I wanted to wade a little deeper into the unpredictable world of presenting analytics data effectively. Last month I discussed four techniques for improving presentations to senior executives. Today, I’m going to share six reasons I see presentations fall off the rails and self-destruct. If you think analytics is more art than science, presenting analytics data is even more so.

1. Too Much Data

You want to bring your audience along as you experienced the analysis from start to finish. You provide screen shots of the query results, roughly 60-100 slides of chart images culled from the analytics data. You present your findings, conclusions and recommendations at points where you’ve concluded an analysis.

Your audience wants to hear your recommendations as soon as possible. They trust that you know what you’re doing. Pages of data will put them to sleep -- or make them antsy and irritated.

Antidote: Think like a journalist and use the “pyramid” approach to your presentation style. That means that you start with recommendations at the beginning of the deck -- an Executive Summary in the first five-10 slides -- a mini-presentation that can stand on its own. Don’t bury the lead in the depths of the presentation. If you want to provide all of the data to back up your recommendation, then use an appendix that can be referenced after the fact.

2. Passive Slide Titles

You try to organize the presentation logically and in order. You carefully write presentation sections and titles with descriptive headlines that accurately tell your audience what is in each section and slide, like Key Findings, or Recommendations or Data Descriptions or Visitor LifeCycle or Campaign Comparison. The actual recommendations that you have, or point of view that you wish to convey is located in the middle or lower part of the text, maybe following an observation, maybe buried under percentage comparisons that lead up to this recommendation.

Your audience doesn’t want to have to read through the slide to unearth the key takeaway. They don’t care so much about the data analysis as the perspective and smarts that you bring to the discussion -- that’s why you have your job in the first place.

Antidote: Think like a Mad Men era print ad copywriter. Start with a headline that provides a point of view, a benefit, something that attracts attention. There is no need to prepare the audience with a signpost that says "I’m going to give you the recommendation," just give it to them in the headline. Highly Engaged Segment X has Greatest Potential for Market Growth says something to pique interest, Key Recommendations doesn’t. If you want to create analysis from data that is actionable and interesting, make it clear to your audience that it indeed is. Don’t make them work hard to figure it out.

3. Metrics That Don’t Add Up

You include a detailed explanation of what you observed in your analysis so it's clear that your findings accurately reflect the state of the website or content section. You provide screen shots of the site to show site visitor interaction. You add observations, like “time between visits is spread out over x days” or “50 percent of visitors did not visit the day after a visit in which they placed an order.” You think it is important for your audience to understand how you reached your conclusion through the compilation of the separate queries you performed and the deductions you made.

Your audience doesn’t understand how this helps them figure out the business problem that they gave you to solve. It might help you figure out the answer, but for the audience, it’s like watching sausage get made.

Antidote: Think like a storyteller. Use the strong headline you created as your lead. Only put the key data points and visuals that will support the headline into the rest of the slide.

4. Overstuffed Slides

You want to present all of the great findings that you have culled from the data. You list all of them out -- 10 points on one slide, or five points with explanations in 12 point type -- so the audience can take them in and slowly digest them. You also have slides that provide lots of important information on data anomalies and reasons why the data may have variances. This is all critical because it makes sure everyone appreciates the accuracy of the data.

Your audience sees a slide with more text than they can read. It blends together. Their eyes glaze over. They are interested in being told what to do with the data. They want to get to the bottom line.

Antidote: If you have only a handful of strong recommendations or perspectives then run with those. If you want to provide background info about the data itself, or the techniques that you have used in your analysis if it is absolutely critical, do a quick summary on one slide and mention it in passing. Spending time on content that isn’t central to your recommendations is just a distraction to the audience.

5. Speaking in a “Foreign Language”

You live and breathe digital and so should everyone else. It's 2014 -- doesn’t everyone understand what SEO is, and PPC and bounce rate and multichannel and digital KPIs, blah, blah, blah.

Your audience doesn’t necessarily live in the digital world. Maybe they live in the world of finance, regulation, operations and legal affairs. Digital is new to them and they don’t understand it quite as you do. They want to understand, but they also want the intersection of your world and their world to be clear and easy to grasp.

Antidote: Think about all of the terms that you might want to use to explain your data. Remove any of the industry language that you’ve grown accustomed to. We live in a world of vocabulary short cuts. While mostly ok and understood by your colleagues, team members and fellow analytics nerds, it isn’t necessarily so for anyone who isn’t a member of the club. You have to think through the recommendations that you want to make and then go through a translation exercise so that you can convey in plain language the importance of it all.

6. Overconfidence in One’s Ability as an Awesome Analyst

You know the data better than anyone. Your recommendations are freakin’ brilliant. Your insights will make your audience swoon. You’re charming and witty to boot. Naturally your presentation will be a stunning success.

But do you know this for sure? Have you shown your deck to anyone? Has it been proofed, edited? Have you done a run through? Is your timing going to be razor sharp?

Antidote: Always have someone read through the deck to get feedback on content, transitions, style and to validate that you are making your points with strength and conviction. You get the deck proofed and edited: no one can be their own editor. Finally, do a run through to know your timing and to make sure that you can deliver the recommendations with all the charm and confidence that you believe yourself to have.

Presenting your data analysis effectively is even more important than doing the analysis itself. Spend enough time to prepare, and your presentation will receive the recognition that it deserves.

Title image by presta via a Creative Commons Attribution-NonCommercial 2.0 Generic license

Editor's Note: Read more from Phil in Blue Collar Big Data: The Work Behind Big Data Analysis