Brandwatch Masterclass: Charts
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NY Masterclass Session, May 8
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Brandwatch Masterclass: Charts
- 1. Brandwatch Masterclass/Charts Alyssa Edelman brains@brandwatch.com | Brandwatch Masterclass | May 2014
- 2. Charts Are Awesome. © 2014 Brandwatch | www.brandwatch.com 2
- 3. Agenda © 2013 Brandwatch | www.brandwatch.com 3 • Charts on the Default Dashboard • Creating Custom Charts • Filtering Options • Views • Troubleshooting Charts • Hands-On Exercises
- 4. Charts on the Default Dashboard •Sentiment by Day •Page Types by Day •Sentiment by Page Type © 2014 Brandwatch | www.brandwatch.com 4
- 5. Creating Custom Charts © 2014 Brandwatch | www.brandwatch.com 5
- 6. Chart Views © 2014 Brandwatch | www.brandwatch.com 6
- 7. Filter Options © 2014 Brandwatch | www.brandwatch.com 7
- 8. © 2014 Brandwatch | www.brandwatch.com 8
- 9. Show (Y-Axis) •Vertical breakdown •Volume is the most commonly used •Unique authors is an interesting metric © 2014 Brandwatch | www.brandwatch.com 9
- 10. For (X- Axis)/Breakdow n By © 2014 Brandwatch | www.brandwatch.com 10
- 11. Queries •Queries •Groups © 2014 Brandwatch | www.brandwatch.com 11
- 12. Sentiment © 2014 Brandwatch | www.brandwatch.com 12
- 13. Authors •Author List © 2014 Brandwatch | www.brandwatch.com 13
- 14. Twitter •Account Type •Gender •Profession •Interest •Author Cities •Author Counties •Author States •Author Countries •Author Continents © 2014 Brandwatch | www.brandwatch.com 14
- 15. Tags and Categories •Tags •Categories •Multiple Parent Categories © 2014 Brandwatch | www.brandwatch.com 15
- 16. Workflow •Assignment •Priority •Status •Checked © 2014 Brandwatch | www.brandwatch.com 16
- 17. Time •Hours •Days •Weeks •Months © 2014 Brandwatch | www.brandwatch.com 17
- 18. Site •Site List •Page Type •Domain •MozRank © 2014 Brandwatch | www.brandwatch.com 18
- 19. Language © 2014 Brandwatch | www.brandwatch.com 19
- 20. Locations •Cities •Counties •States •Countries •Continents © 2014 Brandwatch | www.brandwatch.com 20
- 21. © 2014 Brandwatch | www.brandwatch.com 21
- 22. Sample Chart Views © 2014 Brandwatch | www.brandwatch.com 22
- 23. Volume for Categories, broken down by Sentiment © 2014 Brandwatch | www.brandwatch.com 23
- 24. Volume for Queries, broken down by Categories © 2014 Brandwatch | www.brandwatch.com 24
- 25. Volume for Queries, broken down by Categories © 2014 Brandwatch | www.brandwatch.com 25
- 26. Volume for Days, broken down by Categories © 2014 Brandwatch | www.brandwatch.com 26
- 27. Volume for Days, broken down by Categories © 2014 Brandwatch | www.brandwatch.com 27
- 28. Volume for Days, broken down by Categories © 2014 Brandwatch | www.brandwatch.com 28
- 29. Volume for Days, broken down by Categories © 2014 Brandwatch | www.brandwatch.com 29
- 30. Unique Authors for Months, broken down by Queries © 2014 Brandwatch | www.brandwatch.com 30
- 31. Volume for Queries, broken down by Multiple Parent Categories © 2014 Brandwatch | www.brandwatch.com 31
- 32. Volume for States, broken down by Days © 2014 Brandwatch | www.brandwatch.com 32
- 33. Volume for Days, broken down by Sentiment (with an added Gender filter) © 2014 Brandwatch | www.brandwatch.com 33
- 34. Troubleshooting © 2014 Brandwatch | www.brandwatch.com 34
- 35. Recap © 2014 Brandwatch | www.brandwatch.com 35
- 36. Key Takeaways • Charts are the most flexible way to view your data • There are lots of great filtering options in addition to the the standard Brandwatch filters • Puppies and kittens are encouraging © 2014 Brandwatch | www.brandwatch.com 36
- 37. Chart Practice © 2014 Brandwatch | www.brandwatch.com 37
- 38. © 2014 Brandwatch | www.brandwatch.com 38 Add a Chart component to the dashboard. Create a line chart that shows a volume comparison over time, broken down by day, of male versus female conversation. Create a horizontal bar chart showing the volume of conversation by page type, broken down by week. In a table view, create a chart that shows how many mentions in each flavor category either say “Starbucks” or don’t say “Starbucks” within the mention. Make sure the flavors run along the left side of the table. Create a bar chart showing what flavors people in different professions prefer (mention volume).
- 39. Any Questions? © 2014 Brandwatch | www.brandwatch.com 39
Editor's Notes
- The most powerful and flexible way of viewing your data I believe they’re the most robust, customizable component
- Quick overview of what charts you’ll see and how to add your own custom charts to dashboards Go through the different options for filtering We’ll go through a few examples as well as their business use cases I’ll let you know a quick trick for when your charts look weird And then we’ll practice a bit, I’ll call some of you up here so you can impress everyone with your new skills.
- On the charts tab, you’ll see these three lovely charts. Sentiment by day is going to show you the total query volume on the y-axis, and then it’s broken down by day on the x-axis and finally by sentiment within the bars. Page types by day is a very similar view, but instead of sentiment, it’s broken down by page types The third kind of combines the first two charts, so your x-axis becomes the page types, and you’re looking at the total breakdown of the entire query volume for the selected timeframe. You can click in to any of these bars to see the mentions they represent, which I’ll cover more a bit later.
- Scroll down to the bottom of any tab Click Add a Component This screen will pop up Click General > Chart > Add to Dashboard to add a new chart to your tab Will show, by default, a stacked bar chart showing the total volume of mentions for each day broken down by sentiment. (so, the first chart we just looked at)
- Once this is open, though, you can choose to view the chart in different ways Right now, we’re looking at a stacked bar chart But we can choose any of these options and our view will change, even though it’s the same data
- Within a chart, there are three main controls that let you control the data Take a good look!
- Let’s start with the shorter filter list – the “Show” column (otherwise known as the Y-axis) This is your vertical breakdown, so the metric on the left Volume is the most commonly used one here I’ve seen clients break down Unique Authors by Quarter, which I’ll go into a bit later…but this metric is good to see account growth or campaign success
- Now on to the big lists…I’ve put a puppy on each slide to curb any anxiety, which I’ve either way overestimated or it’ll be a welcome addition I’ve broken it down by heading
- Queries This is used when you want to work with the entire query as the base dataset, which can be broken down later Groups This is used when you want to use a query group as your base dataset
- Sentiment This is what you see on the default charts
- If you’ve already set up an author list, which is a group of mention authors, you can filter your results by that list.
- All of this is Twitter only Account type: individual or organization Gender: male or female Profession: Executive, student, politician, artist, scientist, journalist, software developer, legal, health Interests: animals/pets, fine arts, automotive, beauty/health, books, business, environment, family/parenting, fashion Geolocation data
- If you already have tags or categories set up and applied to your mentions You can compare multiple categories, as a whole, against each other (in a later example, you’ll see total holiday flavor volume compared to total standard flavor volume)
- If you set up workflow within your mentions You can use multiple charts to track workflow success over time, or if you want to see the amount of mentions checked per person over time, for example
- How granular, time-wise, you want your results to be From hours to months
- If you’ve already set up a site list, this is where you can filter that into a chart Page type – so twitter, facebook, etc Domain - .com, .biz, etc. Mozrank – this is not our metric, but helps define social power
- You can see what languages are most popular among your mentions Especially useful if you’re monitoring multiple countries or if you want to find keywords to help eliminate spam that’s in the wrong language
- Relies on geolocation data (all, not just Twitter)
- Mention what uncategorized mentions button does If multiple categories can be applied to a mention, then one mention may be counted in two places To isolate a subcategory, you can do this in the filters section USE CASE: Identify categories with a smaller market share, insight into why (large negative sentiment = something is way wrong, maybe it’s gross) If you saw a large negative spike, see if there is a common thread that you can go in and fix
- First view of a pie chart in this presentation This is a pretty standard “Share of Voice” analysis USE CASE: View your mention volume vs your competitors If you want to see how a campaign is doing, if you were pushing a certain flavor
- Here you can see branded vs unbranded conversation USE CASE Good time to jump into conversations You can see if people are associating your product with being a generic name for the product Expanding your audience session – next timeslot on Advanced track "also show uncategorized mentions"
- more in-depth timeline analysis vs “history” component USE CASE Campaign tracking and success Volume over time like you see on the summary component, but broken down to be more granular You can click in to spikes to see what’s up
- From here, you can add tags, add mentions to a new tab, etc., to analyze View > topics for quick topical analysis of all the mentions to identify why there was a spike in mentions
- Click a topic to zoom in
- USE CASES New social media strategy/trying to build a community - proof it's working Filter by Twitter only
- USE CASE Compare entire categories to each other, making the parent category function almost like a tag Here, I showed how holiday flavors had a bigger share of voice in December, but people were still talking about them in March Use side-by-side components to compare date ranges
- You must filter by US You can click into individual days USE CASE See most influential states for a campaign or in general Honestly, it mostly just looks pretty, but it’s a good/simple way to see mentions broken down by state, especially in the table view
- USE CASE See how different genders differ in opinion Example of how you can compare different demographic data side-by-side
- 2. Y volume X days Breakdown gender 3. Y volume X page type Breakdown weeks 4. Y volume X categories – mention Breakdown categories – frap flavors 5. Y Volume X Categories (Frap flavors) Breakdown Profession