3 Trends in Marketing Technology

Earlier today I had a chance to talk at the Geek Out on Marketing Technology event and one of the topics was MarTech trends. With 4,000+ marketing technology companies, there are a number of excellent trends in the market.

Here are three trends discussed:

  1. Machine Learning – Take large amounts of data and find patterns and actionable insights that just weren’t possible before. Machine learning is the ability for computers to learn without being explicitly programmed. Think of all the applications in marketing from improving campaigns to targeting the best-fit accounts.
  2. Account-Based Marketing – Target named accounts with the right message at the right time. With account-based marketing, marketers are able to proactively engage with accounts that haven’t come through the traditional channels.
  3. Customer Data Platforms – Marketing is more than campaigns to attract prospects. Marketers are now expected to help guide the entire customer experience from first touch to signing as a customer to renewing at a future date. Customer data platforms pull in data from all the customer facing functions — sales, marketing, support, customer success, etc. — and provide a holistic view of the account as well as next actions to take.

It’s a great time to be in marketing technology and look for these three trends to grow in importance over the coming years.

What else? What are some more trends in marketing technology?

Build Sales Capacity in Advance

Nakul Mandan has an excellent tweetstorm on the importance of building sales capacity in advance of growth. The idea is that startups get caught up in the here and now and don’t start hiring and training AEs, SDRs, and SEs soon enough for the long term goals.

The solution: plan 24 months in advance. Figure out the sales metrics and model the sales rep ramp.

When the startup is scaling fast, build sales capacity in advance.

Standard Sales vs Account-Based Sales

With the basics of Account-Based Sales for More Predictable Revenue in place, next comes a deeper explanation as to how “standard sales” differs from account-based sales. First, let’s start with an example.

At Pardot, every August the new Inc. 5000 would come out and Account Executives (AEs) would would go through different relevant categories like software and claim “ownership” of any new accounts on the list that weren’t already in the CRM. Then, they’d go in to LinkedIn (or LinkedIn Sales Navigator) and find the right people based on their department and seniority level. Next, using a scraping tool like LeadIQ or Hunter, the names in LinkedIn would be turned into CRM leads with email addresses. Finally, the AEs would call and email the leads a few times, giving up quickly if there was no response.

This outbound approach, combined with following up to any inbound leads, represents how the majority of companies do standard sales. A few characteristics of standard sales:

  • Reps do both prospecting and selling (no distinguishing between SDRs and AEs)
  • Reaches out to any company that’s loosely relevant
  • Builds a list of two or three people per company
  • Sends an email or two personally and/or makes a phone call or two to each person on the list with generic messaging (most reps give up too early)
  • Treats all companies the same

Now, contrast that to the characteristics of account-based sales:

  • Prospects via SDRs and sells via AEs (specialization of skills)
  • Reaches out to accounts only if they fit the ideal customer profile
  • Looks for every relevant decision maker at the account and has them bucketed into a specific persona based on department and seniority level (e.g. marketing director)
  • Runs a coordinated engagement cadence that involves multiple people in the organization (e.g. the CEO reaching out to the CEO, the marketing director to the marketing director) with persona-based messaging that’s relevant and timely with 10+ touches per contact over time
  • Treats each account uniquely using a system that manages Tier 1, Tier 2, and Tier 3 accounts via a predictive marketing platform (e.g. Tier 1 accounts get 120 minutes of effort per month, Tier 2 accounts get 30 minutes of effort per month, etc.)

Standard sales is more “spray and pray” while account-based sales is targeted and deep.

Entrepreneurs would do well to initiate an internal shift to account-based sales and deliver more predictable revenue.

What else? What are some more thoughts on standard sales vs account-based sales?

Quick Notes on Fast-Growing SaaS Startup Intercom

Intercom is a fast-growing SaaS startup that provides customer communication software for doing live chat, in-app customer messages, email triggers, helpdesk support, and knowledge base content. Their CEO recently published an interesting blog post titled Vanity metrics, the future, and 100,000 thank yous with a number of interesting metrics.

Here are a few notes on the blog post and Intercom:

  • Started in 2011 (source)
  • Took four months to raise $500k (source)
  • Raised $1M angel round in 2012 (source)
  • Raised $6M Series A in June 2013 (source)
  • Raised $23M Series B 30 months after starting the business (source)
  • 7,000 paying customers after four years (source)
  • 50% of the 280 employees are in product and engineering as of last year (source)
  • Raised $35M Series C four years to the day they started the company (source)
  • Raised $50M Series C-1 in mid 2016 for a total of $116M (source)
  • Took two years to hit $1M in annual recurring revenue
  • 300+ employees today
  • 100,000 monthly active users
  • 400,000,000 customer conversations per month
  • Educate, the knowledge base product, is at $1.5M ARR
  • 17,000 companies that are paying customers
  • Grew from $1-50M in ARR in three years ($2,941 average revenue per year per customer)
  • Revenue run rate at end of year:
    • 2013 – $1M
    • 2014 – $7M
    • 2015 – $22M
    • 2016 – $50M
  • 2016 operating margin of -36%

Impressive metrics all around and easily one of the fastest growing SaaS companies in the world. Congrats to Intercom on reimagining customer communication for the modern business and building an incredible company.

The Golden Metric for SaaS – $1 Burned for $1 of Recurring Revenue

Thinking more about the post from a couple weeks ago titled Evaluating a Startup Based on Cash Burned vs Recurring Revenue and how the same idea was brought up again two days ago in Bessemer’s 2017 State of the Cloud Report, I’ve come to believe that $1 of cash burned for $1 of net new recurring revenue is the Golden Metric for SaaS.

As an idea, it’s easy to understand.

As a metric, it’s easy to track.

As a way to create value, it’s excellent.

As a benchmark for entrepreneurs to measure against, it’s perfect.

Some startups will choose to burn more than $1 for each $1 of new new recurring revenue, but most won’t have that luxury. Startups that achieve scale, and burn $1 (or less!) for every $1 of net new recurring revenue, will do well for all stakeholders involved.

What else? What are some more thoughts on the Golden Metric for SaaS being $1 of cash burned for $1 of net new recurring revenue?

Bessemer’s 2017 State of the Cloud Report

There was so much good content at the SaaStr Annual that it’s going to time to get through it all. Next of the list is Bessemer’s 2017 State of the Cloud Report.

Here are a few notes from the Bessemer slide deck:

  • 40% of the market cap of publicly traded SaaS companies has already been acquired representing greater than $300 billion in value
  • Key questions from top CEOs:
    • How fast should I be growing?
    • How much should I burn?
    • How do I scale?
  • How fast should I be growing?
    • Dropbox is the fastest SaaS company ever to hit $1B in run rate (did it in eight years)
    • The pace is quickening for SaaS companies going from $1M – $100M in recurring revenue (5.3 years for top 25%, 7.3 years median, 10.6 years bottom 25%)
    • BVP Growth Benchmark for ARR
      • Good
        • $1 – $10M in four years
        • $1 – $100M in 10 years
      • Better
        • $1 – $10M in three years
        • $1 – $100M in 7 years
      • Best
        • $1 – $10M in two years
        • $1 – $100M in five years
  • How much should I burn?
    • Rule of 40 = % Annual Revenue Growth + % Profit Margins
    • Efficiency Score = % Annual CARR Growth + % Burn
    • BVP Efficiency Rule (> $30M ARR)
      • Expansion ($30 – $60M ARR) – 70% efficiency score
      • IPO (~$100M ARR) – 50% efficiency score
      • Public (>$150M ARR) – 30% efficiency score
    • BVP Efficiency Rule (< $30M ARR)
      • Net New ARR / Net Cash Burn > 1
      • Meaning, for every dollar burned, company needs $1 or more net new dollars of ARR
  • How do I scale?
    • Customer Acquisition Cost (CAC) Payback = Total Sales and Marketing Costs Last Quarter / New CMRR Added Last Quarter * % Gross Margin
    • Understanding Your Sales Model
      • SMB
        • CAC Payback 3-6 months
        • AVG ACV < $12k
        • Churn/Upsell < 3% monthly
      • Midmarket
        • CAC Payback 12 months
        • AVG ACV $12 – $50k
        • Churn/Upsell 1% monthly
      • Enterprise
        • CAC Payback 3-6 months
        • AVG ACV $50k+
        • Churn/Upsell < 1% monthly, upsell

Thanks to the team at Bessemer for putting together the great information. Every SaaS entrepreneur should read Bessemer’s 2017 State of the Cloud Report.

SaaS Numbers that Actually Matter

Continuing with 12 Key Levers of SaaS Success from David Skok at SaaStr, Mamoon Hamid gave an excellent presentation Numbers that Actually Matter. Finding Your North Star.

Here are a few notes from the presentation:

  • Quick Ratio (QR) = New MRR + Expansion MRR / Churned MRR + Contraction MRR
  • Goal is a Quick Ratio greater than 4
  • Product-market fit happens one customer at a time one month at a time
    • Mostly ignored any product-market fit metrics
  • Churn/Expansion/Contraction MRR is a lagging indicator of product-market fit
  • MRR is the price that the customer pays, the North Star is the value that they get
  • Focus on a leading indicator of the MRR decision
  • Your North Star measures the value you deliver
  • Bad: Mostly measuring price paid as opposed to value delivered
    • MRR, paid seats
  • Good: Measures value delivered in bulk
    • MAU, DAU, messages sent
  • Better: Unquestionably indicates Product Market fit has been reached with the customer
    • Number of users with L28 >= 16
    • Messages sent w/in 30 days in signup

Read the presentation Numbers that Actually Matter. Finding Your North Star. and figure out the North Star for your product.