How IoT businesses should approach consumption pricing models

As the Internet of Things (IoT) continues to grow—to a projected 29 billion devices by 2030—organizations are grappling with how to appropriately monetize their corner of this global infrastructure.

Many companies are embracing IoT in order to capture more data about their customers, developing key insights into user behavior and product performance that can shape critical business decisions moving forward.

But as IoT expands, many companies are unsure of how to find ways to generate revenue from these services directly. Traditional pricing models either don’t apply or aren’t effective when it comes to monetizing interconnected services and devices on a large scale.

When it comes to pricing strategies, IoT providers need to explore what works best for their bottom line while demonstrating value to their customers to influence long-term commitment and payment.

In this article, we’ll explain how to create a consumption pricing strategy as an IoT business, including what it takes to generate revenue, justify ROI, and support go-to-market models that you need to succeed.

Defining a flexible approach that suits your business—and your customers

Just like IoT more broadly, there is no one-size-fits-all approach to pricing out these services for consumers. However, what does seem to work across a variety of business priorities, industries, and sizes is a flexible framework that takes into account the consumer’s perspective and usage.

Relying solely on basic consumption-based pricing models, such as pay-as-you-go or tiered with overage, may be tempting since it provides a universal approach. And on paper, these seem easy to roll out across a wide variety of consumers and usage tiers. But many brands find that testing what works best for their customers and creating a more curated approach to pricing serves them better when it comes to demonstrating value and achieving retention.

Consider the range of circumstances and customer journey milestones that monetized IoT needs to cover:

  • When prospects have converted to customers
  • When customers have upgraded
  • When and how to consolidate renewals
  • What a renewal customer profile looks like
  • What a churned customer profile looks like
  • When to save an in-danger account from churn

Finding the right tools to power decision making

Analyzing behavioral trends and applying machine learning models to help signal critical events or junctures in the customer journey can empower IoT brands to more accurately and adeptly monetize their catalog. But for many IoT companies, there are limited pricing and packaging options available to allow them to capture incremental revenue or support customer demands.

This is where using the right tools to guide decision-making and strategy can go a long way in maximizing revenue from existing customer accounts. Solutions that blend support data with sophisticated device data, alongside transactional information, can help account managers see a snapshot of how—and how much—individual customers are using solutions.

Often, the tools that brands use to capture usage data and provide IoT solutions can contain valuable insights. Exploring whether the information obtained about how customers interact with and consume services can provide insight into how to gain more revenue from those existing accounts.

By combining device utilization with purchase history data, companies can project a more accurate account of business impact before customers make their next move.

The best solutions unite customer behavioral and purchasing data in a single platform that allows businesses to target the appropriate customers at the right time for upsell and cross-sell opportunities. This can be difficult to achieve if you’re relying on a transactional system such as an ERP that is only designed for a single purpose.

In fact, many ERP systems rely on extensive, involved, and slow-to-deploy customization that IT professionals can struggle to customize. Turning toward purpose-built solutions rather than fighting to customize existing ERP platforms can be both more expedient to deploy and more cost effective in the long term.

Related: 10 things you should know about your ERP revenue module

Cultivating a pricing strategy you can count on

Adding dexterity to pricing models can go a long way to capturing additional revenue in line with consumer behaviors, rather than relying on the rigidity of solely consumption-based pricing. Curated pricing strategies formulated on a business level, not an industry expectation, can be deployed to integrate both usage and non-usage based charges that bolster the bottom line for any business.

When developing your own pricing strategy, keep these tips in mind to ensure your plan is flexible and practical for both your business and your customers:

  • Remember that net retention is the most important metric for a recurring revenue business.
  • Consider how to make more direct revenue as a result of providing IoT as an add-on service.
  • Integrate non-usage charges to reduce variability for the customer and improve revenue predictability for the organization.
  • Determine how much of a commitment (and payment) can be collected up front to create account predictability.
  • Define metrics that mirror your unique business goals rather than relying on historical data to dictate success.
  • Explore efficient ways to collect payment from customers with more of a direct-to-consumer approach.
  • Deploy comprehensive software solutions that map how the billing relationship has evolved over time.

Pricing as a study in flexibility

Leaders are often surprised not only by the new ways they can maximize revenue through flexible pricing strategies, but also by how much flexibility they have to make changes along the way.

The idea of failing fast is something you hear a lot in the SaaS world, but not as much in regard to IoT. But it’s just as critical. A mentality where an organization embraces change and uncertainty with an openness to failure can lead to greater success in the long term.

That’s because issues are identified in real-time based on real-life scenarios, allowing leaders to make critical decisions and realize the right path without customization but with configuration changes.

IoT leaders have been slower to adopt a fail-fast strategy, but those that do find the flexibility of learning through go-to-market experimentation can give their business an advantage in terms of agility, adaptability, resilience, and more.

Implementing a purpose-built tool can support this responsiveness, helping businesses adjust on the fly as they determine the pricing structures that work for different customer segments. For some, a recurring model may work better, while for others a usage-based approach is more successful. And an increasing number of companies are finding success in implementing hybrid consumption models, which combine usage and recurring charges.

These tools can support going to market with different strategies, freeing leaders from the necessity to commit to a consumption-only pricing model.

The result can be a pricing approach that integrates directly with the customer journey as it exists and adapts to customer behavior patterns based on key segmentation details, leaving brands with huge value when it comes to product organization.

Related: The Goldilocks rule of consumption pricing models

Find a monetization model for your IoT business

Choosing a consumption-based pricing model, or developing a combination of pricing strategies, can be daunting for companies accustomed to more rigid models that fit the offerings of the past. But current IoT monetization lends itself to flexible approaches that can be meted out by technology designed to manage those complexities.

The right monetization platform can help businesses create new income streams with novel options for pricing and packaging services with recurring revenue in mind.