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How often do you hear the phrase "hashtags don't work"? We are several times a week.

Before canceling the visibility of likes under friends' posts (data from Twitter by Jane Manchun Wong), we’ll check from personal experience whether the hashtags still work or not.

Promotion using hashtags on Instagram is one of the main methods of social profile promotion.

Hashtags are a great affordable way to make your users known if your account is still unknown to anyone. But hashtags must be relevant.

So it was before. But does this method work today? Let's figure it out in practice together.


1. What hashtags should you use?

First, we should determine what hashtags could be to understand what we will build on.
We are interested in the frequency of use (number of publications) of tags.

So, it is classified by the frequency of use:

  • low-frequency (LF) – up to 50,000 posts;
  • mid-frequency (MF) – 50,000 – 100,000 posts;
  • high-frequency (HF) – 100,000 – 1,000,000 posts;
  • super-frequency – more than 1,000,000 posts (not very effective, because they are very often used).

There is an updated black-list of hashtags. If you use any tag from that list, your post is guaranteed to lose its visibility by tags.
The shadowban is also nearby, but the official Instagram doesn’t confirm its existence.

We sorted out hashtags by its categories. It’s time to act.
Our copywriter Ekaterina has long had an active and strong interested in free Instagram promotion.
When in August 2018 she caught an eye of an article about the promotion by frequency tags (method has existed since 2017), she immediately decided to use the recommendations and test the operation of the method on her account.

A year ago, the algorithm really worked and brought likes to the topics: nature, cosmetics for care, manicure, books.

Find out if this method works in April 2019.

Principle of method:

1. collect of 30-90 thematic hashtags;
2. splitting tags into 3 groups;

  • high-frequency – 10 – 30 pcs;
  • mid-frequency – 10 – 20;
  • low-frequency – 10;

3. publishing a post with the 1st group of hashtags;
4. after 10 minutes of taking the high-frequency indicators, deleting the first group of tags and publishing the 2nd;
5. after 10 minutes of removing the 2nd group and adding the 3rd with LF;
6. final performance audit.

Mechanism:

  • HF start to collect first likes;
  • MF select the right amount before getting into the TOP-9;
  • LF work for long-term organic traffic.

These are tags that will bring likes for more than one month. So, its number will be small. But likes would be.
In theory, everything is simple: find a bright and interesting photo (nature, sunrise/sunset, seals, etc.). Collect relevant hashtags, publish a photo post and enjoy the effect.

What’s the reality?


2. Inputs

Profile on Instagram – personal user account with your own TA.
Content Topics – Tester’s Interests.
Posting time – at the discretion of thetester.
The type of hashtags – HF, MF, LF and optionally superfrequency.

No geotag used because it’s a different type of tag.

Mechanism:

  • collection of hashtags – through the webstagram.com service;
  • translation of HF, MF, LF tags into other languages to obtain maximum coverage of the topic and a more or less representative sample of users;
  • posting in accordance with the tester’s content plan.

2.1 Experiment 1 #cosmetic

Topic – makeup products (lip balms).
Keywords: balm, balms TM. In different combinations and in different languages.

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An Excel spreadsheet demonstrates how little it was possible to collect the MF tags. And this is still a very good result for the chosen topic. However, there were many LF tags.

Progress:

1. Thursday, 04/25/2019, 10:12 pm – publication of a photo with the 1st group of low-frequency tags.
Not the best time to post on Instagram from Catherine’s point of view. But all the better – she was not afraid of the inconvenience.

2. 10:44 pm – HF performance test.
The publication gets 14 likes, and 10 of it is account followers. And 4 likes were received really by HF posting. We tried to track everyone who liked the photo and like it in response.
Removing the HF, adding the 2nd mid-frequency group to the comments.

3. 11:45 pm – MH results – 21 like.
80% of it brought profile followers.

4. 6:58 am +32 likes, 2 comments and 20 new followers from Korea (which unsubscribed at the end of the day).
Removing MH tags.

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Conclusions of Experiment 1:

  • HF worked poorly.

The reason is that the posting time or topic may have been incorrectly selected. Or both.

  • Short (10 minutes) suggested time to receive primary results.

It takes at least 30 minutes to receive data. Better – from time to time.

  • On the contrary, MH and LH tags exceeded expectations – even today, likes come in this post. There was also a large activity of users from Korea.
  • Post did not hit the TOP-9.

Reason – see p. 1.

  • Translation of key phrases into other languages gave a good growth in likes and subscriptions.

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2.2 Experiment 2 #nails

Topic – competitive photo of a manicure for a jewelry store.
Keywords: nails, nail polish TM and jewelry, products from silver, peridot. In different combinations and in different languages.

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Process:

1. Saturday, 04/27/2019, 8:43 am – posting with HF tags;

2. 9:43 am – remove the high frequency and add the mid-frequency group of tags. +12 likes, including account followers;

3. 10:45 am – removing the mid-frequency, adding the low frequency. +13 likes, including profile followers;

4. A day later at 12:27 pm – results of low-frequency tags: 60 likes and 7 new followers.

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Conclusions of Experiment 2:

  1. HF worked again poorly;
  2. Mid-frequency also quiet upset;
  3. LF turned out to be effective;
  4. The post was in the TOP-9 by tags:
  • MF – #項鏈.

Hashtags

  • HF – #jemstones, # シ ル バ ー ペ ン ダ ン ト, #peridote, #peridotnecklace, #peridotstone.

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Translation of key phrases into other languages again gave a good increase in likes.

Since today TOP-9 is formed individually for each user, it makes no sense to be in TOP-9 for several tags.

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2.3 Experiment 3, #books

Topic – review of a book as part of a book marathon.
Keywords: books, reading, literature, nametag of the author, title.

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Process:

1. Monday, 04/29/2019, 2:39 pm – publication of a post with the 1st group of high-frequency tags.
Lunch hour on a weekend.

2. An hour later at 3:39 pm – check the HF effectiveness.
The publication gets 20 likes, mainly from profile followers.
Removing the HF, adding the 2nd MF group to the comments.

3. 4:39 pm LF results: +12 likes.
Adding 3rd LF group.

4. In a day, 04/30/2019 at 2:39 pm: 35 likes and 3 new followers.

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Conclusions of Experiment 3:

1. HF worked as expected bad.
Such a result was predictable according to the results of previous tests.
2. MF result was also unsatisfactory.
3. Post temporarily hit the TOP-9 for 7 LF tags:

Hashtags books blog

Frequency is greater than 1000

Hashtags frequency

Frequency is lower than 1000

Translation of key phrases into other languages gave a good growth in likes and subscriptions.

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3. Totals

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Together for the Three Experiments:

  1. hashtags work and bring likes;
  2. low-frequency and narrow-topic tags work well (product name and type, TM, author);
  3. good time to publish posts is evening (only from personal experience);
  4. the hardest thing is to put together a group of mid-frequency tags;
  5. get into the TOP 9 really. But only with MF and LF tags;
  6. post with makeup cosmetics got the best result of 3 selected topics;
  7. there are only some narrow-topic ones focused on target users that remained based on the results of the work on all the collected hashtags. It brings likes;
  8. friendly users in particular from Korea. Of course, based on only one publication, it is rash to say so. However, namely users from Korea brought a significant number of likes to one of the posts.

NB. “InstaCats” tactics weren’t deliberately used to select likes because the followers of cats are not TA for research topics.

2 posts are still held in the TOP-9 by 2 low-frequency tags:

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Method complexity:

  • Manual working.

An automated hashtag selection service helps a lot – it pulls up tags similar to the main query. But any tag needs to be checked manually for meaningfulness and relevance. Especially in foreign languages.

  • Time and labour intensity.

Get ready for a long hard work – we only collected and sorted 200 tags for 3 photos in 1.5 working days. Translating keywords and testing tags for relevance to the topic.

+ You will need to allocate time for taking results and replacing tags, processing comments.

  • Relatively low effect.

Not one of the posts became successful and did not collect hundreds or thousands of likes.
So, we managed to get into the TOP-9 by some tags, but there is no practical benefit from this because TOP-9 has its own user.

We found out the main thing – the frequency hashtags method really works.

Even if the number of “hearts” under the publications is hidden, it’s still advisable to promote using the frequency tag method – at least, the likes will remain visible to you.
A post with a lot of “Like” is still ranked better and is higher in the friends’ feed.
The analyzed method can be used if you just chase after likes but don’t want to use mass-liking. Especially if the posts on your profile are completely related to one topic. Because it’s very difficult and resource-consuming to collect and verify tags for each new topic. It’s enough to say that already on the 30th tag you will understand that you’ve gotten into trouble.

It’s totally up to you whether the method is right for you or not. We’ve listed all the difficulties you may have.


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