Compare Competitors, and Prioritize Topics based on Competitor Strength

hello issues and entrepreneurs we will talk about a gbt called interpreter and how to use it for data visualization and data science in terms of the search engine optimization before in our public holistic SEO communities and on and also on my activator I shared this specific visualization this visualization is for comparing competitive relevance to the common keywords which means that this website here every XE represents a website which means that this website has like 175 000 common queries with us and also the relevance or the relevance of the competitor is really really close to us

so it is actually helpful to understand which which comparator we should focus on First and which one we should be actually outranking first even if you share a really good amount of queries with a competitor it doesn't mean that actually you are relevant to them or similar to them in this case to be able to compete against them you will need to actually increase the relevance together with the common queries and it is it can be be done basically by changing your account by using it but to keep things simple in the context of the

blue head SEO series we will mainly focus on taking the data output from hrefs then we will be using this specific prompt then I will be giving you a more detailed sample that you can actually see I have to use jgb to code interpreter for data science and visualization in the context of SEO so this is the data that we will be taking and in this one I will be using a different website basically I come to the organic competitors there is a visualization here already and you see that there are different type of columns

and this is the export of these specific columns in this area we have Pages which represent the webpage count traffic value represent the let's say the total value of these pages and this is the traffic that we get from these Pages this domain rating which is another story here we actually see the targeted domains queries and the common queries together with the competitor at the same time and these are the unique queries for the competitor the share represent the amount of let's say the relevance or the similarity between targeted domain and also the specific competitor

so with that side first I just wanted to use actually a very very simple version and I will start from there not from this specific one so in this case I use this specific prompt create a correlation visualization for common query count and the competitor relevance if you use this specific prompt still it will be actually working but at the same time since I did not give any kinds of detail this chat gbt will be having some hard time first of all they will need to understand what type of UTF you are using then they

if they are lucky or if the system is on the lucky moment you will be finding this and you will be able to make the data readable then they will be giving you the definitions of the column so that you can understand that since the output will be so long you will need to be telling continue where you left off then according to your command which means that actually competitive relevance they will need to understand from these definitions which one is closest column and they will need to be creating at this type of a visualization

here according to your let's say the output or moment of the charge gbt because large language models actually they have a kind of greedy learning and grid optimism method which means they have an internal scoring system and according to the latest situation the highest score output might be changing you can use the same prompt today and tomorrow and you can get a different output from the same input because these greedy learning methodologies they always change this course to make better but it doesn't mean that always also better so basically here we have the common keyword

count here and we have a domain rating this time and the next time the search engine might choose something else but again you can use this you can try to use this in this way if you see that the domain rating is high and if there is a really good amount of common keywords you can assume that outranking this website will be higher compared to this one that's why you can get the top pages of this specific one and you can try to create maybe two three pages you just get most of the authority of

this one then you can move to this this and this you can create a map or let's say Target list and prioritization many people ask me how to use topical Authority but and I usually try to keep things simple but if you want to prioritize the topics sometimes you should focus on The Impressions and the historical data but also you can use this type of competitor analysis as well and outranking this will be very much more cost there for you and in this one you see that the query account is higher too if you merge

these two visualizations you can even get a richer richer Insight but let's move on to our real prompt so this is something that I call actually multi-layered complex prompts to actually help the chegebt to understand everything in one time foreign and the last time too or in the last LGBT and blue hat SEO video as well I used a prompt with the five sections I defined every section's purpose then I have given some syntax information I told shajibita that the comment there is always a comment in every section while telling its purposes and the comment

starts with this specific character I also told the chair gbt that these three quotation marks at the beginning and at the end of the specific section it represents the borders of that prompt area then I tell that this is the first section of the prompt out of 5 then I start to define the data set as I said in that area too I give the column names so that the specific jbt system can actually understand that my prompt and the data that I am giving it is overlapping and consistent with each other and this time

I also tell what kinds of data that it will be finding under these specific sections the r is domain rating of the competitor domain traffic is a traffic amount of the competitor gas traffic value is the amount of monetary value of those specific domain let's say and I also give specific type of file extension or file format related information like use police utf-16 and table separator to read it so that so that things can get easier for them in the second part I tell that this section is for visualization and here I tell that the

purpose of the prompt is visualization of the relevance of these domains to our Target domain and correlating it to the possible cost of outranking these competitors because our purpose here is others to understand which domain first we should be focusing on which one is easier to outrank and which one is cheaper to outrank if you're able to get results earlier we will be able to increase our actual topical Authority faster too in this case basically we give the purpose of the visualization then we explain how they can how the system actually can use this purpose

based on these columns we tell that if the relevance is high for specific domain it means that we are ranking together with them and terrific value traffic amount indicate the amount of cost that we will need to spend for outranking them if the share percentage is low it means that we do not rank for the similar queries if we have too many share queries or shared queries it means we have relevance together and traffic amount and amount of queries which means keywords and the traffic value together represent the possible cost now I give simple information

for visualization then here I give the comments directly the third section of our prompt by easily just gives on the specific comments for the visualization we tell that put labels to the axis use multi-wire access then we tell that represent the cost and relevance correlation between competitors and targeted domain I tell the target domain is same with the the domain that we are using I also give the name of it to the inside the prompt then I give my command I also give the context by saying SEO observation then the fourth section of the prompt

directly tells that the knowledge domain terms as I stated here the fourth section is for defining the knowledge domain terms and I give my knowledge domain terms here I tell that this is the relevance this is definition traffic value is this SEO means that search engine optimization which is a methodology to increase the rankings and overall visibility of a domain the keyword means query I tell because these type of wording differences matter I tell that Dr is a basic domain Authority but it comes from hrefs as a difference with a different formula then I tell

that understand the concepts while visualize visualizing the data for understanding the cost and relevance correlation in the last part we give the latest details as we stated already like last details in the last details section I basically tell that for instance higher the competitor's keywords the cost competing is increased however domain rating goes up the cost of ranking goes higher too and the amount of queries that are not shared increase the cost of ranking one more time because it means I will need to be opening lots of new pages or I will need to write

longer or I wanted to configure these things further I am not talking about just monetary costs also time cost or stuff cost too because we will need more people the amount of pages also increases the cost of ranking because if they too many pages but also too many or high terrific value it means that they have really important amount of pages plus also all these Pages actually create a value and also if they have less pages with higher traffic value it means that value per page is so high too which means domain rating will be

going high higher together with them or average length of the content or Brand Power will be going higher too that's why I'm telling that actually we are not using chegebt here we are using our brains and we know all the knowledge domain Concepts and we correlate them with each other in in a positive or negative way understand how these things are changing with each other and here too I said the cost of ranking is increasing together with the traffic value higher traffic value represents higher value and the cost so once I put on my prompt

directly they repeat what I say in a representative way the purpose of this section is actually helping you to see that jgbt whether understands you or not that's why they always put this section here by telling stop generating password and they'd like to tell that thank you for providing the detailed prompt and they give the details here they give UTF information or let's say knowledge domain terms correlations for instance or other areas and they read the data and as you see here they use actually sometimes my own Concepts or the things that I already defined

in this area too and here they directly use of our website name or these sections as well you can also check the code based on this is a simple reading as you see encoding utf-16 separator is T as I stated in my prompt directly in the first section as well yeah so it helps actually it didn't be like that if you look at here it was hard for them to read it at the beginning it was like this then in the second part they Define these things and they say given the provided guidelines and understanding

of the data set we can now proceed to visualize the data based on the prompt and will they repeat our section and here we they use the concept of potential cost and relevance because they are building these because they try to get your attention through these specific sections then here we actually create a a kinds of subplot by using actually matplotlit and here we created actually three different bars then two different lines then we use all these axes inside the same figure we put our labels directly then we merge them directly in these specific labels

and we actually use specific pipe layout which means that everything will be visible at the same time and we try to show it you know now let's say under this area and it is a good side of matplotlib the chat gbt is able to use it if you will be using actual Pi plot or something or plotly or something like that it would not be working here so as you say this is the first output and what is wrong here the first of all in my prompt I did not put I did not put the

the logarithmic scale that's why everything is different or there are there is a huge difference between these tanks another problem is that according to the output there are orange bars red bars and Brom bars but I see only the orange ones because it represents the traffic value since it represents the traffic value the number is too high but let's say the red one actually represents the page count of each domain and if you scale let's say half million to do 180 that specific small bar won't be visible it means that I will need to tell

that the red bars and brown bars are not visible use like a rhythmic scale and do not use stacked bars in this area I tell since this was a actually very quick feedback this section might be a little bit skipped from time to time that's why in specific area here actually I tell that please pay attention to every part of the prompt and do not skip any comment I say it especially because I also tell that every command starts with that my purpose here is even if the chair gbt skips some of these since I

will be having certain type of a comment here I will force it one more time to read these things and understanding understand these things again I don't have the is directly here for example but you can try to put it if you want once I tell this this visualization is now more visible and comparable to each other but there is also still a problem first of all I am a little bit colorblind and this is very hard for me to see the difference between dark red and white red as might tell one more time please

make colors more distinctive from each other and now we have this specific visualization so now for data science purposes let's let's interpret these together first of all the traffic value has been represented by the orange bar and when I look at here this one which is compare the market has actually the highest traffic value then I check the pages and also the number here I can tell that they have really good amount of pages too compared to let's say insure insurance 6 core UK for instance at the same time I I check this part too

this one also has high amount of pages and traffic value is close to that which means usually the value of the traffic and amount of pages they are correlated with each other at the same time then we see the Dr which is domain rating according to the ashrefs the r is not the athletic but for this type of activations it is helpful in this case we see that actually traffic value if it is over let's use our visualization a little bit here if traffic value is over this line we usually see that domain rating is

also over this specific line as well it is like correlating with each other's like there is a kind of bottom line for both of them and in this case for instance this is a little bit outlier here because the domain rating here is higher but and the page count in this area we can see that actually it is similar to this area but the traffic value is lowered which means that actually their success is a little bit lower compared to others it means that maybe the domain rating is not that much real for this one

or because there is fake TR or maybe the content is not quality enough but still outranking this website might be easier for us in this case because they are not that much successful as much as these another one is share which is the relevance and it is represented with this specific blue line that you see in this area so first of all since the numbers if I could show the data here the share information the highest percentage was 27. it starts with this which is time covered and then since we are using logarithmic scale is

there is not that much visible difference that's why using actual plotlet which to create an interactive dashboard is it would be better here to hover over effects but we since we already know the temp cover was the highest you can use this small differences for example I can see that actually this is lower this has lower shared compared to other one another option is forcing jgb to write some numbers or some labels to over these areas as well or you can force it to put this thing into a another bar plot to the side side

by side as well but you can use this traffic sorry the query share percentage to understand where we are already competing together for example we are competing against the temp cover already and their domain rating is actually let's say in the good number and the page count is not that much bad too compared to others as well but for instance when you look at this one this is lowest in terms of again the the page count domain rating is very low too a traffic value I can tell that it is not that much low as

well when you look at here the page count is higher compared to actually let's say domain rating and terrific value is not that high but let's say compared to the Dr it's more but the page count is a lot too which means there are pages that already failed there but when it comes to here the traffic value per page should be actually higher in this case too the last part is the amount of queries which represented with this green line and in this case you see that actually the queries for this comparator it is too

high and in this case we can understand that query amount per page is actually very successful here yes they have more pages but they also rank for more queries and they share less similarity with us which means we will need to open new pages and they already have too many pages maybe we will need to be opening like 150 really good pages to be able to compare it against this one since our Dr is lower too we will need to be focusing on let's say the content side a bit more further one more time I

am telling if you follow me over three years this video is really simple that's why I'm using the concept of Dr in other case I will be using lots of different type of Concepts from patterns research papers and also from my terminology but I keep things simple for the sake of these blue hat series when I say Dr please do not buy links just based on their metric okay and in this case this is like a little bit like high level of Target and if we need to prioritize things we can start some of the

smaller ones if you look at these other areas here we see that actually since our shade rate is a lot also cut the their unique query count is not that much higher too which means that even if you open new pages we don't need to open that amount of new pages because this represents the shared shared query account then this represents the unique queries which means the difference is not too high and the page count is here and you can get a kind of average number for yourself for the amount of pages that you will

need to be opening if the difference between blue and blue and the green line a lot it means that you can actually open new pages to compete against them and based on the Dr you can get the amount of the idea of the details that you will need to be adding and also based on the traffic value you can get the gain ID of the potential gaining in this area when you look at this one we which is r a SQL UK the the unit query account is way much higher they have way much more

pages as well but value is lower which means they have some informational sections to go after and you can find these specific queries and you can try to create a topical map from the queries and topics of temp cover to the racco UK and you can create a prioritization and connection level according to the situations of the competitors and their feedbacks compared to the latest updates you can create a different type of let's say content either like a Toronto minutes of video I try to keep these things simple but as you see we actually use

a little bit coding we use artificial intelligence we use chat gbt and we use prompt engineering and we also use data science data visualization and competitor analysis for search engine optimization from internal factors and also external factors together too the purpose here is actually helping you to improve your let's say daily soaps your stick issue is mandible for the marketers and entrepreneurs provide this level of information that's why I'm telling that we are training 10 plus years of XP those and entrepreneurs together with like six months of newbies of beginners and this video has series

are actually created for everyone if you have further questions or the requests please drop them to the comment section and I will try to continue to add new videos every bit so we will see each other more you can join to the art holistic SEO communities and the Facebook committees Discord communities you can follow us on Twitter you can also join actually our newsletter as well because here this place will be very active very soon for especially AI you can also join our private Community by joining our topic hello Authority course program as where you

can join our coaching sessions coaching group together with the 50 other entrepreneurs love you all and take care of yourself I've been [Music]