Designer Cloud for Marketing Analytics: Eliminating Ad Fraud

Technology   |   Mark Sarbiewski   |   Jun 18, 2020

This is the fourth post in an ongoing series about how marketers are leveraging Designer Cloud. It follows previous posts on marketing data onboarding, marketing analytics, and building a 360º view of the customer experience.

What is marketing analytics‘ opportunity and challenge in the modern business landscape? Some marketers might say that it’s digital ads. Digital ads present an opportunity for marketers to reach their audiences and communicate messages. But these same ads run the risk of digital ad fraud that can lead to a loss of valuable resources. This challenge can harm a company’s marketing analytics and the future of the ad industry. That’s not to say that marketers should cut back on digital ads though. 

Digital ad spend is often a sizable chunk of any marketing budget. This year, marketers are expected to allocate $97 billion for digital ads, including paid search, video, display ads and social media ads (with a heavy slant toward mobile), which is a 14% increase from 2017. The upswing in this marketing tactic makes sense. Despite ongoing debate over the effectiveness of digital ads, they remain a surefire way to meet consumers where they are: online, and usually by way of mobile devices.

The rise of digital ad fraud

But there’s another number around digital ads and marketing analytics: $19 billion, which is the amount that marketers are expected to lose to ad fraud this year. Ad fraud is rampant across the board, and occurs under a number of scenarios. Digital ads may not be served up to the right customer demographics, which means they generate invalid traffic from the wrong views and clicks. Or, publishers can register fraudulent traffic when bots click or view digital advertisements. In either case, marketers end up paying for ads that quite simply are a waste of money. This dilemma wastes money and valuable marketing analytics resources. 

Attempts to counteract fraud are notoriously difficult, hence why digital ad fraud is a large challenge in marketing analytics. Identifying the right customer demographics requires segmenting huge volumes of customer data. But this data isn’t always accessible, nor easy to prepare or analyze. Similarly, filtering out traffic generated from bots isn’t always straightforward, either. For example, Facebook made headlines in 2016 for removing viewers that watched ads hosted on its platform for less than three seconds, likely in an attempt to rule out accidental or fraudulent viewers. The decision backfired. It severely skewed the average viewing time and misled consumers who weren’t aware that this meaningful subset of data had been removed. Facebook promised to better identify what constitutes “incorrect” metrics, but the difficulty in parsing out fraudulent data remained.

Given that the investment in digital ads isn’t waning, marketers need better technology to help identify target customer demographics and cull through bot-generated traffic. At Alteryx, we’re seeing companies leverage our data preparation platform as a first, critical step to conducting marketing analytics.

Designer Cloud for combatting invalid ad traffic with marketing analytics

Some organizations use marketing analytics software to begin combatting ad fraud and other industry challenges. But marketing analytics software falls short because it’s limited in scope. The key to begin eliminating ad fraud is to focus on targeting and using databases to create nuanced segments of an audience. Where marketing analytics software falls short, Trifacta rises to the challenge.  

Understanding the demographics of customers is key to better targeted (and more effective) ads as well as better marketing analytics. In the pursuit of better understanding the behavior and demographic profiles of its customers, The Royal Bank of Scotland leveraged Designer Cloud (formerly Trifacta) to build more nuanced segments of their customer base. The company was able to prepare huge volumes of customer data across many different databases, and join customer activity with a specific customer ID. Better yet, this work was done by marketing analysts, not data scientists, which allowed them to more appropriately group customer identifiers based upon the questions they needed to answer. The Royal Bank of Scotland is leveraging its enhanced understanding of customers to drive many marketing activities across the bank—product development and customer service training, to name a few—but it can also inform their messaging and digital ad targets. When marketing analytics is combined with databases, marketers are able to combat invalid ad traffic and utilize data toward a more refined brand and improved sales.

Designer Cloud for ad fraud detection and marketing analytics

Designer Cloud also aids in identifying data quality issues related to fraudulent clicks. With its visual interface, it’s easy to spot anomalies, such as spikes in traffic, that signal a bot may have been at work. Marketers can easily wade through data that is meaningful versus poor quality data that muddies marketing analytics insights. It’s also an opportunity to visually address fraud with media suppliers and save the organization millions in wasted marketing budget.

To get a sense for the other features that make Designer Cloud a great fit for cleaning marketing data to combat ad fraud, watch our demo focused on marketing analytics. After watching, we welcome you to try out the technology yourself—sign up for the Designer Cloud 30-day trial.

Finally, to learn more about how other companies are leveraging Designer Cloud for marketing analytics, watch the video below on our customer Malwarebytes: