How does attribution modeling work, and why does it matter?

TLDR: Attribution modeling helps marketers understand which touchpoints in a customer’s journey contribute most to conversions, enabling optimized marketing spend, improved customer insights, better ROI measurement, enhanced cross-channel strategies, and data-driven decision making.

Learning how your marketing endeavors are helping with conversions is more important than ever given the environment we are in. Guess what comes next? Yup, you heard it right, the form of attribution modeling – and this powerful tool is often used to solve the mystery of any customer’s journey and to enhance the marketing strategies in the process. Now, let me explain more about attribution modeling, how this process looks like and why it is critical for your organisation.

What is Attribution Modeling?

However, attribution modeling can well be defined as a technique that defines which marketing initiatives a customer has engaged with on his or her way to conversion. It is rather similar to investigation when one tries to find out, knowing just some of the facts, what factors really drove a customer to a purchase or to follow a specific course of action.

How does Attribution Modeling Work?

Think of the customer journey map as dots that need to be joined to create the big picture. With attribution modeling you can draw a line between these dots and would show which of these points, or marketing touchpoints, had greatest impact in causing the conversion. Here's how it typically works:

1. Data Collection: To begin with, you collect every interaction your customers have had with your business across the multiple contact points – social media clicks to email opens to web visits.
2. Model Selection: Then you select an attribution model that is appropriate for your business needs. Models are of different types which will be discussed in a while.
3. Analysis: The chosen model then assigns credit for the conversion across the different touch mentioned earlier based on its model.
4. Insights Generation: Lastly, you make conclusions based on the data gathered and it allows to determine which channel and strategies are the most effective in generating conversions.

Types of Attribution Models

There are several attribution models, each with its own way of assigning credit:

1. First-Click Attribution: In fact, whatever positive credit can be given to the first touching point a customer has made.
2. Last-Click Attribution: This is usually the last point of contact before the buyer converts and receives all the glory.
3. Linear Attribution: Distribution of credit occurs equally with all of the touchpoints involving credit.
4. Time Decay: Multiple touchpoints are differentiated with recent touchpoints given more credit than earlier ones.
5. Position-Based (U-Shaped): Last and first touchpoints are awarded 40% while the middle ones are awarded 20%.

Understanding Why Attribution Modeling Matters

Well, at this point you could probably ask me: “Why should I care about all of this?” Well, attribution modeling matters for several compelling reasons:

1. Optimized Marketing Spend: Because you know which channels and tactics are driving conversions the most, you can then make proper budget distribution. No longer will it be appropriate to fund approaches that have no measurable returns on investment.
2. Improved Customer Understanding: Attribution modeling provides key information on your customer’s behavior and the factors which affect those behaviors. A marketer gets to know this, and it feels like gold when developing better marketing strategies.
3. Better ROI Measurement: It means you are able to quantify the return on investments for the different marketing activities channeled to your business, which makes it easier for you to justify the spending done and market the value of your work.
4. Enhanced Cross-Channel Strategies: Sophisticated knowledge of how each channel can work simplifies the creation of integrated and efficient multi-channel communications.
5. Data-Driven Decision Making: Instead, what you’re doing at the end of the day is not relying on your own intuition, but on statistics experienced via attribution modeling.

Types of Attribution Models

There are several attribution models, each with its own way of assigning credit:

1. First-Click Attribution: In fact, whatever positive credit can be given to the first touching point a customer has made.
2. Last-Click Attribution: This is usually the last point of contact before the buyer converts and receives all the glory.
3. Linear Attribution: Distribution of credit occurs equally with all of the touchpoints involving credit.
4. Time Decay: Multiple touchpoints are differentiated with recent touchpoints given more credit than earlier ones.
5. Position-Based (U-Shaped): Last and first touchpoints are awarded 40% while the middle ones are awarded 20%.

Understanding Why Attribution Modeling Matters

Well, at this point you could probably ask me: “Why should I care about all of this?” Well, attribution modeling matters for several compelling reasons:

1. Optimized Marketing Spend: Because you know which channels and tactics are driving conversions the most, you can then make proper budget distribution. No longer will it be appropriate to fund approaches that have no measurable returns on investment.
2. Improved Customer Understanding: Attribution modeling provides key information on your customer’s behavior and the factors which affect those behaviors. A marketer gets to know this, and it feels like gold when developing better marketing strategies.
3. Better ROI Measurement: It means you are able to quantify the return on investments for the different marketing activities channeled to your business, which makes it easier for you to justify the spending done and market the value of your work.
4. Enhanced Cross-Channel Strategies: Sophisticated knowledge of how each channel can work simplifies the creation of integrated and efficient multi-channel communications.
5. Data-Driven Decision Making: Instead, what you’re doing at the end of the day is not relying on your own intuition, but on statistics experienced via attribution modeling.