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Navifleet, a leading SaaS player in telematics and fleet management, was established in 2012. The company developed an innovative platform that simplifies fleet management for businesses, catering to over 1500 clients ranging from local enterprises to multinational corporations. Their dedication to continuous improvement sets them apart, consistently exceeding client expectations.
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Working with Valueships was a great experience. Their expertise in SaaS pricing and deep understanding of our challenges were evident from the outset. Their analytical approach, combined with an insightful communication strategy, not only drove our MRR significantly up but also ensured customer retention. The team at Valueships didn’t just provide a solution; they equipped us with tools and insights that will benefit us for years to come.
While Navifleet operates a dual business model consisting of hardware and software, the significant challenge lies predominantly in its software segment. Their pricing model had remained static for years, potentially affecting their competitiveness. Sales costs were escalating, and they were on the verge of launching new product enhancements.
The existing pricing structure no longer reflected the value provided, especially given the diverse range of use cases they addressed. The complexity of more than 15 functionalities in the "choose your own module" system compounded the issue. The industry's fluctuating nature, influenced by varying fuel and car prices and inflation, added further challenges.
The CEO and the extended leadership team at Navifleet believed their pricing no longer reflected the value they provided to their customers, especially considering their product development journey. Thus, we were engaged to assist with both SaaS packaging and pricing.
Given the multifaceted challenges, our traditional survey approach was deemed unsuitable due to the varied user personas. Instead, we focused on Navifleet's internal data, analyzing the business's current state, including legacy pricing and discounting policy patterns.
We delved into the different use cases supported by Navifleet, discerning which customers utilized which functionalities. Our investigations revealed a prevalent discounting and grandfathering policy. Transitioning to probability modeling, we leveraged machine learning to understand combinations of functionalities that customers often purchased together.
This analysis helped identify high, medium, and low upsell potential functionalities. A key challenge was ensuring no customer faced disproportionately high universal price hikes. Our primary principle was to structure the pricing to allow multiple minor price adjustments reflecting the value provided while minimizing major price changes. Considering the sector's challenges, significant price hikes presented a high risk of customer churn.
To mitigate this, we:
1. Segmented price increments
2. Modeled potential churn
3. Created a calculator.
This tool predicted customer reactions to different price change scenarios. Once we identified price adjustments that corresponded to value and maximized revenue potential, we gauged the acceptable churn risk for our client.
To minimize churn resulting from the price increase, we developed a tailored communication strategy. This involved segmenting clients based on size and potential churn risk, then customizing our communication — the language, channels, and contingency plans for any adverse reactions.
We also conducted a workshop with Navifleet's CSM team, equipping them with tools, training, and guidelines to communicate the changes effectively.
Interestingly, our segmentation identified ten distinct client groups. One segment, even without direct price changes, was informed about the overall pricing adjustments. This proactive approach was well-received and likely enhanced our retention efforts with this group.
The results were exceptional, with Navifleet's Monthly Recurring Revenue (MRR) witnessing a 25% surge, even after accounting for churn.
We observed a temporary increase in churn for just one month, after which it reverted to its usual level, highlighting the effectiveness of our strategy. Armed with actionable insights on value and a data-backed rationale, Navifleet confidently navigated the pricing transition, prepared to address any concerns.
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+25% increased MRR
Stable customer retention
We worked only on internal data
Tailored communication strategy to current customers
We identified high, medium, and low upsell potential functionalities
