My Trip.com Content Analytics

02Computed findings TIER 1 · COMPUTED

The part Trip.com doesn't do: which content works. Every block below is computed from your data — nothing is hardcoded, all of it recomputes on refresh.

Metric — drives the charts, hashtags & matrix below

Average views by content angle

Which kind of post your audience rewards

Groups your posts by the type of content (curiosity hook, cafe, hotel, money / value, etc.) and shows the average score per post in each group. Taller bar = better-performing type.

Average views by region

Destination still matters

Groups your posts by country (taken straight from Trip.com's tag on each post) and shows the average score per post in each country. Posts about places people search for tend to win here.

Top region

Other regions

Hashtag analysis

Average views per hashtag — tags used on 5+ posts

For each hashtag you've used at least 5 times, this shows the average score per post it brings. Helps you see which tags actually pull traffic vs which look popular but don't deliver.

Top hashtag

Other hashtags

Topic × angle matrix

Best views combinations — cells need 3+ posts, else greyed

Crosses your top hashtags with your content angles. Darker blue = stronger combination. Use it to find specific wins like "China travel + curiosity hook" instead of just "China" or "curiosity hook" alone.

Lower → Higher avg

Fewer than 3 posts

COMPUTED What makes posts get featured

"Featured" means Trip.com showed your post to its premium (Diamond) viewers — a sign the platform thinks the post is worth promoting. The bars compare how often each group's posts get this treatment. The red line is your overall featured rate; bars to its right beat the baseline, bars to its left lag.

—

Featured rate (this group)

Baseline (overall average)

Note: featured rate correlates with how recent a post is — Trip.com features almost every recent post. For fairer comparison, filter to a specific year above.

COMPUTED Premium Appeal — top posts reaching Diamond viewers

Diamond / Diamond+ / Black Diamond viewers are Trip.com's highest-spending users — the ones most likely to actually book. This list ranks your posts by how many premium viewers each one reached. Click a row to open the post.

—

COMPUTED The biggest problem — content mix

Compares how many posts you publish in each content angle vs how well those posts perform. Flags the type of content you publish the most of but that lags behind your other types — your biggest opportunity to reallocate effort.

—

COMPUTED Title elements that move views

Tests specific patterns inside your titles ("must-visit," a question mark, a number, a place name, etc.) and shows how much views lift when a title has that element vs when it doesn't. 1.0× means no effect; higher = the element helps.

Strong lift (≥1.5×)

Modest lift (≥1.15×)

No real effect

COMPUTED Per-metric reading

Checks whether your views, likes, comments and saves all come from the same kind of content, or whether different content types win different metrics. Tells you whether you have a trade-off to manage, or whether one content type wins across the board.

—

03Runnable analyses TIER 2 · ON DEMAND

Deeper cuts you trigger when you want them. Each runs a real computation on your live data and returns a result panel: compute → finding → evidence → action. Click Run.

🔖

Save-bait audit

What gets saved, and the format pattern behind it.

A "save" means a viewer bookmarked your post to use later — usually because it's practical (a guide, a list, a price). This analysis ranks which kinds of posts get saved most, finds the format pattern they share, and shows your top-saved posts as a template.

🔍

Curiosity-hook formula decode

Breaks your top curiosity-hook titles into a reusable template.

"Curiosity hook" titles are the ones that make people tap to find out what's inside ("Look Up!", "Why the 2nd floor…", "…has NO DOOR"). This pulls your best-performing curiosity titles, finds their common length, opening words, and "gap" devices, and gives you a fill-in-the-blank template.