What are the pros and cons of using first-touch, last-touch, and multi-touch attribution methods?

First touch attribution will tell you which is the right channel to create awareness and bring leads while last touch attribution will tell you which is the right channel that will help you convert the lead into customers. As, there are lot of different products/customer persona for different companies, using a standard touch attribution won't help. In that case, multi-touch attribution helps you give the true picture of how your customer journey looks like from lead to a customer.

Use First-Touch for brand awareness (Demand generation) campaigns. They are harder to measure, and Founders, CEOs and Finance team don't like shooting in the dark. The first touch could help you find where a conversion originated from. Also, bear in mind that unless your CRM has the capability to switch between different attribution models, you are stuck with anonymised data.

First-Touch Attribution Pros: Simple, emphasizes initial touchpoints. Cons: Ignores later interactions, biases toward top-of-funnel. Last-Touch Attribution Pros: Simple, emphasizes conversion point. Cons: Ignores earlier interactions, biases toward bottom-of-funnel. Multi-Touch Attribution Pros: Provides a holistic view, balances credit across touchpoints. Cons: Complex to implement, relies on high-quality data. Choose based on your goals, resources, and customer journey complexity.

understanding of attribution metrics is essential for improving the performance of your campaigns. They provide invaluable insight on the effectiveness of different marketing tactics and channels, helping you to allocate resources appropriately and maximize conversions. Additionally, by analysing attribution data you can easily detect where improvements can be made, enabling you to refine your strategy and optimize your budget.

First-touch attribution reveals the ideal channel for generating awareness and leads, while last-touch attribution identifies the channel best for converting leads into customers. However, with diverse products and customer personas, standard attribution models may not suffice. Multi-touch attribution offers a comprehensive view of the customer journey, depicting the path from lead to customer more accurately.

? Last touch problems: -User saw your Facebook ad, went on your site and bounced, 2 days later, searched for your name, and clicked on your brand search ad. Search ad gets credit, while Facebook shows you're wasting your money ?? - Your sales cycle is long (like in B2B) and every touch point made a 10-20% contribution in building trust. Last-touch ignores all that!

Last-touch attribution is almost always going to be the easiest to track, which means it’s also likely to be most accurate. And the data is usually quite actionable. Sure, there is lots of info missing when you just look at last click. But if you have a finite budget and limited bandwidth, last-click attribution is a great place to start.

In My experiences . Last-touch attribution is typically the simplest to track and often the most accurate, making its data highly actionable. While it may lack comprehensive insights, especially compared to multi-touch models, for businesses with finite resources, last-click attribution serves as an effective starting point.

When it comes to budget allocation, one of the main issues I have with last-touch attribution is that you simply can't buy "the last click"; you can just buy a click. A click always shows that you attracted someone to solve their problem. You may or may not be able to solve their problem, but that is not the problem of the click and also not of that click's position in the user's journey.

Multi-touch attribution offers a comprehensive view of the customer journey, assigning credit to various touchpoints. This method has transformed how I approach marketing strategy, allowing for nuanced understanding and optimization of each interaction. However, its complexity and data requirements present challenges, necessitating careful consideration to minimize bias and errors. By leveraging multi-touch attribution, I've been able to refine marketing efforts and allocate budgets more effectively, though the journey to its successful implementation was paved with trials, underscoring the need for robust analytics capabilities and a clear grasp of the customer's path to purchase.

I'm a big fan of multi-touch attribution. It shows more of the picture of what medium performed to close the deal. As community leader, I want to see the path a prospect took before they became a customer. It's reflective of how long the sales cycle really is - with real data to back it up. Some ways to do this on the cheap without a ton of fancy software is to use the google UTM builder (https://ga-dev-tools.google/campaign-url-builder/). Build out links per marketing campaign, including nurture sequences, and make sure to pull them into your sales cycle software (ie. Salesforce.) Then run reports weekly to track usage.

PR results rarely get the attribution they deserve, certainly requires some kind of assumption when reviewing the data, and is difficult to directly connect with spikes in website traffic. Still, great media coverage deserves a look and the spikes don't lie.

Requires some level of assumption when analyzing data. It's challenging to directly correlate PR efforts with spikes in website traffic. Nevertheless, significant media coverage warrants attention, and noticeable spikes in traffic shouldn't be ignored.

Knowing how a channel performs as a first, last touch or any multiple is only a part of the story. We should ask, “How to communicate to customers about the right subject, and at the right time?” Organisations need to stop siloing their thinking on how to communicate with customers, setting KPIs at a channel level. Leadership teams need to stop assigning budget and praise to different channel teams, setting conversion KPIs per channel. Data analytics isn’t about reporting, it’s a tool to improve customers experience. The first step, stop measuring a single channel and think about the question from a whole different perspective.

I advocate for "Participation" attribution model instead of "Multichannel". The difference is that channel get full credit for every interaction, similar to "Assisted conversions". It shows clearly if channel is at least participating in paying customers journey , or not. Together with first click and last click it's enough to make informed decisions about campaigns.

Another common trend in the attribution sphere is: Self Attribution. Self-reported attribution is when you ask your users how they heard about you on a form on your website. Impact of having self attribution in place Often highlights ‘dark’ touchpoints that traditional software attribution can’t track. Gives you in-depth qualitative insight into what drives the most meaningful marketing conversions. Uncovers channels you had no idea were working for you. Understand your buyer’s preferred ways to self-educate and gather information. Gain a realistic view of your marketing efforts.

Fragmented data is very confusing and, to a degree, is unavoidable (Although there are some ways to clean and unify the data). You could set various Attribution models in your Meta/Google dashboards, but then your CRM or web analytics could show different data. I agree with Tom; I think for most SMBs, looking at the data holistically and supplementing it with qualitative research (like feedback during sales or purchase) could close the gap.

For accurate attribution of upper, mid & lower funnel tactics, model-based attribution is the best. Multi-touch attribution is sometimes only limited to touch points that are being tracked by Google. For PR, Organic Social Media, Organic Searches etc., model-based attribution takes into account all marketing actions and determines the impact on business. The results can be used for Media Mix Optimization and truly understanding the customer journey & experience.