In the age of information or Industry 4.0, data analysis has become central to business practices. And yet, despite the promises of big data, digital marketers and analysts are feeling overwhelmed instead of empowered by the glut of numbers.
With web page traffic metrics like CTR’s and conversions, social metrics like engagement and CPC, not to mention search engine marketing metrics, email performance stats, and event metrics… the amount of stats to collect can seem infinite. And for some companies, it really is endless– an endless headache for their marketing departments.
The problem is around the time “data-driven” became a buzzword in digital marketing the term “data-driven” morphed into a practice of collecting ALL metrics for every channel. Between over collecting data and collecting noisy data, it’s no wonder digital marketers are growing frustrated. Here’s how data can become too much of a good thing:
If you can not map a metric to ROI, it is a) a problem of inaccurate reporting or b) the metric does not actually have a connection to your overall return on investment. It’s not that these metrics may be worthless, but they made not be what’s important to your brand in this moment.
Brand Marketer Molly Greenberg writes about finding your brand niche in Navigating a marketing World with Too Much Data. She posits that for businesses that have a small targeted demographic, understanding which metrics really drive business can prevent marketers from misspending budgets.
Without really understanding your audience, such as their demographics and platforms of choice, then it’s hard to pinpoint what data is truly necessary to collect. For example if you know that the majority of your conversions come from email referrals, then it makes sense to track open and click through rates, as well as unsubscribes because you can estimate the percentage of each metric that convert to a sale. However, you may not need to track how many of these email opens clicked on your social media. Not to say it’s not important, but is it as important to optimize your email to social channel when you could be streamlining your email to sales funnel?
Hence, the cure for over-collecting is knowing that not all data is equal. Not all data will be directly relevant to your profit margins and so learning how to prioritize is key.
— Scraawl (@Scraawl) October 24, 2017
But you should know, with data analysis it’s always Garbage in, Garbage out. The source of your data and the quality of that source directly impacts the quality of your analysis. For example, digital marketers know that if they incorrectly set up their goals in Google Analytics then the result is inaccurate web traffic conversion numbers which can spell disaster for their sales teams.
As influencer marketing grows in importance, global brands are also trying to evaluate the true worth of influencer networks. Setting benchmarks for these influencers means very little for real ROI if the followers of these influencers are mostly bots. But if they collect engagement metrics without assessing the quality of these engagements, then it’s a huge misspend for the brand.
Having the right data begins at the source. Check out the other data downfalls to avoid for your brand here:
Confirm, Collect, Analyze
When learning how to walk the fine line between data-driven and being overwhelmed by data, it’s helpful to think of these three easy steps to a better approach to data.
- Confirm the quality of your data and confirm the importance of your reporting metrics. Consider doing an audit of your channels and confirm what channels really matter to your ROI.
- Collect only the most important data for your company.
- And then analyze the data using martech software or good ol’ Microsoft Excel. We also recommend our data analytics tool Scraawl 😉
Cycle through these three steps as often as you can. With data reporting on marketing campaigns or social brand performance, it’s important to stay agile. What works one day may not work the next quarter. Luckily, instead of being buried under last year’s metrics report, you can stay up to date with leaner, more streamlined data from the start.
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