Content marketing and analysis is an ongoing process of testing and learning to understand what a specific audience segment finds valuable. April Wilson’s recent insightful piece on content marketing analysis using Google Analytics looked at variables such as time on site and bounce rate.
Before we dive into tips for informing the social content analysis process, ask yourself a question:
What good is all your data if the end recipient doesn’t understand what you’re trying to say?
Making your Data Resonate
Let’s take a look at the process for content analysis, and how your data can resonate more closely with your marketing audience. First and foremost, like all marketing, social content should be driven by:
- A strategy based on an understanding of goals, audience needs and interests
- A content infrastructure to support workflows and approvals
Monitoring tools such as Sysomos and search behavior tools such as Moz’s Fresh Web Explorer can help navigate and create direction when it comes to listening and uncovering what specific groups of people are interested in. This in-depth competitive research will uncover how audiences are using content to engage with similar segments and should drive social content strategy.
Social content strategy can take many forms. I prefer identifying specific high-level content categories in alignment with a business or brand goal and creating subcategories within each main category, based on social monitoring and search insights, followed by meta-tags for detailed tracking.
For example, if you are a fashion brand specializing in bold prints consider this format:
|Trends||Style Advice||The do’s and don’ts of Pattern Matching|
Once the content strategy and data sets are defined, the following ongoing activities should take place:
- Content Development
- Analysis & Insights
- Informing content development based on learnings
To effectively categorize, publish and measure, you can create an excel sheet with all data points and import raw data, or use a tool such as SpredFast. If you are running the excel sheet route, consider data points such as; network, category, subcategory, meta tags, posts (the actual content), impressions, comments (such as replies), likes (including favorites), shares (and retweets or regrams), clicks and total engagement.
In order to be effective in this initiative, resource collaboration is critical. Depending on the structure of your organization, no matter the size – enterprise or small business – this is a collaborative effort. In other words, content developers must interact with analysts.
Let’s take a Look at Activities
The first two pieces are dependent on marketing strategists and content developers; however, they are important parts of the process. Using SpredFast as a sample tool, here’s a glimpse:
1. Create Content
While this leans less on the data team and more on marketing strategists and content developers, create content based on the content strategy with an understanding of what is currently being discussed across the web. Searching by topic through key phrases (your brand, competitors and topical), in addition to filtering photos and more will ensure content aligns with what target audiences are interested in.
2. Publish Content
When the community manager uploads content within the publishing tool, they must tag appropriately through what SpredFast calls “content labels.” This will allow you to later track success of specific content batches.
3. Analyze Content Performance
Understanding content performance is critical and done by looking at time frames, channel and content labels. Though there are various approaches, here are three to consider:
- Look at all social channels to gain a holistic view of activity
- Focus on specific networks – for example, what happened on Twitter
- Filter specifically across date, content label and initiatives (E.g. customer care)
Each of these methods can be paired against specific data points; – engagement, fans, impressions and reach, to capture insightful metrics.
Some brands have multiple agencies or individuals running social in order to achieve separate goals. When in this scenario, or when simply looking to measure specific content types, the label feature will also laser focused targeting to uncover how a specific content owner’s assets are performing.
Tips for Maximizing your Analysis
Here are a few key tips to keep in mind when trying to maximize your analysis and delivery across every tool or excel sheet being used:
1. Insights should solve a specific problem
- Ensure insights are relevant to the group you are presenting to and solve a specific,real problem the marketer is aiming to solve (the question should be posed early on). In addition, “Whatever is shared should be able to stand on its own – so the marketer can parrot your insights as they make the case with their stakeholders for their next course of action (making the data visual is very helpful, as is using plain language)”, says Digitaria’s VP of Analytics, Karen Bellin.
2. Quantitative learnings should be easy-to-understand
- Organize your content by the highest performing, particularly useful when in excel, followed by analysis per channel as each network has a different utility.
- Visualizing the content that performed the best and worst is helpful for content developers to understand areas they need to focus on.
- Pinpoint what may be attributed to spikes in performance. Was there a compelling title? Was the content tied to a current event? Show a time grid with stories against spikes (title and link).
3. Qualitative Insights Should Assign Action to Specific Individuals
While a quantitative analysis will focus on the numbers, sift through comments and identify interesting feedback to support various parts of a business – from the research team to PR, writers, creative and more. What types of things are people talking about? Categories? Specific topics? Positives? Complaints? An idea for a new product design?
From there define whom this feedback should inform. For example, if a baked goods company published a post about the most popular flavor of cookies this season, responders may share all types of feedback including the following (which looks at positive and negatives):
- New flavors they are interested in trying > share with R & D
- Positivity and excitement which may indicate an opportunity to develop a larger campaign > share with social strategists
- Negative company bashing > share with PR
- Complaints about a recent batch of cookies they purchased > share with customer service
- Threats > share with legal team
A simple approach for ensuring these learnings are shared across departments on the brand side is to create one slide for each group indicating:
- Who to share this slide with (in the title)
- News, date, link
- Learning – what, so what and now what
- Action required
- Any relevant screenshots or imagery to support the point you are aiming to make
Based on the content labels, analyzing performance of each content type should inform future set up.
4. Inform Content Development
Share content performance and new topical opportunities with writers to inform future asset development. Show them how they can use the data extracted. Remember, writers are not analysts, so they need a simplified way to understand insights. Simple graphs, charts and learnings versus a batch of data in an excel sheet will likely resonate with non-analysts.
Now that Marketers Can Make Actionable Sense of Your Insights
It’s important for analysts to remember that it’s up to them to make data learnings easily consumable to ensure the individuals assigned to take action on your insights have a clear path to execute against recommendations driven by data.