How to Accelerate the Benefits of Dynamic Pricing for Your Business
June 1, 2021
Leading companies like Amazon, Airbnb, Uber, and even Disney are known to continuously update their prices based on real-time demand to maximize their profits. This strategy is known as dynamic pricing, and it has long proven itself as a powerful competitive advantage in today’s digital marketplace.
With the potential to improve revenue by 10% and boost profits by up to 25%, modern companies are keen to build or buy this capability—except implementing dynamic pricing is much easier said than done. From overwhelmed data teams and lapsed customer insights to unproductive software, it often becomes a technical and logistical nightmare ending in delays and millions of dollars in lost revenue.
While the right people and processes are paramount to the success of any business strategy, much of an effective dynamic pricing system boils down to the technology you use to run, test, and improve it.
In this post, we’ll explore the main challenges companies face when implementing dynamic pricing models, and how you can leap ahead of the competition by deploying your pricing strategy faster, easier, and at a surprisingly low cost.
We can compare actual pricing (dynamically set) to a scenario where you vary the static price presented to renters. For this data, you have renters from around 7am to 12pm that is relatively price-insensitive to a daily rate of up to around $103, while you have renters earlier and later than that interval who are in general more price sensitive. Use the slider to vary the static price to see how this affects revenue during the day, and the total revenue collected in 12 hours.
Dynamic Pricing vs Static Price Comparison
The challenges of implementing dynamic pricing
A good dynamic pricing strategy is an intricate web of specialized technologies, skilled data professionals, caffeine, and mountains of customer and competitor data. Your team needs to process this data as quickly as possible, while also keeping an eye on real-time price trends to make timely pricing decisions that can increase your profit margins.
It’s all very tedious and time-consuming, so modern companies rely on software to automate the process. Even so, many find themselves bumping into these common hurdles:
New models take too long to deploy
Typically, data scientists develop sophisticated machine learning (ML) models and pass them onto engineers who run them—often on custom-built software. The problem is that every time the data scientists develop a new, more accurate model of customer behavior that can boost revenue, they rely on the (incredibly busy) engineering team to deploy it.
Between developing new features and maintaining overly-complex technology, engineers can take two weeks or more to deploy a new model. By the time it’s in use, customer behavior has already changed and you’ve missed out on the extra revenue.
Data isn’t processed fast enough
To take advantage of current market trends and offer custom pricing at exactly the right moment, you need to run your ML models against data in real-time. Except most solutions can only handle the data processing in small batches on a set schedule, leaving perfectly good data to expire and dulling your competitive edge.
Progress is restricted by inflexible tools
Most solutions limit you to vendor-locked technologies, which are hard to scale and increasingly expensive to maintain. A familiar setback is having to re-engineer your ML models, commonly built with Python, using specific Java-based libraries. This forces data scientists to learn an entirely new toolset, slowing down progress and also delaying innovation.
Large operational overhead
Dynamic pricing commands a tremendous amount of infrastructure to support data ingestion, analytics, and running multiple pricing models. With each model requiring several servers to run, the high cost and complexity of maintaining your pricing system not only eats into your profits but also limits your ability to scale.
We can capture and produce analytics on unique visitors to the rental website and mobile app and subsequent conversion rate. Run your mouse over the charts to see the number of visitors or conversion rate in each five-minute interval.
Deploy dynamic pricing faster using better software
Dynamic pricing is an undeniably complex undertaking, but it can all be easily managed with the right software. To get the most out of your investment, you need to work with ML deployment technology that’s flexible to your business needs, easy to scale, and can reliably automate what’s known as a highly demanding and costly process.
One such software is Wallaroo, an innovative platform that shortens the time between deploying an ML model and reaping the profits. With everything you need to swiftly launch, test, and iterate your ML models, Wallaroo streamlines bulky processes (like dynamic pricing) so you can leverage your AI/ML quickly, simply, and at a far lower cost.
Here are a few more advantages of this all-in-one platform:
- Simplified deployments: Push models into production with minimal effort and stick with the training frameworks your team already knows. This saves your data scientists hours of re-engineering models and frees them to focus on refining their models to drive even more revenue.
- Live ML models in seconds: With the capacity to process data in microseconds (that’s one-millionth of a second)—Wallaroo is the fastest platform on the market for production AI. You can analyze data 100X faster, react to market changes in real-time, and deploy new and improved models within seconds, not weeks or months.
- Built-in monitoring and audit: Easily understand the business value of your ML and iterate quickly using powerful metrics on real-time model performance; along with recommendations to increase revenue and detailed analytics to streamline model retraining and compliance.
- Low cost and low maintenance: With a single platform for data ingestion, analytics, and deploying ML models, you can save up to 80% on infrastructure and maintenance overhead. Plus, with the ability to run multiple models on a single server, your resources are used more efficiently for lower computing costs.
As an added benefit, Wallaroo can be deployed directly in your environment, whether that’s in the cloud, on-premise, or at the edge, and a dedicated team will help you integrate it with your existing systems. This lets your company leverage the benefits of dynamic pricing sooner, without interrupting your data scientists and engineers so they can concentrate on what they do best.
We can capture and produce analytics on unique visitors to the rental website and mobile app and subsequent conversion rate. Run your mouse over the charts to see the number of visitors or conversion rate in each five-minute interval
Real-time dynamic pricing made simple
Wallaroo essentially acts as a runway between your ML models and business value—speeding up the time it takes you to reach it. As an example, imagine you run a retail company that has already built pricing models and is using Wallaroo to deploy them so they can finally offer custom pricing on their website. Here’s what that might look like:
While a customer explores your site, Wallaroo captures their every interaction, like what pages they visit and which products they click on, along with other factors including their location and what device they’re using. The platform then shoots this information through your models to perform real-time customer segmentation and instantly determine the best pricing model to use. (See Figure 1.)
A few minutes later, the customer searches for a product to see a list of options with their prices, so they can click on the best deal. The moment they hit “search,” Wallaroo takes the customer segment, combines it with other factors (time of day, current demand, inventory, price sensitivity, etc.), and generates a list of optimal prices that this particular customer would be willing to pay. (See Figure 2.)
All of this happens faster than you can blink. This is because, unlike most solutions, Wallaroo processes incoming data in real-time (not in batches), enabling your website to display the results without the customer noticing any lag. Considering every second of delay in a website’s load time can cause a 7% loss in conversions, speeding up your pricing processing is critical to your ongoing success.
If there’s an item that’s selling too fast at too low a price, or if the customer has already seen a lower price for the same item, you can rely on the platform to catch any inconsistent prices that could hurt sales or disrupt the customer experience.
Furthermore, as new data comes in due to changes in demand or buyers’ behavior, you can leverage Wallaroo to refine your pricing models and redeploy them in seconds. This way, your customers will always receive the best prices based on the most up-to-date information, and your company can capture golden market opportunities as they happen.
Behind the scenes, intuitive dashboards let you keep an eye on how your pricing models are performing and easily understand their impact on your business. You can quickly glean conversions, estimated revenue, remaining inventory, customer segments, etc., or dig into specifics like the number of prices computed, current processing times, and audit logs.
With Wallaroo in your corner, you can confidently deploy your ML models in record time, adapt quickly to changes, and keep your customers and data team happy.
Dynamic pricing is a compelling strategy that gives the upper hand to companies that are willing to invest and experiment. With only 18% of B2B companies pricing dynamically, and even fewer doing it efficiently, it’s the perfect opportunity to take the lead in your industry with the help of a high-performing pricing system.
With the flexibility of open-source tools and the power of advanced AI/ML processing, Wallaroo enables your team to launch dynamic pricing 3X faster, with 80% lower compute costs, and 50% lower operational overhead compared to DIY solutions—giving you the best possible return on your investment.
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