Mobile fraud: how to get targeted traffic without wasting your budget
Tags: Traffic, Mobile Apps, Fraud, Mobile Marketing, Digital Marketing

Mobile advertising agency Mobisharks (part of Kokoc Group) decided to understand the fraud problem, categorize and figure out how to get rid of it.

Fraud means advertising an offer using prohibited traffic sources. The problem is not new — almost always unscrupulous contractors tried to achieve the promised results by not the most honest methods. And it turned out that the customer, as it were, received the required figures, but in fact, a considerable part of them turned out to be profanity that did not bring any real benefit to his business.

Let’s start with statistics. Colleagues from Fraudscore analyzed the market and came up with very interesting results.

As you can see from the graph, the fraud percentage is simply huge, reaching a peak of 39%!

The situation is even more interesting in mobile traffic.

Here the share of fraud confidently reaches 40%.

Before you understand what to do with all this, let’s understand the nature and types of this problem.

Types of fraud

Motivated traffic

Everything is as simple as possible — users install the application for a certain reward. It seems that this is not so bad — there is a fact of installation, the indicators go up. In fact, in 99% of cases, such a user has zero interest for the advertiser. After the fact of installation, the interaction with the application ends, the client pays money for the actual action, but in reality he has another dead mobile soul in his statistics.

Bots

One of the juiciest and most common fraud categories. Fraudsters use its capabilities to the maximum. Here you will find fake devices, emulators, traffic from data centers and the active use of proxies.

There has even appeared a special term for this type of fraud — bot farming. Unscrupulous contractors have subcontractors with bots for every taste or even their own bot farms, who are ready at any time to reach out fantastic results in numbers that are absolutely useless for any client.

Bots are the simplest ones, launching from a specific service. Difficult — they already use proxies and dynamic IPs. There are also botnets, which are whole groups of bots united into one network.

In fact, bot is a program that performs a specific function in an automated mode. Most often this is the installation of mobile applications. Everything looks as if the action was performed by an ordinary person. In fact another example of draining the client’s budget to nowhere with zero result for the latter.

Fraud using suspicious patterns by device parameters

Fraudsters skillfully play with a number of parameters — IP, OS version and different types of browsers. Several application installations can be made from one device. For the advertiser, as in all other similar cases, the result will be the same — loss of part of the budget for mobile marketing.

Misgeo

Imagine a situation — a client sets the task of attracting users living in a certain area. Fraudsters use geolocation settings, actively catching up, as it were, targeted traffic. In fact, traffic comes from a completely different location from motivated users or even bots.

Attribution fraud

This type of fraud is also known as clickjacking. In our case it would be more correct to call it installjacking. Its essence lies in placing invisible elements on the screen. The user is interested in some content, clicks on it, but in fact activates an invisible element by clicking on a certain link or performing some action — for example, installing an application. It is easy to guess that the only ones who win in this situation are the fraudsters themselves.

Types of client-side approaches against fraud

According to a Forrester report, about a third of marketers believe that about 40% of their mobile budgets are at some level of risk of being fraudulent. Advertisers have developed a number of methods to combat this problem. Here are the most common ones.

Using antifraud systems

Based on the experience of Mobisharks, we can say that this method is one of the most effective. As the old saying goes: “If you want to do something well, do it yourself.” Experience in using a balanced set of solutions to combat fraud traffic with the involvement of third-party technologies gives very good results. For example, some sources manage to detect up to 95% of fraudulent traffic. The ideal technique in this case is the harmonious combination of automatic and manual interlocks.

Validation system

A striking example of this approach is the automatic rejection of traffic from non-targeted geo. Very often, as described above, scammers drive traffic using bots or motivated users from regions that are not directly related to a specific advertising campaign. It is a wise decision to automatically reject such traffic. Let’s say you are running a geo campaign targeting Moscow and its region. Suddenly a suspiciously large amount of traffic from Vietnam starts pouring in. A reason to think about it and filter out such traffic.

Self-analysis of unloading from MMP

In this approach you should pay attention to CTIT (click to install time). This is the so-called time from click to install. Let’s think about how long it takes for a user to see an ad and click to download an app. As practice shows, about 20 seconds — 10–15 minutes. If the CTIT is less than 20 seconds or more than an hour, it is very likely that this is attribution fraud, which in itself is not very good for advertisers’ budgets. A competent CTIT analysis can be an effective tool for identifying and combating fraudulent traffic.

Traffic analysis based on data from the client’s CRM at the level of purchases / orders/deposits

This approach requires the proper level of professionalism, but if you do everything right, you can achieve impressive results. The meaning of such a solution is in the search for anomalies and various kinds of inconsistencies, the names of buyers and email addresses of the same form. For example, all of a sudden, for completely inexplicable reasons, a region may be activated due to geo. And from there a wave of traffic hits you. This phenomenon raises certain suspicions and requires additional verification. It is also worth considering the fact that some especially advanced bots have even learned how to make deposits, imitating the actions of a real user as fully as possible. So attentiveness and analysis are your faithful helpers in the fight against fraudulent traffic.

Disabling individual sources

In some ways this approach has something in common with the previous paragraph. It is somehow connected with the search for anomalies in traffic analysis. If in the statistics you see completely inexplicable surges in activity, then you should pay special attention to them, double-check and, if necessary, disable these sources.

Fraud in CPI and CPA: what is the difference

In CPI fraudulent traffic consists mainly in the appropriation of installations from other channels — organic and/or installation by inanimate users, bots or fakes.

In CPA fraudsters actively use motivational traffic, earning on the difference from the amount received from the advertiser minus the remuneration paid to the clicker — the person who, on their order, performs pseudo-targeted actions. Attribution of installs and making fake orders (incorrect data in the fields of the order form, cancellation of orders, deposits for the minimum amount) are actively spread in CPA.

Whichever system you work with, it is worth remembering one thing — fraudulent traffic will only bring you losses. Be careful, check traffic sources, do not hesitate to take some moments under manual control — it is better to recheck several times than to find out one day about the loss of a considerable part of the mobile budget.

And now the number you’ve all been waiting for. Get ready, it will be a little scary!

How much can you lose on fake traffic?

Up to 50–80% of the budget for traffic channels with high % of fraud!

Methods that work

Based on our experience, we can say that the following tools have proved to be excellent in the fight against fraudulent traffic.

Here they are:

-Using MMP anti-fraud systems

-Analysis of traffic according to data from the client’s CRM

-Comprehensive assessment of various parameters. For example, a low CR in an install is not a 100% indicator that all traffic is fraudulent. From sources such as Unity or DSP (DV360), the conversion to install can be below 1%, but the fraction of fraud is small — 0–1%.

Tips and tricks against fraud