94% of marketers in small businesses and organizations use content marketing. That’s an impressive number. But there is another number that is at least as impressive, if a bit more depressing and scary: 55%. 55% is the number of content marketers that believe their efforts are, at best, having zero impact. A 2014 benchmark study by Content Marketing Institute uncovered a number of facts that are shocking. (PDF)
One of the most striking findings to me is that fact that approximately half of marketers are using content marketing without a plan. Oh, and guess what, the companies that do have a plan are more effective and feel less challenged than the people without plans. So, with nearly half of content marketers operating without a plan, it’s hardly a surprise that confidence is low. We have been doing more content marketing here at ActionSprout and over the past few months so I have been doing some research and testing to learn what methodologies and tactics work best for small companies and organizations.
One of the first places I turned as I started to think about this was my friend over at Attentively (http://www.Attentive.ly), a social behavior platform for marketing teams.
Here is some of what I have learned.
Big Data Or Small Data
Big Data by itself is not the silver bullet and using it doesn’t guarantee a positive outcome. But data is powerful and can be added to your bag of tricks to increase your chances of success even I said data is relatively not really all that big. In fact, in some ways, small businesses and organizations with relatively small data have an advantage over larger ones when it comes to using to inform their content marketing efforts. Unlike their counterparts at larger companies and organization, folks in small enterprises possess the ability to quickly test new methods without going through significant studies or bureaucracy to get a simple test run of an idea approved.
If you can gather some simple data from your email platform, CRM system or site analytics tool, harnessing the power of Small Data can be done quickly. Here’s one example of a successful use of such a methodology.
Clean Out of the Closet
For most brands and organization, their website and newsletters have simply been focused on content – making no use of data. “We typically see marketing and communications teams that write about what they felt was important for the brand at that time. Then they recycle those campaigns every quarter or they focus on regurgitating seasonal items " said Roz Lemieux, the CEO. “The copywriting process was dictated months in advance with a content calendar tied to particular dates based on what they did last year. We try to bring them towards the concept of observing the behavior of their audience.” Needless to say, Roz had a few words of advice for how to be much more audience centric in what we focus our content marketing efforts around.
Here’s the basic process for doing that. First, start with past content. Pull your old articles, campaigns, blog posts and other content out of the closet. Take a look at the last 10 email marketing campaigns and newsletters. Each edition of your newsletter probably includes several articles produced by staff. Determine which article topics were resonating with subscribers and had the best conversion rates. This simple analysis should result in an initial list of 5 or 10 potential topic categories for consideration.
Once you have identified a few good topic categories form your own content, scan recent trade publications and industry blogs or news sites for topics that may be of interest to your audience. This should generate a second group of 10-15 category suspects.
Separate the Wheat from the Chaff
By the time you’re done with two step process, you will have a potential “Interest Graph” from your customers and advocates based on what your targeted audience is most interested in reading and what they value from your brand categories. In other words, you’ll have a set of topics that your audience may very well be interested in. But you’re really know if or how interested your audience really is. So now, it’s time to sanity check the topics and create an interest graph that you can have confidence in.
To do this, create a Matrix with the 15 to 20 topics listed down a spreadsheet as rows and two columns labeled Frequency and Relevance to your organization’s brand.
Next, load into a social data platform (I use Attentive.ly) along with the email addresses of your customers, supporters, donors and prospects. This will enable you to scan the social media posts, shares, and status updates of just your customers, and create “frequency counts” of which topics get mentioned most often over a one or two week period. Finally, fill in the Relevance column with “High” “Medium” and “Low” next to the topics based on how relevant the topics are to your brand or mission. Hopefully you’ll be able to distribute these across your terms so that roughly 1/3 is High, 1/3 is Medium and 1/3 is Low. If I were a fashion apparel retailer, my Content Matrix might look something like this:
Table 1: Content Interest Matrix
Shoes 77 High
Handbags 88 High
David Yurman 34 Medium
Trish McEvoy 47 Low
Skin Type 51 Low
Dry Skin 74 Low
Vacation 92 High
SPF 71 Medium
Humidity 64 Medium
Swimsuit 67 High
What you’re really looking for are topics with high frequency and relevance. These are the topics you’ll want to be focusing on over the next several months.
The Treasure Map
The sample of data from your Interest Graph and Matrix becomes the basis for a new Content Map, showing which content your audience likes most and probably identifies other categories you didn’t know were popular. By designing content around the higher frequency topics, you can expect significantly higher engagement than previous campaigns.
The data analysis will form the foundation of what your writing team focuses it’s energy on. Their job becomes easier and more effective because they can tailor messaging and special offers around the most popular topics.
After playing with this process a bit, I really do believe that any brand or organization can do this. Roz put it this way: “It’s about uncovering your audience’s needs, motivations, emotions, and frustrations. There are certainly more sophisticated approaches like developing full data warehouses. But this simpler exercise is a first step in bringing to life your brand’s content aligned with current social behavior.”
Of course, these predictions must be validated every few months to stay fresh and current. And according to Roz, some ambitious marketers are even assigning these specific interest topics to individual customer records in order to form interest segments. This is a cool idea and enables them to execute individualized messages and offers -- moving a step closer towards behavior-based marketing. It’s a bit beyond our capabilities, today, though.
I want to thanks the good folks over at Attentively for all of their help! If you’re interested, stop by their website, http://www.Attentive.ly for more content targeting and audience tips fueled by social data.