US Android user screening or iOS user screening, which one is more suitable for low-cost conversion

To achieve low-price conversion in the US market, the dimension of device identification has recently been re-emphasized. In the past, many people screened numbers and paid more attention to user registration status, activity, or gender and age. However, when screening American users recently, Android users andThe differences between iOS users are increasingly being discussed separately.

The reason is not complicated. Low-price conversion itself strives for efficiency, and efficiency largely depends on crowd matching. If the device type is different and the user behavior is different, the conversion results will naturally be different.

So the problem is no longer just US Android user screening andWhich one is better for iOS users to screen? It depends on which type of device users should be prioritized in different low-price conversion scenarios.

Why device identification is starting to impact low-price conversions

Low-price conversions usually look at low-cost starting volume, high response rate and quick transaction.

This type of scenario requires high user response speed and is also more sensitive to crowd matching. If the structure of user devices in the data pool is mixed, it can easily affect the overall conversion performance.

The role of device identification is to help with more detailed crowd filtering.

For example, U.S. Android users are often more likely to achieve scale conversion in certain low-priced products;For iOS users, although the quantity may not be large in some scenarios, the quality may be more stable.

This is why device identification starts to reenter the screen number logic.

Why US Android user screening is suitable for many low-price scenarios

From a practical perspective, US Android user screening does have advantages in low-price conversion scenarios.

First, the scale of Android users is usually easier to measure.

Low-price conversions often depend on volume first, and the Android user pool is more suitable for scale testing in some scenarios.

Second, some low-price products are more compatible with Android users.

For example, tools and small consumer products often perform well among Android users.

Third, Android user screening is more suitable for batch testing.

If the goal is to first run through the conversion path and then gradually optimize, Android users are usually more suitable to put it first.

Therefore, if the goal is low-cost and rapid mass production, US Android user screening is often worthy of priority.

Why You Can’t Ignore iOS User Filtering

But this does not meaniOS users are worthless.

The advantage of iOS users is not necessarily reflected in quantity, but more in quality.

In some low-priced businesses with subsequent repurchase logic,The conversion quality of iOS users may be more stable.

And in some scenes,iOS device identification itself will also be used as an auxiliary judgment at the user level.

This is why many people who do US number detection and device identification screening now do not only look at Android, but also screen separately.iOS users.

Because of the low-price conversion, it is not just about selling at a low price, but also whether the subsequent value is worth accumulating.

Which low-price products are more suitable to prioritize Android users?

If it is a product that emphasizes fast running volume, Android users are usually more suitable.

For example, low-priced tool products, entry-level subscription products, and light decision-making products are more dependent on quick response.

At this time, U.S. Android user screening is usually moreIt is easier for iOS users to filter results.

Especially when doing batch screening, precise reach, and low-price delivery testing, this kind of logic is relatively common.

Which scenesiOS users are more worthy of priority screening

If the product is not expensive but pays more attention to user quality, theniOS user value will increase.

For example, it can lead to subsequent repurchases, lead to user accumulation, or low-price business that requires user levels.

This type of scenario does not necessarily pursue pure scale, but focuses more on subsequent value.

At this time,iOS user screening is not just device identification, but more like crowd stratification.

When doing low-price conversions, should you screen equipment or activity first?

This problem is actually more serious than Android andWhich iOS is better is more important.

If the data itself is not active enough, just screening equipment will have limited meaning.

Therefore, a more reasonable order is usually to screen active users first and then screen devices.

First do active user identification, and then do US Android user screening orWhen iOS users filter, the quality of filtered data will be higher.

In this link, you can first screen active users through Digital Planet, and then combine device identification with crowd filtering to identify American Android users,iOS users are processed in layers for different low-price conversion scenarios.

This process is more stable than looking at the equipment alone.

Why device filtering and active filtering are increasingly used in combination

This is a clear trend recently.

Because looking at the equipment alone, it only solves the problem of crowd attributes.

Looking at activity alone, it only solves the problem of immediate response.

Together, we can get closer to real convertible users.

For example, highly active Android users have completely different values ​​from ordinary Android users.

So now more and more devices identify screen numbers, which are combined with active user screening.

US Android users andiOS users, the point is not who is better

If we must draw a conclusion, the point is not that Android user screening is better, butBetter filtering for iOS users.

The point is what your goals are.

If it is a low price and quick start-up, US Android users are usually more suitable.

If you pay more attention to quality and subsequent value,iOS user screening is worth doing separately.

The more stable method is not to choose one of the two, but to combine active screening, device identification, and user stratification.

Nowadays, the competition for low-price conversion in the United States is no longer a single traffic, but the ability to filter data.

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