Opinions on discounting are endless. Some companies will do anything to close a deal, while others openly market their no-discount policy. 

The benefits of discounting are obvious; the customer feels appreciated, and the sales team can squeeze in extra deals.  But no one really knows what the right discount amount is. 

At Cacheflow, we were curious about this too. So we decided to analyze 10K SaaS proposals to find out what effect discount ranges have on deal amount and number of days to close.

Methodology and findings

Our analysis categorizes discount percentages into five ranges: 1% to 5%, 5% to 20%, 20% to 30%, 30% to 40%, and above 40%.

This data comes from a randomized sample of 10,000 proposals that were created in 2023 from Cacheflow customers. These companies are all global SaaS companies, ranging from 5 to 500 employees. 

The ‘average days to close’ window starts the first time a proposal is viewed by the prospect and ends the day the deal is signed. This isn’t meant to reflect the entire ‘sales cycle’ length which can start well before the proposal is sent, depending on which market you serve. 

Analysis of Discount Bands

Lower discounts (1% to 5%) result in quicker closures: Deals with discounts between 1% to 5% close the quickest (average of 3.11 days) and also have one of the highest average deal sizes. 

Moderate discounts (5% to 20%) enhance deal size: Deals that offer discounts in the 5% to 20% range take longer to close (8.33 days on average) but achieve a higher average deal size ($13,778.56). 

High discounts (20% to 40%) and their impact: Surprisingly, the 20% to 30% discount band has a shorter closure time (5.27 days) but a much smaller deal size ($7,290.73) compared to other bands. Deals with 30% to 40% discounts take significantly longer to close (14.26 days) but have a somewhat higher average deal size ($8,685.75). 

Excessive discounts (above 40%) lead to lowest sized deals: The highest discount band (above 40%) results in the longest closure times (11.51 days) and the smallest deal sizes ($4,415.97).

SaaS discounting insights

Discounts less than 20% close almost 2x faster for 2x the amount

You would think that higher discounts incentivize faster decision-making, but our data shows it's the opposite. Deals with only 1% to 5% discounts had the fastest average days to close - and 5% to 20% had the third lowest overall. 

It's likely that some companies are ‘discount shopping’ vendors once you go above 30%, and therefore take longer to close. It’s important to remember that buyers work on their own schedule, not your company's quarterly calendar. So extreme discounts to hit quota in crunch time may actually hurt you more than help. 

Deals below $5k are very price-sensitive

We spoke about small SaaS deals being very price-competitive in the SaaS Proposal Study #2, and our data reaffirms this. The average deal amount for discounts over 40% is only $4200 ACV. 

Vendors selling annual contacts under $5k are often not differentiated enough in an already crowded market, and therefore a race to the bottom on pricing occurs. 

Larger SaaS deals often focus more on selling clear value and ROI to their enterprise customers, and because it's a differentiated offer, it can command minimal discounts and a shorter time to close.

Recommendations for SaaS discounting

Optimize discount levels: 

Finding the right balance in discounting is crucial to maximize deal size without unnecessarily prolonging the sales cycle. Moderate discounts (5% to 20%) seem to strike a good balance for most deal sizes.

Customize discounting based on expected deal size: 

For larger, more complex deals, consider minimizing discounts as these deals tend to close without the need for significant price reductions. Focus on delivering value and building relationships to close these deals.

Review and adjust high discount strategies: 

The data suggests that very high discounts do not necessarily lead to faster closing times and can, in fact, result in longer sales cycles. Review strategies around high discounts to ensure they’re attracting good-fit customers. 

Leverage data for predictive sales insights: 

Use AI and analytics tools to predict the optimal combination of deal size, discount level, and expected closure time. This can help in forecasting revenue and refining sales tactics to meet targets more efficiently.

Implement targeted sales training: 

Equip sales teams with insights and strategies derived from the analysis. Training should focus on understanding the impact of discounting on sales outcomes and how to negotiate deals that optimize for both speed and deal size.

Software to help you price SaaS deals

While navigating discounts with a prospect may be hard - quoting, billing, and tracking them is even harder. 

But there's good news – Cacheflow makes SaaS discounting easier. Our CPQ allows for ramped discounts, rules-based discount approvals, one-time list price editing, and the ability to display or hide discounts in your quotes. 

Sales leaders can quickly see discounts by rep, product, or geography. Finance managers can see the same data in their ERP, and save 10+ hours per week digging through the CRM, invoices and email chains. 

Book a Cacheflow demo to see how you can take control of SaaS discounting! 

To learn how number of proposal views affects sales win rate, check out the SaaS Proposal Study #1.

To learn how deal amount affects sales win rate, and average days to close, read the SaaS Proposal Study #2