Every marketer is looking for the “best” time to publish content, whether it’s a Tweet, a Facebook post, or an Instagram story. Did you know the answer is hiding in your insights?
It’s no surprise that each business is different; in fact, within each business, the “best” time to publish content will vary depending on the type of content, the site it’s published on, and the core audience. Knowing your followers’ patterns can get you in front of them more often, making your marketing efforts more successful.
While this article focuses on Twitter insights, it’s a good guide to follow when working with other data as well. Once the analysis is completed, marketers can get an idea of:
- What’s working well and what’s not
- When the audience is most apt to consume published content in the way it was intended (clicks, shares, comments, etc.)
- Which changes to social strategy will yield the best results
How does the Twitter Feed Work Exactly?
You need to understand your social audience, specifically those following your brand on Twitter. It’s important to understand how Twitter shares content and the recent changes it’s made to the platform.
Up until recently, Twitter offered a setting that would “show the best tweets”. This meant that content shown first in a user’s timeline would be from accounts users tend to interact with the most, or content that Twitter has identified as important to the user.
Recently, Twitter changed the game a bit by removing this setting to allow feeds to show tweets in reverse chronological order. While consumers loved this change, marketers were faced with a challenge – if the content will be strictly chronological, how do we stay in front of our followers?
Looking into Twitter insights beyond what is automatically generated can help. To better illustrate how this works, a simple case study using a fictitious Twitter account will be shared throughout the process.
Introducing Company Newbie
Company Newbie recently started with social marketing, and Twitter was a platform chosen based on their initial research. After a month of publishing content to the site, they found that they were doing well, but weren’t reaching their goals. Specifically, they hadn’t grown their following as much as they had hoped, and their tweets weren’t gaining a lot of traction. The company wondered if the “best” days and times they originally thought would be effective really were, and if not, what changes were needed. A deep Twitter analysis was used to provide the information they were seeking.
So, how did they do it?
Step 1: Export Twitter Data
While the automated Twitter insights are a good start to understanding performance, the important data can be found after clicking on the export button. The first thought might be, “Great, I can export all of our tweets. What good is that?”
Exporting data allows you to look at all the data, sort, and analyze for a solid overview of Twitter performance. The first step is to click on the “Analytics” tab under settings, then go to “Tweets”. From there, you’ll see a “last 28 days” button on the right side of the page – click on that to display the menu and then choose the date range for the export. Then click “Export”. Twitter only allows exporting one month at a time, so you will need to export 3 months and then merge them into one master file.
Once the data is exported, consider the following:
- Delete unnecessary columns. For this exercise, you will only need the first 7 columns – Tweet ID, Tweet permalink, Tweet text, time, impressions, engagement, and engagement rate.
- Insert 4 additional blank columns right after the “Time” column. Label these columns as “Time Only”, “Day of Week”, “Hour of Day”, and “Time Range.”
- Copy the “time” column and paste into the first column you just created, the one labeled “Time Only.” Highlight this column and use the “text to columns” function to break out the date vs time.
- Convert the “engagement rate” column to a percentage with one decimal point to make the data easier to work with.
- Delete any outliers. Outliers are tweets that have an extreme impression count. To find outliers, simply sort the data by Impressions from largest to smallest and look at the first few results. In the example below, it looks like Company Newbie had a tweet with a significantly higher number of impressions due to advertising efforts. This row of data was deleted.
Step 2: What’s My Baseline?
Now that Company Newbie exported the data and prepared the spreadsheet, it’s time to start the analysis. This is where the fun begins.
The goal of this step is to determine some key information:
- What is the average number of impressions for our content? What does average engagement look like? Which tweets did better than average?
- What does the current content publishing pattern look like?
- Within this pattern, what days and/or times are most effective, and, more importantly, most effective for impressions vs engagement?
- What changes need to be made based on these findings?
Determine Publishing Pattern
Before diving in, publishing patterns need to be identified.
Start with the day of the week
Twitter exports the time of day each tweet was published but does not offer information about the day of the week. To easily get this information, use the following formula in the blank column that was created next to the “time” column: =TEXT(D2,”dddd”) where D2 is the cell the date and time of the tweet are located. Use the “COUNTIF” formula to tabulate the number of tweets by day of the week.
This is what you get:
Company Newbie’s data confirmed that content was being published on a schedule that they originally planned on, with Wednesday and Thursday being the most active publishing days. Monday was the third active publishing day.
Time of day review
Time of day was next. Twitter exports the time each tweet was published down to the minute and second; this is too granular. In the second blank column that was created in step 1, you’ll need to convert the actual time into a 2- or 3-hour time frame.
An Excel formula will be helpful here. In the second blank column created in step 1, use the formula =FLOOR(G2,”2:00″) where G2 is the cell containing the time. This will round the time to the nearest time range by two-hour increments. Now tweets can be looked at for each two-hour window of each day. This is what the chart should look like:
Company Newbie’s day and time analysis did not reveal any surprises – content was posted most often based on the information they believed to be true when they started this marketing strategy. Content is most often published between 6am and 8am and between 4pm and 6pm. Because publishing times are very limited, the time of day analysis will not be helpful to Company Newbie.
Which Tweets are the Best?
Once patterns are noted, it’s time to focus on the content that did better than average to find patterns specific to strong impressions and engagement.
First, find the average number of impressions and engagement using the average function in Excel. The type of engagement isn’t important for this analysis – sharing, favoriting, and commenting are all wanted actions and will be looked at generally for this purpose.
Once the averages are identified, sort data based on the engagement rate column from high to low. The It’s a good idea to copy all rows that are at and above average engagement and paste them as a separate worksheet. Then rinse and repeat with the impressions data. This way you can easily work with the copied sheets without doing too much more sorting and cutting out data.
The point of this exercise is to look at what is working well, so focusing on content that performed at or above average will be used in the analysis. Company Newbie found that of all their tweets, 40 performed above average, so those were looked at more closely.
Step 3: Find the Best Days & Times for Impressions and Engagement
The pattern has been established. The next step will focus on what the tweet activity looked like across days and times. This step involves sorting data by day of the week and then compiling data to look at average impressions and engagement per day and per time of day to identify any patterns or significant performance.
Why is it important to look at both impressions and engagement separately? Isn’t the goal of content publishing to get people to like, share, and comment? Yes, but different content has different goals, so it’s important to know both sets of facts.
For example, if the goal of content is to advertise the brand for visibility, it’s good to get in front of as many people as possible. They may not engage with the tweet, but if they start seeing your company information consistently, it will bring awareness.
So how is this done?
Earlier two additional sheets were created – one that showed tweets with higher than average engagement, and a second that showed higher than average impressions. For each sheet, data should be sorted twice to get all the needed information:
- Sort by day of the week to calculate averages by each day of the week
- Sort by time frame (using the 2-hour increments) to calculate averages by each time frame
For engagement, it’s important to look at the average number as well as the percentage. There are times when engagement averages may be lower. But the actual percentage in comparison to other days or time frames will be higher. This is important to consider when running this type of analysis.
Once these data points are calculated, creating a chart will show patterns and trends. Company Newbie’s chart is shown as an example:
Company Newbie’s chart shows some interesting patterns.
- Tweets are generally published on Wednesday, Thursday, and Monday. Tweets generally have the highest impression rates on Sunday, Monday, and Friday. Wednesday & Thursday had the least average impressions, which are the days content is most often published. This is a signal that perhaps there is an opportunity being missed by publishing the most content on those days as it might not align with consumer behavior.
- Tweet engagement shows a different story. Company Newbie’s data shows that Thursday and Friday content has the best engagement. This is interesting because there is less content posted. It could be the type of content posted, which needs to be looked at in more detail. But it’s good to know that engagement is higher on these days.
So now what?
There are three days with strong impressions and two different days with strong engagement. How does this help Company Newbie align their content strategy?
Even though Company Newbie didn’t have enough data on the time of day to run an effective analysis, there are still some clues when looking at the time of day by day of the week. Take a look at their chart and consider the findings on impressions and engagement.
The high impression days show that the majority of the content was published in the late afternoon (between 4-6pm). The high engagement days show a somewhat broader range of time frames. Specifically, Thursday showing a range of time frames when content is posted. It’s good to look at the content posted on Thursdays to drill down on what engagement looked like throughout the day. However, with such limited data, this may not reveal significantly useful results.
Step 4: Compare the findings to social strategy
Company Newbie’s initial strategy focused on brand visibility and awareness, with a goal of increasing followers on Twitter. There were two streams of content created:
- Informational content to increase visibility & positioning as a thought leader in their industry, which includes press releases, company related news items, and industry-specific articles and information.
- Actionable content such as links to click through to the company’s website, other social sites, or newsletter sign up pages. Each tweet included clickable content with a call to action.
Was their strategy effective? In part, yes. During the first month, the company saw a steady increase in followers, impressions, and engagement though they did not reach their goal. When looking at the data, it becomes clear that they may have been publishing content at times when they’re customers weren’t active on Twitter. Adjusting the content calendar so content is published when followers are most likely to see and engage with it may yield better results.
Step 5: Identify opportunities and adjust strategies
Based on this analysis, Company Newbie was able to implement some new strategies for their marketing efforts:
- Wednesday is not an effective day to post. Despite 25% of the content being published on Wednesdays, there was the least amount of impressions & engagement.
- Sunday was a nice surprise. While it is the day the least content is published, there are strong average impressions. This may be a day to test in publishing informational based content.
- Fridays may be the most effective day to post engagement focused content, as it shows strong impressions and engagement. In looking closer at the content by time of day, Company Newbie learned that content published in the mornings had a lot of impressions with little engagement. But content posted later in the day (between 4-6pm) had above average impressions AND engagement. Friday is a good day to test with engagement type content, specifically later in the day.
A deep dive analysis of social content is exciting – because every company’s follower base is different, looking at this information gives you an idea of when your followers are likely to see & act on your content.
The first time out will be the most daunting. But after walking through the process and saving templates and formulas, data analysis on a regular basis will be much easier.
This is not a be all, end all analysis and should only be used as a guide. As indicated, consumer behavior and social algorithms change often, which will require a change in strategy at times. Staying ahead of the curve will make this easier and give the brand a head start in marketing efforts. Proactively incorporating deep Twitter analysis to the social strategy on a regular basis will make a difference in social media success.