Recently I was meeting with an entrepreneur who’s startup is growing nicely. They just raised a round of financing and will be expanding the sales team. After catching up for a few minutes, he asked about implementing sales territories and I recommended against it.
Here are a few reasons most startups should avoid sales territories:
- Distribution of Best-fit Accounts – While sales territories are often divided based on certain states and their corresponding population centers, in actuality the ideal customer profile isn’t evenly distributed. Apps can automatically find the total addressable market and build smart lists of the best-fit accounts. Having each rep work a set of named accounts ensures all best-fit accounts get worked, not just the best in a certain territory (e.g. 250-500 accounts per rep is recommended).
- Growth in Sales Reps – As the startup grows, and hires more sales people, territories for existing reps must shrink to make room. Shrinking territories results in disillusionment for the existing reps and creates ongoing realignment challenges.
- Inbound Lead Distribution – Just as the ideal custom profiles aren’t evenly distributed across territories, quality inbound leads aren’t evenly distributed either. By not having territories, inbound leads can be qualified and parsed out in a more dynamic fashion.
Sales territories are a relic of the pre-internet era and no longer make sense for most startups. Entrepreneurs would do well to avoid sales territories and take advantage of the opportunity to target the best accounts anywhere, not the best accounts in a certain territory.
What else? What are some more reasons startups should avoid sales territories?
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:
- 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.
- 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.
- 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?
Kyle Porter of SalesLoft tweeted his favorite sales play from today’s TOPO Summit. Sales plays are a repeatable process designed to acquire customers and turn them into advocates. Let’s look at the sales play of the day:
- Create specific content from lessons learned in the disco call.
- Conduct live (mid-sales cycle) value add workshops with multiple stakeholders.
- Reiterate objections and challenges in the sales presentation deck
- Customize the demo to their key challenges so they can see themselves in the product
- Create customized close plan to help deals close on time
- Memorable late stage marketing plays keep buyers from going dark (send them a pound of bacon!)
- Say “thank you” and thank your high value accounts after they sign with you
Entrepreneurs would do well to think through their sales plays and work towards an effective, repeatable process.
What else? What are some elements of your favorite sales plays?
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.
Earlier today I was talking to a successful entrepreneur that has built an excellent company in only a few short years. Intrigued, I asked a simple question: how’d you do it? His response: we built community around our target audience. That sounds straightforward; I wanted details. Here are the four recurring activities to build a powerful marketing engine:
- Two Quality Blog Posts Per Week – Inbound marketing works well when done consistently with great content. Want to see an example of great content? Check out Hitenism.com.
- One Quality Webinar Per Week – Webinars work wonders. At Pardot, we ran a new one every week and they were super successful. Make great slides, get a guest speaker, and run a weekly webinar.
- One Quality Email Newsletter Per Week – Build a list of opt-in subscribers. Find people that care about quality content and send a weekly newsletter. Need an example? HubSpot has over 300,000 subscribers to their newsletter.
- One In-Person Event Per Month – People connect with people first, companies second. Run in-person events locally at first and then in major cities around the country. Build a tribe. Find the 1,000 true fans.
These four activities are hard to do well. After achieving product/market fit, this approach is excellent to build a repeatable customer acquisition process.
What else? What are some more thoughts on these four recurring activities to build a powerful marketing engine?
Terminus put on an excellent FlipMyFunnel class today. One element of the event was walking through an account-based sales and marketing program. Let’s take a look at their example:
Marketing Touch Points
- Pre-cadence: Terminus Ads
- During cadence: LinkedIn and Facebook retargeting to known contacts
- After 1st 8 days: Direct mail to unresponsive accounts
Sales Touch Points
- Day 1: Personalized video email (via Vidyard integration in SalesLoft)
- Day 2: Email
- Day 4: LinkedIn (Attempt to connect)
- Day 6: InMail
- Day 7: Video email (From different team member)
- Day 8: Call, no VM
- Day 8: Direct mail
- Day 13: Call, LVM about the package
- Day 13: Email about the package
- Day 15: Video email
- Day 16: Call, no VM
- Day 20: Breakup video email
Most companies focus on making a certain number of calls and emails per day that ends up being broad and shallow. Modern customer acquisition teams run detailed outbound account-based sales and marketing program against their best-fit accounts using account-based intelligence.
Thanks to Terminus and the FlipMyFunnel team for putting on the event and sharing the excellent ideas.
What else? What are some more components of an effective account-based sales and marketing program?
As the cost to build an app has gone down over the last 10 years due to open source and cloud computing, the number of apps as grown. Now, there are dozens of apps that do the same thing in every category imaginable. The result: customer acquisition is the number one challenge with so much noise in the market. And, it’s only going to get more challenging.
Here are four things to work on to build a customer acquisition machine:
- Community – Work towards 1,000 true fans. Start small. Find the first 10 that care. Then the first 100. Nurture the community and grow it over time.
- Content – Write original content. Make a statement. Have a strong opinion. Put new ideas out there. Find a rhythm.
- Engage – Connect with people. Target best-fit accounts. Run a process. Follow the account-based engagement best practices.
- Experiment – Follow the Traction book. Constantly experiment. Try new ideas like micro apps and social selling.
Customer acquisition is the most difficult challenge required for startups to succeed. Invest in it early and build the expertise over time.
What else? What are some more ways to build a customer acquisition machine?
Jyoti Bansal, founder and long-time CEO of AppDynamics (see S-1 IPO notes) that was recently acquired by Cisco for $3.4 billion, has an excellent blog post up titled The Science of Enterprise Software Sales — My Lessons from AppDynamics. Here are a few notes from the post:
- Your Path to $100 Million (or $1 Billion) Sales
- Need to get to $100M of revenue growing fast than 40% a year to get a $1B valuation
- Calculate the number of customers required for $100M in revenue based on average revenue per customer (e.g. 5,000 customers paying $20K/year)
- The Sales Capacity Model
- Four key variables:
- Number of “ramped” sales reps.
- Productivity of each rep.
- Churn in ramped sales reps.
- Time to ramp a newly hired sales rep.
- Track these variables and build a financial model
- The Demand Generation Model
- Three key variables:
- Average deal size
- Deal close rate
- Average sales cycle
- Track these variables and build a demand generation model
- The Sales Process
- Three main objectives:
- Eliminate opportunities that aren’t well qualified.
- Justify the business case for your solution.
- Eliminate surprises.
- The Growth Constraints
- Only a few constraints:
- Not enough product demand to achieve a higher growth rate
- Can’t compete effectively on product/pricings, etc.
- Need more cash than investors are willing to spend
- Can’t recruit, train, and absorb new people fast enough
Want to learn more? Go read The Science of Enterprise Software Sales — My Lessons from AppDynamics.
Continuing with this week’s theme of account-based engagement (see here and here), there’s another element that needs more discussion: quantifying account-based engagement efforts. Let’s say you have accounts rated by tier with the ‘A’ accounts being best-fits, the ‘B’ accounts being the second tier, the ‘C’ accounts being the third tier, and so on. How do you decide how much effort to devote to each tier?
There are two common approaches:
- Take the most common activities (call, initial email, email reply, demo, etc.) and allocate a number of minutes for each as a proxy for effort (e.g. 5 minutes for an email, 20 minutes for an email reply, 90 minutes for a demo including prep work, etc.)
- Figure out the ideal mix of activities and the corresponding minutes per rep per week, assuming 40 hours:
- 5 hours – general meetings, coaching, etc.
- 25 hours – 50 Tier 1 accounts at 30 minutes each
- 10 hours – 40 Tier 2 accounts at 15 minutes each
- Total: 90 accounts engaged
- Build a CRM report by activity type with a formula to multiply by the number of minutes allocated and then group by the account tier to see the results
- Take the most common touches (call, email, social media interaction, InMail message) and assume each is roughly the same amount of effort
- Take the number of Tier 1 accounts and Tier 2 accounts and start with 2x the effort for Tier 1 accounts
- Assign a required number of touches per Tier 1 account and per Tier 2 account each week (a touches quota)
- Build a CRM report by activity type grouped by the account tier to ensure the efforts match the touches quota
Quantifying account-based engagement efforts takes work to setup and requires an on-going process. Every sales leader knows that more effort equals more results, and this strategy is excellent for more predictable revenue.
What else? What are some more ways to quantify account-based engagement efforts?
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?