AdBenchmarkLab is a market research tool that publishes digital marketing industry averages.
No. Activities such as determining prices for brands, discounting on products, selling products together “bundling”, determining market conditions or determining stock status are not carried out.
At least 5 different companies is needed for the same sector to provide averages.
Industry averages for a sector won't be visible if that sector's data contains less than 5 companies.
The data is collected automatically via APIs once a month.
The collected data is anonymized by AdBenchmarkLab. Total investments are divided by the total data obtained (impressions, clicks, conversions) and the averages are calculated and shown to members.
The system is updated monthly. It offers monthly, quarterly and yearly averages. It does not provide daily and weekly data.
Google
Meta (Facebook and Instagram)
Tiktok
It is not available at the moment, but the programmatic module will be published in the future.
Currently, accounts based on TL, Euro and Dollar can work under AdBenchmarkLab.
Yes, you can download the results of the averages to your computer in Excel format.
No. AdBenchmarkLab was coded to only read data one-way and save it in its own database. The data is first anonymized and then averaged in our own database.
No changes can be made to your advertising platforms.
No. The data is first anonymized and then averaged in our own database. Any information that can reveal brand names is not shared with any brand.. See: “Frequently Asked Questions > About industry questions and
privacy”.
Yes, you can access the data you’re looking for through a question-and-answer interaction with the AI model on the homepage. Additionally, you can receive a monthly summary of your data, both in written and
audio formats, with industry comparisons provided by the AI.
Yes, The averages are calculated based on the historical data. You can use the industry averages in any way you want.
By using AdBenchmarkLab, you can track media unit cost and gain insights into how your digital marketing costs have changed over the years.
Yes. AdBenchmarkLab distinguishes CPAS from Branding campaigns and calculates their averages separately.
Yes. AdBenchmarkLab supports segmentation by campaign type, objective, and advertising platform.
Yes. Sub-category analysis is available when there is sufficient data volume within each category.
Platform-specific standard metrics are provided, but conversion value and value-based metrics set by the advertiser are not included. The KPI scope varies based on the data structure of the connected platform.
Averages for each level of the funnel are provided.
Yes. Depending on the advertiser’s data structure, analyses can be made at the country, regional, or global level, and this feature will be available by 2026.
Both web and app campaigns are included. There is no integration with third-party sources.
The periodical growth rate of platform-based core metrics is calculated, and sector-weighted inflation is derived using each platform’s share in total investment, providing the overall media inflation rate for
the entire market.
About Google Ads:
Your data will be received automatically at the end of each month.
Google - "Brand Keywords" module will be activated once API connection is successful.
Google - "Generic Keywords" module will be activated once API connection is successful.
It is a module that runs under the Google platform. In this module, the most important word of the brand (or previously determined by the brand) to which the logged-in user is affiliated is compared with the
average of the important words of other companies in the same sector.
Unfortunately no. Data is transferred only by signing a confidentiality agreement with the companies (brands) that own the data.
Data sales will begin in 2026 with the increase in the number of sectors.
With the increase in the number of sectors in 2025, data sales will begin in 2026 without sharing your data.
You can use the data you obtain to compare your own data in your presentations.
Due to data privacy and anonymity principles, custom competitor lists cannot be created or shared at the advertiser's request. Competitors are differentiated and grouped within the sector.
Due to competition law, averages are not provided when an advertiser holds more than 50% of the market share.
The data requested from advertisers includes total impressions, views, clicks, costs, and conversion metrics from advertising platforms.
Data not requested from advertisers includes personal data, customer data (phone, email, and name), revenue or earnings information.
Advertisers upload their data to make comparisons with sector averages on an independent platform, assess their performance, make future predictions, and perform data analytics.
Yes.
Sectoral Questions:
No. In accordance with competition law, no company name is mentioned.
No. Directions such as Tier1 - Tier2 - Tier3 or where a brand will come to the fore are not made.
Sectors are determined according to the brand's own declaration.
Yes. Sub-category analysis is available when there is sufficient data volume within each category.
No, since the brands classified within the sector are anonymous, you cannot compare them with a selected brand. You can only compare it with the industry average.
Data Privacy Questions:
Data are matched based on industries integrated through APIs, and analyses are conducted according to each industry's averages. All data are processed in anonymized form.
Data are anonymized using k-anonymity and aggregation methods. Data are automatically collected via APIs, with no human intervention at any stage. Once the transfer process is complete, anonymization is applied
in an irreversible manner.
Depending on the data type, AES-256 or SHA-256 (irreversible) encryption algorithms are used. This encryption applies both in-transit and at-rest.
Each brand's data is logged with unique identifiers. A multi-layered authorization system is applied on the front end, while data flows are regularly monitored on the back end.
Data undergo automated consistency checks at the API level. The system detects anomalies, duplicates, or outliers in uploaded data. Suspicious or inconsistent data are excluded from averages until validated.
Read-only API keys used for connecting ad accounts are stored on servers located in Turkey, encrypted with AES-256. Key validity periods are tracked, and users can revoke access through the platform at any
time.
No. AdBenchmarkLab's infrastructure is not integrated with any AI services. Data, even if encrypted, are never shared with AI companies or transferred abroad.
All data are hosted in Turkey, in full compliance with KVKK and GDPR regulations.
When a client terminates the service, all raw and processed data are permanently deleted from the systems within five business days. After deletion, a signed and sealed confirmation document is issued by the
Data Protection Officer (DPO) and delivered to the client.
All data belonging to the brand are deleted retroactively. The industry average is then recalculated excluding the deleted data.
Yes. The right to delete or withdraw data is regulated within the confidentiality and usage agreement signed between the parties.
Industry averages are calculated using anonymized datasets consisting of at least five different brands. No brand's identity, market share, or competitive advantage is disclosed. This structure fully complies
with Competition Law and all related regulations.
No. AdBenchmarkLab does not use any cloud provider or external data processor. All infrastructure operates on our own servers located in Turkey.
Penetration tests, web application security analyses, and malware assessments are regularly conducted by independent third-party companies. In addition, our platform holds ISO 27000 and ISO 27701
certifications.
About the terms under AdBenchmarkLab:
Each company has its own definition of conversion. Even within the same industry, conversions vary (such as collecting forms or time duration on page). In such cases, a warning is shown in the relevant line on
the panel whose data is not meaningful with AdBenchmarkLab's algorithm.
