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Data Analysis

The document discusses data visualization best practices for dashboards. It recommends creating 3 levels of dashboards: L1 with key metrics, L2 with more detailed metrics, and L3 with general health metrics. It provides tips for simplifying visualizations, such as removing gridlines and legends. It also cautions against misleading or inaccurate visualizations like pie charts. Excel and Tableau are presented as tools that can help with data analysis and visualization.

Marketing◦

@rachelmeyer1#pubcon @rachelmeyer1
nathanwpyle.art
/strangeplanet

@rachelmeyer1#pubcon @rachelmeyer1
tableau, excel,
sheets, looker,
power bi –
data scientists &
business
analysts have an
edge on us

@rachelmeyer1#pubcon @rachelmeyer1
if we up our data analysis & data
viz skills, we have the context to
make changes that
improve outcomes

@rachelmeyer1#pubcon @rachelmeyer1
your role as a
presenter:
leave no room for
interpretation

@rachelmeyer1#pubcon @rachelmeyer1
convince who?
to do what?
how do you plan
to do it?

@rachelmeyer1#pubcon @rachelmeyer1
L1 Dashboard
most important metrics
• health of the business or
channel
• $$$ (usually)

@rachelmeyer1#pubcon @rachelmeyer1
don’t clutter and confuse

@rachelmeyer1#pubcon @rachelmeyer1
do simplify & get to the point

@rachelmeyer1#pubcon @rachelmeyer1
draw attention to what’s important
Product 3
+40% from
June to Sept.

@rachelmeyer1#pubcon @rachelmeyer1
L2 Dashboard
detailed, but not ridiculous
• trending dashboards
• possibly daily metrics

@rachelmeyer1#pubcon @rachelmeyer1
this is lovely, but…

@rachelmeyer1#pubcon @rachelmeyer1
simple heatmap L2

@rachelmeyer1#pubcon @rachelmeyer1
don’t report on
stuff that
will change
constantly.

@rachelmeyer1#pubcon @rachelmeyer1
easy, quick tips
for data viz

@rachelmeyer1#pubcon @rachelmeyer1
Change the
structure:
Pivot by
product
type
instead of
device type

@rachelmeyer1#pubcon @rachelmeyer1
Clean up:
remove
gridlines,
move
legend to
bottom,
clean up
vertical axis

@rachelmeyer1#pubcon @rachelmeyer1
Change the
structure:
Sort from
high to low

@rachelmeyer1#pubcon @rachelmeyer1
And do
your
clean up:
remove
legend,
tidy the
vertical axis,
remove
gridlines,
improve title

@rachelmeyer1#pubcon @rachelmeyer1
data visualization is powerful

@rachelmeyer1#pubcon @rachelmeyer1
you bet your axis
this is a lie…

@rachelmeyer1#pubcon @rachelmeyer1
I increased conversions 1000%!!

@rachelmeyer1#pubcon @rachelmeyer1
That isn’t actually true…

@rachelmeyer1#pubcon @rachelmeyer1
52
47
12
what to do here?
this looks weird…

@rachelmeyer1#pubcon @rachelmeyer1
52
47
12

@rachelmeyer1#pubcon @rachelmeyer1
warning: pie is dangerous!
52
47
12

@rachelmeyer1#pubcon @rachelmeyer1
but we like pie!

@rachelmeyer1#pubcon @rachelmeyer1
it’s like
you’re trying
to tell me
something

@rachelmeyer1#pubcon @rachelmeyer1
L3 Dashboard
General health metrics
keyword rankings
daily traffic
landing page traffic
daily leads/sales

@rachelmeyer1#pubcon @rachelmeyer1
remember this?

@rachelmeyer1#pubcon @rachelmeyer1
so. much. data.

@rachelmeyer1#pubcon @rachelmeyer1
tableau can help you
with keyword
research &
visualization

@rachelmeyer1#pubcon @rachelmeyer1
data viz to make your life easier

@rachelmeyer1#pubcon @rachelmeyer1
excel use case #1
pivot charts to summarize and
see trends

@rachelmeyer1#pubcon @rachelmeyer1
excel use case #2:
quickly sort keywords, urls,
anything that needs sorting

@rachelmeyer1#pubcon @rachelmeyer1
=IF(ISNUMBER(SEARCH(“crm”,A2)),“CRM”)

@rachelmeyer1#pubcon @rachelmeyer1
excel use case #3:
make sense of GA
comparison data

@rachelmeyer1#pubcon @rachelmeyer1
=OFFSET($C$2,(ROW($C3)-2)*2,0)

@rachelmeyer1#pubcon @rachelmeyer1
there are so
many bad charts
out there

@rachelmeyer1#pubcon @rachelmeyer1
Opioid Overdose Death Rate by State

@rachelmeyer1#pubcon @rachelmeyer1
thank you!

@rachelmeyer1#pubcon @rachelmeyer1
Excel Guide: bit.ly/pubcon-excel-2019
CTR Analysis Data Viz: bit.ly/2MmqEBv
Tableau Public: https://tabsoft.co/2LX7Zgk
Excel Dashboard School: bit.ly/2nlu27c

Data Analysis

1.
@rachelmeyer1#pubcon @rachelmeyer1 10+ yearsin digital marketing In-house + Agency Mix of disciplines
2.
@rachelmeyer1#pubcon @rachelmeyer1 nathanwpyle.art /strangeplanet
3.
@rachelmeyer1#pubcon @rachelmeyer1 tableau, excel, sheets,looker, power bi – data scientists & business analysts have an edge on us
4.
@rachelmeyer1#pubcon @rachelmeyer1 if weup our data analysis & data viz skills, we have the context to make changes that improve outcomes
5.
@rachelmeyer1#pubcon @rachelmeyer1 your roleas a presenter: leave no room for interpretation
6.
@rachelmeyer1#pubcon @rachelmeyer1 convince who? todo what? how do you plan to do it?
7.
@rachelmeyer1#pubcon @rachelmeyer1 L1 Dashboard mostimportant metrics • health of the business or channel • $$$ (usually)
8.
@rachelmeyer1#pubcon @rachelmeyer1 don’t clutterand confuse
9.
@rachelmeyer1#pubcon @rachelmeyer1 do simplify& get to the point
10.
@rachelmeyer1#pubcon @rachelmeyer1 draw attentionto what’s important Product 3 +40% from June to Sept.
11.
@rachelmeyer1#pubcon @rachelmeyer1
12.
@rachelmeyer1#pubcon @rachelmeyer1 L2 Dashboard detailed,but not ridiculous • trending dashboards • possibly daily metrics
13.
@rachelmeyer1#pubcon @rachelmeyer1
14.
@rachelmeyer1#pubcon @rachelmeyer1 this islovely, but…
15.
@rachelmeyer1#pubcon @rachelmeyer1 simple heatmapL2
16.
@rachelmeyer1#pubcon @rachelmeyer1 don’t reporton stuff that will change constantly.
17.
@rachelmeyer1#pubcon @rachelmeyer1 easy, quicktips for data viz
18.
@rachelmeyer1#pubcon @rachelmeyer1
19.
@rachelmeyer1#pubcon @rachelmeyer1 Change the structure: Pivotby product type instead of device type
20.
@rachelmeyer1#pubcon @rachelmeyer1 Clean up: remove gridlines, move legendto bottom, clean up vertical axis
21.
@rachelmeyer1#pubcon @rachelmeyer1
22.
@rachelmeyer1#pubcon @rachelmeyer1 Change the structure: Sortfrom high to low
23.
@rachelmeyer1#pubcon @rachelmeyer1 And do your cleanup: remove legend, tidy the vertical axis, remove gridlines, improve title
24.
@rachelmeyer1#pubcon @rachelmeyer1 data visualizationis powerful
25.
@rachelmeyer1#pubcon @rachelmeyer1 you betyour axis this is a lie…
26.
@rachelmeyer1#pubcon @rachelmeyer1 I increasedconversions 1000%!!
27.
@rachelmeyer1#pubcon @rachelmeyer1 That isn’tactually true…
28.
@rachelmeyer1#pubcon @rachelmeyer1 52 47 12 what todo here? this looks weird…
29.
@rachelmeyer1#pubcon @rachelmeyer1 52 47 12
30.
@rachelmeyer1#pubcon @rachelmeyer1 warning: pieis dangerous! 52 47 12
31.
@rachelmeyer1#pubcon @rachelmeyer1 but welike pie!
32.
@rachelmeyer1#pubcon @rachelmeyer1 it’s like you’retrying to tell me something
33.
@rachelmeyer1#pubcon @rachelmeyer1
34.
@rachelmeyer1#pubcon @rachelmeyer1 L3 Dashboard Generalhealth metrics keyword rankings daily traffic landing page traffic daily leads/sales
35.
@rachelmeyer1#pubcon @rachelmeyer1 remember this?
36.
@rachelmeyer1 databox for fastsetup
37.
@rachelmeyer1#pubcon @rachelmeyer1 so. much.data.
38.
@rachelmeyer1#pubcon @rachelmeyer1 tableau canhelp you with keyword research & visualization
39.
@rachelmeyer1#pubcon @rachelmeyer1
40.
@rachelmeyer1#pubcon @rachelmeyer1
41.
@rachelmeyer1#pubcon @rachelmeyer1 data vizto make your life easier
42.
@rachelmeyer1#pubcon @rachelmeyer1 excel usecase #1 pivot charts to summarize and see trends
43.
@rachelmeyer1#pubcon @rachelmeyer1
44.
@rachelmeyer1#pubcon @rachelmeyer1 excel usecase #2: quickly sort keywords, urls, anything that needs sorting
45.
@rachelmeyer1#pubcon @rachelmeyer1 =IF(ISNUMBER(SEARCH(“crm”,A2)),“CRM”)
46.
@rachelmeyer1#pubcon @rachelmeyer1
47.
@rachelmeyer1#pubcon @rachelmeyer1
48.
@rachelmeyer1#pubcon @rachelmeyer1 excel usecase #3: make sense of GA comparison data
49.
@rachelmeyer1#pubcon @rachelmeyer1 =OFFSET($C$2,(ROW($C3)-2)*2,0)
50.
@rachelmeyer1#pubcon @rachelmeyer1
51.
@rachelmeyer1#pubcon @rachelmeyer1 there areso many bad charts out there
52.
@rachelmeyer1#pubcon @rachelmeyer1 Opioid OverdoseDeath Rate by State
53.
@rachelmeyer1#pubcon @rachelmeyer1
54.
@rachelmeyer1#pubcon @rachelmeyer1
55.
@rachelmeyer1#pubcon @rachelmeyer1
56.
@rachelmeyer1#pubcon @rachelmeyer1
57.
@rachelmeyer1#pubcon @rachelmeyer1
58.
@rachelmeyer1#pubcon @rachelmeyer1
59.
@rachelmeyer1#pubcon @rachelmeyer1
60.
@rachelmeyer1#pubcon @rachelmeyer1
61.
@rachelmeyer1#pubcon @rachelmeyer1 thank you!
62.
@rachelmeyer1#pubcon @rachelmeyer1 Excel Guide:bit.ly/pubcon-excel-2019 CTR Analysis Data Viz: bit.ly/2MmqEBv Tableau Public: https://tabsoft.co/2LX7Zgk Excel Dashboard School: bit.ly/2nlu27c

Editor's Notes

#3 give Nathan pyle credit for images
#4 even small companies are looking for intelligent, data-driven insights and reports and there are so many sophisticated ways to present this information. I’ve been in a lot of meetings with channel managers who don’t have data presentation & analysis skills but it’s definitely something they’re being asked for.
#5 data analysis and presentation skills are super valuable when done well, so if you can level up, you become more valuable too. as marketers, we actually have more of edge over data scientists and analysts – we understand the channels and how to optimize against these insights. so I’m going to go through best practices on data presentation, and how to use data visualization to do your analysis faster and better. let’s get started
#6 first of all, some best practices: be so precise in your presentation that there is no question about what is important. use only the numbers that you need to convince them to make the decision you want them to make. Remember that your role, as a presenter, is to recommend one decision over all others.
#7 https://mauriziolacava.com/lean-presentation-design-blog/charts-tables-for-presentations/presenting-data-in-powerpoint/ convince who to do what and how we plan to do it even if things are going well and exactly as expected (which they rarely are), you need to show that in a way that proves your value
#8 try using a system of L1, L2 and L3 dashboards to figure out how to start pulling your data together. an L1 is your highest level for your execs. it’s important to distill this dashboard down to something extremely digestible for this audience.
#9 this dashboard is too much for an L1. there isn’t one obvious place to look, and this runs the risk of dragging your audience so far into the weeds that you don’t have time to discuss the most important metrics. I know the temptation is to put in a ton of information, but you’ll want to choose your strongest metrics that tell the story you’re going after.
#10 make things as clear as possible with no confusion. simple temperature gauges and bullet charts like these can quickly show progress on key metrics.
#11 or something like a simple line chart can also quickly communicate what you’re presenting. by bolding the line for product 3 and calling out exactly what we want everyone to know, we bring the most important metric to the front.
#12 to condense everything together into a dashboard, In house, we use Looker for our main dashboards and data viz, but for my freelancing job, I’ve downloaded a lot of templates from Excel Dashboard School to get myself started and this is one that is very similar to the one I use and looks similar even to what we use in house with Looker. these are very high level metrics that are presented to show exactly where you are tracking. things like daily sessions are not here because it does not matter for this purpose and would take away from the point we’re trying to make on this pretend dashboard, which is while orders are tracking low, revenue and profits are up and we’re tracking fine against those monthly goals. maybe you don’t need to report on these types of metrics, but just remember that whatever it is that you’re reporting on, keep it as clear and simple as possible. if you look up this presentation later, I did include the links to Excel Dashboard School, so you can download their templates and get started there https://exceldashboardschool.com/free-dashboard-widgets/
#13 your L2 dashboard will be for those midlevel stakeholders who need to understand the more nuanced metrics that go into a channel. if daily trends are truly indicative of what’s going on, then it’s fine to include that, but do so with caution – again, so that you don’t detract from what you’re truly trying to show.
#14 never hand this over on an L2. obviously landing pages reports, ranking reports and all of those things are critical for you to be monitoring, but if you present something straight out of GA with all of the metrics, you’re going to get into the weeds and they’ll miss the point you’re trying to demonstrate
#15 or even this! it’s a nice dashboard with great metrics, but this is way too much for your L2 and just confuses things. if you are going to show any kind of daily trailing metrics, I’d recommend something far more simple, like a line or bar chart.
#16 or for those L2s, try something like a simple heatmap to show how we’re trending for the month to give stakeholders that deeper view. this is more detailed than that first dashboard I recommended for the L1, because we know things like form fills and sessions will affect downfunnel metrics, so this would be important information to pass up. it’s detailed without getting too crazy.
#17 so, trending sessions and form fills may be appropriate for that L2, but don’t get into something that doesn’t matter to their big picture like rankings. that’s dangerous
#18 you probably have data that you’re already working with, and there are a few quick ways to make a few tweaks and clean things up, improving your reports.
#19 in this scenario, let’s say the product team is asking us to report on sessions and device splits for the basic and pro versions of our product. fundamentally, this is fine, but there are a few quick changes that we can make to improve it and help our audience come to a conclusion faster.
#20 READ ON THE SIDE this simplifies the chart and makes it easier to understand because we’ve grouped by product instead of device
#21 READ STEPS ON THE SIDE we clean it up a bit more. and by moving the legend to the bottom, it makes everything even more clear because it’s in the order of the devices and allows things to spread out a bit. adjusting the vertical axis by major unit declutters more, and now we can see that for those on the basic product, mobile is the preferred device, while for those on the pro product, they’re logging in via desktop.
#22 in this scenario, we’re being asked by the director of marketing for channel mix. again, this is fine, but let’s make it more clear.
#23 this isn’t a time bound or chronological graph like months of the year or rankings 1-10, so you’ll want to sort it from high to low to draw attention to the point
#24 don’t forget that those getting this data down the line may have no context of what this is, which is why you’ll want to title it in a way that explains what I’m looking at. for anyone wondering how to tidy up the vertical axis, you just click on it, choose “format axis” and then set your major units – I chose 40k on both of these examples
#25 moving on – just a few settings can completely change the story you’re telling. this stuff may seem basic and you may already know it, but I’m not totally confident in that, because I still see crazy stuff all the time!!
#26 for these examples, the axis is critical
#27 this is a great chart, right - it looks like we’ve 10x’d our results
#28 this is axis zero and paints a much more accurate picture. conversions increased, sure, but not that much. 20% increase
#29 ok, so now we know that we need to set the axis to zero, and so on the left, the vertical axis is set at zero but this still isn’t quite right, so should you set the axis to something higher, right?
#30 switch it up to a bar chart in this case to use up the empty space and improve the visualization.
#31 for the conversion chart on the left, it’s difficult to tell any real information from this – we can see that September is slightly bigger, but it’s difficult to see anything else. ‘ and then on the right - don’t use pie for something like this, because most people will assume the pie equals 100% - and the slices here add up to 111.
#32 there can be a few cases for pie charts, but you’ll want to really use discretion and make sure a pie chart is the best choice for your visualization.
#33 if I’m presenting this, I’m making my audience really work for the insight of what I’m trying to show
#34 explode out the two largest slices and add the percentages. now we see very quickly and with no confusion that half of all product sales are coming from products 1 and 2.
#35 moving on to L3s. these can be anything that is important to you that allows you to keep a finger on the pulse of your metrics at a glance. I have some cool ways to visualize your data for both these dashboards and for deeper analysis.
#36 this is good for an L3 and you can grab the template for it at https://exceldashboardschool.com/seo-analytics-dashboard/
#37 I like google’s datastudio, but for the quickest, easiest dashboards that link right into your GA & GSC, databox is awesome. widget based and freemium for basic dashbaords
#38 and so now for the fun stuff. analysis time! we have so much data available to us, what do we do with it and where to start?
#39 tableau is a data visualization tools you can use to take thousands of keywords from SEMRush or Ahrefs and make sense of them, target what is valuable
#40 this takes advantage of HUGE keyword lists and quickly gives you some insights, rather than mining through the whole thing. you can hover over the larger boxes to find combinations of difficult and volume that are useful for you – we’re looking at a keyword difficulty and volume combination here.
#41 this is another tableau visualization that builds a scatter plot for those keywords. here, we’re looking for keywords in the bottom right of the plot, because those will be the terms with lower difficulty and decent volume. this is just another way to visualize huge keyword lists in a usable way.
#42 google sheets low hanging fruit for CTR – this links right to GSC and gives you a fast visualization of where you can optimize for CTR. I had to blur out our data, but you can see the red on the right, which helps you quickly identify areas for improvement on CTR and knock those out really quickly.
#43 for all of the following excel tricks, I built templates that you can download and just add in your data. it’s quick and simple and super easy. on all of these examples, you can totally do this stuff manually, but knowing a few shortcuts in excel will save you massive time and make everything come together quicker.
#44 take a list of days with sessions, pivot them and you can pull out weeks, business days, etc
#46 this is all downloadable
#47 here, we’ve got a big list of keywords that we can theme around. instead of trying to use a filter, throw in a quick excel formula
#48 it’ll group all of your keywords together by matching strings
#50 use this offset formula and take this
#51 this is an example of week over week data taken directly from GA. I used to try to group all of it together manually, but found that there’s an easy excel formula to do the work for you, and then you can use a heatmap to see areas of concern.
#52 I’m going to wrap up with some examples of really terrible charts, because they’re everywhere
#53 there’s an entire reddit dedicated to ugly data (called uglydata), and because reddit is already a damn delight, the whole thing with the comments and everything is a lot of fun. this was from a website about data, called datausa https://datausa.io/visualize?enlarged=c-lineplot-Zpn26u&groups=0-Zpn26u&measure=2sUCF4
#54 spaghetti graph https://datausa.io/visualize?enlarged=c-lineplot-Zpn26u&groups=0-Zpn26u&measure=2sUCF4
#55 actual advertisement on Amazon
#56 the flask that eats a hole into the earth’s core https://datausa.io/visualize?enlarged=c-lineplot-Zpn26u&groups=0-Zpn26u&measure=2sUCF4
#57 and finally a confusing graph from bloomberg
#58 who doesn’t love cheese puffs
#59 on the other side, there’s an Instagram called Chartr that has some really beautiful data visualizations. you can use these for inspiration or just to nerd out over. this one is nice because it makes it really clear that Disney’s acquisition of Marvel is profitable several times over
#60 again, really clear - data makes sense, and they’ve called out that tommy & lucie made the biggest gains in the five days
#61 this is probably one of my favorites. there is a lot of information here, but it’s shown so nicely! this all makes perfect sense and is easy to follow

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Editor's Notes