Good technical documentation is great, but it's not as discoverable as blogs or videos. I'd argue that giving users high quality answers to their Google searches is the best way to connect with a technical audience (cause devs are unlikely to stumble across your docs).
I have a popular tech blog (https://mungingdata.com/) and have a ton of goodwill with my users, mainly cause I'm not trying to sell them anything. You can provide users with equally informative content if you can avoid making it overly biased.
Developers are understandably skeptical in the big data space because they're often given biased benchmarks. It's hard to replicate benchmarking results (e.g. person X says that XYZ runtime can run a certain query in 1 second, then they try out the tech and it's way slower).
Don't be surprised if you're building a big data technology and devs don't like your biased benchmarking.
If you give honest results and try to inform users about your project objectively (the pros and cons), then they're more likely to respond well. Your goal should be to give relevant information, even if it's only tangentially related to your product. Your product should sell itself when users are provided facts that aren't tinted by rose colored glasses. Disclaimer: I work as a Tech Evangelist at Coiled.
> I'd argue that giving users high quality answers to their Google searches
A lot of people have seen this argument. That's why every google search on a technical topic is now polluted by blogs describing "how to do X with Y" that are written either to sell Y, or for pure self promotion.
Unfortunately said blogs are useless for the advanced user since 90% are just a beginner's tutorial with info that i could have figured out from the docs in 2 minutes.
Yet another marketing strategy that failed the nerds...
I have a popular tech blog (https://mungingdata.com/) and have a ton of goodwill with my users, mainly cause I'm not trying to sell them anything. You can provide users with equally informative content if you can avoid making it overly biased.
Developers are understandably skeptical in the big data space because they're often given biased benchmarks. It's hard to replicate benchmarking results (e.g. person X says that XYZ runtime can run a certain query in 1 second, then they try out the tech and it's way slower).
Don't be surprised if you're building a big data technology and devs don't like your biased benchmarking.
If you give honest results and try to inform users about your project objectively (the pros and cons), then they're more likely to respond well. Your goal should be to give relevant information, even if it's only tangentially related to your product. Your product should sell itself when users are provided facts that aren't tinted by rose colored glasses. Disclaimer: I work as a Tech Evangelist at Coiled.