A vast majority of occasions where data is presented (reports, executive dashboards, conference presentations, or just plain here's a automated emailed thingy from Google Analytics ) end up being abject failures because most of the discussion is still about the data. Finally, this is picky, but why is most of the x-axis yearly and then suddenly just until Q2, 2013?
If I had the raw data, I would also fix the x-axis and representation of the partial 2013 data. Next I create a simpler data presentation, God bless Excel, by creating two big clusters next to each other. Notice because the company performance is all in one row, it is much easier to see that their CPC year-over-year change is less than the category (something harder to see in the original version). It is not completely obvious, but the Analyst is expecting that in the very short time the leadership team has to look at this data, that they'll also be clever enough to do the math for each row, commit it to memory and then compare all four rows and figure out which video is performing better.
The recipient can get to the insight really fast because there is less data (fewer words and clutter), it is well thought out, and we can move to asking hard questions about performance. That is what you want, shift the discussion from the data to what happened and what to do now.
Raise your hand if you've not created a slide like the one below for your presentation.
We take the most interesting part, the data, and surround it with clutter that only makes it harder to understand what the point is.
I'd experimented with having a break in the gray x-axis (yes, I worry about those things!), it looked nicer.
If you spend sometime on the think , it is so much easier to decrapify the data presentation to focus on the most essential element and make data the hero (again, so that you can get off the data very quickly and have a discussion about what the business should do). If you are a student of the Market Motive web analytics master certification course, you'll note my love for segmented trends rather than snapshots in time when it comes to data presentation.
I believe this version shows the change much more starkly and since you can look at one channel at a time, you can absorb the change much, much faster than with the line graph. While with the line graph you could see people spent more time with digital than with TV in 2013. Understand who your audience is, think about the point you are trying to make with your analysis, and then use the best-fit data presentation method. It is easy to see how puppies are doing in context of the average number of searches for land animals and sea animals. The graphs make it seem like there are two similar sized problems to deal with for us as PuppiesRUs Inc. Perhaps, for a good reason, we want the company to believe that they are similar sized problems because our company sucks at mobile and we want to light a sense of urgency under our collective butts.
I simply took the data in the two graphs and put it on to one graph, same bar graph, and fixed the title to make the presentation simpler (I hate long complicated titles).
To our leadership team, the recipient of our presentation, it is really clear how we are performing overall and in mobile.
There is no chance that they will inadvertently think the size of both the opportunities is the same. Imagine yourself to be sitting in the audience and trying to internalize everything that's going on here! Even if you only have two minutes, all I had in this case, it is pretty easy to fix the above textual representation and make it much easier to understand what is going on. Then draw a bar in PowerPoint, eyeball the size (no, really, don't even go in Excel to create the graph, no one is going to notice!), and fill in the sub-components. So much easier to see that story is about how many people search for our company topics and that weight management and monitors are the most interesting. Here's another example of eliminating text, reducing complexity, focusing the the key point and visualizing data simply to get off the data quickly and discuss actions. The first simple mistake you likely won't make as an analyst is to use two different things to represent the same number. The second simple mistake, obvious in hindsight I'm sure, is that there is simply too much text.
It takes a tiny amount of time to really look at the data you are presenting, really think about what you are trying to say and identify the singular point. Please share your insights, recommendations, critique, alternatives and complaints via comments. Yet again the content you deliver to the digital analytics community is insightful and adds so much value to the work I deliver to my clients on a daily basis. AJ: It is hard to comment without seeing your graph, but usually I find that data points clutter the story that we are trying to tell. If you want to share your graph with me, I can take a look at it and share a specific recommendation. I'm amazed (dismayed, sometimes, depending on my mood) how much energy I spend trying to coach analysts to put more effort into the presentation of their results.

It’s amazing how good visuals convert even the most die-hard “I want data in tabular format” type of stakeholders. So I started to take some time (it is not about just 30 seconds for me) and think about creating a story with my slides.
Now I can do my analysis , get to the point faster, work around theories with the slides and, as you said, tell a story through math. Poor readability at small sizes, uneven kerning, and a general noisiness makes it a less professional choice.
The data in the first graph showing the acquisition from which channels the conversions happen more can help the advertiser to concentrate on the channels which brings more conversions. Great post, and love the recommendations at the end to take a step back and evaluate the work to make sure the core points from your time intensive research efforts really shine through and move the conversation forward from research to action.
Matthew: You are absolutely right, the legend is very important and should always be included. This post is making me wish that much more to fast forward data collection and accuracy and get to the fun part of presenting the data with actionable insights. Grace: I ended up using the stacked bars because I wanted to denote that they are three completely, if related, things. Once in a previous role I paid heavily for not taking the time to sell my findings properly; raised more questions than decisions! I would like to add a mindset approach in addition to the techniques you've illustrated.
On the puppies search graph, the only thing I didn't quite like is not knowing desktop vs.
What works for one person in situation one might not actually work for the same person in situation two. Excellent analysis Avinash, I'd love to see how we can track multi device conversions. Say you start a search on your phone then you convert when you're back home from your computer. Depending on the technical sophistication in your company, you can also get assistance from a consultant. I've been working on improving my own presentations and this has really come in at the right time.
For those who want further insight on presenting data for reports I highly recommend Jon Moon's book IMPACT. In your version of the graph, it is not stipulated which color represents mobile and what the other color represents. Wow, what a great display transformation in #7 for targeting in-state consumers more effectively. We will look at some simple errors, and some much more subtle ones that end up limiting our ability to communicate effectively with data. It is not a post about expressing your inner Excel geek with the most advanced remastered sparklines or conditional scatter plots.
For me, and perhaps for others, the sloppiness made the data appear to be an amateurish effort (surprising, given the source) and took away from the deservedly mighty McKinsey brand. And if it is only two quarters of data, why is it taking up the same distance as represented by one year? People in the room (in a small room or a board room or a conference auditorium) will know a lot less about the data than you will, their first impression, and often the lasting impression, might be how clean your data presentation is. I bring it center stage, and make the actual CPC as small as I possibly can (in case someone wants it that desperately). Now it's just a matter of two similar columns that we can distinguish with the use of color. I believe it was that using advertising to drive views of a video fueled organic views as well.
The data is the hero, what is the need to have the arrows and the box and the descriptions? Then use three different bars to represent each stage of the process, and to fill each up to represent the percentages.
But visually it ended up representing a break, rather than the continuity that each stage represents. It will look beautiful and the audience with stay with you as you narrate other insights you know that are not represented on the slide.
Just throw in two simple bars (standard shape in PowerPoint, no Excel necessary), and add a touch of color to show targeting efficiency of TV and Radio. In preparing for this post I looked at my work over the last few months and I think nine times out of ten I found at least one small change I would make, usually a big one! The trick is to obsess less about data perfection and devote a bit more time into data presentation.

I started realizing I was showing the same numbers in different dimensions with the same relevance. I admit it still is the most difficult thing for me: doing the math myself, presenting only what needs to be seen and letting the story speak for itself. Data presentation is one important skill I have identified and acquired as a Market Motive student in your course.
In fact more people use the web for research, and not everyone in the 40%, purchase, might have been in the 52% and 44%.
It costs me close to 6 months delay in getting approval to invest in further website optimization work. My gut told me the first couple years were irrelevant but not until you moved it to a bar graph did I realize what to do with that insight. I think the fact that time spent on TV has declined from previous year is a very important bit of information that got lost when you converted the trend graph into bar graph. I tend to do a lot of trend graphs and your 5th example using bar comparisons instead of a trend line was my favorite. It has some really good worked examples in and includes some great information on rounding in reports to clarify data. But if the occasion is a strategic discussion, any occasion about taking action on data, then you need to get off data as fast as you can. You want to show them all data stuff and how much you worked and how cool your technique was.
The most important part seems to be to get the names of the company, gigantic, over two lines and distracting. Then make the hard decisions and figure out how to present data as effectively as you possibly can.
You would not have known that's what you needed if you'd stuck with your original textual version!
Is there any need for the useless stock photos (and what is up with the magnifying glass to represent research, who does that?)? And even then, at a deep gut level, not internalize it (even though to you perhaps it is utterly obvious).
This might not seem like a big deal in isolation, but every little bit like this takes a tiny bit of your credibility away and it causes the audience to have to shift their minds a little. Finally add the bridging text and use the brace (use the little yellow handle to drag the brace so it is aligned) to show how well or badly each media channel is doing. That’s not to say that you compromise on data quality or accuracy, but simply to put a little more thought into how you present the results. For instance, I used to show a trend, create and axis with ordinals and then add percentage. I can talk first hand to the importance of how to best present data at the strategic executive level. Are you opposed to legends and if so, what's your recommendation to give context on what red and blue mean? For example, in lesson 5, I found the line charts to give richer information than the bar graphs :-). The actual output that is almost singularly responsible for driving the change we want in our organizations. Finally, we have it segmented into desktop and mobile and as if that was not joyous enough, further segmented into Brand and Non-Brand. And why repeat "use online sources," is that not obvious in the awfully crafted title? And while TV is physically from Digital in the above picture, you can easily see that one is much higher than the other. Is there any best practices doc that you know of on – how to choose the right chart type for your data? The thing that is the difference between an organization that data pukes and the one that influences actions based on understandable insights. Hence all the insights-free data visualizations floating around the web that are totally value-deficient, even as they are pretty.
Moreover, I noticed I was taking a few minutes to explain the slides, instead of just passing by them, something that shouldn't be happening at all. Is there a visualization strategy that consistently helps you switch the discussion from talking about the data to talking about what to do with the insights?

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