The Journey to Conversion: Unmasking the Influence of Attribution Models

Lately, I've been talking to many startup founders and noticed something important in today's Performance marketing world. We often overlook the significance of our attribution strategies, considering them as mere numbers for reporting. However, I've learned that with most campaigns relying on machine learning algorithms these days, our attribution strategy plays a pivotal role in the success of our marketing channels.

So, I decided to delve into various attribution models and their selection process. There's no one-size-fits-all solution since different industries and channels have unique customer behavior's that require different attribution approaches. In simple terms, we must pick the right attribution model like choosing the right outfit for each occasion. So I decided to uncover the mysteries of attribution to boost the performance of our campaigns!

Let's start by discussing what an attribution model really is. At its core, an attribution model serves as a framework or a set of frameworks that empower marketers to determine the appropriate credit each marketing channel should receive for a conversion in a customer's journey.

Now, why do we need attribution models??

As we pour our valuable time and resources into diverse marketing efforts, it becomes crucial to understand which ones yield the highest return on investment for our business. This is especially true for channels like SEO or top-of-the-funnel campaigns, where the full benefits might take months, if not years, to materialise. In essence, attribution serves as a guiding light for marketers to understand:

1. Which marketing channel plays a vital role in driving growth by generating the maximum conversions?
2. How to smartly allocate marketing budgets to ensure a high return on ad spend?
3. Gain insights into customers' journeys and identify any gaps that may need attention.
4. Provide the right input data to the Ad platform's machine learning algorithm, enhancing campaign performance.

In a nutshell, attribution empowers marketers to make informed decisions and navigate the intricate landscape of marketing success with confidence.

Now let’s dive into the world of different attribution models, step by step. To help understand, we'll use a practical example and apply various attribution models to see how they work.?

EXAMPLE

Meet Sahil, a watch enthusiast who stumbled upon a super watch brand while browsing Instagram. Intrigued, he searched for the brand on Google to explore their collection. Although he wasn't in immediate need of a watch, the brand left a lasting impression on him.

A week later, Sahil's interest was reignited when he spotted a celebrity flaunting the same watch on Pinterest. That's when he made up his mind to buy the watch when he received his salary next month.

Finally, on the first of the month, Sahil directly visited the brand's website and made the long-awaited purchase.

So, let's analyse the various touch points in Sahil's journey - the Instagram discovery, Google Ads exploration, Pinterest inspiration, and the eventual direct website visit leading to the purchase. Each step played a significant role in shaping Sahil's decision-making process.

Now, let's see how you will see this journey on various attribution models.

• First click attribution?

In this marketing attribution model, 100% of the conversion credit is assigned to the first marketing channel a customer interacts with. In our example with Sahil, Instagram was the initial channel of interaction, and thus it receives the entire credit for the conversion. It doesn’t matter that the customer then interacted with 3 more channels before converting.

This attribution model is helpful if your brand tends to convert customers immediately. In this case, the first touchpoint is extremely important. If your brand's? goal is to bring in new top-of-the-funnel customers, the First Interaction Attribution Model is a great way to evaluate the effectiveness of each channel. It’s also a great measure of which channels worked best for brand awareness.?

• Last Click Attribution?

In this marketing attribution model, the last touch point a customer interacts with receives 100% of the conversion credit. As in the case of Sahil, the final channel he engaged with was Direct, making it the sole recipient of credit for the conversion. Subsequent interactions with three other channels do not affect the credit allocation.

It's important to note that this last-touch attribution is the default method used in most platforms, including Google Analytics. Hence, when analysing standard Google Analytics reports, each conversion goal is attributed to the customer's last interaction with the brand.

• Last Non-Direct Attribution

In this marketing attribution model, 100% of the conversion credit is assigned to a single interaction (similar to the options we explored above). However, this model eliminates any “direct” interactions that occur right before a customer converts.

In our example. Rahul saw a Pinterest ad and then came to the website directly to make the purchase. The last non-direct attribution model will assign this value to the Pinterest touchpoint.?

And so, this marketing attribution model considers which channel prompted a customer to visit your client’s website directly.

• Linear Attribution

In this particular attribution method, the conversion credit is evenly distributed among all the touchpoints a customer interacts with before making the purchase. For instance, in Sahil's case, the conversion credit will be evenly divided between Instagram, Google brand search, Pinterest, and Email marketing.Numerically speaking, each touchpoint gets an equal conversion credit of 25%

• Time Decay Attribution

In this attribution model, just like the previous method, conversion credit is distributed among multiple events. However, this model takes into account the timing of each brand interaction. It gives more importance to later touchpoints, assigning them higher conversion credit, while the initial interaction receives less credit. In other words, as we move closer to the final interaction, the credit progressively increases, granting the last interaction the highest weight in the conversion process.

• Position Based Attribution

The position-based attribution model, also known as U-shaped attribution, allocates conversion credit as follows:

1. The customer's first touchpoint receives 40% credit.
2. The last touchpoint before conversion also gets 40% credit.
3. Any other brand touchpoints that occurred between the above stages receive 20% credit.

In Sahil's case, Instagram and Direct will each receive 40% credit, while Google Brand Search and Pinterest will each receive 10% credit. This method highlights the significance of both the initial and final interactions, while also acknowledging the impact of intermediate touchpoints in the customer's journey.

• Data Driven Attribution

Unlike the rule-based attribution models discussed earlier, data-driven attribution takes a different approach. Instead of using a fixed model to assign credits to touchpoints, data-driven attribution leverages machine learning technology to create a customised model for each business. This model is based on real customer data, reflecting their actual journeys.

While traditional rule-based attribution only examines paths that lead to conversions, data-driven models analyse both converting and non-converting paths. This approach allows marketers to understand how each touchpoint influences the likelihood of a customer converting, rather than relying on predefined rules to allocate credits to conversion path touchpoints

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Now, How do you pick the attribution model that works best for your business? Here you need to answer a few questions -

• How would you describe the complexity of your customer journey?

First, you need to evaluate the intricacies of your customers' journey towards making a customer click on the “buy button”. If your customers tend to engage with multiple touchpoints before converting, you might find data-driven or position-based attribution models to be more suitable than the traditional single-touch models. These sophisticated models can handle the complexity of the journey, providing a more accurate picture of how different touchpoints contribute to conversions.?

• What specific goals do you have for your brand?

Consider your primary business objectives. Are you aiming to increase brand awareness, drive more conversions, or focus on customer retention? Different attribution models emphasise different stages of the customer journey, so select one that aligns with your specific goals.Here are some recommendations based on common objectives:

1. Brand Awareness: If your primary goal is to increase brand awareness and reach a broader audience, the first-click attribution model might be suitable. It emphasises the initial touchpoint, which plays a significant role in introducing customers to your brand.
2. Lead Generation: For businesses focused on lead generation, consider the linear attribution model. It gives equal credit to each touchpoint, acknowledging the contribution of all interactions throughout the customer journey.
3. Conversion Optimization: If your goal is to optimise conversions and understand which touchpoints have the most significant impact on driving sales, the data-driven attribution model is ideal. It uses machine learning to analyse the entire customer journey, providing insights into the most influential touchpoints.
4. Customer Retention: For businesses aiming to retain and nurture existing customers, the time decay attribution model could be beneficial. It assigns higher credit to touchpoints closer to the conversion, emphasising the interactions that encourage customer retention.
5. Multi-Channel Effectiveness: If your marketing strategy involves multiple channels, the position-based attribution model, also known as U-shaped, might be a good fit. It gives more credit to the first and last touchpoints, recognizing both the initial awareness and the final conversion.

• What marketing channels are you using for your brand?

Take into account the mix of marketing channels you use. Some attribution models work better for certain channels than others. For example, first-click attribution might be more relevant for top-of-the-funnel channels like social media, while data-driven attribution can provide valuable insights for multi-channel campaigns.

Remember, there is no one-size-fits-all attribution model. Your choice should align with your business objectives, marketing strategy, and customer journey complexity. It's crucial to experiment and analyze the performance of different models to find the best fit for your specific goals.

Finally how can you check the data across different attribution models on GA4 please check the following link - https://bit.ly/GA4_Attribution