Twitter social media conversion is unstable, the core is often not interaction, but the authenticity of the account

Twitter's current traffic characteristics are becoming more and more obvious: interaction is fast, communication is fast, and hot spots are switched quickly. For many projects on Twitter, a situation often occurs - the popularity of the content seems good, and there are not many likes, retweets, and comments, but the actual private message consultation, community accumulation, and transactions behind it are not stable.

Sometimes a piece of content suddenly explodes, but there is almost no conversion later; sometimes the interaction is average, but it can continue to bring high-quality users.

Many times the problem is not the content, but the"Are the people interacting with real users?"

becauseTwitter is different from many long-term private domain platforms. It is naturally easier to appear:

lPan-interactive traffic

lShort-term hot users

lRobot account

lFake active account

If the front-end does not identify the authenticity of the account in advance, subsequent conversion fluctuations will be very large.

WhyTwitter interaction does not equal real traffic

Twitter itself favors open communication.

Therefore, even if a lot of content is highly interactive, it does not mean that it will be valuable later.

For example:

lHot onlookers

lRobot forwarding

lShort term wool account

lUsers from non-target areas

lLow active flood traffic

Although these accounts can create interactions, they will not form real conversions.

especially nowAs more and more AI content becomes available, the gap between superficial interactions and real users will become more and more obvious.

Many projects are discovered later:

Lots of likes;

Not many people actually consulted.

The problem in many cases is not that no one views the content, but that the interactive users themselves are not of sufficient quality.

Why"Account authenticity" will directly affect back-end conversions

The real value of Twitter is never “whether there is interaction”, but:

Are there long-term real users behind the interaction?

For example, real high-quality accounts usually have:

llong-term usage behavior

lStable interaction frequency

lFixed social relationship

lLong online status

lNormal content history

In contrast, a large number of abnormal accounts usually appear:

lShort-term high-frequency interaction

lContent is blank

lexception concern structure

lAbnormal active behavior

Even if these accounts can increase interaction data, they will not form real private domain value.

So now more and more people are starting to:

authenticity identification;

Active status analysis;

long-term behavioral judgments;

put inTwitter operations front.

WhyTwitter is prone to "the data looks good but the results look ugly" in the later period

The most common pitfall for many Twitter projects is excessive focus on interaction numbers.

For example:

lNumber of forwards

lNumber of likes

lBrowse data

lComment growth

While these data reflect spread, they don’t necessarily reflect conversions.

Because what really determines the back-end results is usually:

lIs the user real?

lWhether the user has been active for a long time

lWhether the user belongs to the target region

lDo users have real needs?

If these issues are not screened in advance, what follows:

lprivate message

lcommunity

lcustomer service

ldrainage

will become increasingly unstable.

WhyTwitter operations increasingly rely on “user filtering”

I have done many projects in the pastTwitter, I prefer to follow hot topics.

The hot spot is coming;

Traffic is coming;

The interaction went up.

But now more and more people have begun to realize that truly stableThe core of Twitter operations is not hot spots, but "who is interacting."

because:

Highly active real users will stay for a long time;

Pan-interactive traffic will disappear quickly;

Abnormal accounts will not result in transactions;

Robot interactions do not create a private domain.

So now more and more people are starting to:

Screen users first;

Then amplify the content;

Finally, enter the private domain to undertake.

In this way, the overall conversion will be much more stable later.

WhyTwitter is more afraid of “fake activity” than other platforms

Platforms such as Instagram, Line, and WhatsApp often favor long-term relationships.

butTwitter is naturally more prone to "short-term fake activity."

For example:

lBatch interactive accounts

lAutomatically forward traffic

lHot followers

lShort-term active accounts

This traffic makes the data look good, but has little long-term value behind it.

soWhat really matters on Twitter is no longer the “volume of interactions,” but the “proportion of real users.”

Especially:

lAI tools

lfinancial projects

lcurrency circle

lTool products

lOverseas communities

These industries themselves are particularly dependent on real users.

Front-end authenticity screening will directly affectTwitter private domain quality

a lot ofLater in the Twitter project, you will find:

The content is getting more popular;

The backend is getting harder and harder to convert.

Many times the problem is not the content, but that the front-end accounts are not filtered in advance.

For example:

lLow authenticity account

lShort-term hot traffic

lrobot interaction

lUsers from non-target areas

After these accounts enter the system, they will continue to lower the overall quality of the private domain.

Doing it a lot nowFor projects operated by Twitter, before content promotion and user acquisition, a round of basic filtering will be done through account authenticity detection, activity status analysis and long-term behavioral screening to separate low-quality accounts in advance, and then further stratified by region, interest and interactive behavior.

In this way, subsequent private messages and community operations will be much more stable.

Twitter operations will increasingly be biased toward “real user identification” in the future

I have done many projects in the pastTwitter is more like fighting for traffic. But now more and more people have begun to realize that real long-term and stable conversions actually come from real users.

futureTwitter operations will increasingly be biased toward:

lAccount authenticity identification

lLong-term active user screening

lReal social relationship analysis

lHigh-quality user stratification

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