How To Put Multi-Touch Attribution Into Practice

Multi-touch attribution is a marketing measuring technique that assesses the impact of each touchpoint in driving a conversion, consequently estimating the value of that touchpoint.

Setting up multi-touch attribution might be difficult. That’s not to say you shouldn’t get started; the sooner you do, the sooner you can start optimising your attribution strategy. Marketers who want to use multi-touch attribution models should follow the steps below for the best results:

Step 1: Determine the models and key performance indicators (KPIs).

Marketers must choose various attribution models to use based on their organization’s objectives. Considerations such as the length of the sales cycle and the sorts of campaigns should be taken into account while selecting models. The next step is for marketers to choose their KPIs. These will be the benchmarks against which success and failure will be measured. Marketers who utilise MTA are usually attempting to enhance ROI and user experience, therefore these KPIs must represent what this entails for the unique company.

Step 2: Form a workgroup

Following that, marketing teams must coordinate with important members of the team and stakeholders. Of course, this will need working with professional marketing analysts, as well as budget stakeholders and creative teams, to optimise messaging based on data.

Step 3: Put marketing analytics software to work

When working with numerous complex attribution models, powerful analytics software is required to normalise and correlate the data into easy-to-understand metrics from which insights can be drawn. This platform should provide comprehensive data at the individual level, as well as other insights into the motivation for conversions, such as brand equity or effective creative.

Step 4: Put what you’ve learned to work for you

Marketers that believe they have a thorough picture of how their campaign performed based on the data provided by their attribution model can use those insights in real-time to start course-correcting, allowing them to create a more personalised experience.

Step 5: Keep optimising and testing

This isn’t supposed to be a one-time thing. Rather, marketers should be examining their MTA data on a regular basis in order to refine and test strategies. Marketers will be able to determine the optimal techniques and marketing sequences to reach their customers at the correct moment through regular optimizations and tests.

Multi-Touch Attribution’s Challenges

While multi-touch attribution models provide more information than traditional marketing metrics, they aren’t without flaws. There are a few major hurdles that marketers must overcome as they strive to perfect their attribution measurements.

1.     Offline Metrics Aren’t Available

Because it measures customer activities, MTA is commonly utilised in campaigns that use digital marketing platforms (clicks, etc). Offline data, such as exposure to a TV or print ad, is difficult to add into these models because of this. These, on the other hand, can be critical components of the customer journey.

2.     Data Manipulation

None of these models can provide you a complete picture of the client journey. As a result, marketers will need to use a variety of models and then correlate the data from each to get the most accurate results. The sheer volume of data and the complexity of the models provide a problem, with many marketing analysts spending more time gathering this data into a usable format than generating significant insights. The requirement to use various attribution models adds to the difficulty.

3.     External Factors Have Limited Visibility

Unlike media mix modelling, which examines aggregate data, MTA examines user-level information. Marketers do not have visibility into external factors that may effect marketing efforts and conversions, such as seasonality, unless they incorporate aggregate data.

Multi-touch attribution models are important, yet they are insufficient on their own. This is why marketers should use a single marketing measuring system. Unified measurement combines MTA’s person-level data with media mix modeling’s aggregate data to provide a holistic view of marketing interactions and trends.