Although it can be tricky, content reporting needs to be customized to the complicated B2B sales cycle. Here is a look at three different products and their different sales cycles.
In the early 2000s, website owners first started touting the now-common mantra "content is king." Back then, when asked about which content mattered the most on a site and which content mattered the least, content writers would either point to metrics on pageviews or leads generated directly from specific pieces of content. These limited data points guided content writers to focus very heavily on content that converted quickly. But unfortunately, pageviews and direct leads don't really provide enough context for how strong the content is or how it is used in complex sales cycles.
To give one example, let's look at how visitors research and apply for mortgages on banking websites. Our research shows that, on average, users visit the site 3.2 times before starting an application for a mortgage product. When we analyzed the click paths of the first, second, and third visit, we found that some content, such as rates-related content, is viewed repeatedly on each visit. Other content, such as the product comparison pages, is viewed only on the preliminary visit. And finally, the "About Us" content is mostly only viewed on the third visit.
This multi-visit analysis poses a problem to traditional content analytics reporting. In traditional reporting, the "About Us" content might appear as the highest value because it was the last page viewed before the visitor started the application, when in reality the successfully converted customer likely paid much more attention to the rates-related content. This demonstrates that if Web analytics are going to be truly useful in tracking content value, they need to revolve around the sales cycles of the product.
To fully understand how content reporting needs to be customized to the sales cycle, let's look at three different products and different sales cycles.
With each of these sales cycles there are different reporting needs to understand how effective the content is to the users as they research and make decisions. However, there is one common thread - in each sales cycle, content engagement metrics are important in understanding how the copy educates and drives the loyalty of prospects. In monitoring engagement we look at metrics such as the following:
Engagement data is important in understanding the quality of content. However, typical content engagement reports don't take into account the complex sales cycles such as the one described in the third example above (Inventory Management Solutions). When we have multiple users involved in a sales cycle visiting a website multiple times and viewing multiple different pages specific to the visitor's role in each visit, content reporting becomes more complex. In sales cycles like these we need to understand what content is most important to each user role and when in the sales cycles it is most critical. Three reporting techniques help shed light on these models:
With these three types of reporting, we can start to create different models for valuing content in complex sales cycles. If we understand the average length of a sale cycles, which roles are influencers and which are decision-makers, and the average amount of visits in a sales cycle, we can start to develop content scoring models that show how strong content is at generating leads and assisting the sales team throughout the research and decision-making phases.
Content reporting in Web analytics has come a long way in the last few years, helping us to better understand how content attracts and engages users. But most Web analytics platforms focus reporting on very simple sales cycles and do little to help site owners understand how content performs in more complex sales cycles. I'm optimistic that Web analytics platforms and other tracking sources, such as marketing automation tools, will start to offer more insightful reporting for complex environments in the upcoming years.
Image via Shutterstock.
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Mark leads the analyst team to develop ROI goals, data strategies, digital channel reporting, and establish processes for data analysis for EXTRACTABLE clients. Since joining EXTRACTBLE 14 years ago, he has worked on numerous high-profile websites including Yahoo, DirecTV, Visa, FedEx, and HTC. The most trafficked web page that he's ever worked on received 15 million unique visitors in one day, he has run analytics analysis on over 150 sites, and the biggest ROI he's ever seen on a corporate website redesign was > 800 percent. He is an active member of the Digital Analytics Association and has contributed to the DAA Education Committee for over five years.
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