Deciding whether to buy or build analytics for your applications or software products can depend on a number of factors. For many, the long-term return of buying an embedded analytics solution far outweighs the upfront cost to build one. However, executives that see the value in embedding a 3rd party product occasionally lack the ability to definitively measure their analytics ROI. We’ve put together 3 tips to help.
Put Success Metrics in Place from Day 1
If you’ve implemented or even launched 3rd party analytics into your product it can be hard to objectively define its metrics. The main reason for this is that many of the metrics revolve around measures of improvement which require baseline measures to accurately define how a project has impacted your product’s core value overall. Customer surveys and other forms of market research can reveal the benefits of an added feature or feature set and give you better insight into defining the rights metrics. An example may be a user survey on whether current reporting capabilities satisfy specific critical criteria before embedding a 3rd party product compared to similar studies done after implementation has been completed.
Developer Efficiency & Resource Drain
You should measure efficiency gains for your report developers and application developers. For example, we’ve had customers who had report developers that hard-coded every single report they did spending eight hours per report. With our product, that eight hours went down to 15 minutes per report.
Angela Fox, Manager of Data Development, Franklin American Mortgage Company stated:
“Considering our multiple divisions, we’ve probably saved the time of one employee per week just running and distributing reports. If every report that we now have scheduled was manual, it would take all day, every day to do it.”
There can be some huge efficiency gains from report development efforts as well as overall application development. If your application developers were not burdened with building out reporting and analytics capabilities they could focus on the development of core business competencies. What does that mean to your business as a whole and how much more can you do? The amount of development time that goes into both developing reports and developing reporting capabilities is something you should measure before and after you’ve actually implemented the product to properly gauge efficiency gains.
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Ensure Timely Customer Support
Customer retention for SaaS models often relies on the success of your customer support team. With a homegrown BI solution, the release of a set of hard-coded reports can come with a flood of new requests to your support team for add-ons, edits, and even brand new reports. This leads to a vicious and costly cycle of hard-coding report development by your support and development staff, taking precious time away from answering support tickets and delaying overall customer response time which ultimately leads to a bad customer experience. By embedding a 3rd party analytics solution, this cycle is broken with ad hoc reporting capabilities. Users don’t have to depend on support staff for creating or editing reports. As such, measuring your support team’s response time and its overall affect on your retention rate is another great way to measure your analytics ROI.
It’s All About Defining Good Metrics
When it comes to measuring your reporting and analytics ROI, the most important factor to keep in mind is that objective measures represent how improvements have affected overall value. However, objective measures need a point of reference before and after an event occurs to give you the full context of what’s been achieved. So decide on a solid set of success metrics from the onset of a project, then review and assess those metrics after users’ get their hands on the product to get better idea on its success.