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Using Facebook Insights to Improve Your Page

Using Facebook Insights to Improve Performance

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Slides from a training course on using Facebook Insights - what the various metrics measure and how to use them to evaluate and improve your page. Looks at the new Insights Dashboard, and how to export data and manipulate it in Excel. This was taught in two sessions. Session 1 covered basic metrics, the Insights Dashboard, and how to apply critical thinking and the scientific method towards rigorous decision-making. Session 2 covered how to export data and manipulate it in Excel, including useful Excel skills like performing calculations and using pivot tables.

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Page 1: Using Facebook Insights to Improve Performance

Using Facebook Insights to Improve Your Page

Page 2: Using Facebook Insights to Improve Performance

You will learn

• Which metrics you should be looking at

• What those numbers do (and do not) tell you about your page

• How to use the metrics to develop and test hypotheses

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The goal of using data

Why even bother looking at Facebook metrics?

To figure out what works and what doesn’t, and then do more of what works and less of what doesn’t.

It’s as simple as that.

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The goal of using data

If you know what works, you can work smarter – stop wasting time and effort on things that aren’t effective and concentrate on what works.

Insights can help you learn what to post, how to post and when to post in order to get the most out of your Facebook efforts.

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Just remember…The ultimate driver of success on Facebook is great content that strikes a chord with your audience. Without that, none of this matters.

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Evaluating Basic MetricsDoes “people who saw this” tell you how many people saw this?

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Which page is “better”?

PAGEONE

PAGETWO

Likes5,000

Fans reached per post500

Engagement per post10

Likes30,000

Fans reached per post1,200

Engagement per post12

Example 1

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Which page is “better”?

PAGEONE

PAGETWO

Likes5,000

Fans reached per post500 (10%)

Engagement per post10 (2%)

Likes30,000

Fans reached per post1,200 (4%)

Engagement per post12 (1%)

Example 1

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Which page is “better”?

PAGEB

Likes10,000

Fans reached per post500 (5%)

Engagement per post10 (2%)

Likes10,000

Fans reached per post1,500 (15%)

Engagement per post8 (0.5%)

PAGE A

Example 2

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Metrics matter

Common metrics such as “likes” don’t tell the whole story.

Facebook Insights can give us a more complete picture of how our pages are doing, and allow us to assess our performance with respect to specific goals.

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What “likes” DO tell you

Likes tell you: How many people pressed this button

Likes are a one-time action that display brand affinity or brand recognition.

People who like your page are agreeing in theory to receive content you may post.

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What likes DO NOT tell you

Likes do not tell you: Anything about what your fans did after that single moment when they clicked the like button.

Likes do not tell you: Whether fans have ever seen anything you posted, clicked on anything you posted, or interacted with anything you posted.

Likes illustrate content potential, but you need other numbers to know if that potential is being realized.

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Reach/People who saw this

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Reach/People who saw this

The number of people who received your content in their newsfeed.

Note: Here’s how Facebook decides who receives your content: http://www.insidefacebook.com/2013/08/06/facebook-tweaks-news-feed-algorithm-to-give-more-weight-to-relevance-user-connections/

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The dirty secret of reach

“People who saw this” does not tell you how many people saw a post.

Well, more accurately, it does not tell you how many people read it or consumed it. It does not measure the size of your audience.

Reach measures DELIVERY of content.

Higher reach means a higher potential for people to see and engage with your content. It is correlated to what Facebook sees as the RELEVANCE of your posts.

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Engagement

The most accurate measure we can get is ACTIONS. When people do something with our content, we can tell.

Engagement – Likes, comments, shares

Link clicks – Measurable through bit.ly and other link shorteners

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Your basic metrics

Likes – Brand recognition, content potential

Reach – Delivery, maximum viewership

Engagement – Interactions, observable audience

These three numbers impact each other:

•The more likes you have, the higher your potential reach and engagement.•The higher your reach the larger the pool of people who might engage.•The more engagement you get, the more frequently Facebook delivers your posts (higher reach).

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Exercise #1

Write down your primary goal for your own Facebook page.

What metrics would you look at to measure how effectively you’re reaching that goal?

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How to improve your page

Each month, collect your basic metrics and your goal-specific metrics.

Take some time to think about whether they met your expectations. Are you growing in the right direction? Are you growing as fast as you’d like to grow?

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Facebook Insights DashboardHow to get aggregated data and info about your page

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How to get there

Click here

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Overview tab

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Overview tab

Make observations, notice patterns.

What’s different than you expected? Are there obvious spikes or troughs? Did your metrics go down when you thought they should go up (or vice versa)?

Do you see any posts that did unusually well or poorly?

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Overview tab

Look at changes or patterns and ask yourself:

Why?

Why is this metric going up or down? Did I do something differently this week? What might this say about what my audience wants?

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Past two weeks reach/engagement was higher on Monday. Are we doing something that day that could be replicated?

Photos get higher reach/engagement, but this photo did poorly. Is it because we didn’t write a description?

Reach and engagement dropped this week. Did we do something differently? Was the news different?

Reach and engagement spiked last Thursday. What did we do differently that day?

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Exercise #2

Look through your Overview tab. Write down two observations you might use to make and test hypotheses about how to improve your page performance.

How would you test these hypotheses?

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How to improve your page

This gives you a rigorous and accurate way to determine what works and what doesn’t...

Step One: Observe. Pick out unusual changes or regular patterns.

Step Two: Hypothesize. Make an educated guess about what might improve your page performance based on what you observed.

Step Three: Test. Make a single change to how you post and implement it for 2-4 weeks.

Step Four: Evaluate. Look at whether your performance changed how you expected and decide whether to continue or abandon the change.

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Posts tab

Is there an obvious pattern in when your posts were delivered this week? Try using the scheduler to time posts in accordance with this pattern and see how it changes your outcomes.

Posts tab When Your Fans Are Online

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Posts tab

You will likely see a pattern similar to this one for your posts. Choose the format of your posts based on what you want them to achieve.

If you want:•Reach use a Status update•Engagement use a Photo•Clickthroughs use a Link

Posts tab Best Post Types

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How to improve your page

Optimizing your post timing and post types are two of the most straightforward ways to make gains in the performance of your page.

Example:

Observation: Photos seem to get the most engagement

Hypothesis: If we post more photos, we can generate more discussion on our page

Test: Each day for two weeks, we will take one item we normally would have posted as a link and post it as a photo instead

Evaluation: If the hypothesis is correct, during those two weeks we should see a higher average engagement per post compared to the two preceding weeks, and since the goal is discussion we’d particularly like to see a higher average comments per post

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How to improve your page

Example:

Observation: Our audience seems to be online in the late morning

Hypothesis: I can get more return for the same effort by taking the post I usually do at 6am and putting it up between 9am and noon

Test: Each day for two weeks, when I compose my post at 6am, I will schedule it to go out between 9am and noon

Evaluation: If the hypothesis is correct, during those two weeks I should see a higher overall average reach per post compared to the two preceding weeks, and the average reach on those scheduled posts should be higher than the average reach for other posts

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Exercise #3

Look through your Posts tab. Write down two observations about your content and the corresponding hypotheses you would want to test.

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Page tab

Keep an eye on negative actions as well as positive ones.

Try to keep these low. If they spike, investigate why. Was there a specific post people reacted negatively to? Did you post more items that day, or in a different format than usual?

Page tab Post Reach

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People tab

Think about:

Are you reaching your target audience?

Are you providing content that serves the needs of the audience you have?

Are there major differences between who your fans are and who you’re reaching or engaging?

Why or why not?

People tab Your Fans

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Remember…

The goal is always to figure out what works and what doesn’t, so we can do more of what works and less of what doesn’t.

Step One: Observe. Pick out unusual changes or regular patterns.

Step Two: Hypothesize. Make an educated guess about what might improve your page performance based on what you observed.

Step Three: Test. Make a single change to how you post and implement it for 2-4 weeks.

Step Four: Evaluate. Look at whether your performance changed how you expected and decide whether to continue or abandon the change.

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Takeaways

1) Likes don’t tell the whole story about a page’s performance. Come up with specific goals for your page and focus on meeting those.

2) Keep an eye on your basic metrics. Know what normal looks like so you can recognize when things change. Make sure you’re growing rather than stagnating.

3) Start making observations that can help you identify what works and what doesn’t. Use those observations to run little experiments – replicate what works, eliminate what fails.

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Exporting Insights DataGoing beyond the Dashboard

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Why export?

Facebook actually collects much more data than is available on the dashboard.

Exporting your Insights gives you access to all this data and lets you manipulate it in more ways.

You can get a more nuanced idea of how your page is performing and more accurately test how making changes impacts your outcomes.

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How to export data

1. Click Export Data

2. Select Page data or Post data. Page data is overall for your entire page, Post data gives you data for each individual post. Choose Post data for now

3. Pick a date range. If you’re looking to make general observations you’ll want a fairly wide range (3-6 months)

4. Click Download

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Try this…

Take a few minutes to flip through all the tabs and get a sense of what data is offered.

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Pivot tables

In order to get more out of the data, we’re going to use “pivot tables.” Excel pivot tables make it easy to manipulate and filter your data.

For example, if I have this data and want to know the total sales for each region…

I can use a pivot table and generate this data to get the answer.

I could also have looked at aggregate data for any of the columns – Month, Year, Type, Salesperson, etc.

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Creating pivot tables

Click anywhere inside your data table.

Select the “Insert” tab and then click “Pivot Table.”

Your entire data range should be automatically selected. Place the pivot table in a new worksheet and click OK.

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Creating pivot tables

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Creating pivot tables

Drag and drop fields from the top to the bottom to create your table.

“Row Labels” defines your rows. Each value becomes a new row. “Values” defines your columns. Whatever variable you place there will be calculated for each row.

In this example our rows are the type of post. For each type, we are calculating the total number of impressions (sum) for all posts of that type.

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Creating pivot tables

Change the calculation being performed by clicking the arrow and selecting “Value Field Settings.”

In this example:Sum = the total impressions for all posts of this type

Count = the number of instances of this type of post

Average = the average number of impressions for a post of this type

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Be careful…

Not all values can be accurately summed.

Example:

Reach = the number of people who received a post.

If one post had a reach of 100 and another had a reach of 50, is the total reach 150? NO.

You have no way of knowing whether some of these people are the same people. Adding the numbers together overcounts.

Use impressions instead. Impressions are the number of times a post was delivered. The duplication problem does not exist.

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Manipulating the DataBasic use of pivot tables

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Building a basic pivot table

Task: use a pivot table to find out what types of posts get the most negative feedback (hides, unsubscribes, unlikes, etc.).

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Since you want to compare types of posts, put “Type” in the Row Labels box.

Since you want to compare them based on how much negative feedback they receive, drag Lifetime Negative Feedback from Users into the Values box.

Set the “Value Field Settings” to calculate the average in order to look at the average negative feedback per post.

Notice: We used Lifetime Negative Feedback from Users instead of Lifetime Negative Feedback. Lifetime Negative Feedback describes unique users rather than total actions.

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Why look at the average instead of the sum?

Since sum is an overall total, its value depends on how many of that type of post exist.

Here’s an example, looking at impressions by type of post:

Photos have generated the most total impressions, followed by links. But when you look at the averages you can see that on a per post basis, status updates actually generate the most impressions. It’s just that there haven’t been as many of those.

Averages are useful when you want to compare categories, because they smooth over differences in quantity. Sums are a better measure of overall performance.

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Photos generated the most negative feedback per post, followed by video, then status updates, then links.

Does it matter? If your primary goal was to reduce negative feedback, it would matter quite a bit.

Otherwise, the differences aren’t that large, so it’s probably not that significant. But there is something interesting here: you’d expect negative feedback to correlate to reach – the more people receive your post, the more likely it is that someone will react negatively to it. However, status updates get the most reach of any post type, and they ended up down the list in terms of negative feedback.

Our pivot table of negative feedback by post type:

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Exercise #4

Create a pivot table for the Lifetime Post Stories tab in your spreadsheet, and use it to determine which type of post gets the most likes, which gets the most comments, and which gets the most shares.

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Columns and CalculationsAdding new values to your data

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Adding columns

Click Insert and select Insert Sheet Columns.

Excel will insert the column to the left of whatever column is currently selected.

Facebook gives you certain categories and numbers, but you can insert your own categories and do your own calculations to make other types of comparisons.

To insert a column:

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Adding columns

You can use your new column to categorize posts according to any variable you might want to use to compare them.

Other examples:Breaking news v. feature newsWhat country the story is aboutPosts where you asked a question v. ones where you didn’t

New variable: Did this post have a Soundcloud link?

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Doing calculations

Open a new Excel spreadsheet.

In the first blank cell type the following: =2+4

When you hit enter, Excel should replace that with the value “6”

The equals sign lets Excel know you want it to perform a calculation, and it will follow your instructions in the rest of the cell.

If you click on that cell, you will still see your original formula up at the top of the screen, letting you know how Excel arrived at the value.

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Doing calculations

Now type the value “2” in the first cell and the value “4” in the second cell, like this:

You probably noticed that each cell can be described by a letter and number combination. The “2” is in cell A1, and the “4” is in cell B1.

You can perform calculations using the names of cells instead of entering values directly. In the third cell over, type: =A1+B1

When you hit Enter, you should again get the value “6”

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Task: On average, what percentage of the people who receive your posts engage with them, and does this differ by post type?

Exercise #5 (we’ll do this together)

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First we have to calculate the percentage of people reached who engaged for each post.

% = People engaged/People reached

People engaged = Lifetime Talking About This (column Q)

People reached = Lifetime Post Total Reach (column H)

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Create a new column in your spreadsheet and title it “% Reached who Engaged.”

To calculate that value for your first post, click in the first empty cell and type: =Q3/H3

Click the little box in the lower right and drag it down to fill the entire column. Excel will automatically adjust the formula to give you the correct calculation for each row.

Tip: Right click and select “Format cells” to change how many decimal places display, or to automatically convert the values to percentages

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Since you already have a pivot table created, you just need to update it to include the new column of data.

From your pivot table tab, select Options and then Refresh.

Set up

Result

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Exercise #6

On which day of the week do your posts generate the most engagement?

Hint:

Excel can calculate the day of the week based on the date, using the formula =Weekday(CELL)

Each day gets a number, starting with 1 for Sunday

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WHY? WHY? WHY?!?

Take a break and remember why we’re suffering through all this Excel stuff:

To figure out what works and what doesn’t, and then do more of what works and less of what doesn’t.

It’s as simple as that.

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Final Challenge

When more posts are created in a day, does it impact the reach of each individual post?

Hint 1:

Use the Text to Columns function to separate the date and time into two separate columns

Hint 2:

=Countif($D$3:$D$100,D5) counts the number of times the value in cell D5 appears in the entire range of cells from D3-D100. For example, if D5 contained a date, you could count how many times that date appears in the entire column