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Tips: How to get the most value out of data insights

With more than fifty useful metrics to track, we asked our team for their top tips to surface valuable insights for your business.

Fleet manager using Localz data insights for field service optimisation

The Localz dashboard provides a simple interface to keep track of jobs, operatives, customers and feedback. 

With data insights, you can dive further into job outcomes, staff engagement, and customer satisfaction. It’s easy to view, filter, aggregate and export the data that matters to your business.

By using data insights, you can monitor your service delivery performance and ensure you’re getting the most value out of the Localz platform.

Data insights help your team to:

  • Optimise service delivery using historical insights.
  • Celebrate your team's successes and flag opportunities for improvement..
  • Monitor customer and staff engagement.
  • Tailor insights to your business needs and customer journey.

With more than fifty useful metrics to track, we asked our team for their top tips to surface valuable insights for your business. 


1. Using tags to find the data you need


Tags are great because they let you carve up the data in ways that make sense for your business.




A typical use case is to segment users by team, so team managers can easily drill down to the data that they need. 

You can also view data aggregated by tags, making it easy to compare averages for different teams, trades or regions.  

Since tags can be nested within other tags, you can get as granular as you need. For example, you might create a team, and create different districts within that team.



2. Using active jobs to monitor contact details

Within the ‘Jobs’ tab in data insights, you can find out what percentage of jobs were ‘Active’.




An ‘Active job’ is a job for which Localz is able to power customer communications such as ETA updates. An ‘Active job’ depends on two conditions:


  • Are the customer’s contact details in the system?
  • Is the customer opted in to communications?


This means that the rate of active jobs is a good indicator of the health of your customer contact details.


Typical field service companies using Localz see an average of 12% inactive jobs. If you’re seeing more than 15%, it’s a good idea to check up on the condition of your customer contact details. Your organisation can then take steps to fill in the gaps.


When asking customers for their contact details, be sure to emphasise that they will benefit from increased transparency and communication. And of course, you should always comply with the latest data and privacy regulations when dealing with customers’ information.


2. Job failure and cancellation reasons

Job completion, failure and cancellation workflows allow operatives to provide a reason for the failure or cancellation. The reasons are pre-configured by your organisation.




The Jobs tab shows how many  jobs that failed for each reason, expressed as a number and as a percentage. Common reasons include “no access”, “unsafe to proceed”, or “further work is needed”.

These metrics can help you keep track of your no-access rate or other recurring issues that may be affecting your first-time fix rate. 

If a high proportion of jobs are ending in no access, it might be helpful to ask:

  • Are there any gaps in customer communication?
  • Are appointments at a convenient time for customers?
  • Do operatives have all the information they need to access the property?
  • How has the percentage of no-access jobs changed over time? 


3. Operative usage

The operatives tab lets you easily view key metrics related to mobile operatives - including job volumes, Localz usage, and customer ratings.   


kb-di-operatives-fields (1)


Usage data can help you understand how operatives are using Localz, and where they might need more support. 

Typically, an operative is responsible for two important activities:

  1. Indicating when they’re on their way
  2. Closing down the job, whether that’s marking the job as completed, cancelled, or failed.

Each of these two activities is worth one point. So for a single job, an operative can score 0, 1, or 2 points.

For an operative to have a usage score of 100%, they need 2 points for every job. If they score 1 point for every job, their usage score will be 50%. Most operatives will have a usage score between these two figures. 

You can also aggregate data using tags to compare the usage rate between teams or regions, for example. 


4. Live tracking

The Live Tracking tab is designed to provide insights about how the ETA tracking has been used. For instance, you can see the percentage of jobs that used On My Way tracking, how many customers opened the tracking link, and how many customers clicked the tracking link multiple times. 




The tab also includes a breakdown which shows how many jobs were left in “On My Way” status. These are jobs where the operative indicated that they were on their way, but never “arrived” or closed down the job. 

If a lot of jobs are left in the “On My Way” status, this could indicate that operatives need more encouragement to close down jobs - either by marking them as completed, failed, or cancelled. 


5. Keep track of feedback

Feedback data gives a tangible idea of the quality of customer experience. Since customers submit detailed feedback right after their appointment, the results go so much deeper than an annual statistic or vanity metric. Instead, feedback is attached to individual jobs, operatives and teams, so your business can take action to make improvements and celebrate successes. 




In addition to data about customer satisfaction, you can also find data about the feedback conversion rate.

At the top of the page you’ll see a summary of how customers progressed through the feedback funnel - from the number of feedback links shared, through to the number of responses. 

Looking at the feedback funnel can help you to optimise your feedback collection process. Imagine that  lots of customers are visiting the feedback form, but not submitting  a response. This could be a sign that your questions are too complicated or aren’t relevant to the customer experience. 


Got questions about data insights? Check out the Knowledge Base, or get in touch with your Customer Success Manager to learn more.