Examples of implementing and observing the effects of pricing strategies in software pricing

1. EXPERIENCES WITH SOFTWARE
PRICING STRATEGIES
VikramVisweswaraiah
https://www.linkedin.com/in/vikramvi
@vikram_vi

2. OUTLINE
I’ve worked on designing and executing pricing strategies in the Telco Infrastructure Software space. While the space has been largely
dominated by on-prem perpetual software, I’ve been fortunate to have been in the position of leading transitions into subscription models and
also designing subscription only offers from scratch. Telcos increasingly run their infrastructure software on in-house virtualized infrastructure
(VMWare, OpenStack etc.).While this isn’t the same as running in a public cloud or running a SaaS model, the pricing principles are strikingly
similar. The following slides illustrate some software pricing strategies I’ve implemented and key lessons learnt.
Tiered Pricing
Every figure, model, example, and chart in this deck is my own work and based on REAL data..
Volume Discounts
Bundling
Pricing Ladders
Value Pricing
Metered Pricing
Freemium
ELA
https://www.linkedin.com/in/vikramvi
Goals Metrics
Analysis
•Objective
•Perceptive
Implement Communicate Measure
PRICING STRATEGY: KEY ELEMENTS
I use ARPU to track average revenue per unit.The “unit” is a metric of growth and does not have to be a user.

3. Basic Standard Premium
TotalRevenue
TIERED PRICING
• Middle Tier maximizes revenue
• HighestTier is an anchor
• LowestTier for insertion
In the process of simplifying the offer structure for a flat list of over 300
SKUs, I created pricing tiers after analyzing common feature usage
patterns.The goal was to maximize revenue in the middle tier (Standard),
use the highest tier (Premium) as an anchor. I analyzed bookings data
after a few quarters of implementing this strategy and produced the
accompanying chart that clearly illustrates the benefits of a properly
designed tiered pricing strategy.
Observations:
• Some customers are sensitive to gaps between each tier and you may
need one-offs to satisfy gaps.
• Communicating how to position and sell a tiered offering is key to
success.

4. Tiers
ARPU
97% deals
3% deals
0% deals
77%
deals
14%
deals
11%
deals
Length of bar = ARPU
% = number of deals per tier
NOVOLUME DISCOUNT WITHVOLUME DISCOUNT
VOLUME DISCOUNTS
The presence of pure linear pricing meant very few sales at higher
volume.This is clearly shown by the chart that indicates 97% of deals at
very low volume (albeit higher ARPU).The chart on the right shows how
the deal volume normalizes across all volumes.
Observations:
• The ARPU in lowest tier dropped with volume discount.This was a
conscious decision in product strategy
• Sales teams and customers are more receptive to purchasing at
volume – note highest volume tier had 0% deals that went up by 11%

5. BUNDLING
The presence of an unmanageable list of features led to immense friction
in selling. Sales teams and customers were confused when forced to pick
from a huge list of features. I wrote scripts to determine top features in
use and leveraged that analysis to create bundles.
Observations:
• Sales teams and customers welcomed the simplicity in product
offering.
• Sales teams were able to drive consistently high ARPU
• Units sold declined, there was no net negative revenue impact
• Better foundation to sell newer products
Product LicenseAnalysis
Feature X
Feature Y
Feature Z
…
FEATURE ANALYSIS BY USAGE
ARPU
Change
Total
Units
Net
Revenue
+82% (-48%) 0%
IMPACT OF BUNDLING
Over 3 Qtrs

6. PRICING LADDERS
Even though many teams don’t leverage pricing ladders in software
pricing, I find it a very useful visual aid to validate whether your tiered
pricing meets the observed range of customer willingness to pay. If the
ladder shows large gaps, then the pricing strategy may need to be
revisited.
Observations:
• No large gaps in ladder, products are spread reasonably evenly over
the observed range of prices customers are willing to pay.
SKUs and absolute price points are obfuscated

7. VALUE PRICING
Value based pricing is tricky. I’ve worked on a few models that attempt to
quantify the ROI to the customer. A sample worksheet that bases value
on labor hours saved is shown.
Observations:
• Customers don’t always accept the results of value based pricing
unless it already fits into their perception of what their budget or
price points are.
• Value based pricing is very defensible provided you and the customer
agree to the metrics and inputs to be used. Otherwise the model falls
apart.
Metric Current Future
Device : Personnel Ratio 1:1 3:1
FTE Labor cost ($/hr) $50 $50
Time for activity 3h 1h
Frequency of activity (wkly) 5 2
…
SAMPLE WORKSHEET
Savings of $3M, 43,000 labor hours, 73% ROIi
SAMPLE RESULT SUMMARY

8. OTHER TOPICS
METERED PRICING
It’s critical to pick the right meter.While some meters are simplistic – for
e.g. users, devices and time, some aren’t as obvious.Why is your software
useful?Where does the value come from? Perhaps it comes from data
usage or a graph algorithm that scales with usage. Designing meters
around metrics of value and growth is key.Also critical: your ability to
measure and audit the meter.There’s no point in designing a meter that
can’t be measured easily. I’ve shied away from meters that could
otherwise be valuable but just couldn’t be measured.
FREEMIUM
I’ve used freemium models as insertion strategies. Unfortunately if a
relevant feature-rich offering isn’t on the heels of a freemium offer, there’s
the risk of spending too many cycles on non-paying customers. Freemium
as time-limited promotions can be useful, but I’d be very careful in going
overboard with freemium models
ELA
ELAs are useful when there’s a very large customer with deep pockets
and you have the ability to differentiate your product within the overall
offer.The greatest risk is that of dilution; if your innovation pipeline isn’t
strong, your customer won’t see the value of your product in the ELA
and it’s likely to get devalued or discounted deeply.
Metered Pricing
Freemium
ELA
Match your meter to growth
Timing is key
Keep a strong innovation pipeline

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