increasing twitter click- t hroughs with images

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Increasing Twitter Click-Throughs with Images Michael Levi UNECE Work Session on the Communication of Statistics June 19, 2014

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Increasing Twitter Click- T hroughs with Images. Michael Levi UNECE Work Session on the Communication of Statistics June 19, 2014. Background. BLS began tweeting news release headlines in June, 2012 Expanded to other publications in January, 2013 - PowerPoint PPT Presentation

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Page 1: Increasing Twitter Click- T hroughs  with Images

Increasing Twitter Click-Throughs with Images

Michael Levi

UNECE Work Session on the Communication of Statistics

June 19, 2014

Page 2: Increasing Twitter Click- T hroughs  with Images

Background

BLS began tweeting news release headlines in June, 2012

Expanded to other publications in January, 2013

Added images to selected tweets beginning in January, 2014

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Page 3: Increasing Twitter Click- T hroughs  with Images

Tweets with Images

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Page 4: Increasing Twitter Click- T hroughs  with Images

Motivation

4

Why images? Cheap and easy way to entice users

to access underlying content

Expectation of success We know that visually appealing

layout increases readership of publications

It stands to reason that the same would hold true for tweets

Page 5: Increasing Twitter Click- T hroughs  with Images

Beware the Intuitively Obvious!

Michael Levi

UNECE Work Session on the Communication of Statistics

June 19, 2014

Page 6: Increasing Twitter Click- T hroughs  with Images

Results

Did adding images increase click-throughs? Before looking at data: “Absolutely!” After looking at data: “Not the way we

expected.”

Page 7: Increasing Twitter Click- T hroughs  with Images

Metric Used

7

Number of “click-throughs”

Each tweet has a unique shortened URL, for which we can get reliable counts

Measures how many users are navigating to underlying data and analysis

Page 8: Increasing Twitter Click- T hroughs  with Images

Click-throughs vs. Retweets

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0 50 100 150 200 250 3000

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

Click-throughs vs. Retweets

Retweets

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Click-throughs vs Retweets: Bottom 90%

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0 5 10 15 20 25 300

200

400

600

800

1,000

1,200

Click-throughs vs. Retweets, Zoomed

Retweets

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Page 10: Increasing Twitter Click- T hroughs  with Images

Click-throughs by date

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1 25 49 73 97 1211451691932172412652893133373613854094334574815055295530

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

Click-throughs in Chronological Order

Sequence

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Click-throughs by level

110

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

Click-throughs by level

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Page 12: Increasing Twitter Click- T hroughs  with Images

Click-throughs by level – Top 35

120

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

Click-throughs by level - Top 35

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Employment Situation news releaseTweet with imageOther

Page 13: Increasing Twitter Click- T hroughs  with Images

Comparing Apples to Apples: The Editor’s Desk (TED)

A daily post featuring recent data – news releases, reports, etc.

One or two charts with summary text and link

Before Jan 2014, tweets without images

Since Jan 2014, tweets with images

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Page 14: Increasing Twitter Click- T hroughs  with Images

TED Click-throughs

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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 310

500

1,000

1,500

2,000

2,500

3,000

Click-throughs: TED only

Sequence

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No image

With image

Page 15: Increasing Twitter Click- T hroughs  with Images

TED Click-throughs Summary Statistics

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7 highest-volume tweets have images

4 lowest-volume tweets have images

Mean Median

No Image 355 331

With Image 688 343

Page 16: Increasing Twitter Click- T hroughs  with Images

Other Contributing Factors?

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No particular correlation by Type of chart (map, bar, line, etc.) General topic (employment, prices,

etc.) Day of week Time of day

Page 17: Increasing Twitter Click- T hroughs  with Images

Content: Tweets with relatively many click-

throughs

17

“Find out which occupation has the highest relative concentration in your state”

“Differences in union and nonunion compensation, 2001–2011”

“Productivity and Costs by Industry: Selected Service-Providing and Mining Industries”

Page 18: Increasing Twitter Click- T hroughs  with Images

Content: Tweets with relatively few click-throughs

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“College graduates more likely than those with less education to be married at age 27”

“Investment in higher education by race and ethnicity”

“In honor of Workers’ Memorial Day, trends in fatal workplace injuries”

Page 19: Increasing Twitter Click- T hroughs  with Images

Conclusions

19

Tweeting images has ambiguous results When tweets with images catch on,

they garner relatively high click-throughs

Most tweets with images have comparable click-through rates as tweets without images

It is not obvious what will interest the Twitterverse, but content appears to be more important than presentation

Page 20: Increasing Twitter Click- T hroughs  with Images

So Why Did I Believe Otherwise?

20

Expectations Confirmation bias A narrative, once established, is

hard to overturn

Page 21: Increasing Twitter Click- T hroughs  with Images

Conclusions II

21

Just because something is obvious does not mean it is true

Data analysis may lead to unexpected results

Page 22: Increasing Twitter Click- T hroughs  with Images

Contact Information

Michael D. Levi

Associate Commissioner for Publications and Special Studies

U.S. Bureau of Labor Statistics

[email protected]