IWD and the Gender Pay Gap Bot

Deeds not words. How a bot on Twitter rocked the posturing of comms on International Women’s Day (IWD).

Like thousands of others, I enjoyed the brilliantly powerful campaigning work of the Gender Pay Gap App on Twitter on International Women’s Day created by Francesca Lawson and Ali Fensome. In case you didn’t see it, the bot automatically RT’d organisation’s posts shared with an IWD hashtag, with a quote tweet of their Gender Pay Gap stats sourced from gov.uk data. It was developed for IWD last year and improved to make a significant impact this year.

The tweets

There were some with very minor or no gap. Hooray!

Some reported women receiving a higher median hourly pay than men. Not ok, but these percentages were generally low and not typical across whole sectors.

There were many many many more where the gap was significant and in men’s favour.

The bot aimed to shine a light on the pink-washing of IWD and called for deeds not words. Its profile image says ‘Stop posting platitudes. Start fixing the problem.’

It clearly and simply, using reported data, called out hypocrisy of organisations celebrating the achievements of women, while not actually paying them or having them in senior roles. It asked us to judge these organisations by their actions, not their words.

The response

Law firms, airlines, universities, private schools, NHS organisations, transport groups and some charities came out particularly badly. There were many organisations with gaps of 20, 30, 40%+.

It was fascinating and horrifying to see many of the original tweets being deleted and reposted without the hashtag to out-smart the bot. Madeline Odent created a very long thread of organisations who deleted or re-posted their tweets, generating 25k likes.

It was also interesting to see how other organisations didn’t do anything, even when huge gaps were reported and people replied to the messages with the bot’s tweet. Is it worse if they didn’t care? Or maybe they don’t look at interactions?

Impact

In a single day, the bot raised awareness of the realities of women in the workforce in the UK. Using data like this in a clear and simple way, it cut across all the noise.

Co-founder Francesca very kindly shared some of the stats since 1 March 2022 with me:

  • The bot generated 1136 tweets.
  • It had 78.1m impressions
  • It generated 308.9K likes, 55.2K retweets and 2.4K replies.
  • Followers grew by 197k in one day.
  • The single tweet with the most impressions was a RT of Goldman Sachs which reported a 36.8% lower gap. It generated 5.7m impressions.
  • The most engaged with tweet was this from English Heritage (with a 3.9% lower gap). It had 241k engagements.

Pretty impressive stats for an account which only had 2k followers the day before!

Lessons

Why did it work? Its premise was clean and simple. It’s language was clear and factual, leaving viewers to get angry. It generated tweets automatically using official data. It was well designed and timely. It generated a lot of activity on a busy comms day.

Was it always right? I did see one instance where it appeared to have referenced the wrong organisation. And another where the 73% stat was explained as data from a heavily furloughed workforce in comments and later a statement from the CEO, but the eye-watering stat lead to a swelling of negative pushback.

Will it make any difference? Certainly, it made a lot of noise on Twitter. It gave us as viewers, a new sport and a reason to talk about this. The responses to Francesca’s tweet about the app has had hundreds of people congratulating her. Throughout the day I saw lots of people discussing pay and looking for trends across sectors. Someone said it was a useful tool to see which companies to avoid when looking for a job. Others talked about a damage to brand reputation.

It gave many social media managers a difficult day but did it reach the CEOs or HR teams or shareholders? Will it make them take action? How widely was the data shared on LinkedIn where it might hit organisations harder?

Will we see similar bots using data on other inequalities? Let’s hope so. Using data to challenge empty words is a strong campaigning technique.

Now, more than ever is the time for deeds not words.

Read more about the bot

NB The Gender Pay Gap is based on the difference between the average hourly pay rate for men and the average hourly pay rate for women in an organisation. It is not about equal pay for the same job. This from Timewise explains more.

Written with thanks to Francesca who shared the data with me. She also wrote 5 questions to ask yourself before IWD which you should definitely read.

One thought on “IWD and the Gender Pay Gap Bot

  1. Pingback: Happy Girlboss Christmas: the sham of International Women’s Day | Crimes against English

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