Inconsistent data granularity stunts insights; here’s how we solved it

Marketers today face an overwhelming marketing data volume, variation, and complexity. With each channel shooting out data in inconsistent formats, naming conventions, granularities, and more, getting to actionable insights can be slow, error-prone, and frustrating. If you’ve ever spent hours manually piecing together data from disparate sources to get to the bottom of a critical business question, you’re not alone.

Built by-marketers, for-marketers, Beckon knows better than anyone how essential it is to have clean, aligned, integrated data flowing, but also how uniquely unruly marketing data can be. Our powerful, flexible data model is built to handle marketing’s messiest data, in whatever format it comes. Performance data often comes in broken down by month, by day, by week, or anything in between. When the time comes to combine it for a holistic view, many measurement and analytics tools choke, not knowing what values to assign to the appropriate timeframes, particularly where months and quarters don’t align evenly with weeks. Quickly seeing quarterly fiscal marketing spend, how engagement is fluctuating week over week, or this month’s campaign results are near impossible.

To solve this issue, Beckon uses a method called frequency resampling, effortlessly combining data of varying granularity for ultimate flexibility and analysis. When it’s time to perform a query, all data is normalized down to the millisecond before being combined across the selected granularity and date range. This allows for easy, flexible, and fast comparisons and combinations of data from any and all sources.

The algorithm behind this process is simple, but what makes Beckon unique is the speed, volume, and flexibility with which we’re able to do this. Every time a marketer begins a query to ask, “How much did I spend last fiscal quarter?”, millions of data points are being divided, averaged, combined, and processed to come up with one simple metric. Sure, an analyst could perform these processes manually for one set of data. However, to answer critical performance questions at the speed and scale of modern marketing, when data is continuously flowing in with varying granularity, it is essential to have robust technology in tow to do the heavy lifting.

If you’re getting stuck along the path from data chaos to actionable insights, feel free to drop us a line, we’d love to hear from you.