Pricing Strategy and Pricing Models - Optimizing Sales

Pricing Strategy and Pricing Models - Optimizing Sales

Pricing is your biggest lever that you probably spend the least amount of time testing and optimizing. I totally understand why – pricing is difficult to change (even when you’re small and especially when you are large), and you have to deal with complex questions of involving existing customers and even prospects in your pipeline.

But having a pricing strategy that you manage like your product roadmap has outsized rewards. You can anticipate issues, build a plan, and enable Sales to be significantly more successful. Not only will Sales and Marketing be more successful in optimizing revenue, but Sales will also be able to accelerating closing deals and really simplify the buying process for your future customers.

Pricing is a topic that comes up a lot with companies that I advise, so I thought I’d dig back into the archives and share a great resource that I haven’t published in the past. It’s based off of the Heavybit Pricing Strategy Seminar that I attended, and it’s great reminder of the impact on what to do (and what not to do) 💯.

Key Takeaways

If you don’t have time to read on, then I hope at least these key pricing lessons learned will help:

  • Pricing and packaging needs to be owned by product or product marketing.
  • Build your long term (3, 5 year) pricing roadmap and strategy from the earliest stage possible.
  • Include your best, shiniest features in your freemium (or trial and base) tier and convert based on necessary, almost boring features.
  • Increase your prices now (you are charging too little) (but do so with strategic thinking)
  • Have consumption-based pricing early, so early customers pay more during later growth. Changing pricing later is hard.

Ok, want to dig into the details on all of that? This isn’t a semi-useless blog bloat post like Hubspot’s pricing strategy, but real-world feedback on pricing and strategy.

So, the seminar was held as a series of talks and, below, I’ve gathered my notes highlighting the best and most useful pricing strategy pieces of wisdom. Hard won lessons ahead. 👇

Rainforest QA + the path to 10MM ARR+

Fred talked about the transition from early-stage growth company (series Seed / A) to more mature 10MM+ ARR (series B stage) company and how the metrics become pretty much the only thing that matters. And by metrics, that means your operational efficiency metricsCAC, LTV, COGS.

You really need to understand and tune the efficiency of delivering your product (and generating revenue) if you are going to sustain growth. Not a huge surprise, but a good reminder to use data to influence pricing and strategic decisions moving forward.

Rainforest has continued to expand on their growth, but at the time of the talk here were the details:

About Rainforest QA

  • 1x efficiency ratio
  • 80% gross margin
  • 1 product, 3 core features Series B stage / 10MM+ ARR

Making money - understanding your pricing model

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Pros/cons of some models

Some common models are:

  • Product access - pay to access a platform
  • Platform usage - metered usage that you pay for
  • Services — Selling a business process. Enterprise-focused solutions are often sold this way. As a software company be aware of maintaining 60-70%+ margins (which can be a challenge).

Contracts define the predictability of your business. Content Camel is a monthly SaaS business, so we have to earn the business. Our competitors (like Highspot and others) only do annual deals with big direct sales forces.

Typical contract arrangements:

  • Annual contracts - Good for predictability, but watch out for churn. Can hide product issues.
  • Monthly - Customer has to eval ROI before buying, so good for retention. Not as predictable as longer term deals.
  • Pay as you go - Maybe a one-time purchase or something that is bought regularly but intermittently.

Philosophy by stage

As a business evolves, it transitions from stage to stage. With each stage, the business transforms and operates based on different principles of growth. I generally talk about these as exploration -> expansion -> extraction, but here is a more detailed breakdown:

0 - 100k ARR

  • Have usage based pricing from beginning, so you can grow accounts.
    • For Rainforest, at this stage, nearly 100% were monthly recurring contracts.

100k - 1MM ARR

  • Costs increase, so margins really start to matter.
  • Using margin as a north star metric (that is, keep a focus on margins and focus on keeping them high)
  • For Rainforest: 5050 monthly vs annual contracts

Business model: is your positive margin revenue model. You are going to fail if you don’t find a positive margin model!

1MM - 10MM ARR

  • Value pricing. Start to leverage your size and scale as a business.
  • For Rainforest: 2% monthly, 98% annual. 74% product usage, 15% product access, 1% services. Full time finance team.
  • Use Efficiency scores:
    • CAC payback Efficiency score Quick ratio
    • Understand margins and revenue mechanics deeply
  • Series B is defined by the financial efficiency of the business. Pretty much the only thing that matters — your business focus, domain, etc are all veneer to evaluating the deal.

10MM+

  • CAC:LTV ratio rules everything around me (C.R.E.A.M. - CAC Rules Everything Around Me)
  • TBD for Rainforest at the point of this talk — they were just growing into this area
  • In my past businesses converting to multiyear deals – at least anchoring on MYD – unlocked the next level of growth.

More resources and next steps

Fred referenced the Jerry Chen Talk on units of value as a great resource ✅.


Optimizing for growth

Wait, that’s not all! Not even close.

Patrick from Profitwell spoke on approaches to growth and optimizing pricing as a huge lever that you probably aren’t spending enough time pulling. Mature businesses are just as guilty of this as young companies.

Some highlights:

  • Survey of 8,300 SaaS companies (Profitwell)
  • Growth is changing
    • What worked is no longer working
  • (Customer) Acquisition is now table stakes
    • 1% more acquisition only boosts bottom line by 3% and becoming less efficient
  • A focus on monetization or retention has 2-4x the impact that acquisition had
  • Customer development (non-sales capacity) is key
    • Most companies are not having 10 or more convesations per month
    • Most companies are running 0 tests per month. (Not you, though, right?)
  • New model: Capture sentiment to quantify value of what we’re building
    • Deviation from median Willingness to Pay (Y)
    • Relative preference magnitude (X)


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The dimensions for segmenting your feature value

Experimental design

It’s critical that you treat pricing just like product and run experiments. To test your assumptions. To prove or disprove what the team holds true and the understanding that forms the foundations of a ton of decisions that you are making every day.

So, develop quantified buyer personas that are data driven profiles of the customers you are targeting. Or the ones that you’re purposely ignoring! A couple of things go into these personas:

  • Demographic data (just for segmentation)
    • Stats models:
    • Relative preference
    • Price sensitivity


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Build out buyer personas to analyze and communicate who you should (and are) going after and who you are not (and shouldn’t).

If you don’t already have a persona template, I’d recommend our fantastic buyer personas template.

To run discovery on price sensitivity for your personas, you are going to learn about willingness to pay.

How to measure willingness to pay

Despite the fact that most teams skip this step, understanding the price sensitivity of your audience is one of the biggest gaps you can fill as you figure out pricing and packaging.

How do you start to understand what your prospects and customers are interested in paying?

  • Measured via surveys
    • If uncompensated, keep to < 4 mins, every 3-6 weeks. Typically 30-60 second surveys.
    • If compensated, then keep to < 15 mins.
  • Survey gathers least important vs most important selection
    • This is relative preference
    • Then, segment by demographic to understand areas to focus on
  • How much are people willing to pay?
  • This is the Van Westendorp survey methodology


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Example survey questions for pricing amount

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Max Diff survey results based on feature area

How Profitwell surveyed

  • Surveying can be relatively cheap an efficient. Don’t build the wrong product, pricing, or packaging.
  • Profitwell bought market panelists leads
    • 12 hours of work, cost for leads: $2100
  • You should be surveying customers, prospects, and potential leads. Then you segment by your buyer personas. 🙌

Packaging for scale

Amit from Datadog spoke about packaging desicions make (correctly and incorrectly) as the companies started to really scale. There are some great insights here on building a pricing roadmap – a longer term view of where your pricing can head, so you can test now.

Let’s check out the highlights.

Here was the snapshot of Datadog at the time:

  • 500 FTE
  • 6K customers
  • 100MM revenue
  • 100% YoY growth

🔥 and still are.

Scope Economies at Datadog

Enterprise scale and growth is a bit different. This is the expansion phase vs the previous exploration phase where you were just figuring out the revenue mechanics. Oh, and if you’re wondering what economies of scope means, then it’s really just that building multiple products is more efficient (and profitable) than going deep, deeper, deepest into just one product. As you grow your audience, building additional products expands your ability to cross-sell and generate much more revenue per customer.

  • Leverage existing channels for growth. You need to understand where you have the resources to focus on growth and develop your strategy to maximize your strengths while planning for the future.
  • Growth matrix: markets vs product, new vs existing
    • Market development (e.g. expand into APAC, EMEA)
    • Market penetration (e.g. invest in more sales)
    • Diversification (Refers to creating new products on new market areas. As a startup, almost non-option, too much risk)
    • Product development
    • Are we ready to leverage prod development to achieve economies of scale?


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DataDog was in growth mode and focused on product development

Datadog was investing heavily in product development. This naturally led to a lot of packaing (and pricing) decision. Here’s their thinking:

Why add new products?

  • Cash
  • Platform affinity (adjacencies)
  • Market Opportunity
  • Customers

Key considerations

  • Management bandwidth
  • Sales messaging
  • Brand dilution
  • Core platform development needs (don’t abandon the core!)

What Datadog did

  • Core platform: grew it at existing rate
  • APM (their main product): built a new team
  • Logs (another product offering): acquired a startup

Pricing considerations

  • To bundle or not to bundle? Do you bundle 2-3 products for the price of one, or is everything purchased separately?


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To bundle or not to bundle. Existential questions.

Amit highlighted some key takeaways from the experience at Datadog:

Key highlights

  • Timing of scope economies is important
    • You need to earn your right to expand. Most expand too early, dividing their focus.
  • Remember customer benefits
  • Bundle with caution

Operationalizing Pricing

Christina (Interana, Splunk Zuora) has a fantastic perspective on putting pricing and packaging in place. Something that’s hard to do in practice, but always necessary.

What can we learn?

Pricing Givens

  • Price is part of the product
  • Price must be standardized for successful freemium and trial models
  • Standardized prices are now key to top-down models too
    • New rev rec rules
    • Most favored nation (MFN) clauses
    • Hardcore purchasing departments
    • IPO roadshows - being able to explain the business model

Pricing Ops Highlights

  • Fixing core pricing model in market is painful
  • A pricing model is not a price list
    • But a price list is required
  • Goal of pricing is to maximize the market, not the deal
    • You will leave money on the table for a given deal and walk away from others

Every price list has…

  • SKUs
  • Fixed product definitions
  • Fixed list prices
  • Explicit policies (discounting, mid contract upsell, downsell, MFNs)

Pricing model

  • E.g. Perpetual, annual, subscription
  • Products, editions, and optional features
  • Units of measure
  • Anchor price points
  • Volume structure: platform fee, tiers, packs, usage


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Pros/cons of different pricing models

How you make a pricing model

  • Shining jewels as part of free plan 💎
  • Choosing your units:
    • Proxies for customer value vs impediments to adoption
    • What units do incumbents use?
    • Ability to reliably measure that unit?
    • Future roadmap impact on consumption of that unit
    • This is where CTOs get involved in pricing
      • e.g. Future roadmap item delivered might actually reduce consumption, thus yielding unintended price cut
    • Unit economic constraints in your offering — just a check and balance (bc value based)
  • Set your price point
    • Desired starting point and price at key scale points
    • Value to customer - your observations or theory, not what customers say, not just now but roadmap
    • The value / ROI that you are designing toward
    • Incumbents, GTM Model & purchase process - a $2500 deal vs $25k vs $100k+ mechanics
    • Plan ahead
    • What does a v4 of the pricing look like to do bigger deals?
    • Key takeaway here is to design a pricing model roadmap far into the future


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New product pricing: it's not easy

Price point dilemma for new products

  • Will the price points result in enough deal velocity in your target markets today?
  • Vs can you build a big enough business at these price points to b a valuable company in the future?
  • Possible solutions:
    • Trojan horse: customers today have no idea how much they will consume later
    • Future premium editions / add-ons
    • Price increases as product matures
    • Competitors will likely force you to reduce prices. “Good enough” competitors

Volume structure

  • Don’t bypass the math
  • Has to be rational to pass enterprise purchasing scrutiny
  • Increasing rate of decline of marginal cost expected
  • Exceptions must have logical justification - inflection points of complexity
    • Platform fee could work here
  • Tension between “round numbers” and logic

And if you’re thinking free / freemium plans, then definitely keep this in mind:

  • Freemium - make your first price point the same usage as your free product, so you’re selling on features only
  • Make the boring features the push to premium: access controls, alerting, automation

Decisions made at Splunk

  • Annual or perpetual: Annual
  • Starting price point: $2,500/year (many in company wanted $250)
  • Unit of measure (UoM): GBs of log data “indexed” per day
  • Volume structure: Tiers 500MB, 2GB, 5GB with declining marginal cost


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In the presence of giants

Did not matter

  • Customers complained about pricing loudly and in public
  • We couldn’t win low value high volume commodity deals
    • e.g. firewall data
  • Some customers had bursty or seasonal data volumes
  • We were “missing features” that enterprise customers “needed”
  • We didn’t have a “product line” or “add-on products”

Rollout

If you’ve come this far, your’re on the right path, and I hope it’s been helpful. 🙌

Final words:

  • Treat pricing as a product and pricing updates as a project.
  • Everyone cares about pricing, so build a team-wide coalition and shared understanding. Develop pricing briefs and share updates.
  • Get the business requirements from all across the business. Don’t forget sales ops! Don’t forget engineering!
  • Are the systems ready to meet the requirements? Pricing spans product, engineering, finance, sales, marketing — everywhere. You can’t roll out new pricing if you don’t have the infrastructure to support it across your org.
  • Implementation is harder than strategy!


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Price for scale now (and increase your prices!)