Campaign Attribution: Accelerating Revenue Through a Data-Driven Content Strategy

Mperativ introduces Campaign Attribution -- a clear, concise, and interactive way to visualize the strategic value of content and campaigns across the buyer journey

Daniel Raskin
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6
 MIN READ
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November 8th, 2022

Mperativ is committed to solving marketing's biggest strategic challenges. Attribution is often front and center on this list for most marketing and sales departments. That is because marketing attribution has historically been focused on justifying marketing investments at the tactical level. It is most commonly tied to digital advertising and assigning credit to different advertising channels. Marketing attribution has been useful for measuring campaign ROI, but the granular measures often miss the bigger picture strategy.

Revenue Attribution is centered around the alignment of key business functions and the mix of activities needed to jointly meet or exceed a fiscal plan. It requires tracking of key pipeline and revenue objectives and understanding the cross-functional activities needed to maximize sales velocity across the demand engine. 

Marketing leaders are the “point guards” of Revenue Attribution. They are responsible for understanding the mix of activities needed to achieve a fiscal year plan. Revenue attribution requires that marketing leaders focus on three key business questions.

1) Where is my pipeline coming from?

2) Where is my revenue coming from?

3) What cross-functional activities drive sales velocity?

Pipeline and revenue contribution are typically defined prior to the fiscal year and directly tied to executive team compensation. As the stewards of the buyer journey, marketing is best suited for tracking pipeline and revenue contribution. It is also essential for marketing to understand what activities have the biggest moving an opportunity from stage to stage throughout the buyer journey. Enter Mperativ Campaign Attribution.

Introducing Campaign Attribution with Mperativ

Campaign Attribution tries to measure very specific data points, such as the value of individual clicks, downloads, and interactions, and relate them to their influence on the bigger picture. Because of this, attribution can be notoriously tricky to implement and interpret.

The simplest and  most common marketing attribution models are first-touch and last-touch attribution. Credit is assigned to the first channel a lead engaged with, or to the last touchpoint before a sales opportunity is created. These models have gained popularity because they’re much easier to implement, as they only require you to track one or two points in time for each lead. That said, they fail to connect marketing or sales activity to revenue.

Except for the quickest B2B sales cycles, a buyer typically has many interactions between initial engagement and a sale. Buyers continue to interact with marketing assets even once they’ve been “handed off” to the sales team. The first touch can thus be a misleading measurement of which programs were actually meaningful.

To address these problems, the Mperativ solution is a multivariate (MV) attribution model that measures customer interactions at each stage of the demand engine. 

The main decision to be made when designing a MV attribution model is how to weigh different touchpoints. Simple Linear MV models credit every single touchpoint equally, which makes them easiest to put into place. This approach does measure more data than a first-touch or last-touch model, but it doesn't necessarily provide a more clear picture. It remains unclear which touchpoints mattered amid the noise.

There are more complex MV approaches that require giving custom weightings to different touchpoints. Factors could include whether the touchpoint caused a lead conversion, how many total touchpoints occurred, or how much time elapsed between touches. This is a more sophisticated approach, but it becomes a significant and subjective work effort to determine what weightings make sense, implement the design, and continuously interpret the results.

What makes the Mperativ approach to MV attribution unique is that the results are easy to understand. It focuses on both the first response prior to account creation, and the last responses prior to the conversion at each stage of the demand engine. Mperativ avoids the inflation of attribution metrics by crediting conversions at the account and opportunity level, rather than crediting every conversion of an individual lead. This provides a better sense of a touchpoint’s true efficacy, since it will only be credited with advancing potential deals.

Campaign Attribution Visualization

To track Campaign Attribution, Mperativ has released an interactive visualization that shows  campaign influence at each stage of the buyer journey. Our Campaign Attribution model tracks opportunity conversions as they advance through the stages of the Revenue Supply Chain.

Campaign Attribution is organized by the Salesforce campaign hierarchy of campaigns and child campaigns. A “Webinar Registrations” parent campaign may have many child campaigns tracking specific webinars. This helps marketing teams to implement best practices around campaign tracking.

Because there can be five levels to the Salesforce campaign structure, marketing teams can choose to organize their campaigns based on fiscal year, business function, and channel, before getting to the specific campaign level. The below example shows how a customer could navigate up and down the campaign hierarchy.

The Campaign Attribution Insight provides a heatmap for each stage, making it easy for users to quickly sort and visualize which campaigns are performing well at each stage of the buyer journey.

Market Segments and Date Ranges filters allow for diving deeper into understanding campaign attribution.

Mperativ Campaign Attribution provides a better way for marketing leaders to understand their content and campaign strategy, align objectives across the business, and invest in activities that have the greatest impact on sales velocity.Interested in seeing Mperativ’s attribution capabilities in action? You can request a demo using this link.

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