Data Driven Marketing
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Created for Pubcon 2016, Data Driven Marketing helps marketers get the most of their data and helps with data visualization and collection.
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Data Driven Marketing
- 1. DATA MARKETING driven Erin Robbins | GinzaMetrics @texasgirlerin | erin@ginzametrics.com GETTING THE MOST OUT OF YOUR DATA
- 2. WHAT ARE WE TALKING ABOUT & WHY? DATA VISUALIZATION ‣ What is it ‣ Common mistakes ‣ Choosing the right visual ‣ Making the right visual look less crappy MAKING SENSE OF YOUR MARKETING ‣ Defining market, message, method, medium ‣ Using them to gain strategic insights ON THE AGENDA
- 3. Data visualization is a general term that describes any effort to help people understand the significance of data by placing it in a visual context.
- 4. We need to make sense of a lot of data. The trouble is, there are varying types, tons of sources, and channels that don’t share.
- 5. Excellence in statistical graphics consists of complex ideas communicated with clarity, precision, and efficiency. “ “- Edward Tufte, The Visual Display of Quantitative Information
- 6. SIMPLY PUT, YOUR data IS ONLY AS USEFUL AS ITS ABILITY TO find OR tell A story
- 7. Our brains gather information through visual cues, programmed to look for variations, patterns, and to recognize differentiators in our environment COLOR SIZE ORIENTATIONSHAPE
- 8. Patterns, trends and correlations that might go undetected in text-based data can be exposed and recognized easier with data visualization.. Trends Correlations Outliers
- 10. ‣ How much do they already know about the subject? ‣ How much information do they need to know to make a decision? ‣ What level of detail is necessary? ‣ Are you using icons and symbols that everyone understands? Did you know that 5% of the population is colorblind? (1 in 12 men and 1 in 200 women.) http://colorlab.wickline.org/colorblind/colorlab/ Not taking the audience into account
- 11. Not understanding how much your audience knows about the subject? What you’re talking about How much your audience knows about it
- 12. Understanding how much information they need to make a decision? Information you’re giving them What they need to make a decision What they need to make a decision Information you’re giving them What they thought they’d be getting What you gave them
- 13. Disproportionate axis scaling YES NO WTF Messing with axis scaling can distort the meaning of the data These are all representative of the same data set
- 14. Inconsistent placement of labels, legends & scales Lable Label Title Label Label Title Label Label Title It’s not cute to move things around from visual to visual - just distracts the reader.
- 15. Isolating data Good to remember when building your own visuals as well as when viewing other people’s. What it looks like happened What actually happened
- 17. Title 99% 1% Should use a pie chart Should not use pie chart Title 40% 60% Use a pie chart anyway Choose wisely Or, as I like to call it: STOP USING PIE CHARTS FOR EVERYTHING
- 18. Looking at your data in a variety of ways can tell different stories. Comparisons Chronology Hierarchy ProcessGeography 0 5 10 15 20 0 3 6 9 12Distribution
- 20. WHAT ARE YOU TRYING TO SHOW? Comparison Relationship Distribution Composition
- 21. COMPARISON
- 22. DISTRIBUTION
- 23. DISTRIBUTION
- 24. RELATIONSHIP
- 25. Bar charts Vertical Horizontal Stacked 100% Stacked Best for chronological. Always order left to right. For comparisons that don’t rely on timelines or longer labels. Use when comparing multiple parts to a whole where total count matters. For use when the percentage distribution of each category is the primary concern.
- 26. Pie charts 7% 8% 10% 11% 29% 35% 7% 8% 10% 11% 29% 35% Standard Best for chronological. Always order left to right. Donut Typically used when displaying a graphic element in the center.
- 27. The problem with pie charts Research suggests that people don’t perceive pie slices accurately unless in standard and / or symetrical ammounts such as 25%, 50%, 75%, etc. This means additional “slices” of data may be misunderstood by users or harder to understand. 50% 25% 25%
- 28. Line and area charts 50 100 150 200 April May June July 0 50 100 150 200 April May June July 0 25 50 75 100 April May June July Area Stacked Area 100% Stacked Area Best to illustrate part to whole data over a time period Distribution of each data category as a whole is more important than total 0 25 50 75 100 April May June July Line Best for use with continuous data over time. Shows trends, acceleration, and volatility When you want to compare quantitative data over time
- 29. Other charts 0 5 10 15 20 0 3 6 9 12 0 5 10 15 20 0 3 6 9 12 Bubble Good for nominal comparisons and ranking. Also works well in geographical applications. Scatter Plot Good for large sets of data with two variables. Works well with data over time. Heat Map Best for understanding intensity. Works well for geographic data.
- 30. Bars per capita
- 31. Bars per capita
- 33. Heatmaps for Search Sometimes people tell me heat maps aren’t applicable to search… They’re wrong. Paying attention to usage of specific keywords across various geographies can give you a leg up over the competition. Things to consider include: ‣ Search volume comparison ‣ Competition score ‣ Rank ‣ Competitor rank
- 35. Order data correctly Bourbon Gin Scotch Whiskey General popularity of drinks Gin Bourbon Whiskey Scotch How often I drink them 9pm8pm 10pm7pm Timeline of what I was drinking Gin Bourbon Whiskey Scotch Alphabetically By value Sequentially
- 36. Pie chart ordering 7% 8% 10% 11% 29% 35% 7% 8% 10% 11% 29% 35% Slices go in order of largest to smallest Biggest slice starts in the 12 o’clock position Limit total amount of slices to under 10 whenever possible
- 38. Use consistent iconography, symbols, & fonts
- 39. Color use ‣ Use color sparingly ‣ Choose complementary colors ‣ Use no more than five colors in a visual ‣ Choose colors than match the subject matter and tone of the visual
- 40. Fontchoice Be consistent MATCH THE TONE OF THE CONTENT make it readable for the audience Use text sparingly not just constantly to say anything that you think might fit on the page no matter how much it might just clutter up the page and take up tons of room - because really, people like to have white space around visuals to keep their attention focused on the point of the page. Okay, that about does it. Papyrus is never necessary, neither is comic sans.
- 41. CALLOUTS Use highlights and other jazz-hands types of font tricks as little as possible. Basically never.
- 42. 3D charts are rarely necessary. Don’t do it. Ditto for most animations.
- 43. FINDING A IN YOUR DATA story
- 44. The greatest value of a picture is when it forces us to notice what we never expected to see. “ “- John Tukey
- 46. INSIGHTSDATA ACTION using to gather & turn them into MEDIUMMESSAGE METHOD thethe the is a process to view your information more effectively
- 47. This is your specific value proposition, campaign message, tagline, feature, benefit, etc. MESSAGE{ } the New Feature Product Release Got Milk Nachos > Pizza Back to School Sale
- 48. The Medium is the type of content. A medium is characterized by how it is consumed - not by what channel it is shared on. (Don’t worry we’ll get to that.) MEDIUM{ } the Video Blog Preso/ Slides Webinar Podcast Ebook White Paper Case Study Ad Landing Page
- 49. This is the way the content is distributed - including specific channels. (Toldya we’d get there.) Each medium can have multiple methods. METHOD{ } the Instagram Vine YouTube Pinterest Facebook Slideshare LinkedIn AdWords OutbrainTwitter
- 50. Sell $100K in JoeBob’s Widgetizers in October Message 1: JoeBob’s Widgetizer is the best possible widgetizer Message 2: Enjoy 50% off JoeBob’s Widgetizer at PubCon Message 3: Widgetizers are way better than Widgetozers CAMPAIGN MESSAGES
- 56. The 4th M : MARKET You can overlay your message, medium, and method data geographically to understand how different cities and regions respond to various messages, campaigns, or marketing channels.
- 57. Using Medium, Method, Message, & Market allows you to gather & share insights that maximize what works without dismissing channels, messaging, or distribution based on inaccurate data views.
- 58. And you can use all of the fun chart knowledge you just got to share insights in your organization. 0 5 10 15 20 0 3 6 9 12 0 5 10 15 20 0 3 6 9 12 0 25 50 75 100 April May June July 0 25 50 75 100
- 59. Thank you Erin Robbins | GinzaMetrics @texasgirlerin | erin@ginzametrics.com Deck will be available on Slideshare at slideshare.net/ginzametrics