How to Optimize SaaS Software Development Spend

The world has changed. Today, it’s all about PEG (Profitable Efficient Growth).

Operators must ensure their product development investment is optimized. Every dollar should maximize contribution to strategic objectives.

Investing in R&D is critical. It fuels innovation. It accelerates growth.

But two challenges remain:

Determining the right level of R&D spending
Measuring its business impact

This guide provides strategic insights to optimize your R&D budget and maximize returns.

Setting the Right R&D Budget

Let’s start with industry benchmarks.

Private SaaS Companies

Historically, private high-growth SaaS companies allocate around 24% of ARR to R&D spending.

Public SaaS Companies

Public companies invest 19-30% of revenue. The faster they grow, the more they invest in R&D.

The Efficiency Surprise

The First Round Review analyzed over 300 private SaaS firms. They found something surprising:

Top revenue generators spent much less on R&D:

Average: just 8-12% of revenue
Growth rates: still over 40%

The lesson?

Efficiency and returns matter more than sheer spending levels.

The 30% Threshold

McKinsey research shows diminishing returns beyond 30% of revenue spent on R&D.

When setting budgets, consider:

Your company stage
Target customer segments
Competitive landscape
Product type

Example:

SMB-focused vertical SaaS needs less R&D than horizontal enterprise solutions (Insight Partners).

SaaS R&D Budget — https://www.ey.com/en_us/strategy-transactions/how-saas-companies-can-protect-profits-with-product-led-approach

Evaluating Return on Investment

We all want to assess R&D investments against business outcomes.

Simple ROI Formulas

Basic productivity gauges include:

Revenue per engineering headcount
Incremental revenue vs. project costs

Better: Multidimensional Analysis

To capture full value, use models that include both quantitative and qualitative impacts.

Two proven approaches:

Total Gross Contribution & Maturity Analysis – Calculates profit generated over time while accounting for how far along projects are vs. key technical and commercial milestones (McKinsey).
Strategic Roadmap Budgeting – Compares spending to competitors, maps investments to priority product roadmaps, and tightly manages key developer productivity metrics (Andreessen Horowitz).

The reality is that simplistic ROI calculations alone miss critical factors like technological advancements, process improvements, customer loyalty impacts, and inherently uncertain exploratory outcomes. Using a few different analytical lenses provides a much fuller perspective.

Public companies invest 19-30% depending on their expansion pace – the faster they’re growing revenue, the more they tend to invest back into R&D.

Allocating Resources Strategically

Setting an annual R&D budget is just step one.

Step two is harder:

How do you distribute resources across initiatives, features, and priorities?

Roadmaps evolve. Priorities shift. Without thoughtful planning, you lose strategic alignment.

Widely used allocation frameworks like the 70-20-10 guideline suggest splitting R&D investment across:

The 70-20-10 Framework

A widely used allocation guideline:

70% – Core Product

Maintenance
Enhancements
Sustaining engineering

20% – Growth Drivers

New products
New features
Revenue-focused initiatives

10% – Innovation Bets

Speculative projects
Long-term experiments
Breakthrough ideas

However, predetermined rigid allocations often fail to respond enough to emerging market shifts and signals. Adopting more flexible allocation frameworks enables dynamically redirecting resources based on continuously validated priorities. Maintaining a pool of unallocated “innovation funds” also helps preserve agility to pivot to new opportunities as they materialize (per Insight Partners guidance).

Balancing Customer Acquisition & Expansion

Another lens to look at resource allocation is by key revenue growth drivers – acquiring net new customer accounts vs. systematic expansion of existing relationships. The prioritization across these two levers depends heavily on your underlying unit economics around customer lifetime value (LTV) and cost of acquisition (CAC).

The Rising Cost of Acquisition

CAC has risen 40% since 2019. Mid-market SaaS now averages **$400 per new customer** (CMO Council via Paddle).

What this means:

With acquisition costs climbing, you need:

Product differentiation
Strategic expansion into new markets
Innovative capabilities that open new opportunities

Action:

Allocate more R&D to innovations that accelerate payback periods.

CAC — https://www.paddle.com/blog/how-is-cac-changing-over-time

The Economics of Retention

Growing an existing account costs one-sixth the cost of acquiring a new customer (Accel).

But beware:
Over-focusing on retention slows growth velocity.

The key:
Balance is essential.

There’s also been a broader philosophical shift in the SaaS world around the importance of upsell, cross-sell, and systematic expansion motions. As OpenView articulates, the fastest growing SaaS companies “generate most of their growth not from new logos, but from expansion and land-and-expand within their existing customer base.”

The emergence of ambitious 120-130%+ net revenue retention (NRR) benchmarks further underscores the strategic imperative of robust customer growth and retention efforts. But over-rotating solely on expansion risks unduly slowing new logo acquisition velocity if you’re not still balancing continued product innovation to attract a steady flow of fresh customer relationships.

NRR — https://chartmogul.com/reports/saas-retention-report/2023/

Other Strategic Optimization Moves

Beyond smart budgeting and allocation frameworks, successful SaaS leaders also focus on a few other strategic levers to enhance the productivity and impact of their R&D investments:

Actively Monitor R&D Output Metrics:

Track key performance indicators for development velocity, quality, and deployment speed.

Critical Metrics:

Velocity

Story points completed per sprint
Measures team output

Lead Time & Cycle Time

Time from idea to production
Actual work time per feature

Defect Rates

Escaped defects
Defect removal efficiency
Quality assessment

Deployment Frequency

How often releases ship to production
Speed to market indicator

Closely monitoring trends in these DevOps metrics, as outlined in resources like Atlassian’s Engineering Analytics guide, provides visibility into team productivity. This allows management to identify bottlenecks, make data-driven process improvements, and optimize the return on R&D investments by course-correcting when needed.

Leverage Usage Analytics

Platforms like Amplitude, Mixpanel, and Pendo allow detailed tracking of how customers actually engage with and derive value from products. Going beyond basic metrics like DAU/MAU, these tools can identify top features driving retention, reveal underutilized capabilities, and surface patterns around user behavior.

Aligning R&D priorities to insights surfaced in these usage analytics ensures investments are aligned with validated, data-driven hypotheses about customer needs and behaviors. This avoids misallocations to efforts that may not resonate with the market or target segments. Accel’s Metrics That Matter playbook provides deeper guidance on leveraging these tools.

Preserve Agility to Pivot

Given rapidly evolving markets, customer demands, and continuous learnings, SaaS companies must remain nimble in adjusting priorities and budgets. Replacing rigid annual R&D planning with quarterly funding cycles enables redirection of resources much faster when faced with shifting signals.

Reserving a pool of unallocated “innovation” funds, as recommended in Bessemer’s analysis, preserves flexibility to allocate new projects or realign existing workstreams in response to new insights, changing KPIs, or identified risks. Making regular, incremental funding decisions based on the most recent feedback loops enhances agility.

Takeaways

In summary, optimizing R&D for sustainable SaaS growth means setting dynamic budgets linked to output indicators, implementing multidimensional models to analyze productivity, maintaining adaptable allocation frameworks, and basing decisions on real usage data and validated market signals. Doing so increases your overall R&D efficiency and impact.

Summary of actionable insights:

Set suitable overall budget levels based on benchmarks tailored to your specific growth stage, customer segments, and competitive landscape
Employ analysis models encompassing both quantitative outputs as well as key qualitative impacts
Structure adaptable frameworks to dynamically reallocate spending based on continuously validated market priorities
Balance investments across both new customer acquisition efforts as well as strategic expansion of existing relationships
Avoid solely over-rotating on existing account expansion at the expense of continued new customer acquisition velocity
Closely monitor key output metrics like velocity, quality, deployment frequency to course-correct as needed
Leverage holistic product usage analytics to validate investments align with real-world user behaviors and needs

References and additional reading are linked below. Let me know if you need any other guidance on optimizing your R&D investments to really drive your SaaS growth engine!