Last touch attribution is a model that assigns 100% of the credit for a conversion or sale to the last click or touchpoint that a customer interacts with before making a purchase. This could be an ad click, email open, website visit, or other tracking interaction. While last touch attribution is simple to understand and implement, it has some significant drawbacks that marketers should be aware of.
It fails to account for the influence of early touchpoints
One of the biggest issues with last touch attribution is that it ignores all of the touchpoints that happened before the final click. A customer’s journey often involves multiple interactions spanning different channels over days or weeks. Last touch completely disregards the impact that early ads, emails, social media posts, and other touches had on generating awareness, interest, and consideration.
For example, a customer might see a brand’s Facebook ad, then receive an email newsletter highlighting a sale item, and finally click on a Google Search ad right before making a purchase. Last touch would give 100% credit to Google Ads and none to the other important interactions with the brand along the way. In reality, those early touchpoints likely influenced the final conversion and should receive partial credit.
It skews marketing investment toward lower-funnel tactics
Since last touch only values the final interaction, it tends to incentivize investment in lower-funnel, direct response tactics like paid search ads and promotional emails. These are more likely to deliver the final click than brand-building tactics like social media that focus on awareness higher in the funnel. However, an over-emphasis on direct response can lack longer-term impact.
While last touch will provide full credit for conversions generated, it won’t account for the customer relationships and loyalty built through early interactions. This risks undervaluing tactics that have indirect, cumulative benefits over time. Relying too heavily on last touch attribution could lead to under-investment in channels that provide crucial support early in the customer journey.
It creates channel conflict
Assigning 100% credit to the final touchpoint often creates channel conflict between teams. For example, search and social media teams may fight over which channel receives proper credit for a conversion. This channel bias discourages collaboration between marketing groups that should have shared goals and work cross-functionally.
Channel teams are likely to over-optimize on tactics that allow them to “snipe” conversions at the end of the funnel rather than working together to drive customers through an integrated journey. Last touch essentially encourages channel siloes rather than an omnichannel approach to attribution.
It doesn’t account for differences in conversion value
Not all conversions are created equal. A high-value purchase of a premium product should be credited more heavily than an inexpensive, one-time transaction. However, last touch treats all conversions the same regardless of their value.
A $1000 purchase sparked by an initial email and completed after a website visit would credit the website 100% of that large conversion value. This inaccurately skews attribution data and fails to account for the email’s contribution to generating a high-lifetime-value customer.
It is prone to outlier results and variability
Because it relies on a single touchpoint per conversion, last touch is highly prone to outlier data that may not be indicative of true attribution. Unusual spikes or dips in specific channels receiving last touch credit can occur due to random chance rather than actual changes in marketing performance.
For example, a brand may run both display and paid search ads. Due to the timing of when each ad is served, display ads receive an unusually high number of last touches one week while search ads get very few. The next week could look exactly the opposite. This makes performance trends difficult to analyze over time. Multi-touch attribution models provide more stable results week over week.
It fails to identify wasted spending
If a channel is consistently receiving last touch credit but has low assisted conversion rates, that indicates wasted spending. Assisted conversions look at all instances a particular channel was involved at any point in the journey for a conversion.
A channel could have a high last touch rate but low assisted rate meaning it is stealing credit rather than contributing value. Last touch alone can’t identify these issues – a multi-touch view is required to see if channels are truly earning their attribution.
It struggles to account for long, complex buyer journeys
Last touch attribution works reasonably well for quick, straightforward conversions driven by impulse purchases and direct response. However, for long, complex B2B sales cycles involving multiple touchpoints, last touch is simply inaccurate. High-consideration products require lengthy research across channels before a final transaction.
In these cases, early interactions like trade show meetings, whitepaper downloads, and product demos play a crucial role in generating leads and pipeline. Last touch would fail to properly attribute mid-funnel activities that happen weeks or months before an eventual closed deal.
| Touchpoint | Channel | Interaction |
|---|---|---|
| 1 | Social Media | Viewed Brand Post |
| 2 | Clicked Email Link | |
| 3 | Paid Search | Clicked Ad |
This example customer journey across social, email, and paid search would see 100% attribution to paid search under last touch. The table visualizes how earlier interactions would receive no credit despite their likely influence in driving the final conversion.
It is difficult to implement for offline channels
Online channels like paid ads make it relatively straightforward to capture last clicks digitally and use them for attribution. However, many offline marketing tactics do not have clear last touch viewability before a purchase. Channels like TV, radio, billboards, in-store promotions and more lack easy tracking of when a customer had their final interaction.
This can exclude crucial offline media interactions from attribution under a last touch model. Sophisticated multi-touch models are required to approximate attribution for both online and offline channels in an omnichannel approach.
It fails to account for external factors influencing conversions
Last touch assumes that the final click or interaction is wholly responsible for driving the conversion. However, there are often many external factors that influence a customer’s purchase decision.
These can include reviews, word-of-mouth referrals, promotions by a competitor, economic conditions impacting purchase power, seasonal trends, and more. Since last touch ignores these important factors, it cannot provide a truly holistic view of marketing attribution.
Conclusion
While last touch attribution provides a straightforward, cost-effective way to allocate conversion credit, its limitations are substantial. By ignoring all touchpoints other than the last, it fails to account for the influence of early brand interactions. This can skew marketing investment to only direct response tactics.
Last touch also creates channel conflict, fails to distinguish value of conversions, leads to data variability, and lacks a view of wasted spending. For complex buyer journeys in particular, a multi-touch attribution approach provides far greater accuracy in measuring true channel performance. Understanding the significant cons of relying solely on last touch can help marketers select a more effective overall attribution strategy.