Three ways to link Content and Customer Behaviour

Almost everyone would agree with the statement that 'content must be relevant', but what is relevance? According to Wikipedia, 'relevance' describes how pertinent, connected, or applicable something is to a given matter. So it's relevant if it serves as a means to a given purpose, according to Laura Patterson, President for VisionEdge Marketing, who here examines how the relevance of your marketing content can be leveraged to change customer behaviours.

Let's consider the purpose of content which is to positively impact customer or employee behaviour, such as increasing purchase frequency, purchase velocity (time to purchase), likelihood to recommend, productivity, etc.

Unfortunately when we ask marketers and others how they measure content relevance, we often hear, "we base it on response rate." If the response rate meets the target, then we assume the content is relevant or vice versa. While we intuitively believe that the more relevant the content the higher the response will be; measuring response rate is not the best measure of content relevance. There are many factors that can affect response rate, such as time of year, personalisation and incentives. Also, in today's multi-channel environment we want to account for responses or interactions beyond what we might typically measure such as click-throughs or downloads.

So, what is the best way to measure relevance? There are a number of best-practice approaches for measuring relevance, many of them are complex and require modelling. For example, information diagrams can be an excellent tool. But marketers who are spread a bit thin need a simpler approach. The following three steps provide a way to tie interaction (behaviour) with content. It will be critical that you have a good inventory of all your content and a way to define and count interactions. Once you have this you'll be able to create a measure of relevance.

The process and equation includes the following:

1. Count every single piece of content you created this week (new web content, emails, articles, tweets, etc.). We'll call this C.
    
2. Count the collective number of interactions (opens, click-throughs, downloads, likes, mentions, etc.) for all of your content this week from the intended target (you'll need to have clear definitions for interactions and a way to only include intended targets in your count). We'll call this I.
    
3. Divide total interactions by total content created, so R = I/C.

To illustrate the concept, let's say you are interested in increasing conversations with a particular set of buyers and, as a result this week, you:

• Posted a new white paper on a key issue in your industry to your website and your Facebook page.
   
• Tweeted 3 times about the new white papers.
   
• Distributed an email with a link to the new white paper to the appropriate audience.
   
• Published a summary of the white paper to 3 LinkedIn Groups.
   
• Held a webinar on the same key issue in your industry.
   
• Posted a recording of the webinar on your website, Slideshare and Facebook page.
   
• Held a tweet chat during the webinar.
   
• Tweeted the webinar recording 3 times.
   
• Posted a blog on the topic to your blog.

Tally it all up, and we'll count this as 17 content activities.

For this very same content, during the same week, you also had:

• 15 downloads of the white paper from your site;
   
• 15 retweets of the white paper;
   
• 15 Likes from your LinkedIn Groups and blog page;
   
• 25 people who attended the webinar and participated in the tweet chat;
   
• 15 retweets of the webinar;
   
• 15 views of the recording on Slideshare.

So that counts as 100 total interactions. It's both possible and likely that some of these interactions are from the same people engaging multiple times, and you may eventually want to account for this in your equation.

But, for starters, you can now create a content relevance measure:

R = 100/17 = 5.88

This is a very different view then if we had only measured response. Using the same information, had only measured the response rate, we might have only counted the downloads and attendees, 40, so we might have had the following calculation:

R = 40/17 = 2.35

"As you can see the difference is significant. By collecting this data over time you will be able to understand the relationship between the relevance and the intended behaviour, which in this example is increasing 'conversations'," concluded Patterson. "Start thinking about relevance as a key measure for your content marketing. By tracking relevance you will be able to set benchmarks and performance targets for your content and model content relevance for intended behaviour."