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yes, agree, but you always have to update your code, think about new ways how to analyze data, and so on. No so simple. Great example - Reddit. In 3 weeks most SEO tools that use Reddit API will stop working because of hight API costs
Why invest in expensive SEO tools over python solutions?
1. Opportunity Cost - Learning python takes time. Building out a solution like this takes time. Fixing things when an API endpoint changes or something breaks takes time. You only have a finite amount of time in a day, and that time that may be better spent on other things.
2. Collaboration - if you work alone, a python solution may be perfect. However, if you work with other people who may not be as technically savvy, having something like this may be more of a detriment than a benefit if they ever have to maintain/work with your codebase.
3. Ongoing Maintenance - One of the major benefits of using a 3rd party tool is you're not responsible for fixing it if something breaks. It's like paying for a product warranty instead of having to fix your refrigerator yourself.
I'm not trying to discourage you from building your own tool, I would just think long and hard about the hidden costs associated with it before making the claim you can do it at a fraction of the cost of traditional tools.
nobody has time for this. most people don't even have the time to learn how to use the existing tools properly. stopping to learn how to develop this, also have to support it, and have nobody to turn to when something doesn't work is not realistic.
Not everything is advertising 😂 I personally use DataForSEO but I'm not involved in it. I just use Python to make my own tools and analysis and they are the more "user friendly" I found for developers.
Fair enough 😂
That’s marketing, after all!
Speaking of data, can I ask some questions?
- Can you explain the data behind why you prefer this rather than just using hubspot or whatever other tools?
- Like, how much are you saving per month?
- How many hours did it take you to become proficient, and what tips can you recommend to the rest of us?
- Are you able to quantify how much better your way is, or does it just feel better because you can experiment in any way you choose without feeling constrained by the tool you’re using?
- Do you have an extraordinary set of KPIs or ROIs or churn rates or results, or whatever, from your campaigns?
Thanks!
I'm a data scientist that recently started to explore the Marketing Tech space (so I might be biased).
* Can you explain the data behind why you prefer this rather than just using hubspot or whatever other tools? The main advantage is that I'm not blocked by any tool limitations. I can save as many SERPs as I want and perform all the analysis that I want. I did a simple script to discover the search intent of thousands of SERPs and discovered clusters of entities from the Google knowledge graph in a couple of minutes. Of course, I'm biased because I love to analysis data, and I got a couple of years of experience with Python.. But it was seriously not that hard, and it gives me a great feeling to rely on my own analysis while everybody is looking into the same data on Hubspot (that's how I imagine it.. but again, I'm not a marketer)
* Like, how much are you saving per month? I pay only to save data, and then I'm free to use it. If I need to refresh it every month and I get crazy and I analysis 50k SERPs, then I would pay around 30$. But so far I paid less than 5$ and already got plenty to analysis.
* How many hours did it take you to become proficient, and what tips can you recommend to the rest of us? It is quite fast: 10-20 hours to get familiar with all the API endpoints, save the data, and get my first visualisation.
* Are you able to quantify how much better your way is, or does it just feel better because you can experiment in any way you choose without feeling constrained by the tool you’re using? It just feels better for me.. less constrains..
* Do you have an extraordinary set of KPIs or ROIs or churn rates or results, or whatever, from your campaigns? Sorry, I've nothing to share on that side.
For the API, I use DataForSEO because they are easy to use but I'm not involved with them. I'm a data scientist currently exploring their API along others, like GPT for intent analysis and Google Knowledge Graph to discover entities from tags and meta descriptions.
I have a tutorial about how to get started on my website, but I'll share the steps, (and code?) directly on Reddit as well.
Thanks for sharing this! The other people to make some valid concerns but this is exactly the type of cool data/coding marketing stuff I'm into. I hope you keep putting out tutorials!
Hey,
I've actually stumbled across Google Collab, Data for SEO and the idea of clustering keywords based on SERP similarity.
I never got it to work based on my inability to code beyond the very basics.
I would LOVE it if you would share your scripts, either personally with me or in this thread.
#OpenSourceForTheWin ❤️
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yes, why to by a car if you can use a horse It's a bit of an investment in time, but trust me, it's worth it. - no, this is not
I mean it gives you way more flexibility and you can make targeted analysis for your own business at scale.
yes, agree, but you always have to update your code, think about new ways how to analyze data, and so on. No so simple. Great example - Reddit. In 3 weeks most SEO tools that use Reddit API will stop working because of hight API costs
Why invest in expensive SEO tools over python solutions? 1. Opportunity Cost - Learning python takes time. Building out a solution like this takes time. Fixing things when an API endpoint changes or something breaks takes time. You only have a finite amount of time in a day, and that time that may be better spent on other things. 2. Collaboration - if you work alone, a python solution may be perfect. However, if you work with other people who may not be as technically savvy, having something like this may be more of a detriment than a benefit if they ever have to maintain/work with your codebase. 3. Ongoing Maintenance - One of the major benefits of using a 3rd party tool is you're not responsible for fixing it if something breaks. It's like paying for a product warranty instead of having to fix your refrigerator yourself. I'm not trying to discourage you from building your own tool, I would just think long and hard about the hidden costs associated with it before making the claim you can do it at a fraction of the cost of traditional tools.
nobody has time for this. most people don't even have the time to learn how to use the existing tools properly. stopping to learn how to develop this, also have to support it, and have nobody to turn to when something doesn't work is not realistic.
What APIs are you using for #2?
From the service he’s advertising, duh 😂
Not everything is advertising 😂 I personally use DataForSEO but I'm not involved in it. I just use Python to make my own tools and analysis and they are the more "user friendly" I found for developers.
DataForSEO is great! I've built some PHP scripts with it. the documentation and support is fantastic
Fair enough 😂 That’s marketing, after all! Speaking of data, can I ask some questions? - Can you explain the data behind why you prefer this rather than just using hubspot or whatever other tools? - Like, how much are you saving per month? - How many hours did it take you to become proficient, and what tips can you recommend to the rest of us? - Are you able to quantify how much better your way is, or does it just feel better because you can experiment in any way you choose without feeling constrained by the tool you’re using? - Do you have an extraordinary set of KPIs or ROIs or churn rates or results, or whatever, from your campaigns? Thanks!
I'm a data scientist that recently started to explore the Marketing Tech space (so I might be biased). * Can you explain the data behind why you prefer this rather than just using hubspot or whatever other tools? The main advantage is that I'm not blocked by any tool limitations. I can save as many SERPs as I want and perform all the analysis that I want. I did a simple script to discover the search intent of thousands of SERPs and discovered clusters of entities from the Google knowledge graph in a couple of minutes. Of course, I'm biased because I love to analysis data, and I got a couple of years of experience with Python.. But it was seriously not that hard, and it gives me a great feeling to rely on my own analysis while everybody is looking into the same data on Hubspot (that's how I imagine it.. but again, I'm not a marketer) * Like, how much are you saving per month? I pay only to save data, and then I'm free to use it. If I need to refresh it every month and I get crazy and I analysis 50k SERPs, then I would pay around 30$. But so far I paid less than 5$ and already got plenty to analysis. * How many hours did it take you to become proficient, and what tips can you recommend to the rest of us? It is quite fast: 10-20 hours to get familiar with all the API endpoints, save the data, and get my first visualisation. * Are you able to quantify how much better your way is, or does it just feel better because you can experiment in any way you choose without feeling constrained by the tool you’re using? It just feels better for me.. less constrains.. * Do you have an extraordinary set of KPIs or ROIs or churn rates or results, or whatever, from your campaigns? Sorry, I've nothing to share on that side.
That’s awesome, thanks for the ideas and information!
Where can i learn more about this?
For the API, I use DataForSEO because they are easy to use but I'm not involved with them. I'm a data scientist currently exploring their API along others, like GPT for intent analysis and Google Knowledge Graph to discover entities from tags and meta descriptions. I have a tutorial about how to get started on my website, but I'll share the steps, (and code?) directly on Reddit as well.
Thanks for sharing this! The other people to make some valid concerns but this is exactly the type of cool data/coding marketing stuff I'm into. I hope you keep putting out tutorials!
Hey, I've actually stumbled across Google Collab, Data for SEO and the idea of clustering keywords based on SERP similarity. I never got it to work based on my inability to code beyond the very basics. I would LOVE it if you would share your scripts, either personally with me or in this thread. #OpenSourceForTheWin ❤️