How can Workforce Companies Improve Productivity using Location Analytics?
Drive sales by improving performance, utilization of your workforce geospatially
Key Takeaway
If you are a company with salespeople on the ground selling products, services, insurance policies, and loans, you can use location analytics to improve the productivity of your workforce and give better customer experience. This blog explains how.
Introduction
While working with different kinds of workforce companies who have thousands of salespeople on the ground, we have seen that despite collecting large amounts of data, only ~5% of that data actually gets used. Because of a dearth of the right tools for location analysis, a significant amount of decisions that are taken about operations and movement ends up being gut-driven.
As a result, the productivity of salespeople goes for a toss and we end up ignoring more revenue that we can make by improving utilization as well as taking more precise and data-driven decision.
“Location” is an inherent characteristic of anything that is happening in the physical world. Moreover, location intelligence is so much more than tracking on the map or solving the traveling salesmen problem! In fact, any decision involving the physical world is about location because everything is happening somewhere.
Therefore, it becomes very critical to incorporate location as a parameter and make it a first-class citizen in your decisions and strategies.
Location-Based Decisions for Workforce Use-Cases
In this part, we will cover different kinds of location analyses and the insights that you need to grow sales and utilization.
1- Monitoring Movement of Reps
Monitoring movement of salespeople on the ground for performance, ETAs, halts, bottlenecks is the most basic but the most critical use case for most workforce companies.
City and business teams also monitor KPIs such as idle sales reps, busy sales reps, sales made in real-time across locations to know what’s going on with their business and check for anomalies.
Often, companies also go back in time and do historical analysis of the movement patterns ( ie ‘breadcrumb’ trail) to analyze metrics such as distance traveled, time taken, places visited, delays etc to settle claims and detect inefficiencies.
You can also create cohorts of salespeople in case you aim to monitor the movement for a certain group and stay on top of their journey. For example, evaluating the lowest-performing salespeople.
2- Sales Mapping of Areas
Just analyzing the movement of reps is not adequate. We also need to analyze how different areas perform in different categories and with the time of the day and day of the week. But why? To get answers like:
Is there a specific location, time or day when we see a boost in the sales number? Which category is most sold in the affluent areas in the city?
Because that will help us close more sales by doubling down on areas that we see more opportunity and need to penetrate further, or seizing new opportunities by expanding in the right areas or sometimes just ignoring the areas that haven’t proven to be good for our business.
One very interesting application of this analysis we have seen companies do is debugging whether the sales numbers are low because of a particular area or a group of sales reps and how that’s been changing historically.
3- Offices, POIs or Any Static Locations
Now comes the third part of the puzzle — Analyzing the performance of your offices, POIs and locations where reps go and sell to. Using these insights to set up more targeted and personalized sales strategies for your customers.
Which offices are most frequently visited & never visited? Which offices have gotten us to the most revenue day-on-day? Where do sales reps spend a lot of time but don’t see enough conversions?
Some very interesting use cases that we have seen companies adopt are:
- Flagging all the instances and offices where sales reps spend less than an hour or more than 10 hours at a location.
- Analyzing the distance variation of the actual location of the rep versus the office location.
4- Fraud Patterns
This is a very common use case for all our customers. Most of them go through some kind of fraud/cases of misconduct/malicious activity/incorrect behavior from their workforce. That could range from providing false information of clients, giving incorrect scans, hacking biometric system and the list goes on!
Most of these events have hotspots, with location and time patterns. Companies use this to classify areas as “red zones” and as soon as they detect any kind of suspicious activity in those areas, they take precautionary steps.
Why should you use Locale.ai for workforce use cases?
Locale is a location analytics platform, which means we convert your raw lat-long data across all databases and formats into meaningful insights so that decision-makers can make very precise, data-driven decisions about their ground operations.
If on one hand, we give you the right metrics and insights to help you make the right decisions, we also make the process of working with large amounts of data very seamless and reduce the time to insight. We bring all your location data in one place to make these analyses available in a matter of a few clicks!
Monitoring Movement of Reps
With Locale, you can monitor the movement of your reps in real-time as well as get a historical timeline of their movement patterns. However, what makes this monitoring extremely powerful is the anomaly detection models we have built-in in the system. This means, we study your data historically and alert you with a severity score in case a metric behaves abnormally in a particular area.
Sales Mapping of Areas
Locale helps you identify your hotspots in terms of sales and visit frequency. But, what’s interesting is we just don’t give these insights at an area level because we believe that they are too big. We go down deeper into different areas to help you discover the nuances inside them, using a system of hexagonal grids.
Offices, POIs or Any Static Locations
Locale is amazing at giving you a bird’s eye view of all your offices or the places your sales reps visit. We use a mixture of size and color attributes to help you in a glance figure out which of those locations do you need to focus on or change your strategy. In other words, focus on the places with the maximum visits and lowest revenue generated.
Frauds
Acknowledging that this data might be sensitive, we have roles and permissions built-in along with showing the right hierarchy at each role. In other words, a city manager wouldn’t be able to get any such insights excluding his city.
Actions and Decisions
Apart from giving you the right insights, we also help you take actions and decisions on top through our workflows module. You can create a step-by-step flowchart that sends triggers to your reps on ground as well as get alerts in case of anomalies.
At Locale, we are creating examples of companies who are improving their unit economics, cost per delivery, utilization by doing geospatial analytics. Our product helps you analyze and improve metrics at a city level upto an order level. If you would like a demo, check our website out or get in touch with me on LinkedIn or Twitter.
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Originally published at https://blog.locale.ai on May 5, 2020.
