Developing and implementing a marketing attribution model is a modern-day practice many marketers use to gain a comprehensive view of a customer’s journey.
When tracking multiple steps, from initial engagement to the final purchase and all points in between, marketers salivate at the opportunity to understand customer data derived from those touches.
Who wouldn’t be excited at the prospect of identifying exactly what led to a customer’s making a purchase decision?
Though marketers continue to improve and refine the process, one challenge remains: how to marry offline and online marketing attribution to truly gain meaningful insight.
More specifically, how do marketers use a reliable online tool such as Google Analytics (which provides massive amounts of online customer data) and at the same time properly measure customer actions that occur offline.
The Offline/Online Conundrum
The launch of Google Analytics opened the door for marketers to dive headfirst into online marketing. They were able to provide detailed customer insight not previously available in more traditional advertising.
Granted, those actions and transactions required online engagement, but as use of the Internet grew, every view, click, and purchase could be recorded and analyzed.
Historically, marketers have not been able to track a person’s every move offline. Once a customer viewed a physical advertisement—a television, billboard, or print ad—there was no way to determine how that ad influenced the customer at the individual level.
And as online marketing grew, so did frustrations regarding the inability to track offline behavior.
And that’s the problem: We live in an offline and online world where engagements are mixed and purchasing behavior is influenced by both analog and digital events. So how do marketers know which customers are influenced by offline, online, or both?
That’s the million-dollar question.
The marriage of offline and online attribution has begun to evolve. Marketers and the companies they work for have begun unravelling the mysteries of how offline and online attribution contribute to the buying decision.
Marketers are now harnessing the power of CRM solutions, such as Salesforce Sales Cloud, with Google Analytics 360. Salesforce is one of the premier CRM platforms and has built a reputation over the past 20 years as a go-to platform for understanding prospect and customer behavior. Google Analytics 360, Google’s advanced Web analysis tool that combines reports, queries, and attribution in a single place, is used both by enterprise teams and by marketing experts to gauge online activity, trends, and behavior derived from online campaigns.
Marketers can now import data from Sales Cloud directly into Analytics 360, allowing for an offline-online combination. That may seem fairly straightforward, but the integration of the two goes further. Sales teams don’t have to manually input data from Sales Cloud into Analytics 360. Instead, Goals are created in Analytics 360 based on the different types of individual Sales Cloud events.
In other words, once information is input into Sales Cloud, it can automatically be updated into Analytics 360 based on criteria set up to gauge the performance of the various marketing channels being used—offline and online. Sales-related engagements—whether phone calls, office visits, golf outings, and more—are entered into Sales Cloud as before but are then automatically updated into Analytics 360.
With the integration of these two platforms, marketers can now optimize their digital campaigns. That optimization then enables marketers to have a comprehensive, 360-degree view of the entire customer journey, whether touches occurred offline or online.
CRM data is not the only means of integrating offline data into Google Analytics. Brands might offer a variety of customer reward programs, possibly in partnership with a branded credit card that enables marketers to track offline behavior.
For example, how many times did a customer’s fleet of vehicles fill up at a fueling station? That information can be obtained and automatically input into Google Analytics directly from a database that collects the card data. That data would also include unique customer information.
Marketers can now determine when and where customers went and what they purchased. Furthermore, thar behavior can be further analyzed to determine which online or offline campaign had influence on the actions of that customer.
The primary objective of marrying offline and online attribution is to derive specific return on ad spend (ROAS) data that helps determine future campaigns and hopefully results in increased sales.
In that calculation of which channels derive the most return for an organization’s marketing spend, valuable offline attribution data is as good as gold, helping the organization intelligently allocate its ad spend.
For too long, B2B practitioners have disregarded offline behavior. That wasn’t because of a lack of interest but, rather of the difficulty in knowing how to properly track and attribute such behavior.
Now that marketers can determine how offline behavior affects the customer journey, more organizations will look to combine it with online data. And marrying offline to online marketing data will result in increased harmony between the two data sets, providing greater customer understanding—and increased revenue.
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