How and when to build marketing teams at deep tech companies

Deep tech startups develop cutting-edge innovations with the power to truly revolutionize society. The founding team members at these companies often come from deeply technical backgrounds, which powers rapid product progress but can create bottlenecks on the go-to-market side.

In this post, I outline the answers to four key questions around marketing at early-stage deep tech companies that are post-revenue:

  • What marketing teams at deep tech companies do.
  • When to hire the marketing team.
  • Whether the marketing team needs industry experience.
  • How to source and evaluate talent for the marketing team.

From this post, deep tech startups can formulate their marketing hiring strategy and attract and cultivate top talent to drive their go-to-market plan. Without business execution, even the most groundbreaking innovations do not achieve their intended impact.

What do marketing teams at deep tech companies do?

To set the context, I share below the typical projects of deep tech marketing teams, which look different from marketing in other industries given the greater product focus and complexity, regulatory oversight and longer time to market.

Go-to-market

Marketers leverage the strength of the IP to establish collaborations with large companies, such as pharma companies and institutions, such as the government, universities or hospitals. To this end, marketers develop creative ways to gather lists of, and information on, key contacts at these potential partners. They also build sales collateral, such as demo videos, pitch decks and one-pagers, to more effectively reach and build long-term relationships with these prospects.

More broadly, marketers also develop the go-to-market strategy beyond partnerships. To this end, marketers conduct in-depth market research on business models, monetization strategies and reimbursement channels.

Communications

Marketers create original content to establish the company as a thought leader, build the company’s brand credibility through social media and apply for awards and honors to validate the potential of the company’s solution.

Forecasting

Marketers work with finance and product teams to formulate projections as the company moves into the clinical phase.

When should deep tech companies hire marketers?

The CEO and other members of the founding team take on marketing work in the formation stage to better understand and empathize with the needs, capabilities and opportunities in the department before bringing someone on full time.

Once the product shows signs of repeatable revenue, a marketing lead is needed. Specifically, this is ahead of a large Series A round, after a small Series A round or when a commercial partner has expressed interest in larger, long-term contracts. Instead of the typical chief marketing officer or chief revenue officer title, deep tech startups call this person a chief commercial officer or chief partnerships officer.

For additional support in the formation stage, companies bring on MBA interns and work with their investors. Prior to the Series A, platform teams at deep tech venture-capital funds are hands-on in helping with marketing through actually doing marketing projects for their portfolio companies, ideating on long-term marketing strategy with the founders through regular feedback sessions and connecting founders with vetted marketing contractors or agencies.

For companies that require FDA approval, commercial advisors, consultants and board members fully take on the partnership strategy work (which represents the bulk of the marketing needs) prior to the Series A round. Similarly, external consultants, such as marketing agencies, can take over major projects like launch strategy. External consultants can then join the team should their performance be strong.

For drug-development companies, the marketing leader is most crucial when the company enters the clinical phase and prepares for trials, regardless of funding stage.

Do marketing hires need industry experience?

Of course, it is ideal to hire someone with experience selling into the space and someone who is comfortable with the complex supply chains and long sales cycles. However, if the choice is between someone with functional expertise but no industry expertise and someone with industry experience but limited or no functional expertise, it is better to hire the former candidate and leverage the rest of the team for domain expertise. Deep tech is a niche area, so the other team members can support the marketer in developing industry expertise.

#deep-tech, #ec-entrepreneurship, #ec-marketing, #growth-marketing, #labor, #marketing, #product-management, #product-marketing, #startups, #tc

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3 tips for SaaS founders hoping to join the $1 million ARR club

Building a SaaS company from the ground up is never easy. In fact, it’s generally a grueling, all-consuming process that strains every fiber in your being.

But it is much, much more difficult if you approach it without a tried and true process. After starting and scaling five successful companies, I can tell you that there absolutely is a repeatable process to building a successful SaaS business, one that can reliably guide you to product-market fit and then help you quickly scale.

That doesn’t mean it’s easy, but it does mean that you won’t waste years of your life pursuing a solution that nobody wants.

Begin with finding the right problem

In the earliest stages, the process begins by finding the right problem to solve. At this point, you likely already have a few hypotheses about that problem. But no matter your conviction, you must test those hypotheses against a consistent set of criteria. For example, these are the questions that my co-founder and I used to evaluate the earliest concept of our current company, Drift:

  • Is the problem big enough?
  • Is the market big enough?
  • Does the problem have a recurring use case?
  • Can we build the solution for the problem?

If this sounds like a simple, straightforward exercise, it’s because it is. But not enough entrepreneurs ask themselves these questions at the beginning of their journey. We successfully avoided wasting months or even years of precious time building products that didn’t fit these criteria. This simple step will save you an incredible amount of pain and aggravation.

The only way to find product-market fit

Once you settle on a problem to solve, it’s time to build a barebones product that solves it and to then test that product against the market.

My co-founder Elias and I approached it this way: First, we personally spent hours each day in communities like LinkedIn, Twitter and Product Hunt, giving folks early access to our product and asking them for as much feedback as they could offer.

We were happy if they responded in the comments or to our direct messages, but we always went deeper by asking them to speak over the phone or on a video chat. We also hit the pavement by going to in-person Meetups and events around our hometown of Boston. We even took flights out to small events around the country so that we could interact with potential customers in-person.

If this sounds inordinate, it isn’t. This is the kind of attention that you need to devote to gathering intelligence from potential customers, so that you can relentlessly laser in on a product that they will actually use, value and pay for.

#column, #drift, #entrepreneurship, #growth-marketing, #product-marketing, #saas, #software-as-a-service, #startups, #tc

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Drive predictable B2B revenue growth with insights from big data and CDPs

As the world reopens and revenue teams are unleashed to meet growth targets, many B2B sellers and marketers are wondering how they can best prioritize prospect accounts. Everyone ultimately wants to achieve predictable revenue growth, but in uncertain times — and with shrinking budgets — it can feel like a pipe dream.

Slimmer budgets likely mean you’ll need more accurate targeting and higher win rates. The good news is your revenue team is likely already gathering tons of prospect data to help you improve account targeting, so it’s time to put that data to work with artificial intelligence. Using big data and four essential AI-based models, you can understand what your prospects want and successfully predict revenue opportunities.

Big data and CDPs are first steps to capturing account insights

Capturing and processing big data is essential in order to know everything about prospects and best position your solution. Accurately targeting your campaigns and buyer journeys necessitates more data than ever before.

Marketers today rely on customer data platforms (CDPs) to handle this slew of information from disparate sources. CDPs let us mash together and clean up data to get a single source of normalized data. We can then use AI to extract meaningful insights and trends to drive revenue planning.

That single source of truth also lets marketers dive into the ocean of accounts and segment them by similar attributes. You can break them down into industry, location, buying stage, intent, engagement — any combination of factors. When it’s time to introduce prospects to your cadence, you’ll have segment-specific insights to guide your campaigns.

AI realizes data-based insights

You might find that your data ocean is much deeper than you expected. While transforming all that data into a single source to drive actionable insights, you’ll also need the right resources and solutions to convert raw data into highly targeted prospect outreach.

This is where AI shines. AI and machine learning enable revenue teams to analyze data for historical and behavioral patterns, pluck out the most relevant intent data, and predict what will move prospects through the buyer journey.

#artificial-intelligence, #big-data, #column, #customer-data-platform, #customer-relationship-management, #ecommerce, #finance, #machine-learning, #marketing, #online-advertising, #product-marketing, #targeted-advertising, #tc

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What can growth marketers learn from lean product development?

Old-school approaches to marketing were often described as “spray and pray.” Marketers would launch a massive campaign in as many places as possible and hope that something worked.

More customers would show up, so it would appear that something had in fact worked.

But nobody could be sure exactly what that something was.

When we can’t predict what will have an impact, we need campaigns that cover all the bases, and those campaigns are consequently huge. They take a long time to create, are expensive to launch and come chock full of risk.

If a spray-and-pray campaign is a total failure (and we don’t have to go far to find examples of those), it’s quite possible an entire year’s worth of marketing budget has just been wasted.

Instead, marketers need to take a page from lean product development and begin creating Minimum Viable Campaigns (MVCs). Rather than wait until a massive multichannel launch is perfect, we can incrementally release a series of smaller, targeted, data-driven campaigns.

Over time these MVCs coalesce to look and act much like a Big Bang-style campaign from the spray-and-pray days, but they’ve done so in a much more data-driven and less risky way.

What exactly is an MVC?

Just as with a Minimum Viable Product (MVP), it can be easy to misunderstand the real definition of an MVC. It’s not something thrown together with no regard for brand standards or strategic goals, and it’s not a blind guess.

Instead, a good MVC represents the smallest amount of well-designed work that could still achieve some of the campaign’s goals. Before we have any chance of figuring out what that looks like, we need to know the ultimate goal of the bigger campaign or initiative. If we don’t know this, we can’t possibly measure the effectiveness of the MVC.

#column, #entrepreneurship, #growth-marketing, #lean-startups, #marketing, #product-management, #product-marketing, #social-media, #startups, #tc, #verified-experts

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