▲ ▼ A/B test social media posts without posting
Everyone prefers to get more likes and shares for their social media posts but none more so than social media managers as we are paid to ensure that. But as the algorithms, people's preferences keep changing it's hard even for experienced social media managers to come up with best social media copy.
There are tools which provides analytics to do A/B testing on social media but all of them require the post/tweet to be published and are time consuming.
If there is a tool/service which allows A/B testing of social media posts without publishing by using historical and current data then it can make lives of social media managers easy.
Interesting idea - for sure a gap in the market - but can this be done with confidence. Does historical data provide accurate predicted results? Like say it picks one as the winner and says this will be 10X more impactful - is that going to be trusted or will users doubt it. I guess they have to trust it but overtime they might collect data that pokes holes in it.
I think this problem is validated because marketers currently use scheduling tools to manually do A/B tests, It's just that a solution is needed to predict outcome even without posting twice for a same purpose.
You are right that it might not work in every case as people's sentiments change, but I think it will work most of the time as people's interests don't change often, if it does then these companies wouldn't be collecting so much data on us.
(If I understand you correctly) What you are talking about is interpolating based on past data, but interpolation doesn't work for this situation in practice.
An example: a successful copy from two years ago was ONLY successful because it implicitly referred to (then) current events, and with that missing context it would be irrelevant today.
Market sentiment doesn't always change rapidly, As a copy is dependent upon right grammar for the target psychology I feel historical data is very valuable.
This is s super valid problem! Just get the historical data our from the social media platforms and then test different algorithms for predicting the winning copy texts.
Thanks, why do you think this hasn't been addressed yet?