights to your overall model
Once you have identified trends and understand the data patterns, apply these insights to future marketing efforts to improve the performance of campaigns and channels.
Remember this is an ongoing process, so when you acquire new insights be sure to apply them and improve your results.
Challenges of multi-touch attribution
Multi-touch attribution, for all of its benefits, is not without its challenges. Let’s discuss a few of them here.
No industry-wide standard
As mentioned above, despite the fact that last touch falls short, it is the industry standard for billing.
Why? Because multi-touch is complex and requires buy-in from multiple parties across the ecosystem.
For example, you elect to use the W-model. That would mean the three main touchpoints had agreed to take 30%, instead of the last click receiving the full 100%.
All the partners, advertisers and ad networks need to be on the same page, which requires collaboration across the industry — something that has just not materialized in a meaningful way.
multi-touch models are both challenging to implement and difficult to analyze.
Not all companies have the talent required to deploy the models or the ability to glean the insights they deliver. In fact, data shows that as few as 9% believe that their organizations have a “excellent” understanding of multi-touch attribution.
Difficult to validate results
The path some attribution models take to reach their conclusions remains a mystery to many marketers, making it difficult to validate the results. For example, attribution models will always credit an action to a touchpoint, even though marketers know some actions happen organically.
Marketers can use incrementality testing to identify which conversions were related to a specific marketing campaign, and which would have happened on their own, giving greater clarity to the attribution results.
Incrementality is not a new concept and has been largely overlooked due to its complexity in both execution and analysis. However, it has recently gained traction as a useful tool post iOS 14 to help fill the gap with data-driven insights.
Limited offline metrics
Multi-touch attribution models are intended to factor in multiple channels and devices. These channels should in theory include offline channels such as TV, radio, and print.
However, it is very difficult to attribute these channels and there is a severe lack of data relating to them. Together, this creates a challenge as to how to aggregate any data you do acquire into your chosen model.
No perfect fit
None of the models is a perfect solution.
Each campaign will have different requirements and goals. It is therefore important to assess what these are before starting your campaign and apply the model that is the best fit in this instance.
Remember, you can always change the model if you see you aren’t getting the insights you need. Sometimes it’s simply a case of trial and error.
The limitations on 3rd party cookies and the depreciation of Apple’s IDFA mobile ad identifier will make attribution more challenging because it will be harder to identify customers across channels. Instead, aggregated level attribution and measurement will take center stage through methods like incrementality testing.
Relying on 1st party data will also become much more important, for example, by directing users to a brand’s mobile website and from there to the brand’s mobile app (in such a scenario there’s no need to collect the IDFA).
Multi-touch attribution gives you the ability to analyze the impact of each touchpoint along the customer journey and identify which are delivering the highest value.
To understand which model best fits your need you should remember:
- In today’s digital world where customers jump between channels and devices, multi-touch attribution helps give marketers a truer representation of the customer journey.
- Progress is progress – every touchpoint that you are able to connect into a wider customer journey is progress and helps sharpen the insights into your marketing funnel.
- Decide on the KPIs for your campaign and determine which model fits best
- Understand that is no perfect fit – each model has its pros and cons so it’s up to you to decide which one best fits your goals
- Remember that last-touch remains the industry standard for billing purposes. Multi-touch attribution models can be used in parallel to deliver insights on your marketing efforts and help guide your strategy going forward.