Social Media Marketing & Management (Part B) Flashcards
Social Media Management
Research -> Plan and Campaign Creation -> Campaign Measurement -> Analytics -> Research
What is Social Media Research
To determine how social media can be a strategic tool in the business’ overall communications efforts.
Review organization and size up competitors
Understand your audiences
Understand your industry
Social media plan
- Review social media research done
- Identify target audiences for the brand
- Define social media objectives (Business Goals, Marketing Goals, Social Media Objectives)
- Craft the message and set the creative approach
- Strategy (message, touchpoint, channel, influencer, paid, etc)
- Activations (5W1H)
- Success tracking (using tools to ascertain metrics and ROI)
- Campaign budget allocation and Implementation timeline
Audience Engagement
Brand Voice
Image Direction
Content Strategy
Engagement Strategies and Tactics
Posting Strategy
Social Seeding & Amplification
Creating compelling content published on owned social media platforms, linking to pages on your website.
Use visually impactful content catered to the platform, leverage insights around frequency & timing of posts and aim to drive positive reactions/comments where possible to positively impact trackable
sentiment
How to amplify social content’s reach?
- Paid Boosts of organic social content
- Sharing in interest groups & communities on social media
- Sharing by employees and key company staff
- Tagging & engaging with influencers or Key Opinion Leaders through public & media relations
Ways to drive traffic to social media channels
Cross-channel sharing
Link to your social media profiles
Advertise
E-mail signature
Engage well with your online communities
Which metrics to measure campaign success
Owned social metrics — related to the social channels that
companies are currently maintaining.
Earned social metrics — related to conversations about any communication programs or the brand that the company did not directly gather.
Owned Social Metrics
- Total Likes – number of people who have “liked” the page
- Reach – Organic vs Paid vs Viral
- Engaged Users – number of people who have clicked on one of the company’s posts during a given time
- Comments, shares by post
- Followers
- Clicks – number of times people have clicked a link that the company shared
- Click-through rate (CTR) – number of clicks divided by number of people who had an opportunity to click
- Impressions – number of times someone viewed or had the opportunity to view the company’s content
- Subscribers – number of people who have signed up to receive the company’s content
Earned Social Metrics
- Earned conversations – social media conversations that are taking place outside the owned social media properties
- Share of voice – tracks how much conversation is happening about one brand vs another
- Share of conversation – tracks how much conversation is happening vs the broader industry
- Sentiment – amount of positive, negative or neutral conversation that is happening about a brand or product
- Message resonance – measures how well (or not) a message is being received by the community
- Overall conversation volume – measures how well a message has been received
Benchmarking
- Trended / Historical Benchmarking
* Against own results on a social media platform - Industry / Competitive Benchmarking
* Against competitors on a social media platform - Platform Benchmarking
* Against the overall average on a social media platform, regardless of industry
Social Media Analytics process
Capture, Understand, Present
Opinion mining (or sentiment analysis)
A social media analytics method that uses text analytics methods to automatically extract user sentiments or opinions from text sources
Topic modelling
A social media analytics method that is used to sift through large bodies of captured text to detect dominant themes (topics) that are then used to provide label guides to explore future text collection or to build effective navigational interfaces.
Trend analysis
A social media analytics method used to identify and predict future outcomes and behaviours (trends) based on historical data collected over time.
E.g. forecasting the growth of customers or sales, predicting the effectiveness of ad campaigns
