Nakul Mandan - Partner / Lightspeed Venture Partners at SaaStr Annual 2018 What are the qualitative metrics VCs look for in a Series A? And how can you pre-emptively address those questions in your pitch?

1. BEYOND THE
METRICS: WHAT VCs
LOOK FOR IN AN
EARLY STAGE SaaS
STARTUP?
NAKUL MANDAN
|PARTNER, LIGHTSPEED
VENTURE PARTNERS

2. INGREDIENTS OF A GREAT
ENTERPRISE SOFTWARE
COMPANY Generic answer: Market + Team (duh!)
 Five questions I ask:
• Why now?
• Product/category: Role of product in the buyer and
user’s life?
• Market size: current and extensible?
• Is there an efficient go-to-market / distribution
strategy?
• Long term moat: Data / Network / Engagement. What’s
the lock in?

3. WHY NOW?
 What macro trends are coming together to
make this opportunity happen right now?
• Demand / Supply side?
 Is the user behavior changing to create this
market opportunity?
• Has the user/buyer been trained recently to
look for the solution you’re offering?

4. PRODUCT / CATEGORY
 Role of product in the buyer and user’s life?
 Is it mission critical?
 Is there an opportunity to evolve the product
into a platform?
 Is there an opportunity to be sustainably
differentiated?
• If not, is there at least first mover
advantage?

5. MARKET SIZE
 Always size the market bottoms-up: # of target
customers x customer budget for this problem
 Is the customer willing to pay up for the best
solution?
 Can the addressable market be expanded over
time?

6. GO-TO-MARKET
STRATEGY Is the buyer already in the market looking for a solution?
 Is there a way to establish viral / word-of-mouth based
distribution?
 Is the customer budget for this problem enough to justify the
sales and marketing investment?
 Key business decision to make: Which segment to focus
on + pricing?
• Oft-repeated mistake: Take any customer who agrees to
pay something!
• Important to figure out which segments don’t matter to
the long term success of the business

7. LONG TERM MOAT
 Is there a network or proprietary data based
moat?
 Does feature parity imply product parity?
• Not good, if so!
 Can scale beget scale?

8. CASE STUDY: GAINSIGHT
 Why now?:
• Tech business model has moved to X-as-a-service
• Availability of data to track usage / other indicators and predict churn
• Companies can’t afford to have unhappy customers in the age of social media
 Role of product:
• System of record for account managers – they run their business through it
• Daily use case – once onboarded, cannot live without Gainsight
 Market:
• Starts with recurring revenue companies
• Expands to all repeatable revenue companies
 Go-to-market:
• Build a community around customer success. Become the default player in the
space
 Long term moat:
• Build a brand that is strongly associated with the customer success community
(eg: customer success university launched by Gainsight)

9. THANK
YOU
Q&A