Analytics increasingly faces a challenge in understanding audiences who jump from device to device and online to offline. These users are notoriously difficult to track and categorize, leading some marketers to a shift in thinking about measurement that acknowledges the imperfect reality of most datasets.
Driving Growth with Measurment in a Mobile World, created in partnership with Google, is based on a survey of over 500 enterprise brands.
To test its hypotheses and provide a point for comparison, the study sought to identify “leading” organizations with a successful approach to marketing measurement; companies with a combination of characteristics that include their use of business KPIs, advanced measurement (cross-device and/or online-offline) and experimentation.
Supporting the argument that these qualities contribute to success, leading companies outperform the industry in several ways. Most notably they are more than twice as likely to have significantly exceeded their top business goal in 2015 (42% vs. 19%).
1. Alignment of KPIs with business goals makes marketing more powerful
One of the central hypotheses of the study was that marketing achieves greater success when its measures and processes reflect the goals of the wider organization than when they’re focused solely on the metrics and concerns of marketing.
In the real world we need to look for those metrics that can make the leap between marketing and finance instead of trying to contend with every possible digital marketing statistic, most of which don’t resonate outside the team let alone outside of marketing.
Leading companies’ responses bear out this premise; 95% agree with the statement “to truly matter, marketing KPIs must be tied to broader business goals.”
One advantage of moving to a business focus is that it enables marketing to influence the broader organization more easily, whether through a Center of Excellence model or another learning and development mechanism.
This emphasis on business KPIs has several powerful benefits for marketing:
Drives digital evolution through opportunity instead of mandate.
Teams and individuals are far more motivated to change when they see the benefit than simply as a response to a strategic directive, which is often how organizations try to drive transformation.
Normalizes marketing across divisions and regions by focusing on universal goals.
Every part of an international company is, to varying degrees, an independent actor with unique issues, capabilities and opportunities. Getting them to play in concert is an eternal challenge, but it’s impossible when they use different measures.
Using a limited basket of metrics that are agreed upon by finance and marketing as representing the top business goals is one of the most effective paths to motivating and level-setting between regions.
Advances the strategic role of marketing.
Today’s marketing department is tasked with far more than awareness. It has to be inside the head of a new kind of mobile, social customer and represent their needs for a better experience across the organization.
It also has to adapt to media, channels and platforms that are changing at breakneck speed. Through it all, marketing is asked to contribute more to the bottom line, often with fewer resources.
Despite these rising demands, marketing doesn’t always have a seat at the table.
Perhaps the most important reason to use business goals to define marketing’s KPIs is to ensure that marketing is always speaking the same language as sales and finance.
Where to start: Identify the top three business goals set in 2017 strategy and meet with analytics leaders to argue for the one KPI that best fits with each one.
These “hero” metrics won’t stand alone, but they should be at the center of every measurement conversation.
2. Metrics don’t matter if they don’t affect decisions
It’s one thing to measure, it’s another to use that information. One surprise of the study was the large share of organizations that have one or more advanced measurement capabilities, but fail to use them in decision-making.
For example, 47% of mainstream organizations say they track cross-device behavior but that it doesn’t factor into decision-making.
That’s an equal share to those that do use their cross-device analysis in planning and strategy.
When data is collected but goes unused, there is often a lack of trust in its validity that might be due to the complexity of measurement (such as in the case of cross-device identification) or an inability to use that data in context.
One trait of elite marketers is the realization that there will be gaps in data, especially in emerging areas. They are comfortable making estimates to fill those gaps to move forward with their decision-making.
Where to start: Create a list of all of the available KPIs and measurement capabilities. This might range from simple email metrics through advanced attribution, depending on the organization.
Go through the list and consider whether each metric is unused, used only in reporting or used for planning. Any gaps in the third column indicate a gap in trust, a missed opportunity or a meaningless measure.
3. Perfection isn’t the goal
Between the enthusiasm of technology vendors and the genuine revolution in data driven business, it’s not surprising that marketing has fallen into the trap of pursuing perfection.
Every cycle brings new tools and models and filters, each suggesting a better way of collecting, managing and interpreting data.
Our data describes our customers and customers are people – chaotic, fickle, emotional, mobile people. Even when we fix every technical glitch and connect every database, data will never be perfect.
Some marketers are building their measurement and analytics practices with this in mind. It’s an attitude and approach as much as it is a selection of technologies or models.
It’s about approaching problems in a way that is nimble and effective with the knowledge that there will be gaps and mistakes and odd shapes that won’t fit into square holes.
The most effective analytics organizations are also those that recognize the reality is imperfection.
As we see in the chart above, leading measurement practices are three times more likely than the mainstream to strongly agree that there will always be gaps in the data connecting people, channels and devices (39% vs. 13%).
Where to start: Identify those areas where data issues arise most frequently and explore processes, practices and technologies to address them.
For example, build estimate models based on existing data, look for reliable industry benchmarks or look at tools that analyze and add in missing data.
Of note, elite organizations are more likely to develop specific models and employ technology to fill these gaps than the mainstream, which tends to rely on historical precedents.
4. Experimentation isn’t just optimization
Optimization is an important advantage of digital marketing. It’s fast, easy and makes an incremental, consistent positive difference.
But optimization isn’t the most powerful business use of experimentation. At its best, the scientific method can be used to identify most valuable customers, explore major trends and validate strategic direction.
Leading organizations are more than twice as likely to conduct strategic experiments than the mainstream, and by doing so they overcome some of the issues that often arise in large organizations trying to evolve.
Typically, any major shift in spending or direction will create political divides as gut instinct and inertia work against change. Experimentation can be an antidote to this kind of resistance, giving a black and white answer to key questions.
Where to start: Identify the intersections between business goals and customer behavior and use these lessons to prioritize experiments.
Where are you losing to competitors? What’s important to customers but under-represented in your experience?
Whatever the experiment, make sure that it’s testing a specific hypothesis that’s unambiguous, that the test will be able provide meaningful data and that the test results focus primarily on overall business impact, not simply efficiencies or optimization.
Comments