The document discusses challenges that marketers face in analyzing social media data across multiple channels. It states that 51% of respondents in a survey identified having a "Big Picture Understanding" as their biggest challenge. The solution proposed is to standardize and normalize cross-channel metrics by aggregating all data in one place, establishing standardized terminology for metrics, and bucketing channel-specific metrics into the new standardized terms. This allows marketers to see social media activity and performance holistically and make more effective analyses by comparing metrics across channels on an "apples to apples" basis. The document promises to discuss five essentials for social media data storytelling in an upcoming whitepaper.

1. Cross-Channel Storytelling for Social Marketers

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As marketers, data fuels us.
But how can we bring it all together to tell our story
most effectively?

3. @SimplyMeasured@lindzeemccain
Social Marketing Survey
The survey showed that the majority of marketers struggle with
five key areas of their data analysis:
• "Big Picture" understanding
• Appropriate benchmarking and comparisons
• Owned and earned media in context
• Gleaning deeper insights
• Complete understanding of your audience

4. 51% of respondents ranked a “Big Picture
Understanding” as their biggest challenge
for reporting on social performance.

5. @SimplyMeasured@lindzeemccain
Why is it so difficult to see the big picture?
• The puzzle pieces don’t seamlessly fit together.
• More networks, more metrics!
• The problem with stakeholders.

6. The solution: standardizing and
normalizing your cross-channel metrics.

7. @SimplyMeasured@lindzeemccain
Standardizing Terminology
The key to putting massive amount of data in context is standardization, and
it's surprisingly simple.
1. Aggregate all cross-channel data into one place.
2. Establish standardized terminology. For example, instead of Facebook
Likes and Pinterest and Twitter Followers, you'd use a term like
"Audience."
3. Bucket the channel-specific metrics into your new standardized terms.
Now, you can see your activity cleanly and with holistic context to make your
analysis more effective.

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Example: Total Engagement

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Example: Brand Post Volume and Engagement

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Example: Brand Post Volume and Engagement

11. Without normalizing your cross-channel
data, you’re not comparing apples to
apples.

12. Example: Growth Rate

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Example: Engagement as a % of Audience

14. Example: Benchmarking

15. There are many ways to tell your cross-
channel story, but you must first understand it
holistically.
For the rest of this story, stay tuned for the “5
Data Storytelling Essentials For Social
Marketers” whitepaper.

16. Thank you!