The Stytch Blog

When and How to Use Column Charts and Bar Charts (Stacked and Unstacked)

If pie charts are the placebos of the data visualization world, column charts and bar charts might just be Advil. When it comes to simple, effective data visualizations, they’re tried and true.

We’ve all been exposed to column and bar charts. There’s a graph, with an x and a y axis, just like on your old TI-84 calculator. On that graph there are at least two bars which, at a glance, immediately show you the relative positioning of data — it really is that simple.

These chart types are the bread and butter of rankings or comparisons, whether you’re looking to share election polling data, or need to visualize sales numbers over time. Read More…

By on November 25, 2016

How To Achieve Continuous Product Performance Analysis using JMeter and Stytch

Over my many years working in performance testing and performance engineering, I’ve had the chance to use a broad range of load testing tools. Whether it’s Load Runner, Neoload, JMeter, or even good old Microsoft Homer, they all have one thing in common: they’re great at generating load but mediocre at results reporting and build-over-build product performance analysis.

Sure, you can get some summary statistics on response times and throughput. You may even be able to get graphs that span the duration of a single test. If you’re lucky, the load tool may allow you to compare two performance reports to find regressions. But when it comes to doing advanced reporting and analysis, such as graphing performance results across dozens of iterative builds or drilling down to the performance of every individual HTTP request, these tools fall flat. As a result, many software performance engineers (including myself) find themselves stuck spending hours in Excel trying to summarize data for management reports or find themselves faced with the daunting task of writing a custom reporting solution. Read More…

By on August 18, 2016

The Pros and Cons of Pie Charts (Mostly The Cons Though)

This is the first post in a multi-part series on data visualizations.

Okay, so just between us, I’m not a great fan of pie charts. I almost never use them. There are just so many better ways to display data and communicate information that I typically advise customers against them. That said, people love their pie charts, so I wanted to share a few thoughts as to “the good, the bad and the ugly” of the pie. Read More…

By on August 3, 2016

Marketing Performance Measurement: A Maturity Model

I was recently invited to speak at a digital marketing and analytics event in Toronto. The agenda included an exploration of the current digital marketing landscape, best practices for using data and analytics to drive business growth, and a workshop component to assess how well these best practices were being followed in each of the attendees’ companies. The end goal was to provide practical advice that each person could implement in their business to drive a more effective digital marketing strategy.

The room was packed with Marketing VPs, Directors, Heads of Sales and a handful of Business Analysts, from some of Canada’s biggest businesses. I’ll be the first to admit that as a CEO, I’m not an in-the-trenches digital marketing expert. Fortunately for everyone, my two co-speakers were. My purpose for being at the event was to share my experiences, as well as our customers’ experiences, in applying data and analytics to measure and improve marketing performance.

My favorite part of the event came early on. Having done introductions and some initial scene-setting we asked everyone in the room to honestly evaluate how far along they were on their digital marketing journey. We used what we call a “digital marketing maturity matrix” to help attendees identify their organization’s level of maturity in four specific areas of the marketing cycle; targeting prospects, capturing leads, nurturing leads, and measuring performance. Target, Capture, Nurture, Measure. Read More…

By on July 22, 2016

The Amazing Stytch Race

The rain stopped, the clouds parted and the sun came out for Stytch’s first ever “Amazing Race”!

Every year, we take a few hours away from our desks to take part in some well deserved team fun. With so much to celebrate this year, I decided to plan something a little different (insert evil laugh here) for the team. Something active, a little bit wacky, and with just the right amount of challenge. After a lot of head-scratching, I settled on creating a Stytch-ified version of the popular TV reality show Amazing Race. Part-race and part-scavenger-hunt, seven teams would vie to complete thirty-two challenges within 90 minutes, amid the hustle and bustle of downtown Vancouver.

The teams were randomly selected and given a week to strategize and choose branding. The final team names hinted at the intensity, hijinks, ambition and spirit that would be on display: Rain City Race Committee, Team Victory, DreamKillers, Team Sparkle Pants, Team Ogopogo, Zero Downtime and At Least We Wore Shirts (spot the over-achievers).

The Race was on. Read More…

By on July 15, 2016

5 of the Worst Spreadsheet Blunders

When it comes to complex data blending, spreadsheets should be handled with care. Errors can easily leak out from spreadsheets, contaminating reports and causing mistakes that can cost companies millions of dollars. A study by financial modeling company F1F9 a few years back found that close to 90 percent of spreadsheet documents contain errors. In fact, the report found that spreadsheets contain errors in one percent or more of all formula cells: in large spreadsheets with thousands of formulas, there will be dozens of undetected errors.

Errors like this have led to some catastrophic spreadsheet slip-ups. Here’s a look at some of the worst examples of spreadsheets gone wrong—cautionary tales for anyone relying solely on spreadsheets for business insight. Read More…

By on June 13, 2016

Garbage data in your CRM? We know the perfect solution

Clean up customer and vendor data in a single click using Dun & Bradstreet’s Data Management app for NetSuite.

After several years of using any business system, bad data creeps in. At first, it’s manageable. As it grows, it gets ugly. Administrators develop coping mechanisms to deal with the garbage information. They add new fields so that they can filter reports. Old reports need to be rewritten. As the issue grows larger, companies form teams to clean up data.

But what if you could clean any record with a single click? That’s exactly what Dun & Bradstreet demonstrated at NetSuite’s SuiteWorld 2016 conference last month. Read More…

By on June 3, 2016

This is Stytch

Today we are launching a new kind of analytics platform. One that combines powerful, self-service data preparation tools with data discovery for everyone in your business. One that gives you a single, seamless user experience from initial data connection to collaborative dashboards. One that connects you to the world’s largest business database from Dun & Bradstreet directly from your analytics environment.

It’s called Stytch, and I’d like to tell you about how we got here.

In the Beginning…

“It’s the key to connecting everything together. There’s nothing else like it!”

That was Graham Ross, our VP of Product Management, effusing about the D-U-N-S number roughly a year ago.

If you haven’t heard of the D-U-N-S number, let me explain. D-U-N-S stands for Data Universal Numbering System. It’s the system by which Dun & Bradstreet assigns a unique nine-digit identification number to businesses around the world in order to establish a business credit file. Think of it like a social security number for businesses; used to uniquely identify and maintain firmographic information on more than 250 million global companies. If you’re a data geek like Graham and the rest of my team, the D-U-N-S number is pretty cool. Read More…

By on April 19, 2016

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