Mapping Content to All Points in the Customer Journey

Posted on by Andrew Ramm

By all accounts, brands will more than double-down on their strategic and financial commitments to content marketing in 2018. This includes accelerating the cadence of blog posts, guides, ebooks, infographics, microsites and videos as a means of finding, converting and retaining customers. As a result, marketers need a clearer understanding of customers’ interests, as content marketing strategies are much more likely to thrive (and be ROI effective) when guided by comprehensive data and analysis.

Meeting the goals of increasing awareness, improving conversion rates, and accelerating the sales funnel requires data insights that inform the alignment of specific content to its influence at each stage of the customer journey, necessary to optimize the ROI and effectiveness of that content.

While still a challenge, the good news for marketers is that the technology to measure customer responses to specific content is a rapidly improving sector of martech. The drive to optimize is growing quickly. As this need increases, marketers must proactively apply deep, data-driven insights into their audience, and resulting content marketing effort for the benefit of their customers and their bottom line.

Investments in content marketing are increasing

In terms of budget and resource allocation, content marketing has achieved prominence. Recent research out of IDC found that marketers in the technology industry now spend 40% or more of their marketing budgets on content marketing initiatives. At the same time, a Content Marketing Institute survey finds 39% of businesses planning to increase their content marketing budget, and 70% looking to increase content production. In part, this is due to increasing competition in paid and social media channels, making it more difficult to generate ROI. This shift has broadened the appeal that content offers for marketers, enabling brands to build customer relationships and develop loyalty that can strengthen the fragile brand-customer lifecycle.

Naturally, a heightened investment in content marketing goes hand-in-hand with a drive to more accurately measure results—turning data about customers and content into an actionable strategy that invests in what works and cuts what doesn’t. The CMO Survey, a multi-organization venture that includes Deloitte and the American Marketing Association, reports that while marketers spend an average of 4.6% of their budgets on marketing analytics today, they plan to increase that spend almost five-fold (to 21.9%) in the next three years. The money is there, but the technological capabilities need to scale with that investment.

Content strategy from marketers’ perspective

Most brands need content to serve as a sustainable and long-term engine of growth, one that nurtures audience relationships and improves the customer experience. When successful, this content will attract, engage, convert, support, retain, and earn advocacy from those customers.

Today, marketers have the ability to measure the engagement and conversion their content enables. However, engagement and conversion aren’t revealing enough when the goal is to use content to support each stage of the customer journey. What marketers need is a clear signal about the long-term results of content marketing, and how each piece of content contributes to winning over prospective customers.

It is also the case that success metrics differ depending on the stage of the customer journey. For example, content that effectively plants the seed for later conversion may display short-term results that understate the eventual impact. At the same time, each piece of content includes so many attributes – topic, target audience, author, word length, media type, promotion and distribution tactics, search visibility, etc. – that analyzing results and discovering formulas for success is profoundly complex, and calls for analytics tools suited to the task.

This is all happening in an environment where marketers must prove repeatedly how their investments directly lead to revenue. For this reason, analytics that measure content’s long-term impact is needed. Doing so will definitively demonstrate the value of content marketing strategies designed to maximize impact throughout the conversion funnel.

Today’s tools

Industry surveys show conclusively that most marketers consider themselves unsuccessful in tracking content marketing ROI and are dissatisfied with their current measurement capabilities. I believe there are two core reasons for this:

1) Current content attribution tools focus on single-session visit and engagement metrics. Over the course of their journey, a customer likely consumes many pieces of content during many sessions that collectively build awareness, trust, loyalty, and advocacy. Measuring the true effect of content on the customer journey requires a long-term viewpoint, which session-based metrics aren’t at all equipped to provide.

2) Current tools are too complex. Most solutions available today are intended for large-scale users with robust analytical expertise and the time it takes to perform the analyses themselves. In fact, The CMO Survey concludes that only 3.4% of marketing leaders believe they have the right talent to fully leverage marketing analytics. Because available solutions are limited in their ability to depict the entire customer journey, marketers often struggle with reporting, attempting to pull data from different sources in pursuit of more complete insights – usually with disappointing results.

A new wave?

It is obvious that marketers need content measurement solutions that are much simpler to use, and offer insights into the true ROI and effectiveness of every piece of content that assists (or hinders) customers through their journey. The marketing analytics technology segment is certainly growing to fulfill this need: IDC predicts this space will grow into a $32.3 billion arena in 2018, with a 12.4% compound annual growth rate. When it comes to the direction of this market segment, IDC also concludes that predictive analytics will become a standard tool for marketers with half of companies using machine learning and artificial intelligence to automate their marketing and sales interactions by 2020.

With more intuitive tools, marketers will have the ability to understand which content is most successful – including the topics, authors, content types and more that customers best respond to and find most useful – and to iterate on their content efforts accordingly. The most effective content will be supported with featured website placement, inclusion in email marketing and in paid ads – with data-driven confidence that those investments will pay dividends as the awareness they earn translates into committed customers.

Andrew Ramm is president at

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