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This episode is all about data storytelling at a “traditional” enterprise company like LinkedIn and also at a major news publication. Janie Ho is a former global account analyst at LinkedIn in NYC where she facilitated data-driven presentations to close revenue deals for LinkedIn’s top global strategic accounts. Currently, she is a senior editor in growth and audience at the New York Daily News under Tribune Publishing. This episode goes into best practices for creating data-driven presentations, learning new skills in non-traditional methods, and tools journalists use to find new stories to pursue.

Upleveling skills: from SEO to data

As a former journalist at various publications like ABC News and Businessweek, Janie forged a non-traditional path to a career in data.

In New York there was a popular platform called Mediabistro where they held these one-night courses. Many of them were free, and Janie took as many free courses as she could. She took many courses on SEO, and her SEO skills ended up being her gateway into data analytics.

I always find it interesting how people from all different backgrounds end up getting into data whether it’s learning Excel, SQL, or some other data tool. It further shows that no matter what your role is, you will come across a spreadsheet at one point or another. In the world of SEO, you have tons of data around keyword performance, traffic estimates, rank, and more to play with.

LinkedIn: an enterprise behemoth

Janie eventually found herself at LinkedIn in 2011 as the first analyst in her group focused on global revenue accounts. When she left LinkedIn three years later, there were 50 analysts. Most of the analysts were recruited from management consulting so these analysts most likely had some data experience. Luckily, LinkedIn emphasized professional development so Janie was able to not only learn data skills, but also how to build data-driven presentations.

Most people don’t realize that LinkedIn is expensive enterprise software that powers a lot of hiring functions around the world. Seats for the software cost $10K/year and above. When Janie joined LinkedIn, the company was in high-growth mode since there was so much demand for the product on the enterprise side.

LinkedIn was basically hiring salespeople as fast as they could, and the salespeople were expected to start selling the next day. There wasn’t an extended onboarding period; they just needed people to sell. With all these salespeople doing QBRs and creating new pitch decks for the C-suite, LinkedIn needed many analysts like Janie to help produce these presentations at a fast rate.

Concise business review data presentations

In order to create these presentations, Janie and her fellow analysts were basically downloading LinkedIn usage data and slicing and dicing the data in Excel. She had to show LinkedIn’s top strategic clients how things are going during these QBRs, but also what the opportunities are to spend more on LinkedIn.

Internally, LinkedIn had a program called Data-Driven University which was created by former Bain consultants. Janie would learn the key data storytelling skills from this “university” and turn around and train salespeople. Some examples of slides that Janie would create are below. These are the “after” slides that show how the data could tell a better story where there’s only one key takeaway per slide:

Compare these slides to the slide below where there are too many elements on the slide and the key takeaway for the audience is not clear:

One-click data-driven presentations

The insights team at LinkedIn ended up creating a tool called Merlin that was built on Tableau. All you needed as an analyst was the the client’s company ID and all the visualizations would get created with one click. The output was a 50-slide deck with takeaways written in plain English.

One of the neat features of this one-click dashboard was that it would create an “icebreaker” game in each deck depending on which clients you were talking to. You could just plug in all the names attending. the meeting into the tool, and it would create a slide asking the meeting attendees who the most popular person is on LinkedIn since the tool obviously had access to all meeting attendees’ LinkedIn information.

LinkedIn’s sales data—sometimes close to a petabyte or more—exists among internal databases, Google Analytics, Salesforce.com, and third party tools. Previously, one analyst on LinkedIn’s team serviced daily sales requests from over 500 salespeople, creating a reporting queue of up to 6 months.

In response, the business analytics team centralized this disparate data into Tableau Server to create a series of customer success dashboards. LinkedIn embeds Tableau Server into their internal analytics portal, nicknamed “Merlin.”

Today, thousands of sales people visit the portal on a weekly basis—equivalent to up to 90% of LinkedIn’s sales team—to track customer churn, risk indicators, and sales performance.

Source: Tableau

Janie still had to download additional usage data and do custom reports and PivotTables to get her clients the data they needed. She eventually learned SQL to further automate her data needs. Nonetheless, this solution in Tableau really helped salespeople get the slides they needed to tell data-driven stories and close deals.

Data visualization best practices

Through her training at LinkedIn, Janie learned all types of best practices for how to tell data-driven stories. One of the key questions she would ask herself is this: Can you explain the slide in plain English to someone who is not in that specific industry?

If you can’t, chances are the slide could be simplified and data can be removed. We talked about all types of best practices in this episode, but here were a few that stood out:

• Slide headlines should be in the same position on each slide so your audience isn’t scanning the slide for the headline and instead focuses on the body of the slide.
• Use colors and charts sparingly: you should have one specific bar, line, or color you want the audience to focus on to grasp the key takeaway from the slide
• 3-5 second rule: if you look at the slide for 3-5 seconds you should be able to understand the takeaway

The slides are not for you. They are for your audience.

In this following slide, the audience is drawn to one specific bar and color to understand the key takeaway of the slide:

Janie saw parallels between her experience at LinkedIn and her former journalist days. You’re tempted to add more data and visualizations to the slides, but you don’t want your audience’s attention to be distracted. You want that one key trend or number to be stamped into your audience’s head which is like writing a really catchy news headline.

Learning and teaching Google Sheets/Excel

According to Janie, 80% of a data analyst’s job is cleaning data despite all the expensive tools and AI that have been developed over the years. Even with the Merlin to at LinkedIn, analysts still had to use Excel. That’s why she had to learn how to automate as much as she could in Excel and SQL and then pass on these tools to incoming analysts.

They say the best developer is a lazy developer.

After LinkedIn, Janie started working for smaller companies such as nonprofits and would report directly to the CEO. A lot of them were in Google Sheets all day and couldn’t write formulas like VLOOKUP. They were doing things by hand across thousands of rows and manually changing the formatting with the paintbrush tool in Excel.

To teach these CEOs how to use Excel, she would first walk them through the formulas she was building and the final product in Excel. Then she revert all her changes and ask them to do the exact same thing and say they have to create the same output as what she showed them.

They don’t know what they don’t know.

Speaking of acquiring skills, Janie made an interesting point about how many people learned web programming skills back in the early 2000s. This was during the heyday of Myspace and Xanga. Myspace users were teaching themselves HTML, CSS, and Javascript just to do simple things with their Myspace pages. That same same need to learn how to edit a website is not as common now with platforms like Facebook.

People were learning these 6-figure skills just to get a unicorn to pop out from their Myspace profiles.

Audience development at The New York Daily News

Janie oversees many different assets at The New York Daily News including homepage, social media platforms, podcasts, breaking news emails, mobile alerts, and newsletters just to name a few.

Data is still an important part of what she does in her current role. Tools like Chartbeat and Tableau are used for reporting purposes. OneSignal is used for pushing mobile/web alerts. All the data generated from these platforms are pushed into Google Analytics 360 dashboards built by the national Tribune team.

Twice daily, Janie reports on the best “meta” headlines to NY Daily News journalists (these are the SEO titles from top performing articles). For her team, the One Metric that Matters (OMTM) is getting new subscribers. I think many teams call their OMTM their “north star metric” or something similar. In the world of SaaS, that might be MAUs or DAUs. Here is an example of a chart Janie might show her team during one of these meetings showing the performance of stories:

We talked about how Janie’s team helps journalists predict which stories will be “hits.” The New York Daily News’ biggest news source is still news about NYC. They don’t do feature stories on Broadway openings and restaurants anymore given the size of the team. The stats Janie presents is only one-half of what journalists rely on to figure out what stories and beats to pursue.

Ultimately, it’s an art and science to find a story to pitch the editors.

You can find Janie on Twitter at @janieho16.

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