Learn how NextBillion.ai’s on-premise deployment of Distance Matrix API boosted Grassdoor’s ETA accuracy, increased throughput, reduced latency and lowered operational cost.
Founded in 2018, Grassdoor aims to be ‘the Uber of Cannabis delivery’. Operating across Los Angeles, Orange County and Southern California, Grassdoor offers both on-demand and scheduled deliveries. One of their key promises is to provide same-day deliveries in under 45 minutes to cater to consumer needs. 

Business Context

The increasing acceptance of Cannabis and COVID-driven consumer demand together have sparked a paradigm shift in the way Cannabis delivery operates in recent years. 

When it comes to  on-demand deliveries, accurate ETAs are central to meeting customer expectations and maintaining satisfaction. Complex urban environments, like apartment layouts with multiple entry/exit points,  are particularly challenging in this regard. Since a delivery isn’t complete till the package is in the recipient’s hand, simply arriving at the location on time won’t suffice — the delivery agent must navigate to the customer’s doorstep within the stipulated ETA. This costs precious time in a competitive market where every minute counts.

With a number of  new competitors entering the market, it became critical for Grassdoor to deliver a differentiated customer experience without compromising their unit economics.

Challenges Posed

For last-mile and on-demand deliveries, calculating accurate ETAs and optimized routes is paramount to achieving optimal operational efficiency — and an accurate Distance Matrix API forms the foundation of any optimization engine.

However, existing Distance Matrix APIs come with inherent  limitations. For instance, the matrix size of most APIs  currently on the market is limited to 25*25 elements, which is insufficient for optimization of a large number of deliveries for large-scale operations. 

  • Grassdoor needed a Distance Matrix API that would be able to accommodate large API call volumes at scale, while also running at high throughput and low latency. 
  • Cost was also a concern — the existing APIs proved expensive, and the problem only worsened as Grassdoor scaled up. 
  • They were also trying to figure out a way to improve operational efficiency in terms of increased throughput and reduced latency, as they scale.

“Today’s market is so competitive that a delay of even just a few seconds could mean losing potential customers. Striking the balance between ETA accuracy, scale and operational efficiency is key to success, but this is no easy task. The available mapping solution providers are either prohibitively costly or extremely limited, forcing a trade-off between operational costs and on-time deliveries.”
Abhishek Gupta – Chief Information Officer

NextBillion.ai’s Solution

Having already identified the gaps in the market, these were exact limitations that NextBillion.ai’s proprietary Distance Matrix API was engineered to overcome.

  1. Our API can support a matrix of up to 5000*5000 origins and destinations, as opposed to the typical 25*25. Such a large matrix helps Grassdoor predict exact travel times while accommodating for driver pit stops and other variables. This, in turn, enables Grassdoor to consistently generate optimal routes and project accurate ETAs to maintain customer satisfaction.
  2. As a result of the operational optimizations driven by our Distance Matrix API, Grassdoor managed to lower delivery times and the number of miles driven, as well as expand their service coverage with the same fleet. This greatly boosted their profitability on each order.
  3. We offer flexible pricing models and our costs compare favorably against alternatives such as Google Maps and Mapbox. The competitive pricing — along with the flexibility to choose a payment model that works for their business — further elevated Grassdoor’s unit economics to the level they required.
  4. A key differentiating factor for Grassdoor is the fact that NextBillion.ai’s APIs can be configured for on-premise and cloud-agnostic deployments. The ability to deploy our API within their own cloud environment facilitates lower operational latency and increased throughput, which empowers them to operate at scale with ease.

Key Differentiators

  • Cost effective
  • Cloud agnostic 
  • Customized Distance Matrix API
  • Large matrix size 

Achieved Outcomes

With a cost-effective, distance matrix catering to huge volumes and on-prem deployment, Grassdoor was able to:

  1. Reduce operational latency
  2. Reduce operational costs by almost half of their existing spends
  3. Improve ETA accuracy 
  4. Improve Operational throughput 

“The huge matrix size of NextBillion.ai’s API enables us to factor more real-time variables without skyrocketing our costs. It’s also central to helping us effortlessly scale operations as we expand to new regions. Crucially, the on-premise deployment eliminated our latency and performance issues with ease.”
Abhik Gupta – Chief Technology Officer

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