Don’t let the numerous articles written about “big data” fool you, data is not exciting. In its raw form, data is quite boring. In fact, if data were a movie, it would be “Ishtar.” Data by itself is confusing and lacks a compelling narrative.
Data is only useful when it tells a story and provides insights that can lead to action. Raw data does not provide actionable insights. Most people don’t need access to more data. They need data transformation that turns marketing analytics into insight.
One of the reasons I’ve staked my career in digital marketing is its ability to track results. There isn’t a service that Mason Digital provides that doesn’t include some form of measurement. But measuring something just because you can is not a useful exercise. It should be used for the sole purpose of improving performance over time.
Looking at data without understanding the story it tells is unhelpful — or worse, dangerous. Here are some examples I’ve personally witnessed where poor data interpretation resulted in bad business decisions:
1. Using the wrong metrics: When you don’t understand what the data is telling you it can be very easy to make decisions based on the wrong metrics. A great example of this is determining the effectiveness of your website based on metrics like pages per visit or average visit duration. The goal of your website should be for a visitor to take a specific action like make a purchase or complete a contact form. Pageviews don’t translate to revenue (unless you’re selling ad space). Sometimes more pages per visit means visitors can’t find what they’re looking for.
2. Aggregating data from multiple sources: It can be tempting to combine numbers from various sources in order to summarize results. I’ve seen this with digital advertising campaigns where ad impressions and clicks from paid search, social media, and video are added up together. Each of these tactics are used to achieve different objectives, combining this data doesn’t provide any valuable information.
3. Subjectively defining the level of success: Is a 3.6% conversion rate significant? It might be, it might not be. How is a conversion defined? What is the cost for that conversion? What can we expect the ROI to be on a single conversion? When you have trending data and an understanding of the value of a conversion the conversion rate becomes a useful metric. I’ve had meetings with clients who were discouraged by a 20% conversion rate and meetings where clients were ecstatic about a 4% conversion rate. Our goal is continuous improvement. A 4% conversion rate after three months of performing below 2% should be considered a win.
4. Using data that isn’t statistically significant: That 20% conversion rate I referenced seems great. But what if that metric is derived from three conversions resulting from 15 page visits? Don’t bother hiring a band for the celebration just yet. Rates will fluctuate wildly until there are thousands of data points that allow these metrics to normalize.
5. Comparing apples to oranges: Many marketers like to determine the success of their digital advertising by using industry benchmarks. This might seem like a good way to gauge success; however, you should consider the many variables involved. Looking again at conversion rate, Google will post conversion rate benchmarks by industry. But how is a conversion defined? You might have a form that requires a visitor to fill in multiple fields where another advertiser counts every visit to the “Contact Us” page as a conversion. Comparing these provides very little value or insight.
It’s better to gauge success with your own benchmarks by reviewing trending over time. Establish a baseline for key metrics, then tell the story of how these metrics are increasing or decreasing. It’s great to know that conversion rate is increasing but it’s more important to understand why.
We use landing pages on our clients’ websites to entice visitors to take a specific action. We might have a page that gives a visitor a chance to download a white paper by completing a form. The form submission is the conversion in this case. In order to maximize the conversion rate we test different variables.
After six months, we pull a report that shows conversion rate has increased from 3.5% to 7.8%. That’s outstanding progress but the important element is the story of how we achieved this. We probably learned which call to action works best, which keywords drove visitors most likely to convert, and which layout was the easiest to read. This contextually relevant data is much more helpful than raw numbers because it allows us to transfer those learnings to other campaigns and achieve similar results.
While many marketers believe having a data analytics dashboard at their fingertips is extremely useful, I’d caution them. Without understanding why changes are occurring, it might be more productive to watch Ishtar than it is to stare at a dashboard full of numbers.
Would you like to learn how to turn data into actionable insight? Download our free e-book: The Stories Data Drive Marketers Should Be Telling You.