5 Common Pitfalls and Best-Practices of Analyzing Marketing and Advertising Performance

To improve Advertising Performance, optimize spend and improve the customer experience, marketers need to incorporate data and analytics into every step of their marketing and advertising process. And thanks to the ever-changing types, platforms, and technologies of digital devices, marketers now have access to more audience and performance data than ever before, enabling them to make smarter decisions that deliver meaningful business results.

While more data is a “check” in the plus column, it can present challenges in optimizing marketing and advertising performance: to make the decision, the data must be consolidated, processed, and interpreted correctly; errors are common in this process.

The good news is that these mistakes can be avoided.

Here are five common mistakes when measuring marketing and media performance, as well as best practices for avoiding them.

Pitfall 1: Failure to set clear operational objectives and key performance indicators (KPIs)

Before embarking on any marketing or advertising campaign, it is essential to determine how successful it will be. For some brands, the goal may be to increase sales or improve media efficiency. For others, it can increase engagement with new or existing customers.

Once global goals are set, the right KPIs need to be identified so that progress can be measured and quantified. Defining macro and micro KPIs can be useful, depending on the size of your marketing budget and the sophistication of your media. For example, a macro KPI might focus on the overall performance of your overall marketing and advertising ecosystem, while a micro KPI might focus on the tactical performance of a particular channel or tactic.

Having a structured structure, with clearly defined objectives and associated KPIs, is an important first step. This will set the stage for further measurement efforts and allow you to improve what really matters to the business.

Pitfall 2: Compilation of references without taking into account internal and external factors

An important part of defining KPIs has to do with existing benchmarks. Whether these metrics are derived from your data, competitor data, or vendor data, they should be put into context to provide the most informed metrics to measure KPIs.

For example, analyzing internal historical data to determine benchmarks is common practice, but organizations are constantly changing and often experience cyclical fluctuations. Marketing performance often changes based on internal factors such as short-term promotions and media attacks, as well as external factors such as seasonality, competitive activity, economic factors, and more. To ensure an accurate comparison of performance results, all these variables must be taken into account when defining benchmarks.

Pitfall 3: Waiting for Perfection

Marketers are challenged to try to predict human emotional responses to marketing and Advertising Performance stimuli and then accurately measure which channels and tactics are most effective in generating any desired outcomes.

While these challenges can be analyzed in many ways, every minute that goes by without optimization is a lost opportunity.

All marketers dream of perfect datasets so they can accurately quantify performance by target group and quickly optimize from there. But in reality, perfect datasets are rare. Speed   of measurement and decision-making is essential to sending the right message to the right person at the right place and time, and the risk of waiting too long to optimize action on available data outweighs the risk.

While risk reduction is important, it comes with the understanding that there is no exact predictive science of human behavior and you may be forced to optimize quickly, even if the data is just indicative.

Pitfall 4: Believing Correlation Implies Causation

Marketers often use correlation to understand how their marketing and advertising efforts contribute to specific leads, conversions, sales, or other business outcomes. However, the correlation does not imply causality and can therefore induce marketers to determine what actually produces results.

For example, a retailer might notice an increase in sales for a product that appears to be the result of a new campaign. It may be human nature to want to make a connection, but that doesn’t mean that some other unrelated external factor hasn’t affected product sales.

Only this holistic view can isolate correlation causality and discover the true conversion factors and other desired business outcomes.

Critical thinking and robust marketing solutions can explain the subtle but important distinction between correlation and causality.

Pitfall 5: I think multitouch is just a direct response (DR) tool

Until recently, multitouch mapping was considered a direct response, allowing marketers to directly associate their digital efforts with leads, conversions, revenue, ROI, and other DR metrics. Marketers in industries such as pharmaceuticals and consumer packaged goods, who may not have “difficult” instant-response conversions, still need a holistic view of their ecosystem performance to reach and engage their target audience.

Today, advanced marketing and media attribution techniques are available that span multiple brand engagement activities into a single KPI metric for simplified audience measurement and optimization.

Brand marketers benefit from a holistic view of the true impact of their marketing and media on brand engagement, as well as the ability to effectively optimize touchpoint budgets and deliver coordinated consumer experiences that drive incremental growth of the brand. For companies that spend large budgets on branding efforts, this means completely new levels of responsibility for using their budget and for the business results they deliver.