Old-school attribution no longer works

How misconceptions about marketing attribution can leave you stuck in the past.

Despite the constant technological advancements in the industry, some things are harder to change. Constantine Yurevich, Founder at Conversion Modelling platform SegmentStream explains why attribution needs to catch up.

For years, marketers relied on traditional attribution models to evaluate campaign performance. They would use attribution to understand the value of each marketing channel and how it affects a purchase decision to improve their advertising campaigns.

However, as customer journeys become more complex, marketers can no longer rely on the old-school approach of attribution to make the most of their online advertising campaigns. 

Usually, customers don’t make a purchase on the first visit to a website. They may not even purchase using the same device or browser that they used in the first interaction. And let’s also consider the cookie-tracking restrictions that can make attribution a nightmare.

All these challenges combined limit a marketer’s ability to optimise a campaign, which leads to a lower return on advertising spend (ROAS) from each channel.

To overcome these challenges, we need to understand common misconceptions about attribution and how they can impact marketing efforts.

The biggest misconceptions about attribution 

There are several misconceptions about marketing attribution making the rounds for years that can hurt a campaign’s effectiveness. 

1. “Marketing attribution is only about assigning credit for conversion to a single channel”

For some marketers, attribution is all about finding the one significant touchpoint that generates the conversion. In theory, it seems like an easy way to give credit to the channel that leads to a purchase. But how linear (and accurate) actually is this process these days?

In a world of multi-channel campaigns with cross-browser and cross-device customer journeys, this view of attribution is very narrow. In fact, it ignores others campaign’s impact on brand awareness or customer engagement and can’t show the incremental impact of each touchpoint. 

2. “You don’t need sophisticated attribution tools since you’re investing in a single paid channel”

Let’s say your marketing efforts focus on one channel, such as Facebook Ads. It’s tempting to jump to the conclusion that you don’t need to worry about attribution since you don’t add more channels to the mix.

This is a misconception that can affect your campaign’s effectiveness. Your smart bidding campaigns on Facebook Ads or Google Ads need proper attribution data to help you make the most of your budget and create more successful ads. 

Providing limited or poor data to the ad platforms can affect your campaign’s optimisation and the return on investment.

3. “Marketers use advanced attribution models to evaluate the effectiveness of channels, but continue to optimise campaigns using the last-click model.”

Many marketers use advanced attribution models hoping they will uncover the mystery of complex customer journeys. However, they sometimes forget one important step.

When setting up campaigns on Facebook Ads and Google Ads, they use the default setting of post-click and last-click attribution. This can limit the success of the campaign by restricting optimisation and providing inaccurate data.

How attribution misconceptions influence smart-bidding campaigns

Advertising platforms use conversion data as feedback to train their algorithm and display ads more efficiently. Their algorithms rely on the feedback they collect to tell whether an ad is successful or not. Thus, having access to the right amount of data can shape a campaign’s success.

However, attribution misconceptions can lead to poor analytics, resulting in limited optimization, lower returns on investment, and a waste of resources.

The best way to overcome this challenge is to go beyond the traditional attribution models and evaluate all website sessions to provide ad platforms with more feedback signals and improve the value of an ad click.

Filling the measurement gaps

In today’s world, it's impossible to track user journeys due to the reasons above, which greatly affect the campaigns' efficiency. 

Conversion modelling is gaining ground as a marketing measurement approach that uses machine learning to assess the impact of all traffic sources when conversions cannot be tracked. 

As the customer journey becomes more complicated, conversion modelling allows marketers to go beyond the challenges of tracking cookies or the number of screens a customer uses.

What’s the difference with multi-touch attribution? 

You don’t need to wait for a conversion to access valuable data. The real-time analysis of data points is calculating the probability of conversion and every visit has an attributed value. This means that you won’t have an issue with ad clicks of zero value again.

Moreover, knowing the probability to convert, or “Modelled Conversions”, allows marketers to attribute session value to the traffic source, even if the conversion takes place from another device or browser in the future. Modelled Conversions ad platforms will receive more signals and thus improve smart bidding campaigns with better optimisation and ROAS.

Going beyond attribution

In a world of cross-device customer journeys and multi-channel marketing campaigns, attribution has to catch up. Today it’s impossible to understand the full customer journey. Marketers need the right tools to gain valuable insights and improve the impact of their marketing efforts.

Marketers have to move from old-fashioned attribution models to new options to understand campaigns' performance in different channels. 

Conversion Modelling can help them analyse the value of each website visit to calculate the chances of a future conversion. By providing ad platforms with more feedback signals, they are able to improve a campaign’s performance and make more data-driven decisions in a post-cookie world.

Constantine Yurevich