In this world of endless analytic tools and services, more and more companies are trying to become more data-driven in their approach to marketing, sales, and logistics costs. Fortunately, if you’re trying to pitch your superiors on improving your company’s approach to analytics, there are plenty of problems with entry-level and free analysis tools that can support your argument for higher-end service.
Integration Takes Time
When you’re taking a new product, service, or project to the public, you’ll want to set up your analytics to better equip your company with the metrics they need to adjust and improve as time goes on. Once you’ve established your primary metrics, you’ll want to segment them along several specific avenues in order to best interpret the data. That’s the just the step – what about custom data tracking or integrations with your other systems? Depending on the skill level of your development team, it can take a long time before the tools you need are up and running (let alone leaving room for testing). Otherwise, you may receive wrong or misleading data.
Even if you have all your metrics set up, you still might not be getting all the information you need in a streamlined manner, requiring additional time to process and organize your data.
Excel is Nice, But Inefficient
When most people think of business-centric data, they think in terms of .CSV files. While Excel is an amazing tool for managing and organizing information, it has some severe limitations that are of no fault of its own: it can’t interpret the data for you. This extra elbow grease required to calculate hundreds of standard metrics and convert the information into clear-cut financial metrics is a problem many companies face. While there are some services that help bridge the gap from payment systems to third-party analytics tools, none of them are able to further segment that data into discreet marketing channels or measure conversions to payments or behavior patterns.
But Where’s the Context?
The true beauty of Big Data for most medium-sized businesses is in-depth, detailed, and personalized information for low-density applications. By gathering available data and analyzing it from a so-called “zoomed-out” view, you can begin to detect relationships between actions and results in order to better predict outcomes and customer behaviors. On the business intelligence side, utilizing descriptive statistics in high-density environments allows a company to track trends and look for opportunities to improve their services. Without a complimentary Big Data strategy, your metrics will simply be a jumble of words on a page, waiting to be interpreted. There are better uses for your company’s time. Contact Neal Analytics to find out how much of it we can save.