The exposure of LinkedIn posts is getting lower and lower. How should we systematically troubleshoot?
POST

The exposure of LinkedIn posts is getting lower and lower. How should we systematically troubleshoot?

Qixing Global analyzes the common reasons why LinkedIn posts are getting less and less exposed, how to systematically check the common reasons, the order of troubleshooting, execution methods and core indicators to help individual SOHOs, internal to external factories and foreign trade teams improve the customer accuracy and effective business opportunities of LinkedIn's free natural flow.A common problem is to attribute the decline entirely to the algorithm, without distinguishing between topic fatigue, relationship quality, format, posting time, and account number.

The exposure of LinkedIn posts is getting lower and lower. How should we systematically troubleshoot?
The exposure of LinkedIn posts is getting lower and lower. How should we systematically troubleshoot?

For personal SOHO, internal to external factories and mature foreign trade teams, the resource conditions for this problem are different, but the mistakes are usually the same: all the decline is attributed to the algorithm, without distinguishing between topic fatigue, relationship quality, format, release time and account positioning.So don’t copy your peers’ publishing frequency, audience, or budget just yet.

SOHO should focus its limited time on the most suitable customers and products; when transferring internally to external factories, first complete overseas trust information; and mature teams should unify their marketing and sales caliber.No matter the category, organic flow is determined not only by posting, but also by relationship relevance, review quality, ongoing dialogue, and engagement after content; the number of interactions must be judged along with the target customer identity.Operational goals should all fall into effective dialogue, quotations and business opportunities, rather than stopping at busy data.

It can be advanced in three steps.The first step is to compare the high and low performance content in the past 90 days, and check the differences in crowds, beginnings, themes, formats and interactions one by one. The second step is to determine the target roles before release, and after release, promptly respond to high-quality comments, participate in customer topics, record data access and conversations, and do periodic reviews based on topics and groups of people.Complete the undertaking; the third step is to write down hypotheses for each adjustment, such as which types of customers are expected to increase and which indicators will improve.Changes without assumptions cannot form a team experience.

It is recommended to adopt "quantity + quality" for data review.Quantity includes the proportion of target customer interactions, repeat interactors, data visits, search exposure, attention conversions, effective conversations and content-assisted business opportunities; quality verifies the country, company, role, application, quantity and time.In particular, this question should be judged based on whether the exposure of the target role and the access to data are improved simultaneously.Both sets of data must correspond to the same piece of content, ad, or source.

If there is still no improvement in a continuous observation cycle, you should return to customer positioning and value expression instead of continuing to increase volume.The value of interactive review is to allow the right customers to quickly confirm whether you are suitable, rather than making everyone mildly interested.

When this question is implemented, you can first use a small group of real target accounts to verify: compare the high and low performance content in the past 90 days, and check the differences in crowds, beginnings, themes, formats, and interactive engagements one by one.After execution, don’t just rely on your feelings to judge, but improve your judgment based on whether the target role exposure and data access are synchronized; at the same time, save the customer identity, version, date and subsequent sales results to avoid mistaking accidental replies for replicable methods.

Related content

A LinkedIn post has a lot of likes but no buyers. How to identify invalid interactions?

Qixing Global analyzes LinkedIn posts that have many likes but no buyers. How to identify common reasons for invalid interactions, troubleshooting sequences, execution methods and core indicators to help individual SOHOs, internal to external factories and foreign trade teams improve the customer accuracy and effective business opportunities of LinkedIn's free natural flow.A common problem is to only count total likes, ignoring that interactors may be peers, job seekers, suppliers, or non-target regions.

Read more →

How to reply in the LinkedIn comment section so that it can naturally transition into a business conversation?

Qixing Global analyzes the common reasons, troubleshooting sequence, implementation methods and core indicators of how to reply in the LinkedIn comment area to naturally transfer to business conversations, helping individual SOHOs, internal transfers to external factories and foreign trade teams to improve the customer accuracy and effective business opportunities of LinkedIn's free natural flow.A common problem is that the reply is only a thank you or an immediate sales pitch, which fails to continue the professional discussion and can easily make the other party defensive.

Read more →

How to avoid appearing deliberate when proactively commenting on potential client content on LinkedIn?

Qixing Global analyzes the active comments on potential customers on LinkedIn, how to avoid common reasons, troubleshooting sequences, implementation methods and core indicators that appear deliberate, and helps individual SOHOs, internal to external factories and foreign trade teams improve the customer accuracy and effective business opportunities of LinkedIn's free natural flow.A common problem is using templated compliments or each item with product information, which fails to reflect true reading and professional value.

Read more →