Case Study: FraudScore and Magnit Working on High-Quality Traffic
FraudScore is known for its work with direct advertisers. In a world where online ads are estimated to be worth around $800 billion in 2022, and global ad fraud is expected to reach $100 billion in 2023 — the value of a reliable antifraud solution becomes obvious.
FraudScore’s products for direct advertisers are able to cover all the stages on online ads funnel, and can provide both detection and prevention. Collaboration between an independent antifraud solution and advertiser have a great benefit when it comes to choosing the right traffic sources, signing up new partners, and filtering out bad players.
CIS and Russia-famous retail chain “Magnit” is one of the leading players on the retail market for food product sales, leading in the number of stores and geo representation.
The company is represented in about 4,000 offline stores that generate about 16 million visits daily. “Magnit” operates in a multi-format model that includes home stores, supermarkets, pharmacies, and drug stores. As of June 30, 2022, the company had 26,731 stores in 67 regions in Russia.
“Magnit” is also known to be one of the leaders of the retail market in terms of mobile technologies. There is a number of mobile apps created by the company for the end customers, including:
FraudScore has been a partner of “Magnit” for ad fraud protection and prevention, and we would like to share our interview with Yuliana Zamoshanskaya — affiliate manager of “Magnit” — and her story about ad fraud in online advertising for a major retail chain.
Yuliana, can you tell us a little bit more about your job?
I am an affiliate manager for “Magnit”. My job involves purchasing and analyzing in-app traffic for the company’s mobile applications.
Was there a specific reason why you decided to find an independent antifraud solution provider for your ad campaigns?
The antifraud systems available on the tracking platforms we use are imperfect and currently unable to detect and filter many types of ad fraud. We had long known about the quality of traffic evaluation provided by FraudScore, and decided to give it a proper test run.
Can you give us an example of how FraudScore has become a part of your business processes? What is the scenario to use FraudScore’s solution on a daily basis?
With the help of FraudScore, we receive more accurate data regarding the quality of incoming traffic. It helps to optimize the processes of working with partners, detect and disconnect poor quality sources, and also not pay for fraudulent events.
What is the data from FraudScore’s reports that helps you the most?
While analyzing data from FraudScore’s reports, the main parameters that we use are Fraud Status — to understand the quality of conversions, and Fraud Reason — to understand the reasons for events falling into different fraud categories and possible optimization on the traffic source side.
FraudScore is convenient to use when analyzing incoming traffic — as it always clearly shows the number of fraudulent events, and provides a good estimate of these events based on the fraud index. It allows us to understand which traffic source we should pay extra attention to.
Yuliana, can you tell us more about the recommendations that you share with your partners based on FraudScore’s reports?
Based on the data obtained from the FraudScore system, we either stop or encourage traffic sources. We also make exports from the system so that networks can verify and understand why their traffic was evaluated as fraud.
Can you share some real-life examples on how FraudScore assisted in reaching your goals?
We had an important task to control and manage one of our mobile apps and traffic quality.
When FraudScore was given access to traffic analytics on that app, a major fraudulent source was detected, whose traffic managed to bypass checks by other antifraud systems.
Nearly every conversion from this source was marked as fraudulent. After collecting and analyzing the received data, a decision was made to end cooperation with this source.
Thank you! We are glad to see that FraudScore’s algorithms were there to help you protect your budgets, and we showed more reliable results than other providers.
Regarding your expertise — can you maybe share some advice or recommendations to other advertisers on working with online advertising and combating ad fraud?
Traffic quality assessment is very important as the presence of fraudulent events affects organic traffic and advertising campaign statistics as a whole. That’s why it’s so important to constantly monitor the dynamics of motivated and non-motivated traffic.
FraudScore team wants to thank “Magnit” and, personally, Yuliana Zamoshanskaya, for their great collaboration and eagerness to fight for high-quality ad traffic. “Magnit” is a great example of a large retail company understanding the reality and severity of fraudulent traffic, and the damages it poses on online advertising. When there is a mobile app involved — the stakes are even higher, as more than 29% of iOS and 30% of Android traffic was fraudulent in 2022.
FraudScore team offers a 14-day free trial to test the system, and check your traffic sources with FraudScore’s algorithms. If you have any questions, please feel free to contact us.