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Social Media Strategy

Social Media Strategy

Following an audit of 37 OU-owned social media channels in 2020, the Social Media Engagement Team (SMET) developed a social strategy for The Open University. This strategy will continue to evolve as the social media landscape changes, ensuring it supports the University’s mission.

There’s a heap of work and data that sits behind the social media strategy on a page, highlighting four key content pillars which feed into wider University and Marcomms objectives. Beneath the strategy sits a quarterly editorial planning process, individual channel strategies, social listening and community management, and data and analytics.

How the social strategy informs editorial process

Social media is a powerful communications tool, but it occupies a noisy and crowded space, and it’s increasingly difficult to get impact. When content or campaign requests are received, they’re reviewed as part of an editorial process, considering the following four filters:

1. Universal appeal: Is the content generic enough that it will appeal to a wider audience? If it’s niche, other channels may be more appropriate.

2. Audience sizing: How many people are interested in this topic on social media? And how can we strike the balance between no one (it’s not of interest) and everyone (where so many people are talking about it, it’s hard to get traction)? Enhanced social listening tools are used here to help gauge interest in a topic.

3. Social strategy fit: Does the content align with one of the five pillars of the social media strategy?

4. Earned potential: Is there potential to maximise on this content? Is this content likely to get attention from journalists or influencers who can carry the story further than our owned social channels? Or is there a strong partner involved with options to collaborate?

How data helps us plan ahead

In addition to the social strategy and the four filters, there’s one other thing which impacts what we share on social media – and that’s sentiment analysis. The purpose of sentiment analysis is to show – via data collection – what our audience is saying about our brand. It is used as a constructive tool to understand our audience, gather actionable data, and gain meaningful insights into our brand messaging.