To improve performance, optimize spend, and enhance the consumer experience, marketers must inject data and analytics into every phase of their marketing and advertising process. And thanks to ever-evolving digital device types, platforms, and technologies, marketers now have access to more audience and performance data than ever before, so they can make smarter decisions that drive meaningful business results.
Although more data is certainly a “check” in the plus column, it can pose challenges for optimizing marketing and advertising performance: To guide decision-making, the data must be consolidated, processed, and interpreted correctly; in that process, mistakes are common.
The good news is that those mistakes can be avoided.
Here are five common pitfalls when measuring marketing and media performance, along with best-practices for how to avoid those pitfalls.
Pitfall 1: Not Defining Clear Business Goals and Key Performance Indicators (KPIs)
Before launching a marketing or advertising campaign, it’s essential to define what success will look like. For some brands, that goal may be to increase sales or improve media efficiency. For others, it may be to increase engagement among new or existing customers.
Once the overarching goals have been set, the right KPIs must be identified so that progress can be measured and quantified. It can be helpful to define macro and micro KPIs, depending on the size of your marketing budget and sophistication of your media. For instance, a macro KPI may focus on the combined performance of your marketing and advertising ecosystem overall, whereas a micro KPI may focus on the tactical performance of a particular channel or tactic.
Having a structured framework, with clearly defined goals and corresponding KPIs, is a vital first step. It will set the tone for subsequent measurement efforts, and enable you to hone what’s truly important to the business.
Pitfall 2: Establishing Benchmarks Without Considering Internal and External Factors
A key component of setting KPIs has to do with existing benchmarks. Whether those benchmarks are derived from your own data, competitor data, or vendor data, they must be contextualized if they are to produce the most informed benchmarks for KPI measurement.
For instance, analyzing internal historical data to establish benchmarks is a common practice, but organizations are constantly changing and often have cyclical fluctuations. Marketing performance will shift regularly based on internal factors, such as short-term promotions and media blitzes, as well as outside factors, such as seasonality, competitive activities, economic factors, and more. To ensure an apples-to-apples comparison of performance results, all of those variables must be taken into account when determining benchmarks.
Pitfall 3: Expecting Perfection
Marketers are challenged with trying to predict human emotional responses to marketing and advertising stimuli, and then accurately measuring which channels and tactics were most effective in driving each desired outcome.
Although those challenges can be dissected in a variety of ways, each minute that goes by without optimizing is a lost opportunity.
Marketers all dream of having perfect data sets so that they can accurately quantify performance by audience segment, and quickly optimize from there. But, in reality, perfect data sets are rare. Velocity of measurement and decision-making are critical for delivering the right message to the right person at the right place and time, and the risk of waiting too long to optimize often outweighs acting on the data that’s available.
Although mitigating risk is important, it comes with an understanding that there is no exact predictive science of human behavior, and you may be forced to optimize quickly, even if the data is only directional.
Pitfall 4: Believing Correlation Implies Causation
All too often, marketers use correlation to understand how their marketing and advertising efforts contribute to leads, conversions, sales, or other specific business outcomes. However, correlation does not mean causation, and so it can lead marketers astray when they’re determining what’s actually driving results.
For example, a retailer may see an uptick in sales of a product that is seemingly the result of a recently launched remarketing campaign. It may be human nature to want to draw a connection, but doesn’t mean that another, unrelated external factor didn’t also influence product sales.
Marketers can avoid confusing correlation and causation by considering all touchpoints customers were exposed to on their journey to conversion. Only such a holistic view can isolate causation from correlation and uncover the true drivers of conversions and other desired business outcomes.
Critical thinking and robust marketing measurement solutions can account for the subtle, yet important, distinction between correlation and causation.
Pitfall 5: Thinking That Multi-Touch Attribution Is Only a Direct Response (DR) Tool
Until recently, multi-touch attribution has been perceived as strictly a direct response exercise, enabling marketers to tie their digital efforts directly to leads, conversions, revenue, ROI, and other DR metrics. Yet marketers in sectors such as pharmaceuticals and consumer packaged goods, who may not have “hard” direct response conversions, still need a holistic view of their ecosystem performance in reaching and engaging target audiences.
Today, sophisticated media and marketing attribution and modeling technologies are available that incorporate multiple brand engagement activities into a single KPI metric for streamlined measurement and optimization by audience segment.
Brand marketers benefit from a holistic view of their marketing and media’s true impact on brand engagement, as well as the ability to effectively optimize budgets across touchpoints and deliver coordinated consumer experiences that drive incremental brand lift. For companies that dedicate big budgets to branding efforts, this means entirely new levels of accountability in how their budget is spent—and the business results they deliver.