What are Research And Development metrics? Finding the right Research And Development metrics can be daunting, especially when you're busy working on your day-to-day tasks. This is why we've curated a list of examples for your inspiration.
Copy these examples into your preferred tool, or adopt Tability to ensure you remain accountable.
Find Research And Development metrics with AI While we have some examples available, it's likely that you'll have specific scenarios that aren't covered here. You can use our free AI metrics generator below to generate your own strategies.
Examples of Research And Development metrics and KPIs 1. Latency The time taken for the image to load from the server to the user's end
What good looks like for this metric: Typical benchmark value is under 100ms
Ideas to improve this metric Optimize image sizes Use a Content Delivery Network (CDN) Implement lazy loading Enable browser caching Minimize HTTP requests 2. Cost Per Image Delivered The total cost incurred for delivering each image to the user
What good looks like for this metric: A typical benchmark is under $0.01 per image
Ideas to improve this metric Choose cost-effective hosting solutions Compress images to reduce size Utilise efficient caching strategies Optimise server infrastructure Leverage cost-effective CDNs 3. Image Load Time The amount of time it takes for an image to be fully accessible on a user's screen
What good looks like for this metric: An ideal benchmark is under 2 seconds
Ideas to improve this metric Reduce image dimensions Utilise responsive images Implement file format that loads faster Use asynchronous loading Optimise server response times 4. Scalability The ability to handle increasing load of image delivery without performance degradation
What good looks like for this metric: Should smoothly handle a 100% increase in traffic
Ideas to improve this metric Implement auto-scaling infrastructure Utilise robust load balancing solutions Optimise image storage options Conduct regular stress testing Use scalable databases 5. User Satisfaction Measures how satisfied users are with image load times and quality
What good looks like for this metric: Typical satisfaction rate above 80%
Ideas to improve this metric Conduct user feedback surveys Analyse user interaction data Regularly update images for relevance Ensure high-resolution options as needed Implement faster image formats
← →
1. User Satisfaction Score Measures the satisfaction levels of users with the UX design via surveys like SUS or NPS
What good looks like for this metric: Average score ranges from 68 to 80
Ideas to improve this metric Conduct regular user feedback sessions Implement iterative design improvements Enhance usability based on pain points Improve interface consistency Ensure accessibility compliance 2. Task Success Rate Percentage of correctly completed tasks without assistance
What good looks like for this metric: Typically ranges from 78% to 85%
Ideas to improve this metric Simplify task flows Increase clarity in instructions Use intuitive design patterns Conduct A/B testing for task paths Provide effective user training 3. Time on Task Measures the average time users spend to complete a task
What good looks like for this metric: Varies widely depending on the complexity of tasks
Ideas to improve this metric Identify and remove bottlenecks Streamline task steps Improve information architecture Enhance system responsiveness Use user testing to target slow task areas 4. Error Rate The frequency of errors made by users during tasks
What good looks like for this metric: Aim to be below 5%
Ideas to improve this metric Enhance input validation Provide clear error messages Refine user instructions Improve interface intuitiveness Conduct usability testing to find error hotspots 5. Retention Rate Percentage of users who continue to use the product over time
What good looks like for this metric: Typically above 25% over a year
Ideas to improve this metric Improve user onboarding Enhance engagement with features Encourage feedback and implement changes Ensure regular updates and improvements Analyse and reduce user drop-off points
← →
Tracking your Research And Development metrics Having a plan is one thing, sticking to it is another.
Don't fall into the set-and-forget trap. It is important to adopt a weekly check-in process to keep your strategy agile – otherwise this is nothing more than a reporting exercise.
A tool like Tability can also help you by combining AI and goal-setting to keep you on track.
More metrics recently published We have more examples to help you below.
Planning resources OKRs are a great way to translate strategies into measurable goals. Here are a list of resources to help you adopt the OKR framework:
Tability's check-ins will save you hours and increase transparency
The best metrics for Measuring Image Performance