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How to implement a Data-Driven Content Strategy

Updated: Jun 16

It is becoming increasingly obvious that in the information age we live in, data-driven businesses win. Naturally, that extends to content marketing as well.


But how would it work?

One very big problem that persists against a data-driven solution for content marketing is this- The writer is human, and so, inherently subjective in their writing. So it follows that content creation being a creative process, cannot fully be data-driven.


But it can get pretty close to the finish line, thanks to huge advances in AI and deep learning technology. Here's a brief description of how.


The first step in any Data-driven process is tracking. SME’s and enterprises churn out huge amounts of content every day in pursuit of their online marketing efforts. But how is this content performing? And why?



Performance Tracking


There are many tools in the market that enable performance tracking. Google Analytics being a primary example of these. A marketer needs to identify which performance metrics(KPIs) indicate success. This is dynamic and will change depending on what he/she is trying to achieve with the content.


If they are writing a long-form blog post that intends to inform users/readers about a particular topic(and thereby achieve search engine optimization), a good KPI would be Time spent on-page. Click through rates(CTRs) would also indicate how much the user has engaged with the content.


Conversely, if the marketer is trying to insight an emotional response from the reader, social shares would assess how effective the content is, and what kind of impact it had on the user.


Here is an extensive list of metrics that Google Analytics provides to help track your content performance.


Another good way for enterprises to measure performance is through conversion rates from marketing qualification to sales engagement. This works well as a measure of success for a B2B enterprise trying to establish an online presence, and strengthen its Top-of-the-funnel(TOFU) sales pipeline.


So using internal KPI’s we have performance results, now, what do we compare that with?



Pre- Publishing Analysis


How do you measure the quality or worth of written content?

Of course, there are quantitative metrics like word count, grammar, spelling, etc that measure the basic quality of writing. But these are too impersonal and removed from why a piece of content finds success. To find truly qualitative data that can be used to run comparisons, we need to quantify how words relate to each other and how people react to them.


Enter Natural Language Processing or NLP

At Instoried, we use NLP to measure emotion. Using five primary emotions(Joy, Anger, Sadness, Surprise, and Fear) and three tonal metrics(Positive, Negative, and Neutral) as the primary indices that digest a whole page of content into numbers that can be compared against each other or against preset benchmarks. Here’s a series of blogs on how we did this.


Writing Augmentation: Instoried's tool analyzes the words used in the content and recommends contextually aware changes that affect the emotional valences, and thereby final performance.


Comparative Analysis


So now let's look at the data that can be available to us.

  1. Market Performance/Results (eg: Time Spent, Duration of visit, CTR, Bounce Rate)

  2. Pre-publishing Emotional Analysis (Joy, Anger, Fear, etc)

Now we have both sides of the coin and this unlocks a coveted tool in business - Predictability .


Using historical and industry-specific competitive data, we compare Market Performance against the emotional analysis and analyze and digest what emotional combination gives what results. And also arrive at benchmarks that can be repeated and scaled(by predicting performance) through change to the content(either manually, or by virtue of machine-learning enabled writing augmentation). Instoried uses an AI model that also tries to figure out why, i.e, how do these emotions affect market performance? But that is a very technical question, with a very technical answer and it is for another day. For our purpose here, we use the correlations between the two to scale and repeat our best performing content- Optimizing for our internal KPIs and maximizing business value for creative effort!


-by Havaz Mohammed

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