AWS Startups Blog

Prospecting Mechanisms (Startup Founder Sales Series, Part 6)

You may have heard of the story of the rabbit and the tortoise. It’s the classic Aesop fable where the energetic rabbit and the lethargic tortoise have a race. The rabbit is so confident of winning that it rests before getting started. The tortoise, however, pushes on and eventually wins.

There are a few lessons one can take from the story. You cannot assume success, you should never underestimate your competition, and speed is not necessarily an advantage. But the most important and relevant one for this post is that there are no shortcuts to success.

When you study any successful entrepreneur, the winning formula is alway hard work. It can be frustrating to hear this because it does not feel actionable. We feel like there should be some cheat codes or hacks that must have been the reason for their accelerated growth. That is not to say that there weren’t discoveries that unlocked exponential growth. Airbnb, for example, realized the photos hosts were using for listings were of poor quality. The founders then took more polished photos for the hosts that accelerated uptake of the service. None of this happened by chance or sudden intuition, though. Discoveries are the result of hard work and experiments, failure, and learning.

Sales for an early stage startup is the same. In the beginning, you only have a notion of how to engage prospects. You have proposed personas, markets, and messaging mapped, but you do not know what the response is going to be. This is perhaps the most frustrating thing for startup founders to grasp. Many of the founders I advise are engineering oriented, so they view sales as very process driven. However, they tend to forget the part where iteration and measuring and adjustment is required. They short circuit the process by relying on sales books or blogs and copying the tactics.

It is often at this stage that founders will reach out to me frustrated that they are not seeing results. Sometimes the execution is sloppy, but more often than not, the error is in not putting the tactics into context. Each startup has a unique combination of market, industry, solution, users, and use cases, which all dictate the appropriate sales strategies and tactics. Take the example of a startup that offers payments systems to large banks. Their sales process will be vastly different from a startup that provides online delivery service for local restaurants.

If copying and pasting someone else’s process does not work, you need to figure out how to iterate quickly so you can discover what works in repeatedly generating sales. This means a way of tracking activities and steps, learning how best to use the process, and then measuring results. If this works well, you can continuously tweak things to improve sales outcomes. To do this we are going to start by building a prospecting mechanism.

But what do I mean by a “mechanism”?

At Amazon, we consider a mechanism to be a complete process that creates a “virtuous cycle” of reinforcing and improving itself as it operates. It starts with a tool, becomes ingrained through adoption, and is continuously inspected to determine if course corrections are required.

Mechanisms ensure that change is not just something that is talked about. By thinking in terms of mechanisms, you are actively driving the implementation of change as Jeff Bezos explains:

“When you are asking for good intentions, you are not asking for a change, because people already had good intentions. But if good intentions don’t work, what does? Mechanisms work.”

The prospecting mechanism is a means of taking what is often an ad hoc and scattered activity and turning it into a well-oiled machine. Prospecting is critical to get right because it is a top-of-the-funnel activity that converts interest into opportunities and eventually into closed deals. Because a certain percentage of leads contacted will drop out of the “sales funnel,”  you will need a lot of leads, which means contacting many more people. Without a mechanism in place, you will quickly lose track of your prospecting efforts and miss out on potentially good deals.

Taking the Amazon view of mechanisms then as our starting point, let’s put together a prospecting mechanism, focusing on the tool, adoption, and inspection.

Tool

Prospecting is a high volume activity. This means that you will need to contact many people before getting any positive interest. The only way to do this scalably is to use technology and automation. There are numerous tools for managing prospecting today from high-end solutions for teams such as Salesloft and Outreach to more inexpensive options like Reply.io, Mixmax, and Prospect.io that are better suited for startup founders.

The key thing to keep in mind is that whatever tool you choose, make sure it can do the following:

  • Send emails through your email address (for higher deliverability rates)
  • Allows you to create templates
  • Enables automation of a series of outreach activities
  • Manage responses, bounces, and unsubscribes
  • Integrates with a Customer Relationship Management (CRM) system, like Salesforce, Freshworks, or HubSpot

The value of automation is that you can create a sequence of tasks to engage a prospect. Rarely do prospects respond to your first outreach because people are busy and your message is not considered a priority. With a consistent rhythm of sending a unique message every several days, you increase the likelihood of a prospect responding. How many messages are recommended to send? Context matters, but it is suggested no more than 8 to 10 otherwise it borders on becoming annoying to prospects.

Normally, managing outreach in a number of active sequences across hundreds of prospects would be too difficult to manage in a spreadsheet. Using a tool takes the complexity off of your hands and handles all outreach and responses so you only have to focus on prospects that express interest in speaking to you.

Note that automation is not a replacement for personalizing your outreach. Outreach that is generic and feels like a template will most likely get deleted or flagged as spam. Automation is simply a means to do personalized outreach faster.

The other critical aspect of having a tool is that it has all of your activity for emails, social network connections, and calls in one place for all your prospects. This makes it easier to synchronize data with a CRM system (this is why integration is important) and to do reporting and analysis on effectiveness, discussed in more detail below.

Adoption

In order for a tool to be effective, it has to be easy to use and integrated into how you work. As a team grows, this is of critical importance, otherwise the data is incomplete, causing doubt in decision making. Salespeople not putting in call notes after meetings with prospects or updating pipeline stages of opportunities as new information arises are some common examples.

As the founder that is also the only sales person, adoption is also important to consider. If the system you use is not easy to keep up with, then it will be easy to skip entering data in favor of other priorities. Without a complete set of data, you cannot improve the mechanism because there is not enough feedback. Therefore find a tool that you can both get up to speed on quickly and make use of on a daily basis. The best way to do this is to schedule time in your calendar every day for reviewing data, inputting notes, and updating contacts and templates.

Inspection

Once a tool is in place and being used on a consistent basis, you will now have data to draw insights from to further refine the prospecting mechanism. Every week spend time to review data on response rates and click through rates on emails.

Resist the temptation to continuously tweak your outreach, though. You may want to modify messaging in your templates, change the frequency of outreach, or make other adjustments when you do not immediately see good results. That is to be expected initially given how little you know about your sales process in the early stages.

Instead, take time to collect enough data and then only tweak one aspect of your prospecting at a time in one cohort. A cohort is a group of similar prospects, like heads of engineering at early stage FinTech startups in London or VP’s of Sales at tech companies in Singapore. By doing this, you can see whether a change has a measurable impact on response rates. If so, keep the change. If not, roll back and change another parameter.

Through this mechanism, you should be able to build enough momentum to reliably generate meetings. The magic is in iteratively changing and refining the steps so that it forces you to challenge your assumptions about personas, markets, messaging, and outreach tactics. This is the flywheel effect that can be scaled once you start building the sales team.

The next question then is what happens when a prospect responds positively? What’s next after the prospecting mechanism? Over the next few weeks, I will dive deeper into specific stages of sales as a prospect moves from an opportunity to a customer. The start of this end-to-end sales process is qualifying the prospect which is the topic for next week, so see you then.

Mark Birch

Mark Birch

Mark is a community builder, software entrepreneur, business development expert, and startup advisor. He currently works at AWS as a Principal Startup Advocate advising founders and sharing the stories of how startups across Asia-Pacific successfully build and scale their startups on AWS. Previously, Mark founded the Enterprise Sales Forum, a global community of 25,000 B2B sales professionals, and DEV.BIZ.OPS, a newsletter and blog. Mark was also with Stack Overflow to help launch and commercialize their Enterprise Q&A platform and then led efforts to expand business in APAC working with C-level executives to help them understand how to build internal tech communities in order to improve software delivery performance. Before that he launched an HR tech startup, invested in numerous B2B tech companies and worked at a diverse group of leading technology companies including Oracle, E.piphany, and Siebel.