Last-click attribution for measurement: Is it that bad? Answers from a Data Analyst [template included]

TL;DR If you’d like to get started with last-click attribution right away, swipe our free template for Google Sheets. If you want to learn when last-click attribution makes sense and how to make the most of it, keep reading.

Marketers have a bad habit of declaring something is dead.

SEO is dead. Paid advertising is dead.

And, of course, last-click attribution couldn't escape its unfortunate fate of being on marketing's death list. But I'm here to tell you that, despite what LinkedIn gurus have said and the crazy hype around marketing mix modeling, last-click attribution still has a place—because it's the most practical.

Understanding last-click attribution

Last-click attribution assigns 100% of the credit for a conversion to the final touchpoint before a user converts. For example, if a customer sees an Instagram ad, visits the website from an email campaign, and finally clicks a Google search ad before purchasing, all credit goes to the Google Ads.

This model is the default in many analytics platforms, like Google Analytics 4, and is often the easiest to implement. It doesn’t require tracking users across channels, making it more privacy-friendly and accessible than more complex models.

Imagine your customer journey as an iceberg. Last-click attribution reveals only the tip above water—the final interaction that drives conversion. What you don't see is the larger mass beneath the surface—the impressions, awareness campaigns, and consideration-stage interactions that influenced the decision. While more advanced models like multi-touch attribution (MTA) or marketing mix modeling (MMM) attempt to capture more of the iceberg, they come with added complexity, cost, and data requirements. Last-click may not show the whole picture, but it's better than flying blind.

Why last-click still matters (despite what others say)

Ultimately, the best measurement model is the one you can use and trust. If your team doesn't understand the data or can't act on it, even the most advanced system is pointless. Good measurement fits your workflows, matches your tech maturity, and drives business outcomes.

You should see improvements in marketing efficiency, return on ad spend, and revenue as a result of measurement. If your tools aren't guiding better decisions, it may be time to reevaluate your approach. Last-click attribution can be your first measurement stepping stone because it's:

• Easier to implement compared to other advanced models: you don't need a data science team or a customer data platform to get started
• Privacy-friendly: you don't need to worry about relying on third-party cookies or user-level data
• Good for bottom-of-funnel optimization: you can see which BOFU tactics work the best

It’s accessible and easier to implement

Compared to other advanced models like MMM and MTA, last-click is the easiest method to implement for multi-channel analysis. If you’re comfortable working with Excel or Google Sheets and you’re dealing with 3 months of historical data and viewing results on a weekly or monthly basis, you can absolutely set it up yourself. We even have a Google Sheets template to help you get started.

Get the last-click attribution template for Google Sheets >>

Even if Google Sheets isn't your comfort zone, you can use Supermetrics Marketing Intelligence Platform to perform this kind of analysis without writing a single line of code.

Now, if you need more advanced capabilities, like daily-level data to track your Black Friday campaigns, or access to 2 years of historical data from multiple sources, you'll need a data warehouse. And it requires SQL skills, something many marketers may find intimidating.

But even so, the transformations and logic required for last-click attribution are still simpler to build than those needed for MMM or MTA. This makes it a practical option for companies looking to begin measuring marketing impact without overhauling their tech stack.

It respects privacy

Unlike multi-touch attribution, which relies on tracking individual user journeys (and thus requires persistent identifiers), last-click attribution can be implemented without compromising privacy. It uses anonymized UTM data to connect campaigns with conversions.

It works well for bottom-of-funnel optimization

Marketers often use last-click attribution to evaluate the performance of campaigns that directly drive conversions. When you're focused on optimizing bottom-of-funnel tactics—like retargeting ads or branded search—last-click attribution gives a clear, if narrow, view.

Where last-click attribution falls short

As I said, last-click attribution helps you see the ROI of some of your marketing efforts, but not the entire story. You need to be aware of the following limitations when implementing it:

• It doesn't show the whole customer journey
• It's ineffective when it comes to longer B2B sales cycles
• It can be misleading and overemphasize the performance of one channel over others

It ignores the full customer journey

By focusing solely on the final interaction, last-click attribution neglects the important contributions of upper-funnel channels like display ads, organic content, or influencer campaigns. This skews optimization decisions toward what closes the deal, rather than what starts or nurtures the journey.

It's ineffective in long sales cycles (e.g., B2B)

In B2B marketing measurement, where deals take months or even years to close, last-click attribution offers limited insight. It may give credit to a single interaction that occurred after months of engagement, missing the many touchpoints that educated and influenced the buyer.

It can mislead cross-channel insights

If a customer sees your ad on LinkedIn, clicks an email, and converts via a Google search, last-click attribution only credits Google. Without understanding the full sequence, marketers might underinvest in impactful channels that assist conversions rather than close them.

How to get started with last-click attribution

Set UTM parameters

UTMs are the backbone of any last-click model. They can be seen in a user's browser after they click an ad, and use a coded system to keep your campaign information private. When setting up your UTMs, you should:

• Define naming conventions for source, medium, and campaign
• Ensure consistency and make sure your UTMs match the campaign name on the ad platform
• Avoid duplicate or empty values

Check out Supermetrics' naming convention guide for best practices.

Choose the right tool

Google Sheets or Excel: if you're dealing with smaller volumes of data. Expect limitations in historical data and granularity.

Data warehouse: if you need to analyze large and/or granular datasets, multi-channel datasets, or longer timeframes.

Supermetrics Marketing Intelligence Platform: Let's say you're not confident in mapping your UTMs. Supermetrics is a great option for you. You can build a last-click attribution model by joining datasets using shared campaign-level UTM parameters. You can specify how you want to blend their data—by campaign, date, or channel—and it supports multiple destinations such as Google Sheets, BigQuery, or Looker Studio.

Visualize your data

Whether in Sheets, BigQuery, or a BI tool like Looker Studio, visualizing last-click data helps teams digest and act on it faster. Supermetrics' templates and platform connectors make it easy to create performance dashboards.

When to move beyond last-click

Signs that last-click attribution may no longer be sufficient include:

• You've fully optimized bottom-of-funnel tactics
• You need visibility into top or mid-funnel performance
• Your campaigns span several touchpoints and channels

Rather than abandoning last-click entirely, marketers should treat it as one piece of a larger measurement strategy. Used alongside MMM, experiments, or even platform-native attribution insights, it helps complete the picture.

Each model answers different questions. Last-click shows what converts. MMM shows what influences performance across channels. Experiments show what works when variables are isolated. For example:

• Experiments (e.g., lift studies, holdout tests) to gauge incremental value
• MMM for full-funnel, privacy-friendly impact analysis
• Multi-touch attribution if you have a CDP and user-level tracking capabilities

FAQs about last-click attribution

1. Is last-click attribution dead? Not at all. It's still widely used, especially in industries with short sales cycles or limited analytics resources.

2. Can last-click show performance across channels? Yes—if your UTMs are consistent, you can track last-click conversions across your full marketing mix.

3. What if my UTMs don't match platform names? Some Supermetrics connectors support UTM fields (e.g., utm_campaign) that help reconcile naming mismatches. But it's best to align names proactively. You can use Supermetrics Marketing Intelligence Platform to manage your naming convention.

4. Should I move to multi-touch attribution? Only if you can support the tech and privacy implications. MTA can offer deeper insights, but it's more complex and costly.

5. How do I know when to evolve past last-click? When you feel confident in your bottom-funnel performance and want visibility into what's driving awareness and consideration, it's time to layer on MMM or experiments.

Final thoughts: You need to start somewhere

Last-click attribution isn't perfect, but it's practical, actionable, and accessible. For many teams, it's the gateway to more sophisticated measurement practices. Instead of starting by chasing the most difficult to access measurement methods, start somewhere smaller and make sure you're actually acting on your data instead of just drowning in it. Ultimately, data is to be acted on to drive business outcomes.

And if you're ready to get started, try our last-click attribution template to explore what you can already learn from your last three months of marketing data.