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Let’s be honest, most companies don’t really think about nomenclature when it comes to setting up their tags, goals or A/B testing experiments. And that creates a horrible mess that will steal your teams valuable time and makes sure no-one really knows what’s going on.

At Reflective Data, when we start working with a new client, we always start by figuring out what their current system consists of — and in many cases, it’s a real headache. Not to mention, when we ask the client about a specific tag or goal that they set up 6 months ago, they don’t remember anything — and the name they chose isn’t helping much either.

I guess it’s more or less true with every industry, especially with those related to the internet. There are two kinds of service providers, those who promise the world but hardly deliver anything useful, and those who actually put their hearts in and do whatever it takes to deliver something the client really needs.

While today I’m focusing on digital analytics implementations, perhaps most of you can share the experiences from general web development. I’ve been a part of over 50 web projects, from zero to something and here’s something I’ve seen way too often.

Data visualization allows marketers to physically see and communicate with their target audience. Marketers typically have all the same information via text, but turning it into a visual aid can allow companies to make business decisions much faster. Simple aids like pie charts or line graphs can take thousands of pieces of information and compress them all down into something legible.

Creating these visuals on your own can take more time than reading through the slog of information. The good news is that technology has created data visualization tools for marketers to easily pour their data into and create the visuals for them.

If you run a business, then you are well aware of the fact that there’s nothing more important to your success than your data. It’s data that allows you to make improved business decisions while giving you insight about your customer’s behaviors. It’s important to understand that all data is important and that it needs to be properly tracked, stored, and managed. This includes everything from security logs (via a log aggregation tool) and sales to the success of your marketing campaigns and more.

E-commerce options heavily drive the spending patterns of modern consumers. Instead of getting into their cars and driving to local stores, people can log onto websites and purchase what they need in a few clicks. Stores like Amazon also offer same-day deliveries, meaning buying things online doesn’t necessarily involve a long wait.

But despite the conveniences it offers, online shopping does have shortcomings. For example, people can’t smell a bottle of lotion and dab some on the top of their hand to see how well it absorbs into the skin. They also can’t touch the fabric of clothing or a sheet set to determine how durable it feels.

Running a basic A/B test is easy, but you know what else is easy? – Misinterpreting the results.

In this post, we are covering the common statistics terminology and models, and taking a closer look at the different methods of calculating A/B testing related metrics.

Every day, the digital world gets more and more dangerous which, in turn, means sensitive data stored on open networks becomes more vulnerable. We are all at risk, and so is our data. Everything from social security numbers to addresses and credit card details are potential targets.

Using the power of technology is a must for any business looking to compete in today’s world. Many business owners understand how important technology is, but are unsure about how to implement the use of things like artificial and business intelligence into their daily operation. A recent study shows that a whopping 27 percent of small businesses in the American don’t even have professional IT support.

In determining your marketing strategy, segmentation is critical to success — it’s the foundation on which your advertising rests. When building that foundation, you have time segmentation, media segmentation, price segmentation and more, but in the interest of brevity, we’ll focus on the three most popular forms: psychographic, demographic and geographic segmentation.

Depending on whether you are using the free or 360 version of Google Analytics you get 20 or 200 custom dimensions and metrics to work with.

When used correctly, these custom definitions can be one of the most useful custom features in Google Analytics. They allow you to tailor your analytics to meet your needs and to match your KPI-s.

One of the most common problems related to custom definitions has been that people don’t know what exactly are the dimensions and metrics they should be tracking.