In today’s marketing landscape, campaigns being implemented are only as good as the data we utilize to justify them. Marketers are privy to an exhaustive amount of data – some that is worthwhile and some that is window dressing used to sell a story, rather than affect the bottom line.

I was featured in a recent article by eMarketer, explaining that data exhaust isn’t necessarily a problem for marketers. The key is having a clear purpose and knowing what metrics matter. It’s time for brands and their agencies to be accountable for how marketing initiatives impact business. While many brands focus on ROO or ROE initiatives, in the for-profit world, their end purpose is always about revenue – earning more for their company or stealing share from competitors.

Measuring The Bottom Line

To prove value at the core, it is imperative to know what revenues are being driven as a result of your campaigns. While other metrics may show correlation or even causation to revenue streams, we must first start with the bottom line. Creating a measurement framework that can point to short and long-term revenue generation allows brands to immediately see the effect of their marketing efforts. Short-term revenues can be gathered via on-site sales, click-thru to purchase, coupon/offer redemptions, and much more. Long-term revenues can be tracked through longitudinal studies or projections. Without both, there is a shortsighted view. After all, driving business results is the primary reason for getting marketing budgets in the first place. That is not to say that all ROIs must be positive, but seeing how impactful marketing dollars are to the business is paramount.

With so many 360-degree programs, being able to dissect the results based on variables will help marketers optimize programs – in turn, generating greater business value. Once we quantify the business outcome and how that outcome can be broken down, look to other key metrics to uncover what is driving the result.

For a leading insurance brand, we break down impact on a series of variables – program, event type, geography, consumer profile (which includes several sub-categories), and engagement elements. By doing so, we have been able to optimize our results, delivering greater returns to our client. That’s how you can keep a client for nearly 15 years.

Key takeaway: While brands have varying goals, the most important metric you can track is how an initiative impacts a bottom line.

Mixing Quants & Quals

Understanding the whys behind bottom line measurement provide insights that should lead strategy. Whys can be found through a mixture of quantitative and qualitative metrics. Quantitative metrics can show us statistically-based correlations in data sets, while qualitative information allows us to go deeper to uncover context for the data. The problem is that context is more of a hypothesis than a scientific finding. In the world of analytics, that leaves too great a margin for error.

Due to that challenge, marketers are seeing a rise in quantitative measures for qualitative metrics.

For example, social media scours used to have limited quantitative value. Aside from share of voice, engagement rates, and sentiment ratings, most people looked to social for qualitative feedback from the voice of the customer. Analysts parsed through indicative posts to understand what consumers were talking about in association with a topic. But the ability to see clear differences between two or more variables was more of an art than a science. Today, through algorithmic tagging, companies are quantifying posts based on a series of attributes. A high-end water brand has used this approach, finding that it outperformed competitors in overall satisfaction of the brand and quality of the product, but fell short in insource influence and Net Promoter Score. With that understanding, tactics shifted to drive influence and recommendations of the product, leading to a 25% increase in sales.

Weighting those attributes gives us an overall score for social content focused against the goals and objectives of the brand. Now, these qualitative studies can be utilized in the same way as quantitative findings to look for correlation to business outcomes.

Key takeaway: The more you can create quantitative measures to your support metrics, the more objective you can be in finding a correlation to revenue.

Standardization & Relative Metrics

Various marketing channels offer different data points. In order to understand what is more advantageous to a business, we must build a measurement structure that allows for apples to apples comparisons across channels – from traditional to digital to experiential to PR.

It is far more important to be consistent in your approach than to gather flawless data. There is always going to be a margin of error. Those who worry that the data isn’t perfect will be bound to the age-old saying, “analysis leads to paralysis.” Since we are always trying to improve performance, direction supersedes perfection every day. If you find that there is a correlation between change in perception and sales, you want to optimize toward doing those things that generate the greatest positive perception shift. Accuracy is most important in reference to other marketing initiatives. As marketers, we are constantly looking for ways to optimize programs. If every data point is imprecise, but follows the same logic, the data is still worthwhile.

A state government entity wanted to measure the efficiency of visibility and engagement with the brand. They believed that they could generate a better ROI through more highly efficient programming. After modelling an equation using a series of costs and return metrics, the brand asked to simplify its equation– the cost of the sponsorship divided by the key metric. While we knew the result was not fully accurate, it still allowed the brand to define the right channels to go down, and in doing so, how to better negotiate the top performing ones.  We want to be able to see what is driving greater results. Our ability to shift to more productive avenues that maximize returns, allows us to be good managers and partners.

Key takeaway: Don’t get bogged down trying to assure 100% precision of your data points. As long as you measure consistently cross-platform, you have all of the knowledge necessary to improve business results. 

While there is an extraordinary amount of data that can be collected by marketers, always aim to prove bottom-line business value to the brand. Starting with the end in mind keeps us centered on this most important metric. Be as scientific as possible in understanding the root causes that drive revenues, but don’t fret if data points aren’t precise, so long as they are formulated consistently.  With the right approach, you should welcome the accountability of your marketing campaigns’ performance.