Why You Need to Focus on Sales Attribution Right Now

Today's marketing teams require a multi-channel approach to carrying out both online and offline marketing campaigns. While utilizing multiple channels enables marketers to personalize a customer's sales journey throughout the sales funnel, there are some unique challenges when analyzing a particular marketing campaign and its ROI.

One key metric to determine your marketing ROI is through attribution. If your company is not focusing on sales and lead attribution, here is why it should be at the forefront of your marketing campaign.

What is Attribution?

Attribution indicates how prospective customers enter your sales funnel. Likewise, it serves as a touchpoint of customer experiences throughout the buyer's journey. It specifies what door they came through, what channels and messages resonated with them the most, and what was the deciding factor that led to a purchase.

A common flaw for many businesses is they fail to clearly understand attribution, leading to a lack of understanding of which sales tactics and initiatives are working best for their bottom line. Focusing on lead and sales attribution can help your business determine where it is getting the most ROI for your marketing dollars, and what acquisition channels are the most valuable.

Why is Attribution Important?

Attribution programs require marketers to aggregate consumer data across all levels of your marketing channels. The data is then normalized and properly weighed to give your business better insight into the customer's decision-making process.

​For instance, if a potential customer receives both an email ad and a display ad, but only clicks on the promotion from the email, it indicates to your marketing team the email was more effective at enticing interest for your good or service for that particular customer.

Understanding attribution can improve your business' decision-making process. Attribution helps you determine which channels are better at generating new leads, or which channels are more effective at converting leads into finalized sales. If you find your promotional emails are generating more leads, then you can allocate more resources to your email campaign.

To achieve efficacious attribution requires advanced marketing analytics that can take a large amount of data and convert it into personal-level insights, which you can then use to optimize your marketing campaigns.

Benefits of Effective Attribution

• Optimized Marketing Spend: Attribution models give marketing teams insight on how to best spend their marketing dollars by indicating which touchpoints garner the most engagement from users. With this information, marketers can adjust their budget and media spend accordingly.
• Increased ROI: When you have effective attribution insight, your marketing team knows how to reach the right customers, with the right message, at the right time, which ultimately leads to higher conversions and higher ROI.
• Enhanced Personalization: Marketing teams can also use attribution data to better understand which marketing channels and company messages better resonate with individual customers, which leads to more effective targeting throughout the buyer's journey.
• Better Product Development: Individual-level attribution enables marketing teams to better understand the personal needs of their customers. These personalized insights provide a valuable reference when updating a product that targets the functionality customers want.
• Optimized Creativity: Attribution models can also optimize the creative elements in a marketing campaign, which enables marketers to hone in on their visuals and message. A solid understanding of your messaging helps your company better communicate with users.

Avoid the Pitfalls 

​Despite the many benefits attribution can bring to your business, some common pitfalls can obscure the success of marketing campaigns. To ensure you are getting the most valuable insight from your data, these are the common mistakes marketers should avoid when using attribution models:

• Correlation-Based Bias: When analyzing the customer's journey, attribution models are sometimes subject to correlation-based bias, which can make one event look like it influenced another, when that may not be the case.
• In-Market Bias: In-market bias refers to customers who were in the market to buy a particular product, regardless if they saw your ad or not. The ad may not have been a deciding factor in the final purchase. However, it gets attribution credit for converting the user anyway.
• Cheap Inventory Bias: Cheap inventory bias gives an inaccurate view of how your media is performing, making it look like it influenced the conversion rate when it might not have played any role. For example, cheap inventory falls under most people's price range, while more expensive inventory has a much more limited market. Therefore, there could be a correlation between cheap inventory and someone buying your product, rather than an ad leading to conversion. 
• Digital Signal Bias: Digital signal bias occurs when attribution models do not factor in the relationship between offline sales and online activity. Marketers must make optimized decisions on both offline and online data, not just the data they find online. If you do not take offline sales into account, you do not fully understand the impact of your online marketing campaign, thus creating bias.  

Attribution Models

Single-touch Models
First-touch attribution assumes a customer chose to convert after the first advertisement they came across. Therefore, it gives attribution to the first touchpoint, regardless of any additional messaging subsequently introduced.
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Last-touch attribution gives entire attribution credit to the last touchpoint the customer interacted with before finalizing the purchase. It does not take into account any prior engagements. Both single-touch models fail to account for the broader customer journey.

Multi-touch models
Multi-touch attribution models look at every touchpoint a customer engages with throughout the buyer's journey. Therefore, multi-touch models are more accurate at depicting the efficacy of your marketing efforts. These models are different by how they divide credit between touchpoints. These include:

• Linear attribution models record each touchpoint the customer engaged with leading up to the purchase. It weights each interaction equally, giving each message equal credit for driving the conversion rate.
• U-Shaped models score engagements separately, noting some have more of an impact than others along the buyer's journey. The lead conversion and first-touch are both accredited with 40% weight while dividing the remaining 20% among all the other touchpoints.
• Time Decay models also weigh each touchpoint differently. In this case, touchpoints closer to final purchase weigh more than those early on in the buyer's journey.
• W-Shaped models are similar to the U-shaped model. However, it incorporates one additional core touchpoint in the center. Therefore, the W-shaped model credits first touch, lead conversion and opportunity creation with 30% weight, while dividing the remaining 10% among other engagements.

How to Improve Your Sales Attribution

Sales and lead attribution are crucial aspects for your business, and knowing how to accurately gauge your customer's journey is paramount.  Want to learn more, but not sure where to start and need some expert advice, check out our website to view our informational webinars, or sign up for our weekly newsletter.

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