Excellent Analytics Tip #21: Convert Complex Data Into Simple Logical Stories

Visualize I love this quote from Richard Branson:

Complexity is your enemy. Any fool can make something complicated. It is hard to make something simple.

Is there any place Mr. Branson's words are more relevant than in our big data world?

We are not as awesome as we need to be when it comes to presenting data clearly, logically and simply, and I'm convinced that this contributes to the business world being less than ideally data driven.

And I’m not talking about just in a once-a-month “omg we have to send that pretty dashboard to the big boss so let's call our agency and get some sparklines and tiny fonts” kind of way, but rather in how we communicate with data every day.

So, today a short lesson on how to apply the power of unpacking the data to increase the chances that it clearly communicates the story we want to tell.

The Data Presentation Challenge.

This point came to the fore recently when I saw this "module" on top of a dashboard…

the consumer journey

My first question on seeing any collection of data is: "What the heck is it showing?"

The words "the consumer journey" help. In couple of minutes of moving your eyes back and forth it is easy to see there is some very cool data here. We can see that it is showing research data from the awesome Google Consumer Barometer. The next bit is some digital data, perhaps over 29 days (days to conversion?). Then we see what is surely online Search behavior data. Then back to data likely from the Barometer.

There is online and offline data at the start and end.

The data does seem quite interesting. But what is the story?

And my biggest challenge was: Will a lay person (CEO!) actually understand what we are trying to say here?

Here's what I don't want to do in this post: Question the data, or judge the wisdom of putting 6 completely different sources and 11 metrics next to each other, or question the missing pieces.

I'm going to put myself in the position in which we find ourselves every day. We've collected some data, or someone just gave us a bunch of data, and we have quickly figure out how to communicate the key point in the data.

So I spent 15 minutes with the module above and attempted to create a structure that would more clearly tell the story. I ended up with two ways to communicate the above data more effectively.

Simplifying the Story: Attempt One: Excel Power!

When I look at a set of data the very first thing I want to do is see if it is logically structured. It might be my background as a mechanical engineer, but I like things to be laid out cleanly, I love symmetry, and I love clear connections and flow.

Because of the way the data is presented above, the first thing I'm uncomfortable with is the implication that it presents one whole story

It is not.

Thing 1 is a big thing. Thing 2 is a small part of thing 1. Thing 3 is a small part of thing 2. Thing 4 is… back to thing 1, the big thing.

If you are a person pressed for time (CxO!) it can take much longer than necessary to figure out the point because of this riddle, wrapped in a mystery, inside an enigma structure.

Another subtle problem is that, completely unintentionally, it makes digital look bigger than it might be. While I love digital (Go Internet!), as an Analyst I'm not comfortable with any bias (remember in this case it is unintentional). If you get caught, it looks sub-optimal.

Every time I look through a cluster of data these questions go through my mind:

Are things laid out logically?
Can someone see the multiple strands in the whole story, and pick out the relevant strands?
Do I have extraneous data that I can remove?
Is the macro point being made clearly?

For the module above the answers are: No on 1, 2, 4. Yes on 3.

So how do we fix it, in time-pressed situations?

This might seem odd but the two places where I can lay things out and work through them are PowerPoint and Excel. I find that the boxes in Excel force a good discipline on me, and it is impossible to communicate anything too complicated with PowerPoint (ok, it is possible but I'm unable to do that! :)).

So I open Excel and attempt to pick out all the strands and lay things out logically. All the numbers go into cells. As I identify each riddle and each mystery I simply insert rows and click the Merge & Center icon to group clusters of data.

Remember we started with this…

the consumer journey

This is what I ended up with after a few minutes…

the consumer journey table one

I really wanted the various strands of the story to be crystal clear. For example, it is clear now that most of the data we have is about Research Online. That was less instantly obvious before.

The flow starts with Research Online and then moves into illustrating what it takes to get one sale in this industry category (12 searches, 15 website visits and 5 display ad clicks).

From there it drills down into search (very clearly) and highlights that 79% of the searches are non-brand!

It ends by showing where people ultimately end up making the purchase.

The key point, communicated hopefully by the "bookends" above, is while only 15% of the people buy online in this category, 71% of the decisions are influenced by online. (So buy digital ads! :))

While the table is unsexy (it really is) I think it works better. What do you think?

Did you notice that the darker cell lines? It is my subtle way of visualizing the flow of data and more clearly mark the strands in the story.

Did you notice the "air gap" between the last set of data and the rest? I like using air gaps to visually communicate "stuff on the right is a bit different from stuff on the left of the air gap." It works really well because your eyes have to pause – sometimes that is a good thing.

Finally, did you notice that I killed the Days number? Even though I was not judging the data, that point was just so distracting that I could not bring myself to keep it.

Ok, can we leave the good enough alone?

Of course not.

At this point I wondered if it would be better to put the key elements of the macro point next to each other, rather than as "bookends." The buying behavior next to the research behavior.

Two seconds later, I have this…

the consumer journey table two

Ahhh… much better.

Anyone can instantly see that while purchases are overwhelmingly offline (85%), the influence process is overwhelmingly online (71%). The rest of the "so what is it that the average consumer does online?" data flows from this.

The new format seems to pass the initial sniff test.

At this point my mild obsessive compulsiveness kicks in. Remember I'm a mechanical engineer who likes symmetry, and there is an empty space under Buy Offline, nothing next to Don't Research.

I don't like the "unbalanced" view.

But that's easy to fix in Excel. One more click on Merge and Center icon and boom!

the consumer journey table three

Ahhh … so pretty. I've perfectly placed all the Tetris blocks. It really flows from left to right, and the space under thing three and thing four does not look as odd either!

Done? Not yet. (Are you seeing how the sniff tests and not being done are core skills to develop? :))

One of my habits is that when I'm done with the work, I got back and look at the whole story all over again. Just to make sure.

When I do that, I see a problem. One subtle thing that might be easy to miss if I just cared about the numbers, but I actually care about the story more.

My table above is implying is that 8% of the people who Don't Research buy offline. That is actually not true. We don't know where they buy.

Then (obsessive compulsiveness!) I also worry that the dark line for buy and research (between online and offline on both sides of the air gap) might cause the CxO to infer that everyone who researched offline bought offline as well (ditto for online). Also not true.

Dang it!

While I've made my table balanced and clean and even pretty, I might now be implying things that I should not imply. And when you have to make a choice between sexy and functional, choose functional.

So back to square one. I kill my final version and end up sharing the first version of the table…

the consumer journey table one

It communicates the story much better than the initial module. Most CxOs will grasp the macro points immediately.

But this layout also adds a couple of visual hurdles. They'll be great places for the audience to ask questions. That, when you present eleven metrics from six data sources, is a good thing.

Simplifying the Story: Attempt Two: PowerPoint Power!

I love PowerPoint. I love making numbers invisible. I love trying to figure out how to visually tell a simple, yet compelling, story.

One immense benefit of working with Directors, VPs, CxOs is that the higher up you go in a company, the less likely it is that anyone cares about or can even internalize lots of numbers. (Remember this!)

It took me just five minutes to think about the table above and then to come up with this simple visualization to tell the story using PowerPoint…

the consumer journey chart

Ironically by having fewer numbers I feel this works even better. The relative proportionality of the boxes is more than sufficient to communicate the point.

I've used colors to highlight the three strands of data (teal, green and red). And then shades green to communicate the sub-strands of the digital story.

As digital is always held to a higher standard (and an unreasonable one compared to TV/Mags/Radio), I include the numbers in the sub strands.

There is enough air gap between the elements that each can stand on its own (avoiding the problem with my clean Tetris table above), and yet the colors help your eyes flow nicely from left to right as you pick out the key data segments.

Awesome, right?

Amazingly sometimes you do all this work just for yourself.

In this particular use case I knew going in that it would be impossible to use the above PowerPoint version of the visualization because very little real estate was available in a dashboard. I knew that we would have to go with the table.

Still, the five minutes spent thinking about the problem and five minutes spent in creating it was time well spent – it exercised the brain and it helped me ensure I understood the story well enough.

What do you think? Does the PowerPoint version work for you?

Six Quick, Simple, Data Presentation Tips.

If you want to communicate for impact, in time-compressed situations or when you are not presenting the data yourself, I would like to offer the following six tips for your consideration:

1. You need to ensure that you are not presenting a riddle, wrapped in a mystery, inside an enigma .

It is your job to unwrap the data and the insights and present them as logically and with the simplest flow possible.

2. Consider these two questions: "What is the macro story here?" "What are the sub strands?"

The answers will be illuminating.

3. Every row, every column, every number you present will contain a message. Use this power.

Send a message with what goes first, what goes next, what's metaphorically underlined.

4. Good analysts are great assassins. They are great at finding lame metrics and dimensions and assassinating them.

I was genuinely sad that the only thing I could kill above was the number of days. If I had a bit more time or context, I would have killed at least 3 more metrics (I can see them now!).

5. Sometimes you don't have a choice, but whenever you have a choice use a visualization – even if a simple one created in PowerPoint – and not a table.

6. It might not have been completely obvious above, but in this case I knew about the business situation, the marketing landscape, and the platforms the data was describing. Data presentation and visualization is always easier if you actually understand the business, because you are trying to simplify and communicate what you already know well.

That is the primary reason I've consistently said that great Analysts are good at marketing, they are good at understanding the business.

I hope that you see that it does not take a long time to take something complex and create a simple, logical, and yet powerful story about the key points you are trying to communicate. That way, even if you are not there to explain the data, the person at the other end will likely understand most of the story. If your data presentation can pass that test, you win.

As always, it is your turn now.

Do you have quick and simple tips you would add to my list above? If you got the first blue module and you had ten minutes, would you go down the same route as I did? Perhaps a different one? Of my three table attempts, would you have ended up back with table one? Which of the 11 metrics would you have assassinated? Got an example of complexity to simplicity that you might be willing to share with us?

Please add your stories, tips, critique, kudos via comments below.

Thank you!


  1. 1

    Gold words, Avinash – "I love making numbers invisible".

    For analytics data this is very useful.

    P.S. I buy your last book about week ago and have read 250 pages at this moment (Russian edition, i'm from Kiev, Ukraine) and i want to say "thank you" personally for your work, that you show in this book.

    When we can wait your next book? :)

  2. 2

    Usually, I want to create a story with my data, trying to highlight an actionable insight.

    I created a draft sketch with my own version for these data http://i.imgur.com/ACmWQ.png .

    I used an extra (imaginary) figure, the size of the market, which in most cases is possible to discover.

    I skipped some figures, helping me to focus on a specific item.

    [Update: I've embedded a George's version below, please see link above for a higher resolution version. -Avinash.]

    • 3
      Bilaal Alim says

      Personally, I wouldn't use a doughnut/pie chart, because though they look good, they do not tell the whole story at a glance.

      You have to see the numbers to get a proper feel of where things stand. A simpler bar chart allows you to immediately notice the proportions and dimensions of each part of the story.

      I say this because first impressions matter greatly to the human brain. With a doughnut chart, these impressions can be confused – resulting in a subconscious mistake.

  3. 4


    Love the blog. I think you make great points here.

    I think one of my main problems is in presenting data effectively to people that don't know much about web analytics. I get excited about data (because it's super exciting!) but sometimes fall into these traps of not simplifying the message.

    These tips will be very beneficial when I have to present next on findings!

    • 5

      Andy: I can totally relate to your perspective, we are so into data – all day, every day – that we assume far too much data literacy on the other side. Sub optimal assumption. :)

      Everyone loves stories. But they are especially effective in our super busy uneven data literate/comfort level world.


    • 6

      Yeah, I'm the same way.

      I love numbers and can pretty easily scan over a spreadsheet and pull value from it.

      I often have to make myself realize that many others can't appreciate the story as well unless they get it simplified and visualized!

      Graphs, people love 'em.

  4. 7

    I definitely agree with the core of your message here. What you start out with is confusing and slightly meaningless, and you end up with something insightful.

    One issue. The way your excel produced version is laid out implies that "websites, searches & adclicks" shows the number of people doing research via these channels. However, your power-point version lays it out as a 'conversion journey' – which seems more likely to be referring to these being sources of sales.

    So, are those 15 websites, 5 adclicks etc referring to the people who did research, or the people who converted? From what I can tell of the data, it's likely referring to people who converted, but the original set is so unclear as to what it represents that that's only my best guess.

    It does goes to show it can be really hard to visually lay out data in a way which doesn't misrepresent it, which is a point you made.

    • 8

      Chris: Great feedback, thank you.

      The overall data set is for people who end up buying (across online and offline). I think that was not too obvious, it can be made to be so.


  5. 9
    Julien Delvat says

    Thanks a lot for that post, I really think you took a bunch of numbers and made sense out of them.

    I still think you can make it better:

    – why not merge the "Single-Conversion Journey" with the "Search Journey"?
    – I think ON / OFF is confusion compared to Online / Offline
    – try to show your data in a horizontal stacked bar chart instead of a vertical one. I will be easier to compare.

    This is after all another journey … there's always room for improvement ;o)

    • 10

      Julien: Thanks for the ideas!

      I'd tried the first one, but I wanted to have the search and non search story to stand by itself, as a discussion point, and have the search story stand by itself.

      I do think the horizontal one is a great idea. I'm going to try it. Thank you again.


  6. 11

    Great post Avinash.

    Simplicity is very important in every aspect of life and its all the more important for portraying numbers. The moment you show data in terms of numbers and %ages most of the audience gets into their primary school math phobia. So data in term of graphs (and presentation in term of stories!) is always best.

    I want to share a quote from Steve Jobs on Simplicity:

    “Simple can be harder than complex: You have to work hard to get your thinking clean to make it simple. But it’s worth it in the end because once you get there, you can move mountains.”

    In fact I am of the opinion that if you find something difficult it means you didn't get it completely. Because by nature Everything is Simple, we just have to work towards making it simple. I wrote one blog as well on the topic of simplicity:

  7. 12
    Patrick Sanders says

    Great post Avinash.

    Data visualization is always a challenge for me when presenting to leadership.

    Thanks again!

  8. 13
    Rajeev Jain says

    There are really two stories here and part of the difficulty is in mixing them up in a single table/graphic.

    First story is that consumers are researching mostly online but purchasing mostly offline. Period.

    Second story is just a bit more detail of what exactly are they doing in that online research. So it might make sense to separate the two. They may even need to go to different audiences – online market research, vs. channel strategy.

    Now since I did look at it this far and some thoughts came to mind as I was looking at it.

    Story 1: Is it consumers researching mostly online, or most consumers researching online? Are the purchasers mostly the ones who researched online or offline? What exactly does it mean research offline. What is the 85% metric mean – time spent, or # of people? if # of people, then how do you count those that do their research both online and offline? If the "both" are lumped in with online researchers, then we have a data interpretation problem here.

    Story 2: Just a set of numbers here and no story yet. I would want to ask more questions: Are the 12 searches and the 5 ad clicks leading folks to the 15 websites shown, or do they get there independently? And just as a presentation tip you can merge the 3rd and 4th bar into one.

    I do like your list of questions that an analyst should ask. And I couldn't agree more with the need for an analyst to understand the business.


    • 14


      I share your thoughts for more in-deth questions as the actionable items from the CxO perspective require the more in-depth look. At first glance the data tells us we need to invest in online (but where specifically) and that the offline buying experience is still important.

      Of course a lot depends on the business, but for example, where they are doing the research both offline and online is key. I would also like to know the conversion ratio of the online/offline buyers. Data can always be misleading.

      For example, since the data is only looking at buyers, If the same number of consumers are researching online and in your stores, but the store conversion rate is low, maybe in-store training is needed. Perhaps I am getting off track of the example, which, I think is a terrific job of simplifying the data, but in the end meaningful actionable items are the most important and the reason we collect data.

      Most of us have experienced the increase in consumer product knowledge with the internet and as we see online purchases continue to increase, as this data shows we can't leave the offline experience alone just yet.

  9. 15
    Rajat Khatri says

    Great post Avinash.

    As an Analyst and a Data Analytics professional (with six years of experience in Analytics with conpanies like Fractal, EXL and Isango), I can very well correlate to the problem and understand the solution.

    I personally prefer a graphical form than numbers and of course a storyline (even with additional 2 slides) but many times the client/ the presenter doesn't need that an he need all the numbers as he wants the audience to think and he feels that he can communicate the message during presentation (forgetting post presentation, the deck will be shared and no one will be there to assist the reader with what all these numbers mean).

    Not sure if you can suggest a solution to this.

    Thanks again for you guidance

    Rajat Khatri

    • 16

      Rajat: If the client is looking for more numbers then they really want a dashboard or a customized report. Both are of course doable, but beyond the little problem we were trying to solve in this post.

      I agree with you that typically we won't just share a little module of data. If we send it via email we will write text to explain a few salient points to ensure the CxO will have some context. If we present in person then we'll speak and say that.

      It does take a few times of you sharing the context before our CxOs will totally get it and understand the numbers. After that we can just send the numbers.


  10. 17

    Richard Branson may have borrowed it from Mr.Einstein as he said:

    “Any intelligent fool can make things bigger, more complex, and more violent. It takes a touch of genius — and a lot of courage — to move in the opposite direction.”

    The core remains the same :-)

  11. 18

    Hi Avinash,

    These lines are beautiful….

    "When I look at a set of data the very first thing I want to do is see if it is logically structured. It might be my background as a mechanical engineer, but I like things to be laid out cleanly, I love symmetry, and I love clear connections and flow."

  12. 19

    Great article Avinash!! I prefer the excel version, but I agree with its shortcomings (misleading relations between data points).

    One thing I miss is the *movement* between these individual data points. And there is also the question if the individual data points are measuring the same thing (which they don't seem to be doing).

    And I'm itching all over to try to come up with my own 'if this was a perfect world, what would it look like' version :)

  13. 20

    Hi Avinash,
    This is a great post…& this is 3rd comment here :-) since I was reading this part by part….
    You have mentioned that if you had time & context you would had killed 3 more metrics…
    Are these fields,

    1) Don't Research
    2) Website's

    If Yes, which 3rd will field will you kill?

    I will be grateful for your reply….

    • 21

      Nikhil: I think Don't Research, Days and Websites might be the candidates.

      In this case the tough thing is that there might be other data that might be even more powerful if I had to tell the "here's the role of digital in multi-channel purchase" story. Then more of this data might have gone.

      But in this case, as I said at the start, I'd set a limitation on myself that I'm only going to work with the data I'd received. I wanted to replicate the situation that we analysts find ourselves in every day (and we usually don't have the luxury of seeking the perfect dataset).


  14. 22

    Great post Avinash – this is a nice approach to business analysis, and thanks for giving all us analysts credit for pulling together much more than "just crunching the numbers."

    My approach is largely the same: first I envision the flow of the information (as if they were tables and had relationships to one another like they would in a structured database). Second, I go back to the question (problem) to see what is relevant and what isn't to decide what to keep & throw out. Third, I play with various data visualization choices to see what makes the most impact AND is the most intuitive for anyone to understand. I aim to make my presentations so simple that even a fifth grader would understand it. After that, pull back to look at the big picture and details to see if they make sense and iterate through the same process until I have something to show to someone for a second opinion.

    And that's probably the one [big] thing I would add here (as you have done implicitly by asking our opinion): always ask for a second opinion. I find the synergy that comes from a good collaboration of creative minds and produces a better overall analysis. I rarely produce any important business analysis (especially if major decisions ride on it) as final without peer review.

  15. 23
    Anonymous says


    Wonderful visualization. I think the visual representation makes data easy to understand.

    My instinctive reaction was that the story is incomplete.

    If this is a CEO level insight, then where is the actionability? Example, We have Single Visit Journey shouldn't one compare it to Multiple Visit Journey, better yet, All Visit Journey.

    Why? As this rules out false positives and truly isolates opportunities that work. (e.g. Visit level targeting).

    So, kudos to you in describing the data extremely well but insights / actionability… well it's never a 10 minute exercise…..There are always more questions than answers.

    • 24

      Anonymous: In this post my goal was to demonstrate how you can make a story out of something that is complicated, and might not even be complete. That was the limitation I'd mentioned at the start of the post. That was simply because day to day we find ourselves in that conundrum all the time! :)

      But to share a bit more context…. As I'd mentioned at the start this was just one module in a dashboard, so there was more and page two had the recommended actions. The data does show multiple visits and not single visit (as demonstrated by the search, ad clicks, website visits section). It shows multiple steps that lead to one conversion by looking at all conversions (online and offline).

      You are right though, there are always more questions. If we tell the story right my hope is they'll be the right questions.


  16. 25

    Avinash, once again simplifying the complex – thank you.

    Great post.

  17. 26

    Hi Avinash, Off late I have become great fan of you.

    Please keep up good work. Especially the way you present the complex techniques in very simple way.


  18. 27

    Awesome work Avinash!

    I attended an engage event the Friday before last which covered how to assign KPIs and how to report on those in a way that makes sense to those we send our reports to. I was especially impressed with the NI Framework and how it ties in specific business goals to specific metrics.

    I'm also reading your book at the moment which was passed to me by a colleague. I think one area most of us can improve greatly in is data analysis and meaningful reporting…


  19. 29

    Thanks Avinash, for this interesting and educational post! Enjoyed reading it very much. Thanks for sharing the 6 tips, too.

    One question I have, though, is how this data set is interpreted:

    In the column "consumer research", it ideally assumes that consumers can only have one type of research behavior. What if a certain type of consumers are switching between online and offline research? Or does "consumer research" here mean the very last consumer research channel that triggers one consumer to purchase an item?

    Thanks and look forward to your feedback.


    • 30

      Tracy: In this context it simply looks for the primary channel. So primarily online, primarily offline or no research. And do remember that there is no implication that all those who primarily research online would buy offline.

      Real life is a bit more nuanced. For that data please use the Consumer Barometer. It has data for those who do online only, offline only, online and offline research and no research.

      You can learn more about that tool in this post:

      Global Multichannel Consumer Behaviour (Research/Purchase) Analysis


  20. 31

    I agree with some of the posts above "I love making numbers invisible. I love trying to figure out how to visually tell a simple, yet compelling, story." is so very true.

    This works extremely well of PPC reporting, we've seen competitor reports which literally list every keyword and stat in a spreadsheet – completely useless to the end user/client.

    It has to be said Avinash your posts are both comprehensive and compelling, great work.

  21. 32


    Maybe the cliche infographic may make even more sense from a visual point of view.

    Of course I don't see it working in a fortune 500 co but SME generalists like me would love that (assumption on graphic skills of course).

  22. 33

    Better late than never commenting on this post, Avinash. I was once told that bar charts are always a better choice than pie charts because we can perceive differences in lengths much more easily than we can perceive differences in areas.

    Another tip: when dealing with multiple variables, use your x and y axis for the two most important variables in your story.

    Data visualizations are abused in content marketing these days, but succinctly presenting information in a visual way will never go out of style. Thanks for the pointers!

  23. 34

    Hi Avinash,

    "Complexity is your enemy. Any fool can make something complicated. It is hard to make something simple."

    I do also love this quote.

    Most of us have a mindset that if it is complicated it's complicated. And with your post, it really shows that complicated things can be made as simple as you want it.

    Data's is one of my enemies and it's really hard for me to convert it to the way it can be understood by many. Using analytics is hard but through your article it can be made simple to convert all the data's on it.

    Thanks for sharing it .

  24. 35
    kartesharj says

    Goood article Kaushik.

    Thanks for sharing it.

  25. 36

    Love this!

    My only objection with the excel table is that the buy online box (15%) is the SIZE of the research (71%).

    Another place to play around with merging cells to create accurate size boxes in teh very simple excel version.

    • 37

      Libby: Good point.

      The intention of the boxes is not to show size, rather show "flow" / "how many of x results from y."

      So what it is trying to say is that while 71% research online, the % of purchases online are only 15% (and the "air gap" is to illustrate that not all 15% might have been in the 71%).

      I'll try to play with it a bit more to make that extra clear.

      Thanks for sharing your feedback!


  26. 38


    I definitely feel and find that less numbers and more of a simple visual representation helps my clients to understand the data a little easier.

    Thanks for post!

  27. 39


    Could not agree more with the quote from Branson, "Complexity is your enemy" as big data often just adds to our confusion. Simplicity is the key but there is a need for the art of interpretation using big data which creates the great story.

    Not easy to do as data points continue to increase.

  28. 40
    Ian Donaldson says

    Americans are good at simplifying English – for example coffee to go, when we in the UK used to say takeaway, and skinny latte when we would have said latte with skimmed milk.

    But their spokesmen make simple language complicated. For instance, why do they say – "this will have an adverse impact on our profits", when they mean – "this will hit our profits" ?

  29. 41
    Karan Sood says

    In the second iteration of the table where you move the Buy Online/Buy Offline to the front of the table, the problem that I have faced in that case is that the box size you have you Buy online 15% is much bigger than box size for buy offlince 85%. The relative size difference creates contradictory impression at the first glance.

    I have seen several times in my presentations in this situation that higher management gets confused because they ignore the number and look at the size of the box….

  30. 42

    Very much enjoyed seeing you speak in person I believe at MozCon 2011.

    I appreciated this post because it took me one step beyond where I would normally go with my data analysis. Because I personally consume numbers easily in Excel grid form, I tend to stop there and rarely think to take it to the visualization stage for my superiors who may need to review or present this data.

    It only makes sense that not everyone speaks my language and may appreciate the "story-telling" presentation for putting it in context instead of just being numbers in a spreadsheet. I'll definitely be making visualization a part of my routine when I present data or recap CRO projects.

    Thanks, as always, for sharing your wisdom.

  31. 43
    Jesse Olive says


    A friend of mine Rekha Subramanian suggested I follow you. I read this blog post and have a true appreciation for the moral behind the story. Thank you. I would like to begin creating a similar table for the company I represent.

    With that being said, I have a more fundamental question. How are you determining the percentage of individuals researching online, offline and not at all?

    I would appreciate your direction in this area.

    Best regards,

    Jesse Olive

  32. 45

    Thanks for sharing this data.

    One thing to consider is the table for searches, websites and ads could be considered overall searches which leads to websites or ads.

    Obviously the data doesn't add up properly, but possibly there is a way to distinguish the differences between them so it's clear.

  33. 46
    gemarasedura says

    PowerPoint version work for me fine!!

  34. 47


    I learned a lot from this and this will add a great value in my career.

  35. 48
    Steve Hennigs says

    Hi Avinash,

    Great post as always. This may have been brought up already in the comments but I did not have time to read them all.

    In the PowerPoint representation of the data the bar for "Consumer Purchase" only contains Online and Offline. You correctly mentioned early in the post that [My table above is implying is that 8% of the people who Don't Research buy offline. That is actually not true. We don't know where they buy.]

    With that being the case I would suggest having a Red section in the "Consumer Purchase" bar for Not Sure or something like that in order to accurately represent that group.

    Thank you for all your great work over the years and I look forward to your next post.


  1. […]
    Excellent Analytics Tip #21: Convert Complex Data Into Simple Logical Stories (Occam's Razor by Avinash Kaushik)

  2. […]
    Six Tips To Convert Complex Data Into Simple Logical Stories, http://www.kaushik.net

  3. […]
    Excellent Analytics Tip #21: Convert Complex Data Into Simple Logical Stories – Avinash Kaushik, our favorite analytics guru, gives marketers tips on presenting their data in a way that’s not “a riddle, wrapped in a mystery, inside an enigma”.  Overarching themes in this article are that visualization is critical and it is never a good idea to present information that doesn’t tell a story, or has no business being in your story.

  4. […]
    The question though is how to best do this. Earlier this week, I came across an excellent blog post by web analytics guru Avinash Kaushik. His November 5th post provides a detailed example of how to convert a complex data set into a compelling story. I highly encourage you to spend some time reading this inspiring blog post.

  5. […]
    Avinash Kaushik has another analytics goodie for us on his Occam’s Razor Blog: Excellent Analytics Tip #21: Convert Complex Data Into Simple Logical Stories. In this piece Avinash has some great tips on how to make your data tell a story. As we are inundated with more and more data, this type of skill is going be more and more in demand.

  6. […]
    Komplexe Daten in einfache Geschichten übersetzen Ein Plädoyer für die Einfachheit in einer komplexen Analytics Welt. Avinash Kaushik beschreibt seinen Prozess Daten aufzubereiten und gibt am Ende sechs Tipps für das schnelle Zusammenfassen von Kennzahlen. (kaushik.net, englisch)

  7. […]
    Six Tips To Convert Complex Data Into Simple Logical Stories

  8. […]
    By now, you will probably have insights about the usage of your site that no one else has – and almost certainly not your management. Such knowledge is very hard to communicate clearly – partly because we all have strong preconceptions about how a site is used, based mostly on our own limited use of it. Avinash’s ‘Excellent Analytics Tip #21: Convert Complex Data Into Simple Logical Stories’ explains how to create compelling and accessible arguments from analytics data. Be warned though that there’s no simple formula, and you will have to work your data hard and think carefully to ensure that you’re presenting a useful and truthful picture.

  9. […]
    Como siempre que Avinash Kaushik escribe un post, este es completo y muy interesante. En este caso, su consejo sobre analítica web es convertir datos complejos en simples y lógicas historias. Aquí os explica como Excellent Analytics Tip #21: Convert Complex Data Into Simple Logical Stories

  10. […]
    In this article, analysis guru Avinash Kaushik talks about how it’s easier to conceptualize data if you’re working in a domain you already understand. I love the idea of allowing employees who are living and breathing a particular issue the opportunity to find meaningful data that could help inform their decisions — liberating data to enable smarter design. Will be interesting to see if other companies follow this type of decentralized data model.

  11. […]
    本来今天准备翻译一篇Avinash Kaushik的博文,没错,就是写Web Analytics 2.0的那哥们。但是我发现哥们太对得起读者了,每篇博文都无限的长。所以我决定还是简化一下,挑重点编译。全文猛点:https://www.kaushik.net/avinash/analytics-tips-complex-data-simple-logical-stories/ Richard Branson说过的一句著名的话:Complexity is your enemy. Any fool can make something complicated. It is hard to make something simple. 大体意思就是复杂是你的天敌!傻子才把事情复杂化。把事情简单化老难了!

  12. […]
    https://www.kaushik.net/avinash/analytics-tips-complex-data-simple-logical-stories/ I choose this article mostly because it actually had complex data in a simplified form. Some of the blog entries were extremely long so this fits appropriately with what I was supposed to do. I had to make a piktochart of the information included in the blog into a neat little picture.

  13. […] Data eşliğinde sunum yapanların ve datadan hikaye yazanların okuması gereken çok değerli bir yazı. Avinash'dan: https://www.kaushik.net/avinash/analytics-tips-complex-data-simple-logical-stories/ […]

  14. […] Avinash Kaushik: Convert Complex Data Into Simple Logical Stories […]

  15. […]
    By mastering your digital goals, you will be able to translate them into key performance indicators (KPIs) and concentrate on statistics that are meaningful for your organization. I once read in Avinash Kaushik’s blog: “Good analysts are great assassins. They are great at finding lame metrics and dimensions and assassinating them.” This quote represents, to me, one of the most important ideas about web analytics.

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