Incremental Lift: Everything A Marketer Needs to Know

Incremental Lift: Everything A Marketer Needs to Know

Online advertising comes loaded with endless measurable parameters that help in analyzing the performance of running campaigns and in building better futuristic strategies. With focus on the Return on Advertising Spend, marketers are keen to understand these metrics so as to track the impact on revenue.

Incremental lift is one such metric that has gained popularity lately. It is able to track the influence of a campaign on revenue.

Quick Introduction of Incremental Lift

Incremental lift is the measurement of the contribution of any ad channel, platform, or format in the revenue generated by a campaign. Let’s say you are running a programmatic ad campaign with a Demand Side Platform that enables you to run ads on different platforms (social media, in-app, etc.) and formats (video, native, banner, etc.). Your target audience will interact with different with them across different touchpoints. Some of them will have more impact than others. Incremental lift helps you calculate the exact contribution of different touchpoints.

Depending on the campaign KPI that you are using, the incremental lift can be adjusted accordingly. So, it means that the advertisers is can see the ROI from different (direct and indirect) touchpoints on which users have engaged during the campaign.

Why Do You Need Incremental Lift?

To understand the importance of incremental lift better, let’s consider a sample user journey of a consumer:

Kyla, your existing customer, is looking to purchase a pair of shoes while working on her laptop. So, she goes to Google and searches for your brand name. She clicks on the first search results (your PPC ad) and checks out some pairs of shoes, but before she could choose a pair and proceed with the purchase, her phone beeped. She got distracted by social media notification and started scrolling through her Instagram account now.

To ensure that you do not lose the sale, you are running cross-device ads. Your ad on Instagram with the pair of shoes that she checked reminds her of it. So, she clicks your ads on the phone, visits your app, and then proceeds to make the purchase.

In this journey, Kyla clicks your ads: PPC ad in search results and display ads in social media. However, there are some other contributors to your campaign as well: your branding ads which made her search for your brand name and your app install campaign because of which she already had your app. While your attribution model will allow you to pay to the search ads as well as social media ads, incremental lift measurement will help you trace the contribution of those indirect sources. In the user journeys that more complex and have even more touchpoints, such calculations are of great importance.

Is Incremental Lift An Alternative for Attribution?

No. Incremental lift doesn’t replace attribution models. It simply adds deeper insight into revenue. While attribution doesn’t provide much value in planning ad spend, incrementality measurement can do that for you.

Incremental Lift and Attribution are two different calculations based on the data generated from your campaigns. It implies you have both the calculations available. Depending on your strategy and advertising model, you can choose the one that needs more focus.

Attribution Model: You can focus more on the attribution model instead of incremental lift when your marketing campaigns involve only a few touchpoints and limited user data.

Incremental Lift: Incremental lift needs more focus on large-scale ad campaigns. Such campaigns may involve multiple touchpoints along with a deeper understanding of the customer journey.

Wrapping Up

Just like there are different attribution models available for advertisers, there are several incremental lift calculations as well. It is calculated by serving different groups with different journeys and observe the revenue differences. Though you can perform it manually, some leading Demand Side Platform, like RevX, are capable of doing it automatically. With Artificial Intelligence, testing between different groups is automated. It allows us to see which touchpoint delivered higher results at which stage of the journey. So, it can optimize your campaigns consistently to deliver high RoAS.

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