It's hard to understate the vital importance of what big data and analytics have for modern marketers. The accessibility to, and availability of, troves of data which speak to everything from individual preferences to broad trends present companies with impressive new ammunition for making better decisions.

Even so, collecting data is only part of the equation. To be useful, data must be properly parsed, stored, organized, processed, and retrieved. Tools such as Google's BigQuery are excellent for business intelligence warehousing needs, but they have a high barrier to entry for most marketers due to the complex setup processes involved. Although cloud-based solutions such as these are useful for storage, real-time processing, and are highly scalable, the technical barriers to getting the most out of BigQuery can be a turnoff for line-of-business users.

This hasn't stopped companies from using BigQuery, although the search for a simpler way to connect is an ongoing priority. Marketing analytics integration company Supermetrics unveiled a potential solution to overcome the challenges faced by BigQuery's would-be users.

Unveiled at the 2019 Google Cloud Next event, Supermetrics's new BigQuery integration promises to reduce the barriers to entry and provides a more effective data warehousing solution to improve insight quality.

While the rollout is surely promising, it's worth asking what could this app, and others like it, achieve for data-driven marketing.

The Marketer's Dilemma

Marketers are constantly on the lookout for any tidbit or insight about consumers that can improve the efficacy of their strategies. Big data has shifted the paradigm for research towards a more empirical data-driven approach, placing a higher value on hard facts rather than preconceptions or established ideas.

To that end, it's common for most marketing groups to draw from as many data streams as possible — social media, points of sale, ad promotions, websites, email campaigns and more.

With so many possible channels to choose from, marketing teams can afford to pick and choose, finding the most valuable data in clean structures that make it easier to uncover insights. Unfortunately, this is rarely the case, with many teams experiencing difficulty in terms of maximizing their data's potential due to technical complications and a lack of expertise.

It's also emerging as a serious problem for companies that produce their own data. One study found that nearly 95 percent of businesses surveyed require management for unstructured data. With the potential to increase profits by up to 10 percent and reduce costs by an additional 10 percent, businesses need to dramatically enhance their analytics capabilities.

"Marketing tools and platforms are becoming highly advanced in terms of usability and accessibility for non-technical professionals," notes Supermetrics CEO Mikael Thuneberg. "It is relatively easy to find the information you are looking for from Facebook Analytics, for example. The management, organizing and transferring of data, however, has been out of reach."

Supermetrics's Contribution

With these problems in mind, Supermetrics has introduced a new tool designed to connect marketers directly to BigQuery, minus the complicated setup and with no need to code queries. The new module lets marketers set up their BigQuery data streams and warehouses using nothing more than a series of dropdowns and permission screens. This empowers teams to centralize data from diverse sources including Facebook, LinkedIn, Adobe Analytics and more.

Supermetrics, which is largely known for modules that integrate with Google Sheets and Excel, may have taken a step out of its comfort zone, but consequently potentially provided a game-changing tool for marketers. The company's existing solutions are excellent for smaller, less immediate analytics, but they're not meant for rapidly evolving ecosystems and reports that change on a second-to-second basis.

That's why automated data warehousing is only one part of the picture. Supermetrics's BigQuery connector also makes it easy for marketers to select subsets of the data in their data warehouses and export it all, on a self-service, on-demand basis, into environments where they feel at home — namely, spreadsheets.

"Some marketers are more comfortable working with spreadsheets, some less. For many, it is the 'sketchbook' or 'sandbox' where they can crunch numbers and analyze freely for internal purposes before building dashboards for their customers for example. It's not possible to do that with dashboard solutions in the same way," Thuneberg asserts.

"Then there is that freedom of organizing and combining the data. Many PPC reporting solutions are visually great, but they are limited in terms of how you can organize and present the data. A limitation can be as simple as many don't allow you to easily do monthly and yearly data comparison."

How Could This Integration Impact Marketing?

By removing technical barriers to access, integrations such as Supermetrics make BigQuery a better overall tool. This type of solution reduces the issues that stem from keeping data siloed in different analytics engines while concurrently making it easier to build data warehouses that store information in a logical and optimal structure.

The end result is a better analytics stack for marketers. Instead of having to divert resources to data scientists and developers, companies can quickly engage their own business intelligence tools and start processing vital data in real time.

Most importantly, it grants marketers the ability to make rapid decisions thanks to simpler ad hoc analyses, more comprehensive data sets, and unified data streams.

While it's still early to tell, Supermetrics may have just introduced a highly worthwhile platform for marketers. Despite the exciting power modern analytics tools deliver, they're still cordoned off for everyday users who are less familiar with the complexities of using cloud server systems. By simplifying the process, Supermetrics may have prompted a course correction towards a new, better, industry status quo.

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