What to focus on 03/21-04/30

The fundraise is complete and the term sheet is signed! Contour is now officially backed by Chemistry and Lightspeed. We raised almost 12M dollars at a 60M dollar valuation. Honestly, these overblown valuations are personally quite astounding for a pre pmf pre product startup, but now it’s time to prove the investors right. We got things to do. The only question is what should we be focused on? It’s pretty clear that we want to go after implementation teams with a services + agents based model, but this model can be extended to virtually anybody.

I think with all the pressure to move before competitors hit the space, we’ve been randomly spazzing out in terms of which customers to service. Fundamentally, servicing factorial, faire, samsara, gainsight and the PSO’s look super different. This is a byproduct of not doing proper organized discovery AND being too good at getting in the room with the decision makers we can sell.

Extending this though, the most important question now is who, how and why? This is a question that even while we were raising money we had a hard time figuring out, and I think that’s because we didn’t have enough data. So let’s go back to first principles and dissect how we should even think about this question fundamentally.

Why is the Priority 0?

The least efficient way to build a business is randomly servicing customers. Our initial plan to service 5 different customers, who all have different needs and product directions so we can understand each problem deeply is not only very inefficient, but I’m now convinced will yield very unsatsified customers across the board. The way to building a generational company is understanding one painpoint very deeply for a very small subset of your customers and service them fully. Then, use that as a wedge to expand into other adjacent customers and cover ground from there. So BEFORE, we do any sales and close + service even one customer, we should understand the entire lay of the land across all potential customers and choose the path that has the highest EV across the N dimensional matrix that is our skillset, the customers pain, the feasibility to service them, the TAM, and any other factors that we might think is important. This is how we will find the absolute max and not a local max. This is also how, after we do our diligence, we can come to be confident enough to full steam ahead in one direction and bet our companies next few months or years on a direction we took time to choose. I acknowledge that it’s counterintuitive because it feels slow to spend a month on discovery, but my claim is it will be worth it simply because you can’t build a castle on an unsolid foundation.

TLDR: The goal should be to understand WHY we’re servicing a specific sector fundamentally so as more data comes in we can objectively determine how we should steer the ship.

What are the different sectors that we have currently found?

I’m going to list out all the sectors that we can reasonably service.

  1. SMB - this is series A - D startups that are starting to build their deployment teams and are struggling to scale
  2. Mid market - These are you faires, ramps, samsaras of the world that have a long tail of customers that aren’t getting serviced because the EV isn’t there to allocate people to do it
  3. True enterprise SAAS + PSOs - These are the gainsights, salesforces, workdays of the world that have huge and expensive pso’s whether that’s outsourced or in house
  4. Banking and financial services - These are your DFins of the world that have very heavy compliance requirements but also have huge offshore services teams
  5. Agent companies - These are the Decagons and Sierras who have a context gathering problem instead of an implementation problem

There are definitely more sectors than this, the course of actions from here are to think about all sectors we as a team can feasibly service, rank them in accordance with the evaluation criterion below after we’ve gathered some data in terms of how promising we think they are, and iterate week over week on each sector until we’ve reached confidence in which sector we want to full send.

What are the evaluation criterion that we should consider for each sector?

Right now I’m thinking it’s

  1. Team + Category fit - how easy it is for us to penetrate and actually talk to these guys/service these guys
  2. Pain - How bad do they want the broad servicing, this might be in combo with why they haven’t found a solution yet/willingness to adopt a solution?
  3. TAM - how big of a business can we become (understanding this means you know every company in the space what they do how they would use your product etc.)
  4. Extendability - How easy is it to extend the same kind of servicing into other categories -> This can be sector to sector which includes midmarket -> enterprise transitions and such

Where should we start?

I think we should splatter across all the categories meetings for the first week or two to get a general sense of where the most likely starting point is. Of course this is after we have defined templates that we can iterate on in terms of how to actually run the discovery so this is fruitful in the first place. The discovery templates need to be detailed enough that each data point can be quanitified and compared to other data points across other sectors.

Now, I will say that because of the reasons below, I think we are one of the handful of young teams in the world that can sell enterprises top down and actually deliver on the services. My intuition tells me we should start there, but we should do the unbiased discovery in case we’re wrong.

What are we the best in the world at doing?

For my cofounder Ivory, I believe it’s

  1. Networking and getting into the right rooms with the right people - this extends to the VCs, customers, advisors
  2. Resourcefulness and creatively getting things done
  3. Nose to the grind stone.

For me it’s

  1. Output/Organization - whether that’s engineering, product, ops
  2. Enterprise company building intuition - I’ve seen how to build a company over the last 4 years
  3. Team building

How should we do this?

If we agree that one of the spikes on our team is resourcefulness + networking, then the most optimal way to run discovery is relationship building, not cold outbound. Since, we also have basically infinite money to do this, we should do whatever we can to wine and dine these guys - this includes airpods, money whatever to get the top down decision makers in the room with us. If we are to prioritize this efficiently, then while I’m building the customer discovery templating and attack plan strategy Ivory should be booking out every single breakfast lunch dinner for the next 3 weeks with decision makers and doing whatever we can do to get them in the room with us for 2-3 hours.

Loosely, the discovery template might be

  1. Find CCOs, VPs of implementation, Directors of implementation
  2. Understand each of their priorities deeply - whether that’s reducing head count, increasing efficiency, etc
  3. Understand what the blockers are to doing so right now? How good each product is, how much they trust AI, how critical their services are
  4. Understand if we can mitigate the blockers - this might be understanding how long it would take to build these solutions, how fast we can scale post these facts?

How does this impact our priorities.

Discovery should be done by us. In my eyes there’s no point in onboarding anybody until we’re concrete on the direction. There’s no product to build and people to sell to until we’ve hammered out our true direction. The goal should be to commit to a true ICP and understand why we chose that, so if more data comes in we can adjust as we go. The best founders are those that can predict the future the best.

Actionables

  1. Get as many people on the calendar in as short of a time as possible.
  2. Build out the N dimensional matrix for each potential customer
  3. Create attack plans for each customer subset
  4. Create organized templates for which questions to tangibly know the answers to
  5. Post execution of attack plans, quantifiably compare the results across all customer subsets to pinpoint where to focus on