Now more than ever, data is the key to monitoring, identifying, and making smart decisions for your business. No matter your tech stack, if your company is like most, your systems vary from team to team, sending data back and forth through everything from email attachments to spreadsheets and CSVs. We’ve heard you, and our team has been working on ways to make it easier to share your data across the systems and teams in your company who need this important info to do their jobs. One of the biggest things we’ve heard from customers is something we’re excited to launch today, the DataTrue Reporting API. The Reporting API allows a more in-depth layer of specifications: Dimensions which are attributes of the test such as suite, test name, browser, start time and othersMetrics which are the quantitative values that can be summarized based on the dimensions provided such as:Tests total or passed or failedTag Validations total or passed or failedFilters: drill down on the data you need, and focus on key points to find the data you need With this new Reporting API, you’ll be able to essentially retrieve all summary data that is available in the test summary graphs...
These are unprecedented times we are all living in, how we respond, adapt and change can really impact our future. The COVID-19 Pandemic is on the front of everyone’s mind right now, and besides our health care professionals and essential workers who are fighting this head on - we salute them! - many companies are concerned about the impacts of the virus on their business. What Impact are Businesses Seeing? The global increase in online traffic has surged recently as businesses quickly move to run their interactions online, which also means that more personal identifiable information or PII is being passed through websites at a higher than average rate. People turn to online shopping to curb their anxieties over the COVID-19 crisis, or to source household products online to avoid the physical retail stores. Companies who sell products online that are most in demand, such as household items or canned food and dried goods, are experiencing exponential growth How Can We Be Responsible with Data? The importance of having a tag audit and data governance automated solution in place to manage the increase of online traffic that many e-commerce companies are experiencing due to COVID-19. Implementing a software solution like...
Deliveries...opens...clicks...conversions…if you work in email marketing, you’ve probably been muttering those four words in your sleep. And with good reason — tried-and-true funnel metrics are the backbone of email performance measurement, and you could do much worse than to focus on them. However, there are also big benefits to going beyond the basics. Mixing up your metrics can help you see opportunities you might otherwise miss, and can ensure that you’re taking a well-rounded approach to improving your overall email ROI. Bringing in new metrics can also provide a useful shift in perspective when you start to see your basic metrics plateau, which happens to even the best email marketers at some point. If you’re ready to measure something new, here are four ideas to help you get started. e 1. List growth rate Email performance metrics are often expressed in percentages, but when it comes to determining ROI, it’s the absolute numbers that matter. And while absolute ROI is certainly influenced by delivery, open, clickthrough, and conversion rates, it’s also heavily affected by another metric — the size of your subscriber list. We all know that unsubscribes happen, so it’s normal to have some attrition in your list over time....
There are a number of big advantages to implementing a data layer, including better data consistency, improved reliability, and increased flexibility when it comes to sending data to different analytics vendors. However, there is one downside — a data layer is yet another possible failure point in your analytics pipeline, which means that you need to test regularly to ensure that it’s collecting and sending complete, accurate data. In a previous blog post, we talked about how to validate the data that’s passed to your tag manager from your data layer. But what about verifying that the data layer is firing the correct tags in response to user actions? For example, if a customer adds an item to their cart, you want your data layer to record that event (along with relevant details such as the item name, price, quantity, etc.) and fire a tag to pass the new information to your analytics tools. If the tag doesn’t fire, or fires incorrectly, you could be missing critical data. You may be able to trigger certain data layer updates by visiting your site and manually stepping through the relevant actions, or (more efficiently) by running a Simulation Test, but there are...
What is a customer journey? A customer journey, or user journey, is a series of steps that a customer performs to accomplish a goal. That goal might translate to a positive business outcome, such as a completed purchase, or it might be negative, such as cart abandonment or a cancelled subscription — but regardless of the “destination”, each step serves as a checkpoint that marks the customer’s progress and asks them to choose whether they’ll continue on that particular journey. Although customer journeys certainly play out in the brick-and-mortar world, too, the concept is most useful in a digital context, since digital interactions are easier to monitor. It would be a little odd to have someone following customers around a retail store and taking notes whenever they glanced at an item, picked it up, or placed it in their cart. With ecommerce customers, similar data on the product consideration process can be collected easily and non-invasively. What is customer journey analytics? “Customer journey analytics” refers to the technology and methods that help us identify, track, understand, and influence customer journeys. By collecting and analyzing data on how customers move through various checkpoints, we can identify opportunities to shape their journeys,...
If you’re reading this, you probably don’t need to be convinced that manual QA is a real pain — it’s slow, it’s tedious, and problems usually slip through the cracks despite your best efforts. Plus, even if you catch and fix every single mistake today, chances are good that tomorrow’s first code push will render all your hard work irrelevant. You might also know, or at least sense, that manual QA is a huge time and money sink. Studies show that knowledge workers waste a whopping 50 percent of their time “hunting for data, identifying and correcting errors, and seeking confirmatory sources for data they do not trust”. If we zero in on data scientists, the picture gets even bleaker — sixty percent of data scientists spend “most of their time” cleaning and labeling data, and with the majority of those folks earning six-figure salaries, that makes for a pretty big QA bill. Unfortunately, though, skimping on data QA is even more expensive. Organizations included in one Gartner study estimated that, on average, poor data quality costs them about $15 million per year. Eighty-four percent of CEOs also say that they’re “concerned about the quality of the data they’re basing...
Our development team kicked off 2020 with a whirlwind round of feature updates and enhancements, and the results are now live for all DataTrue customers! Here’s a summary of the changes we released last weekend: It’s now possible to view batched Google App+Web tags as individual requests to simplify validation. Sensitive data detection is now supported for mobile app tests; we’ve also added options to automatically fail tests when sensitive data is detected, and to exclude non-sensitive persona items from detection. Finally, we’ve updated our email reports to provide more information about sensitive data detection. Our data governance dashboard, currently in beta, now features a new Reporting API to return test run statistics, including tag depth summaries for coverage tests. We’ve also added our DataStudio Connector to retrieve test run statistics data from DataTrue. You can now inspect browser console logs to aid in debugging issues; Chrome users can also view warning logs to check for upcoming issues (e.g., changes to cookie handling) that may impact tracking solutions. The DataTrue Chrome Test Builder extension now supports validation of custom tags and cookies from local test runs, improved step naming for recording Select List steps, and improved styling for long step...
Mishandling customer data has never been good for business, and it became an even more serious issue when the EU’s General Data Protection Regulation (GDPR) went into effect in May 2018. Companies that fail to comply with GDPR requirements, which include strictly limiting access to customers’ Personally Identifiable Information (PII), face fines of up to 4 percent of their total annual global turnover — a provision that’s already resulted in hundreds of millions in penalties for some major global firms. Despite the high potential costs, however, only 28 percent of companies said they were fully compliant with the GDPR as of September 2019. Many businesses have invested heavily in technology designed to automate consent tracking (for data collection and email marketing) and customer-initiated data access and redaction — but data leakage is still a big problem, and human error is a leading cause. According to the UK’s Information Commissioner’s Office (ICO), human error was responsible for 88 percent of data breaches in the UK during the past two years, and a 2018 report from data security firm Netwrix concluded that “insiders who make mistakes are more dangerous than hackers”. What do these errors look like? And how do you know...
The data layer is generally regarded as the best practice for structuring how data is transferred from your website to your tag manager, and ultimately your tags. Adding a data layer to your analytics implementation introduces a new component that can be tested, enabling you to ensure your data collection systems are running reliably, and collecting accurate data. The problem with the data layer The data layer introduces a more structured way of passing data from your application to your analytics and marketing platforms. For those people concerned with data quality, the data layer provides another test point to validate the integrity and quality of the data being collected. The downside is the extra effort required to test. The best way to address this problem is via automated testing. Automated testing allows you to quality assure your data with minimal effort freeing you up to focus on data analysis. Automated data layer testing Automated data testing is regarded as the best practice approach to achieve good data quality and governance. DataTrue’s new Data Layer Validation feature enables you to test the data passed via your data layer as well as your tags. The following screenshots demonstrate how this feature alerts...
DataTrue is a proud sponsor of Adobe Summit, Las Vegas for the fourth time! We will join thousands of marketing professionals March 24–28 at The Venetian and The Palazzo, Las Vegas. Adobe Summit is one of our favourite events of the year, a fantastic opportunity to surround ourselves with interesting people, great ideas and take a deep dive into the future of experience marketing. Save $400 with promo code S19SCDP. Visit DataTrue in the showcase area – kiosk 771-J , enter to win a Nintendo Switch We will be showcasing our powerful validation software, DataTrue, and demonstrating how it can help business leaders guarantee that their data is high-quality, accurate and useful. Our passion is helping enterprises to have confidence in their data by providing them with a tool that can audit and monitor their website tracking implementation and ensure the quality of the information they collect. You also have the chance to win a Nintendo Switch with Gray Joy Con™ worth over USD $299! All you have to do is visit the booth, scan your conference badge or throw your business card into the designated entry box. Can't make Adobe Summit? Don’t stress! If you are interested in tracking...
It’s all over the news these days - since last September, when the British Airways cyber theft first made the news, this week the fines were announced: a record $328 million fine for British Airways, the highest penalty to date under current data protection rules. For businesses that deal with data and security, this is a serious concern, and working out ways to keep their customers’ data safe and prevent these types of attacks. Read on for more details on the Magecart cyber attacks, and how DataTrue’s solution provides tools to prevent this kind of attack on organizations. (more…)
As a Showcase sponsor at Adobe Summit 2018 there has been plenty to keep us busy in recent weeks preparing for the Summit. As we have now packed our bags and are on our way, I have the time to look forward to the Summit presentations, inspiration and learning opportunities. Here’s a summary of the top three sessions that the DataTrue team is looking forward to at Adobe Summit 2018. (more…)
DataTrue is excited to be returning for a third year to the 2018 Adobe Summit, the premier event for digital marketing and analytics professionals. DataTrue is a Showcase sponsor for the Summit held in Las Vegas from 26-29 March 2018. (more…)
If you’re familiar with AdWords and you’re looking to learn some techniques that can help you to more fully analyze your PPC data, this is the guide for you! (more…)
Hi, in this blog post we are going to talk about some of the most common mistakes that can lead to bad data or a poor analysis of that data. We are also going to recommend steps you can take to ensure better data integrity. (more…)
