RedSwan Intelligence started out as a social listening/generic media monitoring tool and then steered into the direction of market intelligence. We wanted to launch it through a SaaS launchpad like Appsumo or Pitchground. These launchpads help SaaS companies raise funds from customers by selling lifetime deal offers for the software. While a launch like this helps avoid fundraising hassles, getting the unit economics right is essential. I’m going to pen down the approach we took while pricing RedSwan and preparing for the LTD launch. Keep reading –
My approach was as follows:
- Estimate Cost-plus based pricing
- Estimate Competition based pricing
- Try to evaluate Value-based pricing
- Prepare a cash flow model and use different pricing options to estimate projections
Finally, I used the results from Cost-plus based pricing, competition-based pricing along with cash flow projections to decide the final pricing for the LTD launch. The first step was to bring our unit economics under control and I started with cost-based pricing.
Cost-plus based pricing
With our first launch, we expected 500 – 1000 customers including SMEs and agencies in the first month. I calculated the numbers for our unit economics accordingly.
The steps I followed were –
- Calculate the fixed infrastructure cost per month: We used AWS services to build our product and fixed infrastructure meant EC2 instances, ElasticSearch instances, S3 storage. These costs are not truly fixed but increase with every 500 new customers. However, we can consider it fixed between intervals.
- Calculate the variable infrastructure costs: These vary with the number of signups/projects/users or amount of usage. These services included Cognito, Lambda, API gateway, Dynamo DB, SNS, etc.
- Calculate costs for external APIs: We used many external APIs to collect content and data from different platforms like Twitter, Youtube, News aggregators, Reddit, Blogs aggregators, etc. We also had APIs which provided firmographics and technographic data about companies. External APIs can be expensive and should be priced in very carefully while paying attention to their different tiers.
- Total the costs and find the cost per customer: Calculate the variable costs for 500 customers and add the fixed costs to it (We take 500 customers to maximize the total cost per customer). Divide the total cost by 500.
- Calculate the marginal cost per customer: Calculate how much it would cost to add another customer over 1000 customers.
I didn’t intend to use cost-plus based pricing to calculate the final pricing for the product. However, I calculated it to get an estimate of our unit economics as well as profit margins.
After considering all our external API costs and software infrastructure costs, a very rough estimate of the cost of running an active license on our platform was $3 – $5/month. Our costs would vary with the amount of activity per customer and there was no way to be sure of the actual costs. Thus, we used the higher end to calculate our pricing.
Note: To calculate variable cost per customer and external APIs costs, I had to put a hard cap on the usage per user and per project created on our platform. Pricing made me recreate our tier plans and add limits to them.
Links to sheets for reference:
Competition Based Pricing
It is easy to understand competition-based pricing and find the data to calculate it. However, it can become tricky when different SaaS products have different types of plans and packages, even if they are similar products. To complicate it further, my competitors had different types of limits on their plans. Some had hidden limits.
Moreover, there was a difference in the number and type of sources that each product covered. Another variation was in the amount of analytics and the accuracy of them. This can be thought of as the quality of the software.
I followed the following steps to conduct competitor research:
- Made a list of competitors and segmented them according to their feature sets and ranked our product against them.
- Used G2 ranking to rank competitors in their capabilities and individual features. This is a quality comparison.
- Found the latest similar product that had done a life-time deal. It gave us the closest estimate for the pricing that we could use.
Ranking the competitors gave me a range that I had to price my product while a similar lifetime deal gave me a good benchmark.
Link to sheet for reference:
RedSwan Intelligence Competitors
Value-based pricing
Value-based pricing gives the best premium for any software and enables the product teams to truly create value for their customers. However, establishing value requires case studies and successful pilots. Further, it is comparatively easier for products that impact revenue directly to justify value-based pricing. For products that improve the efficiency of teams and have an indirect impact on revenue, it becomes even more important to justify value before using value-based pricing.
RedSwan Intelligence improves the performance of marketing and PR teams and reduces the time they take in daily research, creating reports, and tracking competitors. However, we did not have any famous companies as pilots or successful case studies to use as the basis for value-based pricing.
Since I could not justify the value-based pricing, I used the competition based pricing as it provided a good benchmark and a proxy for the value we provided to our customers. Competition based pricing also provided us a fair margin over the cost-plus based pricing that we were comfortable with.
Pricing for LTD launch using cashflow projection model
Our launch strategy was laid out for the next 12 – 24 months. An LTD launch is usually followed by a reduced yearly price launch which is followed by regular yearly offers. I decided to do a 3 part launch –
- Launch with our LTD partner – Close to 4 months process and then continue to partner with them for marketing and advertising.
- Launch on ProductHunt – Leverage the community built through LTD launch to do a bigger reduced yearly price launch on ProductHunt. I expected the visibility from the ProductHunt launch to give a boost for the next 2 months. For ProductHunt, I had kept a special discounted yearly price.
- Launch on other communities – There are various product communities and marketplaces that I planned to launch on after ProductHunt at regular reduced yearly prices.
- Regular sales and yearly prices – The above 3 launches would go on for a year. Afterwhich, we would shut down discounted offers and focus on shifting to value-based pricing.
Doing an LTD launch on a SaaS product is risky as it goes against all the conservative principles of cash flow management. However unreliable cash flow projections are, I decided to build one to understand how sensitive our business was to a variable number of signups and our pricing. To keep it simple, I used only the annual pricing of the software. I have also used very discounted salaries for our team as costs and should be adjusted to reflect yours. I’m going to share the cash flow model sheet I built in the end so that you can make use of it to build yours.
Some terms to understand the cash flow model:
- Months of reserve for LTD users: We decided to store a part of our raised funds as a reserve to pay for the running costs of the lifetime users. We decided to keep 6 months of the reserve.
- LTD price per license: The price at which we decided to sell an LTD license.
- Recurring yearly price for Producthunt: Price at which I wanted to list on ProductHunt
- Yearly plan afterward: Reduced yearly price for other product communities
- Yearly plan in the second year: Price I expected to be able to sell in the second year.
- Product operation cost per license per month: Average Estimated cost of an active license
- Customer Acquisition Cost in the First year (in % commission): Our launch & marketing partner charged a commission on the revenue that they generated.
- Customer Acquisition Cost in the Second year (approx. % com): In the second year, we expected our costs for customer acquisition to reduce to 30% commission.
I adjusted our signups numbers to get 2 projections – realistic projections and pessimistic projections. I do not claim that these projections can be completely relied upon. However, these are the closest we can get to a realistic projection. Most LTD launches are done as a leap of faith. Many LTD launches fail either because the product isn’t ready to handle the incoming flow of signups and support requests or the community rejects the software because it is too niche. We floated somewhere between trying to plan for these 2 potential crises and never did a lifetime deal launch.
Important Insights from the LTD community:
- Only 20-30% of LTD customers actually use the software.
- The average lifetime that an LTD customer uses the product for is less than a year. A very small percentage of customers use it for more than a year.
- LTD launches should be used to build the initial feedback loops with the customers instead of used solely for raising funds.