Tactyc - a platform to visualize Excel models. Need help in thinking about pricing.

I've built Tactyc: a platform that transforms Excel models into interactive dashboards. Just load an Excel model, pick the inputs and outputs you care about and go. Tactyc will run detailed sensitivity analysis, Monte Carlo simulations, tell you which inputs are most important, and even allow you to control the model with simple sliders from a browser.

  • The target market is the financial modelling space - investment banks, hedge funds, consulting firms etc. as Tactyc can save them hundreds of hours in sensitizing and analyzing models that they deal with on a daily basis.
  • The key differentiator for Tactyc vs. Tableau/PowerBI/AirTable etc. is that Tactyc can actually analyze the formulas and logic inside a spreadsheet (i.e. a model), while Tableau and friends are only mostly focused on raw data.

I am struggling however on how to price this or even come up with pricing comps. I am thinking a per seat pricing of ~$10,000 / seat / year with a minimum number of X seats.

Questions for the community:
- Does $10,000 / seat sound crazy high (or crazy low?). The pricing datapoints are all over the map
- Should I have a free or low-cost consumer option? Benefit of this would be more awareness of the product, but the disadvantage is lower pricing potential on the enterprise side

AnujAdhiya's avatar
3 years ago

A likely reason for your struggle is that you don't quite know what the value metric for your product it.

Rather than all the questions you posed, I would suggest figuring this metric out first. It will guide you to a pricing strategy that makes sense.

Here's an MVP process to figure it out:

  1. Target 3-5 buyer groups to test
    Identify groups
    What do we believe they value?
    What do we believe they don't value?
    Willingness to pay

  2. Give each buyer cohort a persona
    Naming convention [group attribute] [first name]
    Assign descriptions — both demographic and behavioral — to each persona.
    For eg things like:
    Size (small/medium/large)
    Their annual revenue
    Level of sophistication
    What they care about most

  3. Collect data from potential customers that fall into each of these personas: features and price sensitivity — with a relative preference methodology.

a. Feature preference surveys to understand:
Out of these n features, which one is most important?
Out of these n features, which one is least important?

b. Price Sensitivity surveys (can be combined with feature preference survey)
To understand willingness to pay:
At what point is this way too expensive that you would never consider purchasing it?
At what point is this starting to get expensive, but you'd still consider purchasing it?
At what point is this a really good deal? (You'd buy it right away.)
At what point is this way too cheap that you'd question the quality of it?

If issue with sample sizes for each persona, use any of these services: Instantly, Fulcrum, Ask Your Target Market.

7 points
Wahidtashkandi's avatar
@Wahidtashkandi (replying to @AnujAdhiya )
3 years ago

8/10 times someone quotes Price Intelligently they've said it all. The only thing I'd is that you should be iterating on your pricing every 6 months ideally. Customers are evolving, competitors are evolving, you're evolving and also as time goes on you learn more and more.

Price Intelligently have also posted some content around this. On our side at Paddle we also seen that Sellers who do iterate on pricing have the best understanding of their positioning, value and customer perception as the pricing exercise forces you to deeply understand each of those elements.

2 points
maguay's avatar
@maguay (replying to @AnujAdhiya )
3 years ago

This reminds me of Superhuman’s work at finding product/market fit, and Superhuman founder Rahul’s AMA answer here about how Superhuman decided to charge $30/mo. for their email app. That answer includes a number of resources to help determine the price people would pay for your product, and how loyal your customers are.

1 point
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