Incorporating embedded analytics into your platform doesn’t have to be a complicated or cumbersome process. Unfortunately, most companies don’t have analytics as one of their core competencies, which means mistakes are all too common. Most of these mistakes lead to the same place, to implementations with low adoption rates that fail to deliver insights to those who need them most. Here are the top 8 most common pitfalls you need to avoid when embedding analytics into your product or workflow.

Here are the top 8 most common pitfalls you need to avoid when embedding analytics into your product or workflow Share Tweet

Pitfall #1: Not Setting Clear Goals

It’s not enough to just say “we’re adding analytics to our product.” Every implementation needs to have clear goals in mind from the start. The time to think big and choose the right platform is before you begin development. If you truly want to bring the promise of being a data-driven organization into reality, you need to plan ahead and make sure your tools can indeed be used by everyone.

Pitfall #2: Not Assembling the Right Team

If you intend to bring analytics to a large number of users, everyone’s feedback must be considered. Your users will probably have lots of things they hope to do with your embedded analytics software, so it’s important to embed a self-service solution that can easily handle everything they’ll need. It’s also important to work with an analytics partner that has your company’s best interests in mind.

Pitfall #3: Choosing the Wrong Architecture

When it comes to analytics, architecture matters. Choosing an old, legacy system will limit your flexibility, scalability, and performance. Choosing a modern, cloud-native solution will allow you to offer more tools to more people in more places than you ever thought possible.

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Pitfall #4: Forgetting About Good Design

Not everyone is a data scientist or a computer nerd. Fortunately, they don’t have to be. Analytics platforms like Qrvey make it easy for anyone to build their own charts, reports, metrics and dashboards. And, since it’s embeddable, all of these tools can be easily accessible inside of the tools they’re already using.

Pitfall #5: Not Including All Of Your Data

This is a big one. According to recent reports, only a fraction of corporate data is ever made available for analysis, leaving users with only a partial picture of their data and incomplete answers. The problem is semi- and unstructured data, which most analytic tools simply cannot process. Fortunately, there is one tool that can process all of your data, no matter its size, type, or where it lives.

Pitfall #6: Forgetting About Integration

Analytic tools offer no value if no one uses them. That means for them to be truly valuable, they need to be fully embedded into the tools your users are already using every day. If you want maximum adoption and usage, an embeddable platform is a must. While many solutions claim to be embeddable, make sure the one you choose was built from the ground up for simple, yet powerful embeddability

Pitfall #7: Missing The Boat On Privacy & Security

The privacy and security of your data is an ever-growing concern. Many companies simply cannot trust sending their data to a third-party analytics tool, which leaves them with few options. That’s why Qrvey took a unique approach to the cloud, deploying our platform into your cloud, rather than our own. Now you’re always in control of your data and infrastructure, making security, privacy, and compliance a non-issue.

Pitfall #8: Neglecting Automation

There’s only one thing better than having a lot of users discover new insights with your new analytics platform, and that’s having your platform discover those new insights for you.  Automation is a vital, but often overlooked component of analytics, but it shouldn’t be. By adding automation, users can automatically be alerted when conditions are met and workflows can be triggered if thresholds get exceeded. Only with automation can your analytics platform be working for you 24 hours a day.

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