Twitter Analytics Opens to Every Account

Numbers beside every tweet

Since yesterday, any Twitter account can open an analytics page that lists its recent tweets with figures beside each one. Until now that page was mainly for advertisers.

Signing in shows three columns: impressions, engagements and engagement rate. Clicking on a tweet breaks the engagements down into retweets, replies, link clicks and smaller actions.

The first reaction is often surprise. Some tweets show more impressions than the account has followers, and a figure like that is easy to mistake for an audience.

Some of these numbers describe customers. Others describe a screen scrolling past.

What the dashboard counts

The terms are narrower than they sound:

• Impressions are the times the tweet was shown on a screen, in a timeline, a search or a profile.
• Engagements are every click or action on the tweet, of any kind.
• Engagement rate is the engagements divided by the impressions.
• Link clicks are clicks on the web address in the tweet.
• Retweets and replies are people passing it on or answering it.
• Profile clicks are people opening the account to see who sent it.

Link clicks, retweets, replies and profile clicks each involve a decision by a person. Impressions and the engagement total mostly measure activity on screens.

An impression is not a reader

An impression is counted when the tweet appears on someone's screen. Whether they read it or scrolled past while looking for something else makes no difference to the count.

One person can add several impressions by meeting the tweet in different places, and a retweet by a busy account can add a great many from people far outside your area.

For a business that serves one town, a tweet seen widely somewhere else has done little. Impressions say how far a tweet travelled, not who it reached.

What sits inside the engagement total

Engagements add every kind of click together. A tap to enlarge a photograph counts the same as a reply asking how to book.

A tweet with a striking picture can show a high engagement rate built almost entirely from people opening the picture. That is not the same as interest in the business.

Open the breakdown for any tweet that looks successful. The useful question is which kinds of engagement made up the total.

The numbers worth a monthly look

For most small business accounts, four figures say something about customers: link clicks, replies, retweets and profile clicks.

Link clicks show which tweets sent people to your site. Replies show which ones started a conversation. Retweets show what your followers thought worth passing on.

Profile clicks are quieter but telling. Someone who opens the profile after a tweet wants to know who you are, which is often the step before a follow or a visit.

A worked example

An animal rescue society in Prince George finds new homes for cats and dogs, with a small paid staff and a long list of volunteers. Its Twitter account posts animals ready for adoption.

When the dashboard opened, the volunteer who runs the account looked back over the past month. The tweets with the most impressions and the highest engagement rates were photographs of puppies.

The breakdown told another story. Most of those engagements were clicks to enlarge the photo. The tweets that drew replies and link clicks were plainer ones naming an animal, describing its temperament and linking to its own page.

The society now tweets each animal with its name, one sentence about it and a link to its profile page rather than the home page. The volunteer records link clicks and replies each week instead of impressions.

Those are the actions that lead toward an application. A photo enlarged on a phone ends there; a click through to an animal's page is someone reading about adopting it.

Matching clicks to visits on your site

Twitter's link clicks and the visits Google Analytics records from Twitter will not match. A click is counted when it happens; a visit only when the page loads and the tracking code runs.

Some visits from Twitter's phone apps also arrive without saying where they came from, and Google Analytics files them as direct visits. The gap is normal.

Adding campaign tags to the links you tweet makes those visits easier to find. The tags name the source and the campaign, so the visits appear under that name whichever app they came through.

Followers are not the audience

The follower count sits at the top of every profile, and it is the number owners quote most often. It says little about customers.

Followers include other businesses, people who followed once and stopped reading, accounts nobody uses any more, and some that were never people. Many of them will never see a given tweet.

A small account whose tweets get replies from people nearby is doing more useful work than a large one talking to strangers.

Reading a month, not a morning

Any one tweet's numbers depend on the hour it went out and who happened to be looking. A single good morning proves very little.

Patterns across a month are more useful: which kinds of tweets bring clicks, which bring replies, and which hours get answered. The dashboard lets you export its figures, so a monthly copy can sit with the rest of your records.

The counter-case

Some businesses use Twitter mainly to be seen. A new shop introducing itself, or an event in the weeks before it opens, may care how far its tweets travel, and impressions measure exactly that.

Still, the useful reading is local and taken over time: whether the account is reaching the right people month by month, not whether one tweet went far.

And for an account that exists to answer customers, the most valuable work never shows as a number. A good reply to a complaint matters more than any figure on the page.

A month of tweets, read properly

1. Open the dashboard and choose the past month.
2. Note the link clicks and replies for each tweet.
3. Open the breakdown of any tweet with a high engagement rate.
4. Add campaign tags to the links you tweet.
5. Compare link clicks with visits in Google Analytics.
6. Group tweets by kind and see which kinds draw replies.
7. Export the figures once a month and keep them.

Step three is where most of the misreading happens. A high engagement rate made of photo clicks looks like success, and only the breakdown shows whether anyone did something that leads to business.

The new Google Analytics setting that leaves known robots out of those visit counts, and why to try it on a separate view first, has its own post: filtering known bots out of analytics.

Frequently asked questions

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