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3 Tips to More Accurately Measure Your Content Effort

3-tips-measure-content-effort

Many people jump into content marketing because they were inspired by all the success stories and case studies they read. You know what I’m talking about, the content marketing for content marketing.

But while content marketing seems straightforward, actually measuring its success can be challenging in practice. Customer journey mapping, attribution modeling, and segmentation can help you improve and more accurately measure your content marketing efforts.

1. Identify and document content goals with customer journey mapping

Before getting into the more technical aspects of measuring your content, it’s paramount that you create clear goals for benchmarking purposes. Without a system of measurement, you won’t be able to make data-informed decisions — and that’s simply no good.

Without a system of measurement, you won’t be able to make data-informed decisions says @jacobwarwick. Click To Tweet

To identify your content goals, use a process called customer journey mapping.

Customer journey mapping is a technique that can help you better understand your customer’s experiences through their interactions and touchpoints with your brand, wherever the customer may be in the lead cycle. It also aligns your content efforts with personas and identifies gaps and optimization opportunities within your content.

First, document the five stages of your customer’s journey: awareness, interest, evaluation, decision, and retention. Using Microsoft Excel or Google Sheets should suffice.

document-customer-journey

Image source: Blast Analytics and Marketing: Customer Journey Mapping

Next, craft goals and key performance indicators (KPIs) for each stage.

For example, your overall goal could be to increase leads 15% or boost white paper downloads by 50%. Regardless, each stage of the customer journey can drive those goals and should have KPIs to keep you on track.

Consider tracking the following KPIs to get started:

  • Awarenesskeyword rankings, impressions, and overall search visibility
  • Interestwebinar registrations, white paper downloads, and marketing-qualified leads
  • Evaluation – quote requests, demos, and sales-qualified leads
  • Decision – conversions and total customers
  • Retention – shares, comments, subscription renewals, and social community engagement

tracking-kpis

Image Source: Blast Analytics and Marketing: An example of what to build in your customer journey map in Google Sheets

After documenting your goals and KPIs, audit your current content and assign it to the appropriate customer journey stage. This will help you create stronger and more realistic goals, while also helping identify gaps in your content coverage.

2. Apply attribution modeling to understand channel performance

Note: Before working with attribution, you must have implemented an analytics platform such as Adobe Analytics or Google Analytics 360 and have your content properly tagged using Google Tag Manager, Tealium, Ensighten, or another tag manager. Without tagging, your data will be insignificant.

The concept of attribution modeling is to assign a set of rules to determine how much credit a touchpoint should receive during your customer’s journey to complete a conversion. That can help you determine how valuable your marketing channels are.

A successful attribution model will help you see how your marketing channels work together to create a lead, conversion, or sale while ultimately identifying where you should invest resources.

Start by finding an attribution model that best meets your needs.

Some common attribution models include:

  • First-touch attribution – full credit is given to first customer touchpoint
  • Last-touch attribution – full credit is given to last customer touchpoint
  • Linear attribution – credit is evenly distributed among all customer touchpoints
  • Time-decay attribution – credit is given to each touchpoint based on the amount of time that passed between the first touchpoint and conversion
  • Participation attribution – full credit is given to each touchpoint that participated in a conversion
  • Position-based attribution – a majority of the credit is given to the first and last touchpoint and any remaining credit is distributed evenly amongst the middle touchpoints

The key is to find a model that balances the data you need without being too complex, which could cause analysis paralysis (particularly with less mature marketing and analytics teams).

For most content marketing strategies, I recommend staying away from first- or last-touch attribution because it doesn’t show the entire customer journey.

If you’re newer to attribution modeling, I would start with the linear or participation attribution model to get a general idea of what touchpoints your customers use before converting.

As your needs evolve and become more mature, you can use a more advanced attribution model such as time decay, position-based, or even a custom solution.

I personally like the position-based attribution model because it stresses the importance of both the first- and last-touch channel, while also considering the complementary channels that lead to conversion.

For example, the first touch could have come through an organic search result to your blog, second touch was a white-paper download, third touch from a social media link, fourth touch from another blog visit, and finally, last touch from a product-spec download. Position-based attribution gives credit to the assisting visits — and helps you identify the value of your channels.

multi-channel-attribution-modeling

Image source: Occam’s Razor, Multi-Channel Attribution Modeling – Avinash Kaushik

If you’re fortunate enough to work with an analytics team, ask them about attribution modeling and whether they have implemented a model of your organization. If you’re on your own, reference these guides for Adobe Analytics attribution modeling and Google Analytics attribution modeling to dive into the specifics. (Disclosure, I work at Blast Analytics and vouch for the content too.)

3. Use segmentation to understand content performance

This section builds a case for why you should use segmentation. For detailed how-to on segmentation, visit these guides for Google Analytics segmentation and Adobe Analytics segmentation.

Segments are subsets of your analytics data that can help you better examine your customer trends by drilling down into your data. You can segment each channel (e.g., only people who have converted, males over 40 who live in Australia), if that’s your prerogative.

Segmentation can become complex, so you should use it to answer specific business questions.

For example, say that you are developing a content marketing strategy for next quarter. The goal is to increase conversions 25% and you’re tasked with scheduling and creating high-converting content.

Start by segmenting visitors who have made a purchase and ask questions such as:

  • What channel(s) attracted these customers?
  • How old and what gender are these customers?
  • Are these customers using a desktop or a mobile device?
  • What content did they read before becoming a customer?

With segmentation, you can answer these questions, identify trends, and better inform your content marketing strategy moving forward.

Segmentation can answer ?'s, identify trends, & inform your #contentmarketing strategy says @jacobwarwick. Click To Tweet

audience-overview

Image source: Google Analytics

Take notes of trends that you identify to inform your ongoing buyer persona research.

You should become intimately familiar with all of the segmentation options that your analytics platform provides so that you can understand what type of marketing questions you can answer with your data — even if you don’t use analytics in your day-to-day routine.

As you begin to mature with your analytics, you can evolve to use more complex segmentation techniques, such as recency, frequency, and monetary (RFM) analysis.

Again, attribution modeling and segmentation can get extremely complex; however, with a game plan and goals to meet, you can begin making more data-driven decisions with your content marketing efforts.

Do you have other methods to more accurately measure your content marketing efforts? Did I miss anything that you could expand upon? Please put your comments and links to helpful resources in the comments.

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Cover image by publicdomainpictures.net via pixabay.com

Please note:  All tools included in our blog posts are suggested by authors, not the CMI editorial team.  No one post can provide all relevant tools in the space. Feel free to include additional tools in the comments (from your company or ones that you have used).