{"id":2824,"date":"2022-10-20T10:35:00","date_gmt":"2022-10-20T14:35:00","guid":{"rendered":"https:\/\/beomniscient.com\/?p=2824"},"modified":"2023-10-10T17:59:37","modified_gmt":"2023-10-10T21:59:37","slug":"the-hard-problem-of-content-prioritization","status":"publish","type":"post","link":"https:\/\/beomniscient.com\/blog\/the-hard-problem-of-content-prioritization\/","title":{"rendered":"Field Notes #016: The Hard Problem of Content Prioritization"},"content":{"rendered":"\n

Many prospects and clients have asked, \u201chow do you prioritize the content roadmap?\u201d <\/p>\n\n\n\n

I always sort of squirm and give a half answer around \u201cworking backwards from your goals and then choosing the highest impact actions,\u201d but if I\u2019m being honest, I haven\u2019t come up with a documented prioritization process. <\/p>\n\n\n\n

\u2026which is weird. <\/p>\n\n\n\n

See, my background is largely in growth & experimentation. In this discipline, prioritization is a HUGE deal. You\u2019re dealing with limited resources and large opportunity costs. <\/p>\n\n\n\n

But guess where else you\u2019re dealing with limited resources and large opportunity costs? Content! <\/p>\n\n\n\n

So why don\u2019t we have a good content prioritization framework?<\/p>\n\n\n\n

I\u2019ll tell you: it\u2019s hard. There are three big challenges with developing a holistic prioritization framework for content marketing, which I\u2019ll get to in a minute. <\/p>\n\n\n\n

First, a bit of background on existing prioritization models for product management, growth, experimentation, etc. <\/p>\n\n\n\n

All of them, at the end of the day, are trying to maximize \u201cexpected value,\u201d which is \u201ca predicted value of a variable, calculated as the sum of all possible values each multiplied by the probability of its occurrence.\u201d<\/p>\n\n\n\n

The two main inputs for expected value are \u201ccost\u201d and \u201cpredicted reward,\u201d and the predicted reward can further be broken down into the estimated payout and the probability of that payout.<\/p>\n\n\n\n

So if it costs you $1 to pull a lever with a 10% chance of winning $10, the expected value is essentially breakeven (10% of $10 is $1, which is what it costs to pull the lever). <\/p>\n\n\n\n

Again, EV = [Probability of winning * What you win] + [Probability of losing * What you lose]<\/strong><\/p>\n\n\n\n

Here, EV = [10% * $10] + [100% * -$1] = $0. <\/p>\n\n\n\n

Digression over, this is why the main frameworks for prioritization include a) cost (ease) b) impact and c) confidence (probability):<\/strong><\/p>\n\n\n\n