After receiving a $500k budget increase, someone in the C-suite must decide where to allocate these funds: remarketing budget, R&D, events, website redesign, etc.
What should they do? Do they need more information to decide? Even with new information, will that clarify the percentage allocation of funds?
As consumer needs and technology become increasingly complex, so too do the decisions.
Modeling is critical for complex decision-making. Relying on intuition alone can set you up for failure.
Are you a CMO who thinks
accurate attribution is a pipe dream? Or a customer experience director who has to hack together data to create something resembling a customer journey?
In digital analytics, it’s all about asking the right questions.
Sure, in the right context, you can probably get by doing what Avinash Kaushik refers to as “data puking,” but you won’t excel as an analyst or marketer.
In addition, you’ll consistently come up short on bringing true business value to your company.
For a web analytics analyst or a data-driven marketer, these are words to live by: “Without data, you’re just another person with an opinion.”
Optimization isn’t about educated guesses and hunches, no matter how many years you’ve been in the industry. It’s about doing the research,
asking the right questions, digging for clues in problem areas, paying attention to the signs when they appear, and running smart A/B tests.
Web analytics analysis is a big part of that. It helps separate the optimizers from just another person with an opinion.
Subscriptions are an increasingly common way to buy products online, whether consumables like coffee and energy supplements, or personalized lifestyle boxes and fashion.
Traffic attribution identifies which sources drive visitors to a web property. And it’s impossible to credit a
conversion to the correct source without first knowing how a visitor got to a website.
In other words, the foundation of
conversion attribution is traffic attribution. Simple as it may sound, attributing a session to its traffic source can be tricky, even impossible.
There are hundreds of services for site tracking, advertising, customization, and, in general, souping up your ability to measure, reach, and convert your visitors.
Google Analytics, AdRoll, Adobe Analytics, etc.
How do you coordinate the
analytics setup of a web shop that sells their products all over the world—if you have to handle 10+ languages and currencies in over 80 countries?
Kaggle, the Google-acquired data science platform, started as a virtual meeting point for machine-learning geeks to compete on predictive accuracy scores.
It evolved into a Swiss Army knife for data science and analytics—one that can help data professionals, including data-driven marketers, elevate their analytics game.
According to a study, 71% of website visitors complete their purchases offline.
Online, we have plenty of ways to track visitor behavior—cookies,
heat maps, click tracking, retargeting, etc., but as soon as that person picks up the phone, we’re lost. We don’t have to be.