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Embedded Analytics: Building vs. Buying

Once you’ve decided to make the move to embedded analytics, you’ve taken a huge step in increasing your company’s overall data maturity. The next step is to determine how you get from where you are now to a point where your embedded analytics are running smoothly. For most companies at this stage, it’s time to decide whether you’ll build your own solution or purchase these capabilities from a third party.

In general, building gives your team greater control over the final product but takes longer to build and requires a heavy investment of your development resources. Purchasing those capabilities will streamline the delivery of your analytics, but your team will have less control over the solution.

There are benefits and risks to each approach. Below is a quick summary of what your team can expect with regard to building vs. buying embedded analytics capabilities.

Pros: Building embedded analytics
  • Complete customization to match your data infrastructure and brand look and feel of analytics
  • All security and stability concerns can be managed internally
  • New features are built according to a company's most pressing needs
Cons: Building embedded analytics
  • Requires engineering resources that could be used on more strategic initiatives
  • Takes longer to build, test and deploy
  • New feature creation and maintenance will consume future resources
Pros: Buying embedded analytics
  • Available immediately with high quality out-of-the-box functionality
  • Product improvements can be made without additional internal developer resources
  • Predictable costs for long-term budgeting
Cons: Buying embedded analytics
  • Reporting design/features are dependent on third-party solution
  • Potential for integration issues or complications
  • Vendors take roadmap input from multiple clients, not just your company

The questions to help you decide

If your team is debating whether to build or buy your embedded analytics, here are a few simple questions that can help you come to a conclusion. Gather the necessary stakeholders together and have a discussion about each of these questions, going in depth on your company’s current needs and future plans.

1. Which is more important?

  • Maintaining complete control over the look and feel of the information — If you want embedded analytics made to your exact specifications, you’ll need to keep it in house. Build it yourself.
  • Making embedded analytics available as soon as possible — The infrastructure is already there, just plug in your data and send. Buy it.

2. Which resource does your team want to invest in this project right now?

  • Developer bandwidth — Have extra developers waiting on projects and want to make analytics a key differentiator? Build.
  • Money — Have the budget to invest and don’t need to make analytics delivery a strategic business focus? Buy.

3. Who should control the roadmap for your embedded analytics features?

  • You’ll blaze your own custom trail — You know where you’re going and an external partner might not keep up. Build.
  • The professionals can handle that — Data platforms have a clear vision for what a modern company will need. Buy.

4. Do security concerns limit your company’s ability to integrate with other tools?

  • There can’t be any opportunity for company information to be compromised — Your company/product can’t integrate with other modern products. Build.
  • If a vendor has the right security certifications, they’re trustworthy — Once third-party products have been thoroughly vetted and approved, they’re reliable. Buy.

5. Where do you want to invest future engineering resources?

  • Analytics tool maintenance — If embeds are a point of differentiation for your product, you’ll need to constantly devote resources to update it. Build.
  • Product improvements — Want to focus 100% of your personnel resources on new features for your proprietary product? Buy.

To learn more about the power of embedded analytics, download our free guide: The Product Manager's Guide to Embedded Analytics.


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Amy Lin
Amy joined Periscope Data's product marketing team to understand customer needs and bridge the gap between people and product. Outside of marketing and positioning Periscope Data, you can find her at a local yoga studio, enjoying live music or thinking about what to eat next.