Why Content Creators Need Data Analytics
Perched on gilded thrones built on user information, Zuckerberg and Bezos appear godlike. However data (like God) isn’t exclusive to corporations, frameworks and analytics tools enable content creators to perform the same tasks as tech titans. In an Information Age, it’s not enough that content creators simply be “creative”. Fortunately, just as Prometheus gave fire to man, tools exist for content creators to perform the same tasks as tech titans, empowering them to optimise and grow.
- What is data analytics?
- Why creators need analytics
- How to think about data
- Data metrics for creatives
- The analytics value chain
- How to build a data infrastructure
What is data analysis?
Data analysis is the process of collecting and condensing information in order to guide decision making. At a high level, it’s as simple as that. Performing data analysis as a digital publisher or content creator doesn’t require a fistfull of the mind-opening amphetamine in “Limitless”.
Though film is littered with characters and plots in which data analysis serves at the core, they’ve done little to dispel our irrational fear of the topic. Instead, films play to archetypes; depicting analytical thinkers as droll, socially oblivious geniuses. Such intellects rely on a charismatic leader to interpret their madness, deepening the perceived gulf between art and science. Even in films based on true events this is presented as the primary source of conflict.
We see this in ‘Moneyball’, where a baseball team on a shoestring budget overcomes well-funded franchises by replacing “hunches” and “marketability” about players with data-driven decisions. Only by pairing the awkward genius of Jonah Hill with Brad Pitt’s charismatic salesmanship is the team able to catapult a Stone Age Sport into the 21st century when American Baseball with data mining, statistics and predictive modelling. We see the same dynamic play out in ‘Steve Jobs’ (2015), where tensions fracture a relationship between the gifted technician, Steve Wozniak is set into conflict with the creative visionary of Steve Jobs.
Why creators need analytics
Despite what Hollywood would have us believe, creativity and analytics aren’t incompatible. Instead, learning high-level data analysis skills can enrich the quality of your output and provide you a dominant advantage over your competitors. Here are the top benefits basic data analysis skills will provide you:
1. Understand your audience
Do you know which content is receiving the most engagement, when viewers are dropping off and where your audiences are originating from? Basic data analysis on platforms like Google Analytics, Youtube Studio and Facebook Insights delivers an understanding of who and how your fans are consuming your content.
2. Test assumptions
Armed with a greater understanding of your audience, you can experiment with new formulas for creativity. By pairing demographic information like age or location with interests and browsing behaviour, you might: test the ideal time to post, pilot a concept for a new series, or target a specific audience segment more likely to buy from you.
3. Optimise content
Implementing the outcomes of your experimentation supercharges your content. The more insights gained from experimentation, the stickier your content. You can now begin to make more informed decisions on what and to whom you’re crafting content.
4. Competitive advantage
Any content creator versed in data analysis immediately has an edge in a saturated market. Combining analytical and creative skills, applied data analysis creates a positive feedback loop. This recipe for success is the reason Netflix has achieved such dominance in the streaming entertainment industry.
5. Evaluate ROI
In an ideal world creatives could live off the fumes of their creative talents. Unfortunately we’re governed by rules of physics. If you’re to afford both your chai lattes and your prescription of performance-enhancing dexamphetamines, then you’ll want to ensure that your efforts are yielding a sustainable return.
How to think about data
Before starting your journey in data analytics, it’s useful to adopt a data framework. Below is a basic analytics framework that helps you, as a content creator, work with your data. Following a proven approach to analysis means you’re not reinventing the wheel, allowing you to focus your energies in the process of creating content.
If you’re already harvesting data and mining insights, established frameworks like CRISP-DM provide a great blueprint for processing of your organisation’s data. For small businesses just getting started, the below is an easier way to dip your toes into the process of extracting insights from data.
| Step | Stage | Summary |
| 1 | Definition | Identifying an opportunity, a case is made as to what the company seeks to achieve from data analysis. |
| 2 | Collection | Structured data (CRMs, marketing tools, excel spreadsheets and databases like Xero) and unstructured data (social media data) are collected either directly or via API integrations. |
| 3 | Cleaning | Data is handled to make sure it’s valid and accurate. The adage “Garbage in, Garbage out” highlights the need to ensure only correct data is made available for analysis. |
| 4 | Analysis | The mining of insights from a clean set of data. By manipulating data and viewing it in the aggregate, visualisation explores patterns and tells a story. Reports, dashboards, scorecards and charts can be used. |
| 5 | Interpretation | The act of understanding insights and transforming them into meaningful action. This often results in a feedback loop that triggers the creation of a new business case. |
By avoiding the common mistake of tracking everything you will stay sane, preventing you from becoming a mathematical savant who writes algorithms on windows.
Data metrics for creatives
Now you’re familiar with how to work with your data at a high level, the next step is using a filter to track only the data points that are of greatest value. Knowing which metrics are meaningful reduces noise, helping you focus on the most valuable data points that you can measure and improve.
Avoid the common mistake of tracking everything. Applying the 80/20 Principle, identify and track the few metrics that result in the greatest yield to your creative enterprise. Identifying and adhering to these to the exclusion of all others will ensure you stay sane, preventing you from becoming a mathematical savant who writes algorithms on windows.
As a creative video production company dabbling in publishing our own content, we use the following table to track performance (inspired by Hubspot). Keep in mind that there are more ways to map a sales funnel than there are interpretations of a David Lynch film.
- Awareness Stage: The buyer realises they have a problem.
- Consideration Stage: The buyer defines their problem and researches options to solve it.
- Decision Stage: The buyer chooses a solution.
| Buyer Stage | Video | Website | Social Media |
| Awareness | View count | Traffic | Impressions |
| Engagement | Likes, comments, shares, average view time | Average session, bounce rate | Likes, comments, clickthrough |
| Conversion | Form completion | Signups, purchases | Signups |
The analytics value chain
As you embed data analytics into your creative process, different types of data analytics will begin to emerge. From hindsight to foresight, each type is based in a different tense and seeks to answer a different question. While predictive analytics may seem like something straight from Alex Garland’s mini-series ‘Devs’, being aware of what’s possible will provide opportunity for you to capitalise on future opportunities.
| Phase | Data Process | Definition |
| 1 | Reporting | Used after the fact. Asks the question, “what happened?” |
| 2 | Monitoring | Based in the present. Asks the question, “what is happening now?” |
| 3 | Prediction | Future focused. Asks the question, “what is likely to happen?” |
How to build a simple data infrastructure
Now that you have an understanding of data analytics, a framework for thinking about data and a shortlist of metrics to track, let’s look at a basic data infrastructure you can set up that will allow you to track these. Below is a data pipeline that you can set up in an afternoon.
| Application | Tool | Description |
| Website Analytics | Google Analytics | Collect website performance data and track conversions for valuable behaviours. |
| Data Storage | Hubspot | Centralised repository to store analytics and assign actions to individual users. |
| Data Visualisation | Databox | Track key metrics in real time with an easy to use interface. |
| Social Media Analysis | Hootsuite | Reporting, publishing and listening tool to collect your unstructured social media data. |
| Script Management | Google Tag Manager | To track advertising conversions from social media platforms you’ll need to insert tracking codes into your website. |
Conclusion
While data is the world’s most valuable resource, it’s the process of making meaning from data that is the modern version of divining water from wine. An efficient pipeline for collecting and distilling insights from data will provide creatives an enormous bounty. Combined with your natural flair as a creative, data analytics will provide a competitive advantage in any industry or niche.
