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Setting Up Revenue Attribution Models for Highly Compensated Employees

Nov 09, 2022
5 min read
Finding the right attribution model is a challenge for any business. Here's what you need to know about attribution models for highly compensated employees.

Highly compensated employees (HCEs) are often an individual who has a salary equivalent to the top 20 percent in pay for a company. In addition, an HCE is any person with more than 5 percent ownership of shares in a company. The 5 percent ownership may be split between shares owned by the employee or their immediate family (spouse, parents, grandparents, or children).

What Is Revenue Attribution?

A revenue attribution model matches costs to the revenue received. Furthermore, revenue attribution models analyze and convey what worked and what didn't. They are also used to help companies understand where to better allocate their marketing and sales spend with the objective of saving time and money.

Finding the right revenue attribution model setup for HCEs can pose a challenge for many businesses. To help you get started, we've put together a strategy for correctly setting up a revenue attribution model for HCEs in your company. 

Developing an Attribution Strategy

Setting up a revenue attribution model for a HCE is a process because several steps must be taken to assign the right revenues for multiple marketing and sales efforts. To illustrate, you have to track the origin of a sales lead and determine if it came from an online ad, social post, or something else.

The HCE may also need to perform due diligence to ask how the prospect heard about your company, whether it was from their direct marketing efforts, a referral, or an ad. Nonetheless, marketing attribution works because it helps companies figure out how to make the most of their resources.

The data and insight gained from marketing attribution can help you decide which campaigns are working and which aren't. As a result, you can then refocus your efforts and resources into the sales campaigns to drive the most revenue.

Understanding Customer Touchpoints

An average buyer's journey can span multiple touchpoints from ads to referrals, to social media and more. The route can vary for each lead, which requires each purchase to be treated a little bit differently.

How do you keep track of the effectiveness of the efforts of a HCE? Through revenue attribution and marketing attribution tools. Attributions fall into two different models, single and multi-touch attributions. Multi-touch attribution models allocate touchpoints to all points in the buyer's journey. According to Think with Google, "a company moved to multi-touch models and was able to identify optimizations in digital marketing channels to increase enterprise revenue by as much as 20% in year one.”

Single Touch Attribution Models

Last Touch Attribution

Last Touch attribution refers to the last touchpoint before the sale. This model is a bit off-putting simply because it does not give much credit to any of the previous touchpoints that led up to the sale. At the same time, it is easy to track and configure.

For example, a prospect might see a Facebook ad. After the ad, the prospect might follow a link to your company's social media profiles. Then, the might visit your website, where they download an ebook or whitepaper after providing their contact information. Finally, they click on an email ad and make their purchase. Although, email was the final touch before sale, each touchpoint along the way probably reinforced their decision to buy.

So, the Last Touch model is not the most impactful way to track revenue attribution, but acts as a simplified, easy-to-track method.

First Touch Attribution

First Touch attribution is the opposite of the Last Touch model. This model places all the value on the first touchpoint. When you ask customers, "how did you find us?" usually, the prospect will state the first touchpoint and won't mention that they also traveled through five other touchpoints.

Multi-Touch Attribution Models

Multi-touch attribution model gives credit to multiple marketing channels that contribute to the final conversion. These attribution models can help ensure every touchpoint in a customer's journey is accounted for.

Linear Attribution Models

Linear marketing attribution models assign equal values to every touchpoint through the sales funnel. For example, if a prospect experienced five touchpoints, each would be assigned a value of 20 percent.

This process results in a more comprehensive model because every touchpoint is assigned a value. However, it does not take into consideration how some touchpoints may have influenced the buying decision more heavily than others.

Time-decay Attribution

Time-decay attribution models are algorithmic models that assign different values to touchpoints based on proximity to conversion. The touchpoint closest to conversion is given the highest value, and as touchpoints move farther from conversion, their value decreases.

Position Based Attribution

A position based attribution model focuses on the first and last touch, assigning each 40 percent of the values. Then, it divides 20 percent among the touchpoints in the middle. This falls in line with multi-touchpoint attribution models. Still, it does not place a high enough value on the middle touchpoints, which can skew the results.

Data-Driven Attribution Models

A data-driven attribution model uses machine learning to track large amounts of consumer data. It gives credit for conversions based on how people engage with your various ads and decide to become your customers. 

Utilizing this attribution model will help you understand how multiple marketing channels work together. For example, You might discover that you’re over-invested in a specific channel, and need to switch efforts to a different channel. Many companies are moving to this attribution model.

There Is No Perfect Revenue Attribution Model

The most difficult step in setting up a revenue attribution model is realizing that there is no perfect model. However, there is an additional that can be customized based on your target audience, business objectives, and marketing campaigns. Yet, this can be quite the complex undertaking–especially when you are dealing with analytics and large data sets.

Initially, you may experience a lot of trial and error, but implementing a revenue attribution model helps your company gain a more insightful understanding of customer purchase influencers, buyer journeys, and shopping habits.

It is also important to know how your HCE contributed to each channel and touchpoint. Let's say you opt for a version of the Time-decay model and add a few customizations. In this situation, it is critical to look at your client's behavior and determine which ones are relevant to your business objectives.

Ultimately, you want to determine how your HCE has worked with the sales funnel and customer communication to ensure they make a purchase.

Conversions Vary On Your Marketing Attribution Model

Even soft conversions, such as sending newsletters and whitepapers, sharing a presentation, and multiple calls with the client carry value because they ultimately result in a sale. This is when you should look at how the HCE assisted conversions either by communicating directly with clients and accepting the order or guiding them proactively through the sales funnel.

On the opposite end, consider the touchpoints that aren't providing the results you seek and determine how you can repurpose those resources as high-value touchpoints..

Put It All Together

A revenue attribution model empowers you to take control of your revenue potential with stronger, more intentional sales strategies at every stage of the buyer journey. Over time, it helps you achieve more predictable revenue streams that lead to higher growth.

To achieve these goals, you need the right tools in place to drive success.

Xactly Forecasting® delivers data-informed pipeline analytics to drive consistent sales execution and accelerate predictable revenue.
 

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The Xactly News Team reports on the latest products, events, and market trends taking place within Xactly and throughout the revenue intelligence industry.