IAB taxonomy is an important part of brand safety toolkit.
With rise of alternative ecosystems that will slowly add ads (perplexity, chatgpt et al.) publishers selections may need to become less restrictive and one way is to incorporate other features, e.g. webpage quality, for more unconstrained approached.
We built a taxonomy of 8 desirable & 8 undesirable traits (1–10) for site evaluation— applied on https://t.co/4jgWAMwQbn in attached example (avg. 8.3). Webpage quality is also available as API (along with IAB and our other APIs) at our website https://t.co/W41HlajQlL
This quality approach allows new ways of filtering, e.g. advertisers can filter webpages by “would buy intent” ≥5 or “clickbait” ≤2. #AdTech #BrandSafety
On https://t.co/9nNBQXlfiJ, for each brand, we provide 10 most typical customer personas. You can ask them about upcoming campaigns, design changes, or even brand repositioning strategies. Our AI-based personas provide quick feedback, are available at any time and are saving you time and resources. Example screenshot:
To keep track of performance across all features, we publish monthly https://t.co/VB4Oq3e4m9 Brand Index, for each industry and country, while also attributing why brands moved in their positions, example screenshot for Automotive sector:
Our platform, https://t.co/W2S4olj2RM helps companies:
- Monitor what AI models (ChatGPT, Gemini, Claude, etc.) are saying to your customers about your brand
- Explain why they are saying specific things (attribution)
- Influence AI models to change and improve your brands perceptions (AI optimization)
As AI-based chat platforms increasingly replace traditional search engines—ChatGPT alone has over 300 million weekly users—impact of AI Chat on consumer decision-making continues to grow.
The rise of autonomous AI agents and capable open source on-premise models (like Deepseek) will only amplify this trend. Our platform https://t.co/lWjaQAog7Z was built to help companies and brands deal with this drastic change that is occurring in how clients interact with brands.
For each industry we monitor ranking of brands for 30 most relevant features, across time, for different countries and using different AI models (OpenAI, Gemini, Claude). We track 12,875 consumer brands and 3,871 software brands.
Attached is example of rankings of Automotive companies for feature Brand Reputation in United States (for Automotive industry we track performance of brands in 51 countries).
These comparative rankings can be used to directly compare brands performance in specific countries, Attached is example of comparing @AudiOfficial and @BMW in United States for a subset of 30 features that track in total.
Another way to quickly get insights is compare brand performance across different countries, by using either another country as baseline or another brand,
Example of showing @Audi strength in Build Quality (as perceived by average over all AI models) in different countries, with @BMWGroup as the baseline is attached
You can learn more about our other advanced features here: https://t.co/hFgZS9DW8d
If you are an agency, we offer a white label version, which you can use for your clients to differentiate yourselves from your competitors.
On our platform leadsquantum we have several ways of suggesting you which technologies are interesting for you to use in your business.
We have trained an advanced machine learning recommender which predicts with high accuracy which technologies are interesting for a website that uses specific list of technologies.
It was trained on usage of 4000+ different technologies by millions of websites (more than 100 million data points).
First approach to utilize our recommendation engine is to simply search for your online store in our database and if found, then check out the list of technologies that are recommended for it.
Attached is an example for one of domains in our database (recommendations are marked with green box):
If your domain is not in our database, you can still use our engine to find out which technologies are interesting for you to use.
You can enter your currently used technologies in the search box and get the list of technologies that are recommended for you, below is an example for a website that uses mouse flow, crisp live chat and shopify. We provide you with 1000 recommendations.
Note that for each recommendation we also provide "explainability", i.e. we tell you which technology that you currently use is most responsible for each specific recommendation.
Do you have a list of domains for which you would like to get recommendations from our engine? No problem, you can send us up to 500 domains and we will provide you with recommendations for all of them.
We have several ways of suggesting you which technologies are interesting for you to use in your business.
We have trained an advanced machine learning recommender which predicts with high accuracy which technologies are interesting for a website that uses specific list of technologies.
It was trained on usage of 4000+ different technologies by millions of websites (more than 100 million data points).
First approach to utilize our recommendation engine is to simply search for your online store in our database and if found, then check out the list of technologies that are recommended for it.
Attached is an example for one of domains in our database (recommendations are marked with green box).
If your domain is not in our database, you can still use our engine to find out which technologies are interesting for you to use.
You can enter your currently used technologies in the search box and get the list of technologies that are recommended for you, below is an example for a website that uses mouse flow, crisp live chat and shopify. We provide you with 1000 recommendations.
Note that for each recommendation we also provide "explainability", i.e. we tell you which technology that you currently use is most responsible for each specific recommendation.
We categorized 5 million most popular websites on the internet, based on widely used IAB taxonomy on our platform LeadsQuantum (for link see profile).
For each of 5 million websites, we determined many metrics, like OpenPageRank (from DomCop), domain age, technologies used and others, using approach that we pioneered in 2019 with our SEO focused platform UnicornSEO.
This allows us to offer unique ways to research and find new niche sites.
First, let us say that you are interested in finding young niche sites in the vertical of "Pets" that are attracting great interest, which is usually reflected in above average growth of links and thus high open page rank for given domain age.
In our platform we select the main category of "Pets" and then set maximum "Domain age" to 5 years, followed by ordering by "OpenPageRank" to get the list of interesting sites in this vertical, see image attached
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We have found that websites with young domain age and high OpenPageRank are usually very interesting and have great potential.
Second, we can combine the data considered above with our data on technologies used by websites to find another way of finding exciting new niche sites.
For example, we can focus on just those niche sites that use Google Adsense, which is a great way to find sites that are monetized and thus have a good chance of being profitable.
And we can decide on just those sites that are from "Personal Finance" vertical see attached image
This gives us a list of interesting websites using Google Adsense, from "Personal Finance" vertical.
By focusing again on those with young domain age and high OpenPageRank, one can find interesting niche sites.
That are worth to research further if you are interested in monetizing website in "Personal Finance" sector.
Like this analysis for "Personal Finance", you can do this type of analysis for 439 other main niches.
If you are more used to using Excel or Google Sheets, you can also export list of sites to Excel and do your analysis there. Or export to csv and do analysis with python, etc. on our platform
We've classified 5M most popular domains worldwide using IAB taxonomy, a widely used categorization taxonomy.
We then analysed 4,000+ technologies usage across these 5M domains, based on which we can identify above-average verticals for any technology from these 4,000.
Adding charts for @WooCommerce and Shopify. This is for Tier 1 categories, on platform you can check out distribution with respect to 440 categories of IAB Tier 2.
You can also make direct comparison on up to 10 technologies in same chart, to quickly get insights on given field.
For tech companies this type of usage data in terms of IAB verticals can help drive more targeted and thus better marketing campaigns.
We've classified 5M most popular domains worldwide using IAB taxonomy, a widely used categorization taxonomy.
We then analysed 4,000+ technologies usage across these 5M domains, based on which we can identify above-average verticals for any technology from these 4,000.
Adding charts for @WooCommerce and Shopify. This is for Tier 1 categories, on platform you can check out distribution with respect to 440 categories of IAB Tier 2.
You can also make direct comparison on up to 10 technologies in same chart, to quickly get insights on given field.
For tech companies this type of usage data in terms of IAB verticals can help drive more targeted and thus better marketing campaigns.
2/n
for those working for a (big) company,
then if not yet already, might be a good idea to start exploring/building own platforms/products/services.
as a personal hedge against big companies inevitable shrinkage in terms of employees with rise of GPTn/AGI.
chatgpt/GPTn impact asymmetry. 1/n
1 - founder/coder -> do more in less time
-> better in non-coding, like marketing.
less need for external funding
mostly ++++
2 - employee in company
more done in less time ->
better profitability, but for company. less workers needed
two opportunities in the coming chatGPT, GPT4/5 era.
1 - use GPT3/4 to build "Lego" parts of companies - covering marketing, UI, SEO, VAs and then offer those.
2 -specialize in integration of these individual AI parts in complete, digital companies, selling those as turnkey.
in chatGPT/GPT4 era
new companies may start to be built like Lego sets, you will just find right AI piece for function - marketing, SEO, VAs, etc
-> rise of "small employee count"/"huge revenue" companies -> what I would term "Picassos"
key ability -> finding sources of moat
BittsAnalytics social #crypto#feargreed index chart.
Based on sentiment analysis of 1+ million social posts per day on $btc and other #coins (using #machinelearning model).
BittsAnalytics social #crypto#feargreed index chart.
Based on sentiment analysis of 1+ million social posts per day on $btc and other #coins (using #machinelearning model).